In Silico Detection of Sequence Variations Modifying Transcriptional Regulation

PubMed Central

Andersen, Malin C; Engström, Pär G; Lithwick, Stuart; Arenillas, David; Eriksson, Per; Lenhard, Boris; Wasserman, Wyeth W; Odeberg, Jacob

2008-01-01

Identification of functional genetic variation associated with increased susceptibility to complex diseases can elucidate genes and underlying biochemical mechanisms linked to disease onset and progression. For genes linked to genetic diseases, most identified causal mutations alter an encoded protein sequence. Technological advances for measuring RNA abundance suggest that a significant number of undiscovered causal mutations may alter the regulation of gene transcription. However, it remains a challenge to separate causal genetic variations from linked neutral variations. Here we present an in silico driven approach to identify possible genetic variation in regulatory sequences. The approach combines phylogenetic footprinting and transcription factor binding site prediction to identify variation in candidate cis-regulatory elements. The bioinformatics approach has been tested on a set of SNPs that are reported to have a regulatory function, as well as background SNPs. In the absence of additional information about an analyzed gene, the poor specificity of binding site prediction is prohibitive to its application. However, when additional data is available that can give guidance on which transcription factor is involved in the regulation of the gene, the in silico binding site prediction improves the selection of candidate regulatory polymorphisms for further analyses. The bioinformatics software generated for the analysis has been implemented as a Web-based application system entitled RAVEN (regulatory analysis of variation in enhancers). The RAVEN system is available at http://www.cisreg.ca for all researchers interested in the detection and characterization of regulatory sequence variation. PMID:18208319

In silico analysis of cacao (Theobroma cacao L.) genes that involved in pathogen and disease responses

NASA Astrophysics Data System (ADS)

Agung, Muhammad Budi; Budiarsa, I. Made; Suwastika, I. Nengah

2017-02-01

Cocoa bean is one of the main commodities from Indonesia for the world, which still have problem regarding yield degradation due to pathogens and disease attack. Developing robust cacao plant that genetically resistant to pathogen and disease attack is an ideal solution in over taking on this problem. The aim of this study was to identify Theobroma cacao genes on database of cacao genome that homolog to response genes of pathogen and disease attack in other plant, through in silico analysis. Basic information survey and gene identification were performed in GenBank and The Arabidopsis Information Resource database. The In silico analysis contains protein BLAST, homology test of each gene's protein candidates, and identification of homologue gene in Cacao Genome Database using data source "Theobroma cacao cv. Matina 1-6 v1.1" genome. Identification found that Thecc1EG011959t1 (EDS1), Thecc1EG006803t1 (EDS5), Thecc1EG013842t1 (ICS1), and Thecc1EG015614t1 (BG_PPAP) gene of Cacao Genome Database were Theobroma cacao genes that homolog to plant's resistance genes which highly possible to have similar functions of each gene's homologue gene.

In silico characterization of a novel pathogenic deletion mutation identified in XPA gene in a Pakistani family with severe xeroderma pigmentosum

PubMed Central

2013-01-01

Background Xeroderma Pigmentosum (XP) is a rare skin disorder characterized by skin hypersensitivity to sunlight and abnormal pigmentation. The aim of this study was to investigate the genetic cause of a severe XP phenotype in a consanguineous Pakistani family and in silico characterization of any identified disease-associated mutation. Results The XP complementation group was assigned by genotyping of family for known XP loci. Genotyping data mapped the family to complementation group A locus, involving XPA gene. Mutation analysis of the candidate XP gene by DNA sequencing revealed a novel deletion mutation (c.654del A) in exon 5 of XPA gene. The c.654del A, causes frameshift, which pre-maturely terminates protein and result into a truncated product of 222 amino acid (aa) residues instead of 273 (p.Lys218AsnfsX5). In silico tools were applied to study the likelihood of changes in structural motifs and thus interaction of mutated protein with binding partners. In silico analysis of mutant protein sequence, predicted to affect the aa residue which attains coiled coil structure. The coiled coil structure has an important role in key cellular interactions, especially with DNA damage-binding protein 2 (DDB2), which has important role in DDB-mediated nucleotide excision repair (NER) system. Conclusions Our findings support the fact of genetic and clinical heterogeneity in XP. The study also predicts the critical role of DDB2 binding region of XPA protein in NER pathway and opens an avenue for further research to study the functional role of the mutated protein domain. PMID:24063568

In silico genome-wide identification and characterization of the glutathione S-transferase gene family in Vigna radiata.

PubMed

Vaish, Swati; Awasthi, Praveen; Tiwari, Siddharth; Tiwari, Shailesh Kumar; Gupta, Divya; Basantani, Mahesh Kumar

2018-05-01

Plant glutathione S-transferases (GSTs) are integral to normal plant metabolism and biotic and abiotic stress tolerance. The GST gene family has been characterized in diverse plant species using molecular biology and bioinformatics approaches. In the current study, in silico analysis identified 44 GSTs in Vigna radiata. Of the total 44 GSTs identified, chromosomal locations of 31 GSTs were confirmed. The pI value of GST proteins ranged from 5.10 to 9.40. The predicted molecular weights ranged from 13.12 to 50 kDa. Subcellular localization analysis revealed that all GSTs were predominantly localized in the cytoplasm. The active site amino acids were confirmed to be serine in tau, phi, theta, zeta, and TCHQD; cysteine in lambda, DHAR, and omega; and tyrosine in EF1G. The gene architecture conformed to the two-exon/one-intron and three-exon/two-intron organization in the case of tau and phi classes, respectively. MEME analysis identified 10 significantly conserved motifs with the width of 8-50 amino acids. The motifs identified were either specific to a specific GST class or were shared by multiple GST classes. The results of the current study will be of potential importance in the characterization of the GST gene family in V. radiata, an economically important leguminous crop.

In silico quantitative structure-toxicity relationship study of aromatic nitro compounds.

PubMed

Pasha, Farhan Ahmad; Neaz, Mohammad Morshed; Cho, Seung Joo; Ansari, Mohiuddin; Mishra, Sunil Kumar; Tiwari, Sharvan

2009-05-01

Small molecules often have toxicities that are a function of molecular structural features. Minor variations in structural features can make large difference in such toxicity. Consequently, in silico techniques may be used to correlate such molecular toxicities with their structural features. Relative to nine different sets of aromatic nitro compounds having known observed toxicities against different targets, we developed ligand-based 2D quantitative structure-toxicity relationship models using 20 selected topological descriptors. The topological descriptors have several advantages such as conformational independency, facile and less time-consuming computation to yield good results. Multiple linear regression analysis was used to correlate variations of toxicity with molecular properties. The information index on molecular size, lopping centric index and Kier flexibility index were identified as fundamental descriptors for different kinds of toxicity, and further showed that molecular size, branching and molecular flexibility might be particularly important factors in quantitative structure-toxicity relationship analysis. This study revealed that topological descriptor-guided quantitative structure-toxicity relationship provided a very useful, cost and time-efficient, in silico tool for describing small-molecule toxicities.

In Silico Functional Networks Identified in Fish Nucleated Red Blood Cells by Means of Transcriptomic and Proteomic Profiling.

PubMed

Puente-Marin, Sara; Nombela, Iván; Ciordia, Sergio; Mena, María Carmen; Chico, Verónica; Coll, Julio; Ortega-Villaizan, María Del Mar

2018-04-09

Nucleated red blood cells (RBCs) of fish have, in the last decade, been implicated in several immune-related functions, such as antiviral response, phagocytosis or cytokine-mediated signaling. RNA-sequencing (RNA-seq) and label-free shotgun proteomic analyses were carried out for in silico functional pathway profiling of rainbow trout RBCs. For RNA-seq, a de novo assembly was conducted, in order to create a transcriptome database for RBCs. For proteome profiling, we developed a proteomic method that combined: (a) fractionation into cytosolic and membrane fractions, (b) hemoglobin removal of the cytosolic fraction, (c) protein digestion, and (d) a novel step with pH reversed-phase peptide fractionation and final Liquid Chromatography Electrospray Ionization Tandem Mass Spectrometric (LC ESI-MS/MS) analysis of each fraction. Combined transcriptome- and proteome- sequencing data identified, in silico, novel and striking immune functional networks for rainbow trout nucleated RBCs, which are mainly linked to innate and adaptive immunity. Functional pathways related to regulation of hematopoietic cell differentiation, antigen presentation via major histocompatibility complex class II (MHCII), leukocyte differentiation and regulation of leukocyte activation were identified. These preliminary findings further implicate nucleated RBCs in immune function, such as antigen presentation and leukocyte activation.

In Silico Functional Networks Identified in Fish Nucleated Red Blood Cells by Means of Transcriptomic and Proteomic Profiling

PubMed Central

Puente-Marin, Sara; Ciordia, Sergio; Mena, María Carmen; Chico, Verónica; Coll, Julio

2018-01-01

Nucleated red blood cells (RBCs) of fish have, in the last decade, been implicated in several immune-related functions, such as antiviral response, phagocytosis or cytokine-mediated signaling. RNA-sequencing (RNA-seq) and label-free shotgun proteomic analyses were carried out for in silico functional pathway profiling of rainbow trout RBCs. For RNA-seq, a de novo assembly was conducted, in order to create a transcriptome database for RBCs. For proteome profiling, we developed a proteomic method that combined: (a) fractionation into cytosolic and membrane fractions, (b) hemoglobin removal of the cytosolic fraction, (c) protein digestion, and (d) a novel step with pH reversed-phase peptide fractionation and final Liquid Chromatography Electrospray Ionization Tandem Mass Spectrometric (LC ESI-MS/MS) analysis of each fraction. Combined transcriptome- and proteome- sequencing data identified, in silico, novel and striking immune functional networks for rainbow trout nucleated RBCs, which are mainly linked to innate and adaptive immunity. Functional pathways related to regulation of hematopoietic cell differentiation, antigen presentation via major histocompatibility complex class II (MHCII), leukocyte differentiation and regulation of leukocyte activation were identified. These preliminary findings further implicate nucleated RBCs in immune function, such as antigen presentation and leukocyte activation. PMID:29642539

Discovery of Novel Anti-prion Compounds Using In Silico and In Vitro Approaches

PubMed Central

Hyeon, Jae Wook; Choi, Jiwon; Kim, Su Yeon; Govindaraj, Rajiv Gandhi; Jam Hwang, Kyu; Lee, Yeong Seon; An, Seong Soo A.; Lee, Myung Koo; Joung, Jong Young; No, Kyoung Tai; Lee, Jeongmin

2015-01-01

Prion diseases are associated with the conformational conversion of the physiological form of cellular prion protein (PrPC) to the pathogenic form, PrPSc. Compounds that inhibit this process by blocking conversion to the PrPSc could provide useful anti-prion therapies. However, no suitable drugs have been identified to date. To identify novel anti-prion compounds, we developed a combined structure- and ligand-based virtual screening system in silico. Virtual screening of a 700,000-compound database, followed by cluster analysis, identified 37 compounds with strong interactions with essential hotspot PrP residues identified in a previous study of PrPC interaction with a known anti-prion compound (GN8). These compounds were tested in vitro using a multimer detection system, cell-based assays, and surface plasmon resonance. Some compounds effectively reduced PrPSc levels and one of these compounds also showed a high binding affinity for PrPC. These results provide a promising starting point for the development of anti-prion compounds. PMID:26449325

In silico analysis of a novel MKRN3 missense mutation in familial central precocious puberty.

PubMed

Neocleous, Vassos; Shammas, Christos; Phelan, Marie M; Nicolaou, Stella; Phylactou, Leonidas A; Skordis, Nicos

2016-01-01

The onset of puberty is influenced by the interplay of stimulating and restraining factors, many of which have a genetic origin. Premature activation of the GnRH secretion in central precocious puberty (CPP) may arise either from gain-of-function mutations of the KISS1 and KISS1R genes or from loss-of-function manner mutations of the MKRN3 gene leading to MKRN3 deficiency. To explore the genetic causes responsible for CPP and the potential role of the RING finger protein 3 (MKRN3) gene. We investigated potential sequence variations in the intronless MKRN3 gene by Sanger sequencing of the entire 507 amino acid coding region of exon 1 in a family with two affected girls presented with CPP at the age of 6 and 5·7 years, respectively. A novel heterozygous g.Gly312Asp missense mutation in the MKRN3 gene was identified in these siblings. The imprinted MKRN3 missense mutation was also identified as expected in the unaffected father and followed as expected an imprinted mode of inheritance. In silico analysis of the altered missense variant using the computational algorithms Polyphen2, SIFT and Mutation Taster predicted a damage and pathogenic alteration causing CPP. The pathogenicity of the alteration at the protein level via an in silico structural model is also explored. A novel mutation in the MKRN3 gene in two sisters with CPP was identified, supporting the fundamental role of this gene in the suppression of the hypothalamic GnRH neurons. © 2015 John Wiley & Sons Ltd.

In silico identification of anthropogenic chemicals as ligands of zebrafish sex hormone binding globulin

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thorsteinson, Nels; Ban, Fuqiang; Santos-Filho, Osvaldo

2009-01-01

Anthropogenic compounds with the capacity to interact with the steroid-binding site of sex hormone binding globulin (SHBG) pose health risks to humans and other vertebrates including fish. Building on studies of human SHBG, we have applied in silico drug discovery methods to identify potential binders for SHBG in zebrafish (Danio rerio) as a model aquatic organism. Computational methods, including; homology modeling, molecular dynamics simulations, virtual screening, and 3D QSAR analysis, successfully identified 6 non-steroidal substances from the ZINC chemical database that bind to zebrafish SHBG (zfSHBG) with low-micromolar to nanomolar affinities, as determined by a competitive ligand-binding assay. We alsomore » screened 80,000 commercial substances listed by the European Chemicals Bureau and Environment Canada, and 6 non-steroidal hits from this in silico screen were tested experimentally for zfSHBG binding. All 6 of these compounds displaced the [{sup 3}H]5{alpha}-dihydrotestosterone used as labeled ligand in the zfSHBG screening assay when tested at a 33 {mu}M concentration, and 3 of them (hexestrol, 4-tert-octylcatechol, and dihydrobenzo(a)pyren-7(8H)-one) bind to zfSHBG in the micromolar range. The study demonstrates the feasibility of large-scale in silico screening of anthropogenic compounds that may disrupt or highjack functionally important protein:ligand interactions. Such studies could increase the awareness of hazards posed by existing commercial chemicals at relatively low cost.« less

In silico analysis of protein toxin and bacteriocins from Lactobacillus paracasei SD1 genome and available online databases

PubMed Central

Surachat, Komwit; Sangket, Unitsa; Deachamag, Panchalika; Chotigeat, Wilaiwan

2017-01-01

Lactobacillus paracasei SD1 is a potential probiotic strain due to its ability to survive several conditions in human dental cavities. To ascertain its safety for human use, we therefore performed a comprehensive bioinformatics analysis and characterization of the bacterial protein toxins produced by this strain. We report the complete genome of Lactobacillus paracasei SD1 and its comparison to other Lactobacillus genomes. Additionally, we identify and analyze its protein toxins and antimicrobial proteins using reliable online database resources and establish its phylogenetic relationship with other bacterial genomes. Our investigation suggests that this strain is safe for human use and contains several bacteriocins that confer health benefits to the host. An in silico analysis of protein-protein interactions between the target bacteriocins and the microbial proteins gtfB and luxS of Streptococcus mutans was performed and is discussed here. PMID:28837656

The cytochrome P450 genes of channel catfish: their involvement in disease defense responses as revealed by meta-analysis of RNA-Seq datasets

USDA-ARS?s Scientific Manuscript database

Cytochrome P450s (CYPs) encode one of the most diverse enzyme superfamily in nature. They catalyze oxidative reactions of endogenous molecules and exogenous chemicals. Methods: We identifiedCYPs genes through in silico analysis using EST, RNA-Seq and genome databases of channel catfish.Phylogenetic ...

Cadmium effects on sperm morphology and semenogelin with relates to increased ROS in infertile smokers: An in vitro and in silico approach.

PubMed

Ranganathan, Parameswari; Rao, Kamini A; Sudan, Jesu Jaya; Balasundaram, Sridharan

2018-06-01

Smoking releases cadmium (Cd), the metal toxicant which causes an imbalance in reactive oxygen species level in seminal plasma. This imbalance is envisaged to impair the sperm DNA morphology and thereby result in male infertility. In order to correlate this association, we performed in vitro and in silico studies and evaluated the influence of reactive oxygen species imbalance on sperm morphology impairments due to smoking. The study included 76 infertile smokers, 72 infertile non-smokers, 68 fertile smokers and 74 fertile non-smokers (control). Semen samples were collected at regular intervals from all the subjects. Semen parameters were examined by computer assisted semen analysis, quantification of metal toxicant by atomic absorption spectrophotometer, assessment of antioxidants through enzymatic and non-enzymatic methods, diagnosis of reactive oxygen species by nitro blue tetrazolium method and Cd influence on sperm protein by in vitro and in silico methods. Our analysis revealed that the levels of cigarette toxicants in semen were high, accompanied by low levels of antioxidants in seminal plasma of infertile smoker subjects. In addition the investigation of Cd treated sperm cells through scanning electronic microscope showed the mid piece damage of spermatozoa. The dispersive X-ray analysis to identify the elemental composition further confirmed the presence of Cd. Finally, the in-silico analysis on semenogelin sequences revealed the D-H-D motif which represents a favourable binding site for Cd coordination. Our findings clearly indicated the influence of Cd on reactive oxygen species leading to impaired sperm morphology leading to male infertility. Copyright © 2018 Society for Biology of Reproduction & the Institute of Animal Reproduction and Food Research of Polish Academy of Sciences in Olsztyn. Published by Elsevier B.V. All rights reserved.

Genome-Wide Analyses of the Soybean F-Box Gene Family in Response to Salt Stress

PubMed Central

Jia, Qi; Xiao, Zhi-Xia; Wong, Fuk-Ling; Sun, Song; Liang, Kang-Jing; Lam, Hon-Ming

2017-01-01

The F-box family is one of the largest gene families in plants that regulate diverse life processes, including salt responses. However, the knowledge of the soybean F-box genes and their roles in salt tolerance remains limited. Here, we conducted a genome-wide survey of the soybean F-box family, and their expression analysis in response to salinity via in silico analysis of online RNA-sequencing (RNA-seq) data and quantitative reverse-transcription polymerase chain reaction (qRT-PCR) to predict their potential functions. A total of 725 potential F-box proteins encoded by 509 genes were identified and classified into 9 subfamilies. The gene structures, conserved domains and chromosomal distributions were characterized. There are 76 pairs of duplicate genes identified, including genome-wide segmental and tandem duplication events, which lead to the expansion of the number of F-box genes. The in silico expression analysis showed that these genes would be involved in diverse developmental functions and play an important role in salt response. Our qRT-PCR analysis confirmed 12 salt-responding F-box genes. Overall, our results provide useful information on soybean F-box genes, especially their potential roles in salt tolerance. PMID:28417911

Genome-Wide Analyses of the Soybean F-Box Gene Family in Response to Salt Stress.

PubMed

Jia, Qi; Xiao, Zhi-Xia; Wong, Fuk-Ling; Sun, Song; Liang, Kang-Jing; Lam, Hon-Ming

2017-04-12

The F-box family is one of the largest gene families in plants that regulate diverse life processes, including salt responses. However, the knowledge of the soybean F-box genes and their roles in salt tolerance remains limited. Here, we conducted a genome-wide survey of the soybean F-box family, and their expression analysis in response to salinity via in silico analysis of online RNA-sequencing (RNA-seq) data and quantitative reverse-transcription polymerase chain reaction (qRT-PCR) to predict their potential functions. A total of 725 potential F-box proteins encoded by 509 genes were identified and classified into 9 subfamilies. The gene structures, conserved domains and chromosomal distributions were characterized. There are 76 pairs of duplicate genes identified, including genome-wide segmental and tandem duplication events, which lead to the expansion of the number of F-box genes. The in silico expression analysis showed that these genes would be involved in diverse developmental functions and play an important role in salt response. Our qRT-PCR analysis confirmed 12 salt-responding F-box genes. Overall, our results provide useful information on soybean F-box genes, especially their potential roles in salt tolerance.

Unlocking the potential of publicly available microarray data using inSilicoDb and inSilicoMerging R/Bioconductor packages.

PubMed

Taminau, Jonatan; Meganck, Stijn; Lazar, Cosmin; Steenhoff, David; Coletta, Alain; Molter, Colin; Duque, Robin; de Schaetzen, Virginie; Weiss Solís, David Y; Bersini, Hugues; Nowé, Ann

2012-12-24

With an abundant amount of microarray gene expression data sets available through public repositories, new possibilities lie in combining multiple existing data sets. In this new context, analysis itself is no longer the problem, but retrieving and consistently integrating all this data before delivering it to the wide variety of existing analysis tools becomes the new bottleneck. We present the newly released inSilicoMerging R/Bioconductor package which, together with the earlier released inSilicoDb R/Bioconductor package, allows consistent retrieval, integration and analysis of publicly available microarray gene expression data sets. Inside the inSilicoMerging package a set of five visual and six quantitative validation measures are available as well. By providing (i) access to uniformly curated and preprocessed data, (ii) a collection of techniques to remove the batch effects between data sets from different sources, and (iii) several validation tools enabling the inspection of the integration process, these packages enable researchers to fully explore the potential of combining gene expression data for downstream analysis. The power of using both packages is demonstrated by programmatically retrieving and integrating gene expression studies from the InSilico DB repository [https://insilicodb.org/app/].

Definition and characterization of a "trypsinosome" from specific peptide characteristics by nano-HPLC-MS/MS and in silico analysis of complex protein mixtures.

PubMed

Le Bihan, Thierry; Robinson, Mark D; Stewart, Ian I; Figeys, Daniel

2004-01-01

Although HPLC-ESI-MS/MS is rapidly becoming an indispensable tool for the analysis of peptides in complex mixtures, the sequence coverage it affords is often quite poor. Low protein expression resulting in peptide signal intensities that fall below the limit of detection of the MS system in combination with differences in peptide ionization efficiency plays a significant role in this. A second important factor stems from differences in physicochemical properties of each peptide and how these properties relate to chromatographic retention and ultimate detection. To identify and understand those properties, we compared data from experimentally identified peptides with data from peptides predicted by in silico digest of all corresponding proteins in the experimental set. Three different complex protein mixtures extracted were used to define a training set to evaluate the amino acid retention coefficients based on linear regression analysis. The retention coefficients were also compared with other previous hydrophobic and retention scale. From this, we have constructed an empirical model that can be readily used to predict peptides that are likely to be observed on our HPLC-ESI-MS/MS system based on their physicochemical properties. Finally, we demonstrated that in silico prediction of peptides and their retention coefficients can be used to generate an inclusion list for a targeted mass spectrometric identification of low abundance proteins in complex protein samples. This approach is based on experimentally derived data to calibrate the method and therefore may theoretically be applied to any HPLC-MS/MS system on which data are being generated.

Methodological flaws introduce strong bias into molecular analysis of microbial populations.

PubMed

Krakat, N; Anjum, R; Demirel, B; Schröder, P

2017-02-01

In this study, we report how different cell disruption methods, PCR primers and in silico analyses can seriously bias results from microbial population studies, with consequences for the credibility and reproducibility of the findings. Our results emphasize the pitfalls of commonly used experimental methods that can seriously weaken the interpretation of results. Four different cell lysis methods, three commonly used primer pairs and various computer-based analyses were applied to investigate the microbial diversity of a fermentation sample composed of chicken dung. The fault-prone, but still frequently used, amplified rRNA gene restriction analysis was chosen to identify common weaknesses. In contrast to other studies, we focused on the complete analytical process, from cell disruption to in silico analysis, and identified potential error rates. This identified a wide disagreement of results between applied experimental approaches leading to very different community structures depending on the chosen approach. The interpretation of microbial diversity data remains a challenge. In order to accurately investigate the taxonomic diversity and structure of prokaryotic communities, we suggest a multi-level approach combining DNA-based and DNA-independent techniques. The identified weaknesses of commonly used methods to study microbial diversity can be overcome by a multi-level approach, which produces more reliable data about the fate and behaviour of microbial communities of engineered habitats such as biogas plants, so that the best performance can be ensured. © 2016 The Society for Applied Microbiology.

When Genomics Is Not Enough: Experimental Evidence for a Decrease in LINE-1 Activity During the Evolution of Australian Marsupials

PubMed Central

Gallus, Susanne; Lammers, Fritjof

2016-01-01

The autonomous transposable element LINE-1 is a highly abundant element that makes up between 15% and 20% of therian mammal genomes. Since their origin before the divergence of marsupials and placental mammals, LINE-1 elements have contributed actively to the genome landscape. A previous in silico screen of the Tasmanian devil genome revealed a lack of functional coding LINE-1 sequences. In this study we present the results of an in vitro analysis from a partial LINE-1 reverse transcriptase coding sequence in five marsupial species. Our experimental screen supports the in silico findings of the genome-wide degradation of LINE-1 sequences in the Tasmanian devil, and identifies a high frequency of degraded LINE-1 sequences in other Australian marsupials. The comparison between the experimentally obtained LINE-1 sequences and reference genome assemblies suggests that conclusions from in silico analyses of retrotransposition activity can be influenced by incomplete genome assemblies from short reads. PMID:27389686

Molecular genetic analysis of macular corneal dystrophy patients from North India.

PubMed

Paliwal, Preeti; Sharma, Arundhati; Tandon, Radhika; Sharma, Namrata; Titiyal, Jeevan S; Sen, Seema; Vajpayee, Rasik B

2012-01-01

To identify underlying genetic defects in the carbohydrate sulfotransferase-6 (CHST6) gene in North Indian patients with macular corneal dystrophy (MCD). 30 clinically diagnosed MCD patients from 21 families and 50 healthy normal controls were recruited in the study. Detailed clinical evaluation in the patients was undertaken followed by histopathology and ultrastructural studies in corneal tissues. DNA from blood samples was amplified for the CHST6 coding and upstream region followed by direct sequencing and in silico analysis. We identified pathogenic mutations in 17 patients from 11 families. Of these 4 were novel (p.Ser54Tyr, p.Gln58Arg, p.Leu59His and p.Leu293Phe), 2 were previously reported (Arg93His and Glu274Lys) homozygous, 1 heterozygous stop codon (p.Trp123X) and 2 compound heterozygous (p.Arg93His + p.Arg97Pro; p.Leu22Arg + p.Gln58X) mutations. A missense single-nucleotide polymorphism was also identified in 11 patients. The novel mutations were conserved as shown by in silico analysis. Thirteen patients did not show any pathogenic CHST6 changes. This is the first report on molecular analysis of MCD in North Indian patients. All cases could not be explained by mutations in CHST6, suggesting that MCD may result from other changes in the regulatory elements of CHST6 or from genetic heterogeneity. Copyright © 2012 S. Karger AG, Basel.

In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development.

PubMed

Ozerov, Ivan V; Lezhnina, Ksenia V; Izumchenko, Evgeny; Artemov, Artem V; Medintsev, Sergey; Vanhaelen, Quentin; Aliper, Alexander; Vijg, Jan; Osipov, Andreyan N; Labat, Ivan; West, Michael D; Buzdin, Anton; Cantor, Charles R; Nikolsky, Yuri; Borisov, Nikolay; Irincheeva, Irina; Khokhlovich, Edward; Sidransky, David; Camargo, Miguel Luiz; Zhavoronkov, Alex

2016-11-16

Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy.

In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development

PubMed Central

Ozerov, Ivan V.; Lezhnina, Ksenia V.; Izumchenko, Evgeny; Artemov, Artem V.; Medintsev, Sergey; Vanhaelen, Quentin; Aliper, Alexander; Vijg, Jan; Osipov, Andreyan N.; Labat, Ivan; West, Michael D.; Buzdin, Anton; Cantor, Charles R.; Nikolsky, Yuri; Borisov, Nikolay; Irincheeva, Irina; Khokhlovich, Edward; Sidransky, David; Camargo, Miguel Luiz; Zhavoronkov, Alex

2016-01-01

Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy. PMID:27848968

In silico lineage tracing through single cell transcriptomics identifies a neural stem cell population in planarians.

PubMed

Molinaro, Alyssa M; Pearson, Bret J

2016-04-27

The planarian Schmidtea mediterranea is a master regenerator with a large adult stem cell compartment. The lack of transgenic labeling techniques in this animal has hindered the study of lineage progression and has made understanding the mechanisms of tissue regeneration a challenge. However, recent advances in single-cell transcriptomics and analysis methods allow for the discovery of novel cell lineages as differentiation progresses from stem cell to terminally differentiated cell. Here we apply pseudotime analysis and single-cell transcriptomics to identify adult stem cells belonging to specific cellular lineages and identify novel candidate genes for future in vivo lineage studies. We purify 168 single stem and progeny cells from the planarian head, which were subjected to single-cell RNA sequencing (scRNAseq). Pseudotime analysis with Waterfall and gene set enrichment analysis predicts a molecularly distinct neoblast sub-population with neural character (νNeoblasts) as well as a novel alternative lineage. Using the predicted νNeoblast markers, we demonstrate that a novel proliferative stem cell population exists adjacent to the brain. scRNAseq coupled with in silico lineage analysis offers a new approach for studying lineage progression in planarians. The lineages identified here are extracted from a highly heterogeneous dataset with minimal prior knowledge of planarian lineages, demonstrating that lineage purification by transgenic labeling is not a prerequisite for this approach. The identification of the νNeoblast lineage demonstrates the usefulness of the planarian system for computationally predicting cellular lineages in an adult context coupled with in vivo verification.

In silico predicted reproductive endocrine transcriptional regulatory networks during zebrafish (Danio rerio) development.

PubMed

Hala, D

2017-03-21

The interconnected topology of transcriptional regulatory networks (TRNs) readily lends to mathematical (or in silico) representation and analysis as a stoichiometric matrix. Such a matrix can be 'solved' using the mathematical method of extreme pathway (ExPa) analysis, which identifies uniquely activated genes subject to transcription factor (TF) availability. In this manuscript, in silico multi-tissue TRN models of brain, liver and gonad were used to study reproductive endocrine developmental programming in zebrafish (Danio rerio) from 0.25h post fertilization (hpf; zygote) to 90 days post fertilization (dpf; adult life stage). First, properties of TRN models were studied by sequentially activating all genes in multi-tissue models. This analysis showed the brain to exhibit lowest proportion of co-regulated genes (19%) relative to liver (23%) and gonad (32%). This was surprising given that the brain comprised 75% and 25% more TFs than liver and gonad respectively. Such 'hierarchy' of co-regulatory capability (brain

Metabolic engineering of Escherichia coli for the production of l-valine based on transcriptome analysis and in silico gene knockout simulation

PubMed Central

Park, Jin Hwan; Lee, Kwang Ho; Kim, Tae Yong; Lee, Sang Yup

2007-01-01

The l-valine production strain of Escherichia coli was constructed by rational metabolic engineering and stepwise improvement based on transcriptome analysis and gene knockout simulation of the in silico genome-scale metabolic network. Feedback inhibition of acetohydroxy acid synthase isoenzyme III by l-valine was removed by site-directed mutagenesis, and the native promoter containing the transcriptional attenuator leader regions of the ilvGMEDA and ilvBN operon was replaced with the tac promoter. The ilvA, leuA, and panB genes were deleted to make more precursors available for l-valine biosynthesis. This engineered Val strain harboring a plasmid overexpressing the ilvBN genes produced 1.31 g/liter l-valine. Comparative transcriptome profiling was performed during batch fermentation of the engineered and control strains. Among the down-regulated genes, the lrp and ygaZH genes, which encode a global regulator Lrp and l-valine exporter, respectively, were overexpressed. Amplification of the lrp, ygaZH, and lrp-ygaZH genes led to the enhanced production of l-valine by 21.6%, 47.1%, and 113%, respectively. Further improvement was achieved by using in silico gene knockout simulation, which identified the aceF, mdh, and pfkA genes as knockout targets. The VAMF strain (Val ΔaceF Δmdh ΔpfkA) overexpressing the ilvBN, ilvCED, ygaZH, and lrp genes was able to produce 7.55 g/liter l-valine from 20 g/liter glucose in batch culture, resulting in a high yield of 0.378 g of l-valine per gram of glucose. These results suggest that an industrially competitive strain can be efficiently developed by metabolic engineering based on combined rational modification, transcriptome profiling, and systems-level in silico analysis. PMID:17463081

In silico pathway analysis in cervical carcinoma reveals potential new targets for treatment

PubMed Central

van Dam, Peter A.; van Dam, Pieter-Jan H. H.; Rolfo, Christian; Giallombardo, Marco; van Berckelaer, Christophe; Trinh, Xuan Bich; Altintas, Sevilay; Huizing, Manon; Papadimitriou, Kostas; Tjalma, Wiebren A. A.; van Laere, Steven

2016-01-01

An in silico pathway analysis was performed in order to improve current knowledge on the molecular drivers of cervical cancer and detect potential targets for treatment. Three publicly available Affymetrix gene expression data-sets (GSE5787, GSE7803, GSE9750) were retrieved, vouching for a total of 9 cervical cancer cell lines (CCCLs), 39 normal cervical samples, 7 CIN3 samples and 111 cervical cancer samples (CCSs). Predication analysis of microarrays was performed in the Affymetrix sets to identify cervical cancer biomarkers. To select cancer cell-specific genes the CCSs were compared to the CCCLs. Validated genes were submitted to a gene set enrichment analysis (GSEA) and Expression2Kinases (E2K). In the CCSs a total of 1,547 probe sets were identified that were overexpressed (FDR < 0.1). Comparing to CCCLs 560 probe sets (481 unique genes) had a cancer cell-specific expression profile, and 315 of these genes (65%) were validated. GSEA identified 5 cancer hallmarks enriched in CCSs (P < 0.01 and FDR < 0.25) showing that deregulation of the cell cycle is a major component of cervical cancer biology. E2K identified a protein-protein interaction (PPI) network of 162 nodes (including 20 drugable kinases) and 1626 edges. This PPI-network consists of 5 signaling modules associated with MYC signaling (Module 1), cell cycle deregulation (Module 2), TGFβ-signaling (Module 3), MAPK signaling (Module 4) and chromatin modeling (Module 5). Potential targets for treatment which could be identified were CDK1, CDK2, ABL1, ATM, AKT1, MAPK1, MAPK3 among others. The present study identified important driver pathways in cervical carcinogenesis which should be assessed for their potential therapeutic drugability. PMID:26701206

Genetic Epidemiology of Glucose-6-Dehydrogenase Deficiency in the Arab World.

PubMed

Doss, C George Priya; Alasmar, Dima R; Bux, Reem I; Sneha, P; Bakhsh, Fadheela Dad; Al-Azwani, Iman; Bekay, Rajaa El; Zayed, Hatem

2016-11-17

A systematic search was implemented using four literature databases (PubMed, Embase, Science Direct and Web of Science) to capture all the causative mutations of Glucose-6-phosphate dehydrogenase (G6PD) deficiency (G6PDD) in the 22 Arab countries. Our search yielded 43 studies that captured 33 mutations (23 missense, one silent, two deletions, and seven intronic mutations), in 3,430 Arab patients with G6PDD. The 23 missense mutations were then subjected to phenotypic classification using in silico prediction tools, which were compared to the WHO pathogenicity scale as a reference. These in silico tools were tested for their predicting efficiency using rigorous statistical analyses. Of the 23 missense mutations, p.S188F, p.I48T, p.N126D, and p.V68M, were identified as the most common mutations among Arab populations, but were not unique to the Arab world, interestingly, our search strategy found four other mutations (p.N135T, p.S179N, p.R246L, and p.Q307P) that are unique to Arabs. These mutations were exposed to structural analysis and molecular dynamics simulation analysis (MDSA), which predicting these mutant forms as potentially affect the enzyme function. The combination of the MDSA, structural analysis, and in silico predictions and statistical tools we used will provide a platform for future prediction accuracy for the pathogenicity of genetic mutations.

Simultaneous use of in silico design and a correlated mutation network as a tool to efficiently guide enzyme engineering.

PubMed

Nobili, Alberto; Tao, Yifeng; Pavlidis, Ioannis V; van den Bergh, Tom; Joosten, Henk-Jan; Tan, Tianwei; Bornscheuer, Uwe T

2015-03-23

In order to improve the efficiency of directed evolution experiments, in silico multiple-substrate clustering was combined with an analysis of the variability of natural enzymes within a protein superfamily. This was applied to a Pseudomonas fluorescens esterase (PFE I) targeting the enantioselective hydrolysis of 3-phenylbutyric acid esters. Data reported in the literature for nine substrates were used for the clustering meta-analysis of the docking conformations in wild-type PFE I, and this highlighted a tryptophan residue (W28) as an interesting target. Exploration of the most frequently, naturally occurring amino acids at this position suggested that the reduced flexibility observed in the case of the W28F variant leads to enhancement of the enantioselectivity. This mutant was subsequently combined with mutations identified in a library based on analysis of a correlated mutation network. By interrogation of <80 variants a mutant with 15-fold improved enantioselectivity was found. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Linking disease-associated genes to regulatory networks via promoter organization

PubMed Central

Döhr, S.; Klingenhoff, A.; Maier, H.; de Angelis, M. Hrabé; Werner, T.; Schneider, R.

2005-01-01

Pathway- or disease-associated genes may participate in more than one transcriptional co-regulation network. Such gene groups can be readily obtained by literature analysis or by high-throughput techniques such as microarrays or protein-interaction mapping. We developed a strategy that defines regulatory networks by in silico promoter analysis, finding potentially co-regulated subgroups without a priori knowledge. Pairs of transcription factor binding sites conserved in orthologous genes (vertically) as well as in promoter sequences of co-regulated genes (horizontally) were used as seeds for the development of promoter models representing potential co-regulation. This approach was applied to a Maturity Onset Diabetes of the Young (MODY)-associated gene list, which yielded two models connecting functionally interacting genes within MODY-related insulin/glucose signaling pathways. Additional genes functionally connected to our initial gene list were identified by database searches with these promoter models. Thus, data-driven in silico promoter analysis allowed integrating molecular mechanisms with biological functions of the cell. PMID:15701758

In Silico Analysis of Expression Data for Identification of Genes Involved in Spatial Accumulation of Calcium in Developing Seeds of Rice

PubMed Central

Goel, Anshita; Gaur, Vikram S.; Arora, Sandeep; Gupta, Sanjay

2012-01-01

Abstract The calcium (Ca2+) transporters, like Ca2+ channels, Ca2+ ATPases, and Ca2+ exchangers, are instrumental for signaling and transport. However, the mechanism by which they orchestrate the accumulation of Ca2+ in grain filling has not yet been investigated. Hence the present study was designed to identify the potential calcium transporter genes that may be responsible for the spatial accumulation of calcium during grain filling. In silico expression analyses were performed to identify Ca2+ transporters that predominantly express during the different developmental stages of Oryza sativa. A total of 13 unique calcium transporters (7 from massively parallel signature sequencing [MPSS] data analysis, and 9 from microarray analysis) were identified. Analysis of variance (ANOVA) revealed differential expression of the transporters across tissues, and principal component analysis (PCA) exhibited their seed-specific distinctive expression profile. Interestingly, Ca2+ exchanger genes are highly expressed in the initial stages, whereas some Ca2+ ATPase genes are highly expressed throughout seed development. Furthermore, analysis of the cis-elements located in the promoter region of the subset of 13 genes suggested that Dof proteins play essential roles in regulating the expression of Ca2+ transporter genes during rice seed development. Based on these results, we developed a hypothetical model explaining the transport and tissue specific distribution of calcium in developing cereal seeds. The model may be extrapolated to understand the mechanism behind the exceptionally high level of calcium accumulation seen in grains like finger millet. PMID:22734689

Identification of potential drug targets by subtractive genome analysis of Escherichia coli O157:H7: an in silico approach

PubMed Central

Mondal, Shakhinur Islam; Ferdous, Sabiha; Jewel, Nurnabi Azad; Akter, Arzuba; Mahmud, Zabed; Islam, Md Muzahidul; Afrin, Tanzila; Karim, Nurul

2015-01-01

Bacterial enteric infections resulting in diarrhea, dysentery, or enteric fever constitute a huge public health problem, with more than a billion episodes of disease annually in developing and developed countries. In this study, the deadly agent of hemorrhagic diarrhea and hemolytic uremic syndrome, Escherichia coli O157:H7 was investigated with extensive computational approaches aimed at identifying novel and broad-spectrum antibiotic targets. A systematic in silico workflow consisting of comparative genomics, metabolic pathways analysis, and additional drug prioritizing parameters was used to identify novel drug targets that were essential for the pathogen’s survival but absent in its human host. Comparative genomic analysis of Kyoto Encyclopedia of Genes and Genomes annotated metabolic pathways identified 350 putative target proteins in E. coli O157:H7 which showed no similarity to human proteins. Further bio-informatic approaches including prediction of subcellular localization, calculation of molecular weight, and web-based investigation of 3D structural characteristics greatly aided in filtering the potential drug targets from 350 to 120. Ultimately, 44 non-homologous essential proteins of E. coli O157:H7 were prioritized and proved to have the eligibility to become novel broad-spectrum antibiotic targets and DNA polymerase III alpha (dnaE) was the top-ranked among these targets. Moreover, druggability of each of the identified drug targets was evaluated by the DrugBank database. In addition, 3D structure of the dnaE was modeled and explored further for in silico docking with ligands having potential druggability. Finally, we confirmed that the compounds N-coeleneterazine and N-(1,4-dihydro-5H-tetrazol-5-ylidene)-9-oxo-9H-xanthene-2-sulfon-amide were the most suitable ligands of dnaE and hence proposed as the potential inhibitors of this target protein. The results of this study could facilitate the discovery and release of new and effective drugs against E. coli O157:H7 and other deadly human bacterial pathogens. PMID:26677339

Alzheimer's disease biomarker discovery using in silico literature mining and clinical validation

PubMed Central

2012-01-01

Background Alzheimer’s Disease (AD) is the most widespread form of dementia in the elderly but despite progress made in recent years towards a mechanistic understanding, there is still an urgent need for disease modification therapy and for early diagnostic tests. Substantial international efforts are being made to discover and validate biomarkers for AD using candidate analytes and various data-driven 'omics' approaches. Cerebrospinal fluid is in many ways the tissue of choice for biomarkers of brain disease but is limited by patient and clinician acceptability, and increasing attention is being paid to the search for blood-based biomarkers. The aim of this study was to use a novel in silico approach to discover a set of candidate biomarkers for AD. Methods We used an in silico literature mining approach to identify potential biomarkers by creating a summarized set of assertional metadata derived from relevant legacy information. We then assessed the validity of this approach using direct assays of the identified biomarkers in plasma by immunodetection methods. Results Using this in silico approach, we identified 25 biomarker candidates, at least three of which have subsequently been reported to be altered in blood or CSF from AD patients. Two further candidate biomarkers, indicated from the in silico approach, were choline acetyltransferase and urokinase-type plasminogen activator receptor. Using immunodetection, we showed that, in a large sample set, these markers are either altered in disease or correlate with MRI markers of atrophy. Conclusions These data support as a proof of concept the use of data mining and in silico analyses to derive valid biomarker candidates for AD and, by extension, for other disorders. PMID:23113945

In-silico Metabolome Target Analysis Towards PanC-based Antimycobacterial Agent Discovery.

PubMed

Khoshkholgh-Sima, Baharak; Sardari, Soroush; Izadi Mobarakeh, Jalal; Khavari-Nejad, Ramezan Ali

2015-01-01

Mycobacterium tuberculosis, the main cause of tuberculosis (TB), has still remained a global health crisis especially in developing countries. Tuberculosis treatment is a laborious and lengthy process with high risk of noncompliance, cytotoxicity adverse events and drug resistance in patient. Recently, there has been an alarming rise of drug resistant in TB. In this regard, it is an unmet need to develop novel antitubercular medicines that target new or more effective biochemical pathways to prevent drug resistant Mycobacterium. Integrated study of metabolic pathways through in-silico approach played a key role in antimycobacterial design process in this study. Our results suggest that pantothenate synthetase (PanC), anthranilate phosphoribosyl transferase (TrpD) and 3-isopropylmalate dehydratase (LeuD) might be appropriate drug targets. In the next step, in-silico ligand analysis was used for more detailed study of chemical tractability of targets. This was helpful to identify pantothenate synthetase (PanC, Rv3602c) as the best target for antimycobacterial design procedure. Virtual library screening on the best ligand of PanC was then performed for inhibitory ligand design. At the end, five chemical intermediates showed significant inhibition of Mycobacterium bovis with good selectivity indices (SI) ≥10 according to Tuberculosis Antimicrobial Acquisition & Coordinating Facility of US criteria for antimycobacterial screening programs.

In silico prediction of splice-altering single nucleotide variants in the human genome.

PubMed

Jian, Xueqiu; Boerwinkle, Eric; Liu, Xiaoming

2014-12-16

In silico tools have been developed to predict variants that may have an impact on pre-mRNA splicing. The major limitation of the application of these tools to basic research and clinical practice is the difficulty in interpreting the output. Most tools only predict potential splice sites given a DNA sequence without measuring splicing signal changes caused by a variant. Another limitation is the lack of large-scale evaluation studies of these tools. We compared eight in silico tools on 2959 single nucleotide variants within splicing consensus regions (scSNVs) using receiver operating characteristic analysis. The Position Weight Matrix model and MaxEntScan outperformed other methods. Two ensemble learning methods, adaptive boosting and random forests, were used to construct models that take advantage of individual methods. Both models further improved prediction, with outputs of directly interpretable prediction scores. We applied our ensemble scores to scSNVs from the Catalogue of Somatic Mutations in Cancer database. Analysis showed that predicted splice-altering scSNVs are enriched in recurrent scSNVs and known cancer genes. We pre-computed our ensemble scores for all potential scSNVs across the human genome, providing a whole genome level resource for identifying splice-altering scSNVs discovered from large-scale sequencing studies.

An in silico pipeline to filter the Toxoplasma gondii proteome for proteins that could traffic to the host cell nucleus and influence host cell epigenetic regulation.

PubMed

Syn, Genevieve; Blackwell, Jenefer M; Jamieson, Sarra E; Francis, Richard W

2018-01-01

Toxoplasma gondii uses epigenetic mechanisms to regulate both endogenous and host cell gene expression. To identify genes with putative epigenetic functions, we developed an in silico pipeline to interrogate the T. gondii proteome of 8313 proteins. Step 1 employs PredictNLS and NucPred to identify genes predicted to target eukaryotic nuclei. Step 2 uses GOLink to identify proteins of epigenetic function based on Gene Ontology terms. This resulted in 611 putative nuclear localised proteins with predicted epigenetic functions. Step 3 filtered for secretory proteins using SignalP, SecretomeP, and experimental data. This identified 57 of the 611 putative epigenetic proteins as likely to be secreted. The pipeline is freely available online, uses open access tools and software with user-friendly Perl scripts to automate and manage the results, and is readily adaptable to undertake any such in silico search for genes contributing to particular functions.

Text mining-based in silico drug discovery in oral mucositis caused by high-dose cancer therapy.

PubMed

Kirk, Jon; Shah, Nirav; Noll, Braxton; Stevens, Craig B; Lawler, Marshall; Mougeot, Farah B; Mougeot, Jean-Luc C

2018-08-01

Oral mucositis (OM) is a major dose-limiting side effect of chemotherapy and radiation used in cancer treatment. Due to the complex nature of OM, currently available drug-based treatments are of limited efficacy. Our objectives were (i) to determine genes and molecular pathways associated with OM and wound healing using computational tools and publicly available data and (ii) to identify drugs formulated for topical use targeting the relevant OM molecular pathways. OM and wound healing-associated genes were determined by text mining, and the intersection of the two gene sets was selected for gene ontology analysis using the GeneCodis program. Protein interaction network analysis was performed using STRING-db. Enriched gene sets belonging to the identified pathways were queried against the Drug-Gene Interaction database to find drug candidates for topical use in OM. Our analysis identified 447 genes common to both the "OM" and "wound healing" text mining concepts. Gene enrichment analysis yielded 20 genes representing six pathways and targetable by a total of 32 drugs which could possibly be formulated for topical application. A manual search on ClinicalTrials.gov confirmed no relevant pathway/drug candidate had been overlooked. Twenty-five of the 32 drugs can directly affect the PTGS2 (COX-2) pathway, the pathway that has been targeted in previous clinical trials with limited success. Drug discovery using in silico text mining and pathway analysis tools can facilitate the identification of existing drugs that have the potential of topical administration to improve OM treatment.

In Silico Prediction and In Vitro Characterization of Multifunctional Human RNase3

PubMed Central

Kuo, Ping-Hsueh; Chen, Chien-Jung; Chang, Hsiu-Hui; Fang, Shun-lung; Wu, Wei-Shuo; Lai, Yiu-Kay; Pai, Tun-Wen; Chang, Margaret Dah-Tsyr

2013-01-01

Human ribonucleases A (hRNaseA) superfamily consists of thirteen members with high-structure similarities but exhibits divergent physiological functions other than RNase activity. Evolution of hRNaseA superfamily has gained novel functions which may be preserved in a unique region or domain to account for additional molecular interactions. hRNase3 has multiple functions including ribonucleolytic, heparan sulfate (HS) binding, cellular binding, endocytic, lipid destabilization, cytotoxic, and antimicrobial activities. In this study, three putative multifunctional regions, 34RWRCK38 (HBR1), 75RSRFR79 (HBR2), and 101RPGRR105 (HBR3), of hRNase3 have been identified employing in silico sequence analysis and validated employing in vitro activity assays. A heparin binding peptide containing HBR1 is characterized to act as a key element associated with HS binding, cellular binding, and lipid binding activities. In this study, we provide novel insights to identify functional regions of hRNase3 that may have implications for all hRNaseA superfamily members. PMID:23484086

Using diverse U.S. beef cattle genomes to identify missense mutations in EPAS1, a gene associated with pulmonary hypertension

USDA-ARS?s Scientific Manuscript database

The availability of whole genome sequence (WGS) data has made it possible to discover protein variants in silico. However, existing bovine WGS databases do not show data in a form conducive to protein variant analysis, and tend to under represent the breadth of genetic diversity in U.S. beef cattle...

Rapid in silico cloning of genes using expressed sequence tags (ESTs).

PubMed

Gill, R W; Sanseau, P

2000-01-01

Expressed sequence tags (ESTs) are short single-pass DNA sequences obtained from either end of cDNA clones. These ESTs are derived from a vast number of cDNA libraries obtained from different species. Human ESTs are the bulk of the data and have been widely used to identify new members of gene families, as markers on the human chromosomes, to discover polymorphism sites and to compare expression patterns in different tissues or pathologies states. Information strategies have been devised to query EST databases. Since most of the analysis is performed with a computer, the term "in silico" strategy has been coined. In this chapter we will review the current status of EST databases, the pros and cons of EST-type data and describe possible strategies to retrieve meaningful information.

In vitro and in silico analyses of Vicia faba L. on Peroxisome proliferator-activated receptor gamma.

PubMed

Prabhu, D Sathya; Rajeswari, V Devi

2018-06-20

The agonists of peroxisome proliferator-activated receptor gamma (PPARγ) from natural victual products were used as antidiabetic agents. Faba bean (Vicia faba L.) is a consequential legume that was known to possess potential antidiabetic activity, whose mechanism of action was unknown. The current study was focused to ascertain gene expression of the nuclear receptor PPARγ by Faba bean pod extract in rat cell lines (RINm5F).The real-time polymerase chain reaction analysis demonstrated that Faba bean pod extract in concentrations of 160 µg/mL have shown 4.97-fold stimulation compared with control. The cells treated with 320 µg/mL has shown 5.89-fold upregulation, respectively. Furthermore, in silico docking analysis was carried out against PPARγ, using the bioactive compounds identified from Faba bean pod extracts, which were known reported compounds from the literature. The results suggest that gene expression of PPARγ was inhibited by the constituents in Faba bean. In silico analysis prognosticates, butein has a high binding energy (-8.6 kcal/mol) with an atomic contact energy of -214.10, followed by Apigenin and Quercetin against PPARγ. Similarly, the percentage of interaction was high for butein, followed by Apigenin and Quercetin than other compounds comparatively. Hence, the results conclude inhibition of PPARγ by the bioactive compounds from Faba bean, which may provide insights into developing future therapeutic molecules for diabetes mellitus. © 2018 Wiley Periodicals, Inc.

In-Silico Integration Approach to Identify a Key miRNA Regulating a Gene Network in Aggressive Prostate Cancer

PubMed Central

Colaprico, Antonio; Bontempi, Gianluca; Castiglioni, Isabella

2018-01-01

Like other cancer diseases, prostate cancer (PC) is caused by the accumulation of genetic alterations in the cells that drives malignant growth. These alterations are revealed by gene profiling and copy number alteration (CNA) analysis. Moreover, recent evidence suggests that also microRNAs have an important role in PC development. Despite efforts to profile PC, the alterations (gene, CNA, and miRNA) and biological processes that correlate with disease development and progression remain partially elusive. Many gene signatures proposed as diagnostic or prognostic tools in cancer poorly overlap. The identification of co-expressed genes, that are functionally related, can identify a core network of genes associated with PC with a better reproducibility. By combining different approaches, including the integration of mRNA expression profiles, CNAs, and miRNA expression levels, we identified a gene signature of four genes overlapping with other published gene signatures and able to distinguish, in silico, high Gleason-scored PC from normal human tissue, which was further enriched to 19 genes by gene co-expression analysis. From the analysis of miRNAs possibly regulating this network, we found that hsa-miR-153 was highly connected to the genes in the network. Our results identify a four-gene signature with diagnostic and prognostic value in PC and suggest an interesting gene network that could play a key regulatory role in PC development and progression. Furthermore, hsa-miR-153, controlling this network, could be a potential biomarker for theranostics in high Gleason-scored PC. PMID:29562723

Reversal of the hair loss phenotype by modulating the estradiol-ANGPT2 axis in the mouse model of female pattern hair loss.

PubMed

Endo, Yujiro; Obayashi, Yuko; Ono, Tomoji; Serizawa, Tetsushi; Murakoshi, Michiaki; Ohyama, Manabu

2018-07-01

Despite high demand for a remedy, the treatment options for female pattern hair loss (FPHL) are limited. FPHL is frequent in postmenopausal women. In ovariectomized (OVX) mice, which lack β-estradiol (E2) and manifest hair loss mimicking FPHL, E2 supplementation has been shown to increase hair density. However, the mechanism by which E2 exhibits its biological activity remains elusive. To identify the downstream targets of E2 in the context of FPHL pathophysiology and discover a potential therapeutic agent for the E2-dependent subtype of FPHL. Human dermal papilla cells (hDPCs) were cultured with E2, and a microarray analysis was performed to identify the genes regulated by E2. Using OVX mice, the identified gene product was intradermally administered and then quantitative image analysis of hair density was conducted. In silico analysis to link E2 and the identified gene was performed. Global gene expression and bioinformatics analyses revealed that the genes associated with the angiopoietin-2 (ANGPT2) pathway were upregulated by E2 in hDPCs. ANGPT2 was significantly downregulated in OVX mice than in sham-operated mice (P < 0.01). Importantly, hair density was higher in OVX mice treated with ANGPT2 than in control mice (P < 0.05). In silico analysis showed DNA sequences with high possibility of estrogen receptor binding in the promoter region of ANGPT2. The E2-ANGPT2 axis is present in hair follicles. ANGPT2 provides a strategy for the management of E2-dependent and postmenopausal subsets of FPHL. Copyright © 2018 Japanese Society for Investigative Dermatology. Published by Elsevier B.V. All rights reserved.

Exploring internal features of 16S rRNA gene for identification of clinically relevant species of the genus Streptococcus

PubMed Central

2011-01-01

Background Streptococcus is an economically important genus as a number of species belonging to this genus are human and animal pathogens. The genus has been divided into different groups based on 16S rRNA gene sequence similarity. The variability observed among the members of these groups is low and it is difficult to distinguish them. The present study was taken up to explore 16S rRNA gene sequence to develop methods that can be used for preliminary identification and can supplement the existing methods for identification of clinically-relevant isolates of the genus Streptococcus. Methods 16S rRNA gene sequences belonging to the isolates of S. dysgalactiae, S. equi, S. pyogenes, S. agalactiae, S. bovis, S. gallolyticus, S. mutans, S. sobrinus, S. mitis, S. pneumoniae, S. thermophilus and S. anginosus were analyzed with the purpose to define genetic variability within each species to generate a phylogenetic framework, to identify species-specific signatures and in-silico restriction enzyme analysis. Results The framework based analysis was used to segregate Streptococcus spp. previously identified upto genus level. This segregation was validated using species-specific signatures and in-silico restriction enzyme analysis. 43 uncharacterized Streptococcus spp. could be identified using this approach. Conclusions The markers generated exploring 16S rRNA gene sequences provided useful tool that can be further used for identification of different species of the genus Streptococcus. PMID:21702978

In Silico Analysis Identifies a Novel Role for Androgens in the Regulation of Human Endometrial Apoptosis

PubMed Central

Marshall, Elaine; Lowrey, Jacqueline; MacPherson, Sheila; Maybin, Jacqueline A.; Collins, Frances; Critchley, Hilary O. D.

2011-01-01

Context: The endometrium is a multicellular, steroid-responsive tissue that undergoes dynamic remodeling every menstrual cycle in preparation for implantation and, in absence of pregnancy, menstruation. Androgen receptors are present in the endometrium. Objective: The objective of the study was to investigate the impact of androgens on human endometrial stromal cells (hESC). Design: Bioinformatics was used to identify an androgen-regulated gene set and processes associated with their function. Regulation of target genes and impact of androgens on cell function were validated using primary hESC. Setting: The study was conducted at the University Research Institute. Patients: Endometrium was collected from women with regular menses; tissues were used for recovery of cells, total mRNA, or protein and for immunohistochemistry. Results: A new endometrial androgen target gene set (n = 15) was identified. Bioinformatics revealed 12 of these genes interacted in one pathway and identified an association with control of cell survival. Dynamic androgen-dependent changes in expression of the gene set were detected in hESC with nine significantly down-regulated at 2 and/or 8 h. Treatment of hESC with dihydrotestosterone reduced staurosporine-induced apoptosis and cell migration/proliferation. Conclusions: Rigorous in silico analysis resulted in identification of a group of androgen-regulated genes expressed in human endometrium. Pathway analysis and functional assays suggest androgen-dependent changes in gene expression may have a significant impact on stromal cell proliferation, migration, and survival. These data provide the platform for further studies on the role of circulatory or local androgens in the regulation of endometrial function and identify androgens as candidates in the pathogenesis of common endometrial disorders including polycystic ovarian syndrome, cancer, and endometriosis. PMID:21865353

In Silico Synthesis of Synthetic Receptors: A Polymerization Algorithm.

PubMed

Cowen, Todd; Busato, Mirko; Karim, Kal; Piletsky, Sergey A

2016-12-01

Molecularly imprinted polymer (MIP) synthetic receptors have proposed and applied applications in chemical extraction, sensors, assays, catalysis, targeted drug delivery, and direct inhibition of harmful chemicals and pathogens. However, they rely heavily on effective design for success. An algorithm has been written which mimics radical polymerization atomistically, accounting for chemical and spatial discrimination, hybridization, and geometric optimization. Synthetic ephedrine receptors were synthesized in silico to demonstrate the accuracy of the algorithm in reproducing polymers structures at the atomic level. Comparative analysis in the design of a synthetic ephedrine receptor demonstrates that the new method can effectively identify affinity trends and binding site selectivities where commonly used alternative methods cannot. This new method is believed to generate the most realistic models of MIPs thus produced. This suggests that the algorithm could be a powerful new tool in the design and analysis of various polymers, including MIPs, with significant implications in areas of biotechnology, biomimetics, and the materials sciences more generally. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development of predictive pharmacophore model for in silico screening, and 3D QSAR CoMFA and CoMSIA studies for lead optimization, for designing of potent tumor necrosis factor alpha converting enzyme inhibitors

NASA Astrophysics Data System (ADS)

Murumkar, Prashant Revan; Zambre, Vishal Prakash; Yadav, Mange Ram

2010-02-01

A chemical feature-based pharmacophore model was developed for Tumor Necrosis Factor-α converting enzyme (TACE) inhibitors. A five point pharmacophore model having two hydrogen bond acceptors (A), one hydrogen bond donor (D) and two aromatic rings (R) with discrete geometries as pharmacophoric features was developed. The pharmacophore model so generated was then utilized for in silico screening of a database. The pharmacophore model so developed was validated by using four compounds having proven TACE inhibitory activity which were grafted into the database. These compounds mapped well onto the five listed pharmacophoric features. This validated pharmacophore model was also used for alignment of molecules in CoMFA and CoMSIA analysis. The contour maps of the CoMFA/CoMSIA models were utilized to provide structural insight for activity improvement of potential novel TACE inhibitors. The pharmacophore model so developed could be used for in silico screening of any commercial/in house database for identification of TACE inhibiting lead compounds, and the leads so identified could be optimized using the developed CoMSIA model. The present work highlights the tremendous potential of the two mutually complementary ligand-based drug designing techniques (i.e. pharmacophore mapping and 3D-QSAR analysis) using TACE inhibitors as prototype biologically active molecules.

In silico fragment-based drug design.

PubMed

Konteatis, Zenon D

2010-11-01

In silico fragment-based drug design (FBDD) is a relatively new approach inspired by the success of the biophysical fragment-based drug discovery field. Here, we review the progress made by this approach in the last decade and showcase how it complements and expands the capabilities of biophysical FBDD and structure-based drug design to generate diverse, efficient drug candidates. Advancements in several areas of research that have enabled the development of in silico FBDD and some applications in drug discovery projects are reviewed. The reader is introduced to various computational methods that are used for in silico FBDD, the fragment library composition for this technique, special applications used to identify binding sites on the surface of proteins and how to assess the druggability of these sites. In addition, the reader will gain insight into the proper application of this approach from examples of successful programs. In silico FBDD captures a much larger chemical space than high-throughput screening and biophysical FBDD increasing the probability of developing more diverse, patentable and efficient molecules that can become oral drugs. The application of in silico FBDD holds great promise for historically challenging targets such as protein-protein interactions. Future advances in force fields, scoring functions and automated methods for determining synthetic accessibility will all aid in delivering more successes with in silico FBDD.

In silico pharmacology for drug discovery: applications to targets and beyond

PubMed Central

Ekins, S; Mestres, J; Testa, B

2007-01-01

Computational (in silico) methods have been developed and widely applied to pharmacology hypothesis development and testing. These in silico methods include databases, quantitative structure-activity relationships, similarity searching, pharmacophores, homology models and other molecular modeling, machine learning, data mining, network analysis tools and data analysis tools that use a computer. Such methods have seen frequent use in the discovery and optimization of novel molecules with affinity to a target, the clarification of absorption, distribution, metabolism, excretion and toxicity properties as well as physicochemical characterization. The first part of this review discussed the methods that have been used for virtual ligand and target-based screening and profiling to predict biological activity. The aim of this second part of the review is to illustrate some of the varied applications of in silico methods for pharmacology in terms of the targets addressed. We will also discuss some of the advantages and disadvantages of in silico methods with respect to in vitro and in vivo methods for pharmacology research. Our conclusion is that the in silico pharmacology paradigm is ongoing and presents a rich array of opportunities that will assist in expediating the discovery of new targets, and ultimately lead to compounds with predicted biological activity for these novel targets. PMID:17549046

Experimental and in silico analysis of cordycepin and its derivatives as endometrial cancer treatment.

PubMed

Fong, Pedro; Ao, Cheng N; Tou, Kai I; Huang, Ka M; Cheong, Chi C; Meng, Li R

2018-04-19

The aim of this study was to investigate the inhibition effects of cordycepin and its derivatives on endometrial cancercell growth. Cytotoxicity MTT assays, clonogenic assays and flow cytometry were used to observe the effects on apoptosis and regulation of the cell cycle of Ishikawa cells under various concentrations of cordycepin, cisplatin and combinations of the two. Validated in silico docking simulations were performed on 31 cordycepin derivatives against adenosine deaminase (ADA) to predict their binding affinities and hence their potential tendency to be metabolized by ADA. Cordycepin has a significant dose-dependent inhibitory effect on cell proliferation. The combination of cordycepin and cisplatin produced greater inhibition effects than did cordycepin alone. Apoptosis investigations confirmed the ability of cordycepin to induce the apoptosis of Ishikawa cells. The in silico results indicate that compound MRS5698 is least metabolized by ADA and has acceptable drug-likeness and safety profiles. This is the first study to confirm the cytotoxic effects of cordycepin on endometrial cancer cells. This study also identified cordycepin derivatives with promising pharmacological and pharmacokinetic properties for further investigation in the development of new treatments for endometrial cancer.

A comprehensive characterization of rare mitochondrial DNA variants in neuroblastoma.

PubMed

Calabrese, Francesco Maria; Clima, Rosanna; Pignataro, Piero; Lasorsa, Vito Alessandro; Hogarty, Michael D; Castellano, Aurora; Conte, Massimo; Tonini, Gian Paolo; Iolascon, Achille; Gasparre, Giuseppe; Capasso, Mario

2016-08-02

Neuroblastoma, a tumor of the developing sympathetic nervous system, is a common childhood neoplasm that is often lethal. Mitochondrial DNA (mtDNA) mutations have been found in most tumors including neuroblastoma. We extracted mtDNA data from a cohort of neuroblastoma samples that had undergone Whole Exome Sequencing (WES) and also used snap-frozen samples in which mtDNA was entirely sequenced by Sanger technology. We next undertook the challenge of determining those mutations that are relevant to, or arisen during tumor development. The bioinformatics pipeline used to extract mitochondrial variants from matched tumor/blood samples was enriched by a set of filters inclusive of heteroplasmic fraction, nucleotide variability, and in silico prediction of pathogenicity. Our in silico multistep workflow applied both on WES and Sanger-sequenced neuroblastoma samples, allowed us to identify a limited burden of somatic and germline mitochondrial mutations with a potential pathogenic impact. The few singleton germline and somatic mitochondrial mutations emerged, according to our in silico analysis, do not appear to impact on the development of neuroblastoma. Our findings are consistent with the hypothesis that most mitochondrial somatic mutations can be considered as 'passengers' and consequently have no discernible effect in this type of cancer.

One Hundred False-Positive Amphetamine Specimens Characterized by Liquid Chromatography Time-of-Flight Mass Spectrometry.

PubMed

Marin, Stephanie J; Doyle, Kelly; Chang, Annie; Concheiro-Guisan, Marta; Huestis, Marilyn A; Johnson-Davis, Kamisha L

2016-01-01

Some amphetamine (AMP) and ecstacy (MDMA) urine immunoassay (IA) kits are prone to false-positive results due to poor specificity of the antibody. We employed two techniques, high-resolution mass spectrometry (HRMS) and an in silico structure search, to identify compounds likely to cause false-positive results. Hundred false-positive IA specimens for AMP and/or MDMA were analyzed by an Agilent 6230 time-of-flight (TOF) mass spectrometer. Separately, SciFinder (Chemical Abstracts) was used as an in silico structure search to generate a library of compounds that are known to cross-react with AMP/MDMA IAs. Chemical formulas and exact masses of 145 structures were then compared against masses identified by TOF. Compounds known to have cross-reactivity with the IAs were identified in the structure-based search. The chemical formulas and exact masses of 145 structures (of 20 chemical formulas) were compared against masses identified by TOF. Urine analysis by HRMS correlates accurate mass with chemical formulae, but provides little information regarding compound structure. Structural data of targeted antigens can be utilized to correlate HRMS-derived chemical formulas with structural analogs. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Identification of centromere regions in chromosomes of a unicellular red alga, Cyanidioschyzon merolae.

PubMed

Kanesaki, Yu; Imamura, Sousuke; Matsuzaki, Motomichi; Tanaka, Kan

2015-05-08

To investigate the evolution of centromere architecture in plant cells, it is important to identify centromere regions of primitive algae, such as Cyanidioschyzon merolae. In a previous genome project, in silico analysis predicted an AT-rich region in each chromosome as putative centromere regions. Here, we identified a centromere position in each chromosome by ChIP-on-chip analysis using an anti-CENP-A antibody. The identified centromeres were of the regional type, about 2-3 kb in length and contained no consensus or repeat elements. Centromeres in primitive eukaryotic plant cells may have originated from these regional type centromeres. Copyright © 2015 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

In Silico PCR Tools for a Fast Primer, Probe, and Advanced Searching.

PubMed

Kalendar, Ruslan; Muterko, Alexandr; Shamekova, Malika; Zhambakin, Kabyl

2017-01-01

The polymerase chain reaction (PCR) is fundamental to molecular biology and is the most important practical molecular technique for the research laboratory. The principle of this technique has been further used and applied in plenty of other simple or complex nucleic acid amplification technologies (NAAT). In parallel to laboratory "wet bench" experiments for nucleic acid amplification technologies, in silico or virtual (bioinformatics) approaches have been developed, among which in silico PCR analysis. In silico NAAT analysis is a useful and efficient complementary method to ensure the specificity of primers or probes for an extensive range of PCR applications from homology gene discovery, molecular diagnosis, DNA fingerprinting, and repeat searching. Predicting sensitivity and specificity of primers and probes requires a search to determine whether they match a database with an optimal number of mismatches, similarity, and stability. In the development of in silico bioinformatics tools for nucleic acid amplification technologies, the prospects for the development of new NAAT or similar approaches should be taken into account, including forward-looking and comprehensive analysis that is not limited to only one PCR technique variant. The software FastPCR and the online Java web tool are integrated tools for in silico PCR of linear and circular DNA, multiple primer or probe searches in large or small databases and for advanced search. These tools are suitable for processing of batch files that are essential for automation when working with large amounts of data. The FastPCR software is available for download at http://primerdigital.com/fastpcr.html and the online Java version at http://primerdigital.com/tools/pcr.html .

In silico analysis of stomach lineage specific gene set expression pattern in gastric cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pandi, Narayanan Sathiya, E-mail: sathiyapandi@gmail.com; Suganya, Sivagurunathan; Rajendran, Suriliyandi

Highlights: •Identified stomach lineage specific gene set (SLSGS) was found to be under expressed in gastric tumors. •Elevated expression of SLSGS in gastric tumor is a molecular predictor of metabolic type gastric cancer. •In silico pathway scanning identified estrogen-α signaling is a putative regulator of SLSGS in gastric cancer. •Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. -- Abstract: Stomach lineage specific gene products act as a protective barrier in the normal stomach and their expression maintains the normal physiological processes, cellular integrity and morphology of the gastric wall. However,more » the regulation of stomach lineage specific genes in gastric cancer (GC) is far less clear. In the present study, we sought to investigate the role and regulation of stomach lineage specific gene set (SLSGS) in GC. SLSGS was identified by comparing the mRNA expression profiles of normal stomach tissue with other organ tissue. The obtained SLSGS was found to be under expressed in gastric tumors. Functional annotation analysis revealed that the SLSGS was enriched for digestive function and gastric epithelial maintenance. Employing a single sample prediction method across GC mRNA expression profiles identified the under expression of SLSGS in proliferative type and invasive type gastric tumors compared to the metabolic type gastric tumors. Integrative pathway activation prediction analysis revealed a close association between estrogen-α signaling and SLSGS expression pattern in GC. Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. In conclusion, our results highlight that estrogen mediated regulation of SLSGS in gastric tumor is a molecular predictor of metabolic type GC and prognostic factor in GC.« less

A case study of an integrative genomic and experimental therapeutic approach for rare tumors: identification of vulnerabilities in a pediatric poorly differentiated carcinoma.

PubMed

Dela Cruz, Filemon S; Diolaiti, Daniel; Turk, Andrew T; Rainey, Allison R; Ambesi-Impiombato, Alberto; Andrews, Stuart J; Mansukhani, Mahesh M; Nagy, Peter L; Alvarez, Mariano J; Califano, Andrea; Forouhar, Farhad; Modzelewski, Beata; Mitchell, Chelsey M; Yamashiro, Darrell J; Marks, Lianna J; Glade Bender, Julia L; Kung, Andrew L

2016-10-31

Precision medicine approaches are ideally suited for rare tumors where comprehensive characterization may have diagnostic, prognostic, and therapeutic value. We describe the clinical case and molecular characterization of an adolescent with metastatic poorly differentiated carcinoma (PDC). Given the rarity and poor prognosis associated with PDC in children, we utilized genomic analysis and preclinical models to validate oncogenic drivers and identify molecular vulnerabilities. We utilized whole exome sequencing (WES) and transcriptome analysis to identify germline and somatic alterations in the patient's tumor. In silico and in vitro studies were used to determine the functional consequences of genomic alterations. Primary tumor was used to generate a patient-derived xenograft (PDX) model, which was used for in vivo assessment of predicted therapeutic options. WES revealed a novel germline frameshift variant (p.E1554fs) in APC, establishing a diagnosis of Gardner syndrome, along with a somatic nonsense (p.R790*) APC mutation in the tumor. Somatic mutations in TP53, MAX, BRAF, ROS1, and RPTOR were also identified and transcriptome and immunohistochemical analyses suggested hyperactivation of the Wnt/ß-catenin and AKT/mTOR pathways. In silico and biochemical assays demonstrated that the MAX p.R60Q and BRAF p.K483E mutations were activating mutations, whereas the ROS1 and RPTOR mutations were of lower utility for therapeutic targeting. Utilizing a patient-specific PDX model, we demonstrated in vivo activity of mTOR inhibition with temsirolimus and partial response to inhibition of MEK. This clinical case illustrates the depth of investigation necessary to fully characterize the functional significance of the breadth of alterations identified through genomic analysis.

Eight novel F13A1 gene missense mutations in patients with mild FXIII deficiency: in silico analysis suggests changes in FXIII-A subunit structure/function.

PubMed

Biswas, Arijit; Ivaskevicius, Vytautas; Thomas, Anne; Varvenne, Michael; Brand, Brigitte; Rott, Hannelore; Haussels, Iris; Ruehl, Heiko; Scholz, Ute; Klamroth, Robert; Oldenburg, Johannes

2014-10-01

Mild FXIII deficiency is an under-diagnosed disorder because the carriers of this deficiency are often asymptomatic and reveal a phenotype only under special circumstances like surgery or induced trauma. Mutational reports from this type of deficiency have been rare. In this study, we present the phenotypic and genotypic data of nine patients showing mild FXIII-A deficiency caused by eight novel heterozygous missense mutations (Pro166Leu, Arg171Gln, His342Tyr, Gln415Arg, Leu529Pro, Gln601Lys, Arg703Gln and Arg715Gly) in the F13A1 gene. None of these variants were seen in 200 healthy controls. In silico structural analysis of the local wild-type protein structures (activated and non-activated) from X-ray crystallographic models downloaded from the protein databank identified potential structural/functional effects for the identified mutations. The missense mutations in the core domain are suggested to be directly influencing the catalytic triad. Mutations on other domains might influence other critical factors such as activation peptide cleavage or the barrel domain integrity. In vitro expression and subsequent biochemical studies in the future will be able to confirm the pathophysiological mechanisms proposed for the mutations in this article.

An in silico method to identify computer-based protocols worthy of clinical study: An insulin infusion protocol use case

PubMed Central

Wong, Anthony F; Pielmeier, Ulrike; Haug, Peter J; Andreassen, Steen

2016-01-01

Objective Develop an efficient non-clinical method for identifying promising computer-based protocols for clinical study. An in silico comparison can provide information that informs the decision to proceed to a clinical trial. The authors compared two existing computer-based insulin infusion protocols: eProtocol-insulin from Utah, USA, and Glucosafe from Denmark. Materials and Methods The authors used eProtocol-insulin to manage intensive care unit (ICU) hyperglycemia with intravenous (IV) insulin from 2004 to 2010. Recommendations accepted by the bedside clinicians directly link the subsequent blood glucose values to eProtocol-insulin recommendations and provide a unique clinical database. The authors retrospectively compared in silico 18 984 eProtocol-insulin continuous IV insulin infusion rate recommendations from 408 ICU patients with those of Glucosafe, the candidate computer-based protocol. The subsequent blood glucose measurement value (low, on target, high) was used to identify if the insulin recommendation was too high, on target, or too low. Results Glucosafe consistently provided more favorable continuous IV insulin infusion rate recommendations than eProtocol-insulin for on target (64% of comparisons), low (80% of comparisons), or high (70% of comparisons) blood glucose. Aggregated eProtocol-insulin and Glucosafe continuous IV insulin infusion rates were clinically similar though statistically significantly different (Wilcoxon signed rank test P = .01). In contrast, when stratified by low, on target, or high subsequent blood glucose measurement, insulin infusion rates from eProtocol-insulin and Glucosafe were statistically significantly different (Wilcoxon signed rank test, P < .001), and clinically different. Discussion This in silico comparison appears to be an efficient nonclinical method for identifying promising computer-based protocols. Conclusion Preclinical in silico comparison analytical framework allows rapid and inexpensive identification of computer-based protocol care strategies that justify expensive and burdensome clinical trials. PMID:26228765

Comparative Genomics of Oral Isolates of Streptococcus mutans by in silico Genome Subtraction Does Not Reveal Accessory DNA Associated with Severe Early Childhood Caries

PubMed Central

Argimón, Silvia; Konganti, Kranti; Chen, Hao; Alekseyenko, Alexander V.; Brown, Stuart; Caufield, Page W.

2014-01-01

Comparative genomics is a popular method for the identification of microbial virulence determinants, especially since the sequencing of a large number of whole bacterial genomes from pathogenic and non-pathogenic strains has become relatively inexpensive. The bioinformatics pipelines for comparative genomics usually include gene prediction and annotation and can require significant computer power. To circumvent this, we developed a rapid method for genome-scale in silico subtractive hybridization, based on blastn and independent of feature identification and annotation. Whole genome comparisons by in silico genome subtraction were performed to identify genetic loci specific to Streptococcus mutans strains associated with severe early childhood caries (S-ECC), compared to strains isolated from caries-free (CF) children. The genome similarity of the 20 S. mutans strains included in this study, calculated by Simrank k-mer sharing, ranged from 79.5 to 90.9%, confirming this is a genetically heterogeneous group of strains. We identified strain-specific genetic elements in 19 strains, with sizes ranging from 200 bp to 39 kb. These elements contained protein-coding regions with functions mostly associated with mobile DNA. We did not, however, identify any genetic loci consistently associated with dental caries, i.e., shared by all the S-ECC strains and absent in the CF strains. Conversely, we did not identify any genetic loci specific with the healthy group. Comparison of previously published genomes from pathogenic and carriage strains of Neisseria meningitidis with our in silico genome subtraction yielded the same set of genes specific to the pathogenic strains, thus validating our method. Our results suggest that S. mutans strains derived from caries active or caries free dentitions cannot be differentiated based on the presence or absence of specific genetic elements. Our in silico genome subtraction method is available as the Microbial Genome Comparison (MGC) tool, with a user-friendly JAVA graphical interface. PMID:24291226

Identification and molecular characterisation of a homozygous missense mutation in the ADAMTS10 gene in a patient with Weill-Marchesani syndrome.

PubMed

Steinkellner, Hannes; Etzler, Julia; Gogoll, Laura; Neesen, Jürgen; Stifter, Eva; Brandau, Oliver; Laccone, Franco

2015-09-01

Weill-Marchesani syndrome is a rare disorder of the connective tissue. Functional variants in ADAMTS10 are associated with Weill-Marchesani syndrome-1. We identified a homozygous missense mutation, c.41T>A, of the ADAMTS10 gene in a 19-year-old female with typical symptoms of WMS1: proportionate short stature, brachydactyly, joint stiffness, and microspherophakia. The ADAMTS10 missense mutation was analysed in silico, with conflicting results as to its effects on protein function, but it was predicted to affect the leader sequence. Molecular characterisation in HEK293 Ebna cells revealed an intracellular mis-targeting of the ADAMTS10 protein with a reduced concentration of the polypeptide in the endoplasmic reticulum. A large reduction in glycosylation of the cytoplasmic fraction of the mutant ADAMTS10 protein versus the wild-type protein and a lack of secretion of the mutant protein are also evident in our results.In conclusion, we identified a novel missense mutation of the ADAMTS10 gene and confirmed the functional consequences suggested by the in silico analysis by conducting molecular studies.

Prediction of the Hydrogen Peroxide-Induced Methionine Oxidation Propensity in Monoclonal Antibodies.

PubMed

Agrawal, Neeraj J; Dykstra, Andrew; Yang, Jane; Yue, Hai; Nguyen, Xichdao; Kolvenbach, Carl; Angell, Nicolas

2018-05-01

Methionine oxidation in therapeutic antibodies can impact the product's stability, clinical efficacy, and safety and hence it is desirable to address the methionine oxidation liability during antibody discovery and development phase. Although the current experimental approaches can identify the oxidation-labile methionine residues, their application is limited mostly to the development phase. We demonstrate an in silico method that can be used to predict oxidation-labile residues based solely on the antibody sequence and structure information. Since antibody sequence information is available in the discovery phase, the in silico method can be applied very early on to identify the oxidation-labile methionine residues and subsequently address the oxidation liability. We believe that the in silico method for methionine oxidation liability assessment can aid in antibody discovery and development phase to address the liability in a more rational way. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

NAC transcription factor genes: genome-wide identification, phylogenetic, motif and cis-regulatory element analysis in pigeonpea (Cajanus cajan (L.) Millsp.).

PubMed

Satheesh, Viswanathan; Jagannadham, P Tej Kumar; Chidambaranathan, Parameswaran; Jain, P K; Srinivasan, R

2014-12-01

The NAC (NAM, ATAF and CUC) proteins are plant-specific transcription factors implicated in development and stress responses. In the present study 88 pigeonpea NAC genes were identified from the recently published draft genome of pigeonpea by using homology based and de novo prediction programmes. These sequences were further subjected to phylogenetic, motif and promoter analyses. In motif analysis, highly conserved motifs were identified in the NAC domain and also in the C-terminal region of the NAC proteins. A phylogenetic reconstruction using pigeonpea, Arabidopsis and soybean NAC genes revealed 33 putative stress-responsive pigeonpea NAC genes. Several stress-responsive cis-elements were identified through in silico analysis of the promoters of these putative stress-responsive genes. This analysis is the first report of NAC gene family in pigeonpea and will be useful for the identification and selection of candidate genes associated with stress tolerance.

A dominant negative mutation at the ATP binding domain of AMHR2 is associated with a defective anti-Müllerian hormone signaling pathway.

PubMed

Li, Lin; Zhou, Xueya; Wang, Xi; Wang, Jing; Zhang, Wei; Wang, Binbin; Cao, Yunxia; Kee, Kehkooi

2016-09-01

Does a heterozygous mutation in AMHR2, identified in whole-exome sequencings (WES) of patients with primary ovarian insufficiency (POI), cause a defect in anti-Müllerian hormone (AMH) signaling? The I209N mutation at the adenosine triphosphate binding domain of AMHR2 exerts dominant negative defects in the AMH signaling pathway. Previous studies have demonstrated the associations of several sequence variants in AMH or AMHR2 with POI, but no functional assay has been performed to verify whether there was any defect on AMH signaling. Ninety-six unrelated female Chinese Han patients were diagnosed with idiopathic POI and subjected to WES. In silico analysis was done for the sequence variants followed by molecular assays to examine the functional effects of the sequence variants in human granulosa cells. In silico analysis, immunostaining, Western analysis, genome-wide expression analysis, quantitatively polymerase chain reaction were applied to the characterization of the sequence variants. We identified one novel heterozygous missense variant, p.Ala17Glu (A17E), in AMHR2. Subsequently, A17E and two independently reported missense variants, p.Ile209Asn (I209N) and p.Leu354Phe (L354F), were evaluated for effects on the AMH signaling pathway. In silico analysis predicted that all three variants may be deleterious. However, only one variant, I209N, showed severe defects in transducing the AMH signal as well as impaired SMAD1/5/8 phosphorylation. Furthermore, using genome-wide gene expression analysis, we identified genes whose expression was affected by the mutation, these included genes previously reported to participate in AMH signaling as well as newly identified genes. They are EMILIN2, FAM155A, GATA2, HES5, ID1, ID2, RLTPR, SMAD7, CBL, MALAT1 and SMARCA2. None. Although the in vitro assays demonstrated the causative effect of I209N on AMH signaling, further studies need to validate its long-term effects on folliculogenesis and POI. These results will aid both researchers and clinicians in understanding the molecular pathology of AMH signaling and POI to develop diagnostic assays or therapeutics approaches. Research funding is provided by the Ministry of Science and Technology of China [2012CB944704; 2012CB966702], and the National Natural Science Foundation of China [Grant number: 31171429]. The authors declare no conflict of interest. © The Author 2016. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Engineering Proteins for Thermostability with iRDP Web Server

PubMed Central

Ghanate, Avinash; Ramasamy, Sureshkumar; Suresh, C. G.

2015-01-01

Engineering protein molecules with desired structure and biological functions has been an elusive goal. Development of industrially viable proteins with improved properties such as stability, catalytic activity and altered specificity by modifying the structure of an existing protein has widely been targeted through rational protein engineering. Although a range of factors contributing to thermal stability have been identified and widely researched, the in silico implementation of these as strategies directed towards enhancement of protein stability has not yet been explored extensively. A wide range of structural analysis tools is currently available for in silico protein engineering. However these tools concentrate on only a limited number of factors or individual protein structures, resulting in cumbersome and time-consuming analysis. The iRDP web server presented here provides a unified platform comprising of iCAPS, iStability and iMutants modules. Each module addresses different facets of effective rational engineering of proteins aiming towards enhanced stability. While iCAPS aids in selection of target protein based on factors contributing to structural stability, iStability uniquely offers in silico implementation of known thermostabilization strategies in proteins for identification and stability prediction of potential stabilizing mutation sites. iMutants aims to assess mutants based on changes in local interaction network and degree of residue conservation at the mutation sites. Each module was validated using an extensively diverse dataset. The server is freely accessible at http://irdp.ncl.res.in and has no login requirements. PMID:26436543

Engineering Proteins for Thermostability with iRDP Web Server.

PubMed

Panigrahi, Priyabrata; Sule, Manas; Ghanate, Avinash; Ramasamy, Sureshkumar; Suresh, C G

2015-01-01

Engineering protein molecules with desired structure and biological functions has been an elusive goal. Development of industrially viable proteins with improved properties such as stability, catalytic activity and altered specificity by modifying the structure of an existing protein has widely been targeted through rational protein engineering. Although a range of factors contributing to thermal stability have been identified and widely researched, the in silico implementation of these as strategies directed towards enhancement of protein stability has not yet been explored extensively. A wide range of structural analysis tools is currently available for in silico protein engineering. However these tools concentrate on only a limited number of factors or individual protein structures, resulting in cumbersome and time-consuming analysis. The iRDP web server presented here provides a unified platform comprising of iCAPS, iStability and iMutants modules. Each module addresses different facets of effective rational engineering of proteins aiming towards enhanced stability. While iCAPS aids in selection of target protein based on factors contributing to structural stability, iStability uniquely offers in silico implementation of known thermostabilization strategies in proteins for identification and stability prediction of potential stabilizing mutation sites. iMutants aims to assess mutants based on changes in local interaction network and degree of residue conservation at the mutation sites. Each module was validated using an extensively diverse dataset. The server is freely accessible at http://irdp.ncl.res.in and has no login requirements.

InSilico DB genomic datasets hub: an efficient starting point for analyzing genome-wide studies in GenePattern, Integrative Genomics Viewer, and R/Bioconductor.

PubMed

Coletta, Alain; Molter, Colin; Duqué, Robin; Steenhoff, David; Taminau, Jonatan; de Schaetzen, Virginie; Meganck, Stijn; Lazar, Cosmin; Venet, David; Detours, Vincent; Nowé, Ann; Bersini, Hugues; Weiss Solís, David Y

2012-11-18

Genomics datasets are increasingly useful for gaining biomedical insights, with adoption in the clinic underway. However, multiple hurdles related to data management stand in the way of their efficient large-scale utilization. The solution proposed is a web-based data storage hub. Having clear focus, flexibility and adaptability, InSilico DB seamlessly connects genomics dataset repositories to state-of-the-art and free GUI and command-line data analysis tools. The InSilico DB platform is a powerful collaborative environment, with advanced capabilities for biocuration, dataset sharing, and dataset subsetting and combination. InSilico DB is available from https://insilicodb.org.

Insights and Perspectives on Emerging Inputs to Weight of Evidence Determinations for Food Safety: Workshop Proceedings

PubMed Central

Bialk, Heidi; Llewellyn, Craig; Kretser, Alison; Canady, Richard; Lane, Richard; Barach, Jeffrey

2013-01-01

This workshop aimed to elucidate the contribution of computational and emerging in vitro methods to the weight of evidence used by risk assessors in food safety assessments. The following issues were discussed: using in silico and high-throughput screening (HTS) data to confirm the safety of approved food ingredients, applying in silico and HTS data in the process of assessing the safety of a new food ingredient, and utilizing in silico and HTS data in communicating the safety of food ingredients while enhancing the public’s trust in the food supply. Perspectives on integrating computational modeling and HTS assays as well as recommendations for optimizing predictive methods for risk assessment were also provided. Given the need to act quickly or proceed cautiously as new data emerge, this workshop also focused on effectively identifying a path forward in communicating in silico and in vitro data. PMID:24296863

In Silico Prediction of Organ Level Toxicity: Linking Chemistry to Adverse Effects

PubMed Central

Cronin, Mark T.D.; Enoch, Steven J.; Mellor, Claire L.; Przybylak, Katarzyna R.; Richarz, Andrea-Nicole; Madden, Judith C.

2017-01-01

In silico methods to predict toxicity include the use of (Quantitative) Structure-Activity Relationships ((Q)SARs) as well as grouping (category formation) allowing for read-across. A challenging area for in silico modelling is the prediction of chronic toxicity and the No Observed (Adverse) Effect Level (NO(A)EL) in particular. A proposed solution to the prediction of chronic toxicity is to consider organ level effects, as opposed to modelling the NO(A)EL itself. This review has focussed on the use of structural alerts to identify potential liver toxicants. In silico profilers, or groups of structural alerts, have been developed based on mechanisms of action and informed by current knowledge of Adverse Outcome Pathways. These profilers are robust and can be coded computationally to allow for prediction. However, they do not cover all mechanisms or modes of liver toxicity and recommendations for the improvement of these approaches are given. PMID:28744348

In Silico Prediction of Organ Level Toxicity: Linking Chemistry to Adverse Effects.

PubMed

Cronin, Mark T D; Enoch, Steven J; Mellor, Claire L; Przybylak, Katarzyna R; Richarz, Andrea-Nicole; Madden, Judith C

2017-07-01

In silico methods to predict toxicity include the use of (Quantitative) Structure-Activity Relationships ((Q)SARs) as well as grouping (category formation) allowing for read-across. A challenging area for in silico modelling is the prediction of chronic toxicity and the No Observed (Adverse) Effect Level (NO(A)EL) in particular. A proposed solution to the prediction of chronic toxicity is to consider organ level effects, as opposed to modelling the NO(A)EL itself. This review has focussed on the use of structural alerts to identify potential liver toxicants. In silico profilers, or groups of structural alerts, have been developed based on mechanisms of action and informed by current knowledge of Adverse Outcome Pathways. These profilers are robust and can be coded computationally to allow for prediction. However, they do not cover all mechanisms or modes of liver toxicity and recommendations for the improvement of these approaches are given.

Novel approaches for targeting the adenosine A2A receptor.

PubMed

Yuan, Gengyang; Gedeon, Nicholas G; Jankins, Tanner C; Jones, Graham B

2015-01-01

The adenosine A2A receptor (A2AR) represents a drug target for a wide spectrum of diseases. Approaches for targeting this membrane-bound protein have been greatly advanced by new stabilization techniques. The resulting X-ray crystal structures and subsequent analyses provide deep insight to the A2AR from both static and dynamic perspectives. Application of this, along with other biophysical methods combined with fragment-based drug design (FBDD), has become a standard approach in targeting A2AR. Complementarities of in silico screening based- and biophysical screening assisted- FBDD are likely to feature in future approaches in identifying novel ligands against this key receptor. This review describes evolution of the above approaches for targeting A2AR and highlights key modulators identified. It includes a review of: adenosine receptor structures, homology modeling, X-ray structural analysis, rational drug design, biophysical methods, FBDD and in silico screening. As a drug target, the A2AR is attractive as its function plays a role in a wide spectrum of diseases including oncologic, inflammatory, Parkinson's and cardiovascular diseases. Although traditional approaches such as high-throughput screening and homology model-based virtual screening (VS) have played a role in targeting A2AR, numerous shortcomings have generally restricted their applications to specific ligand families. Using stabilization methods for crystallization, X-ray structures of A2AR have greatly accelerated drug discovery and influenced development of biophysical-in silico hybrid screening methods. Application of these new methods to other ARs and G-protein-coupled receptors is anticipated in the future.

Biochemical profiling in silico--predicting substrate specificities of large enzyme families.

PubMed

Tyagi, Sadhna; Pleiss, Juergen

2006-06-25

A general high-throughput method for in silico biochemical profiling of enzyme families has been developed based on covalent docking of potential substrates into the binding sites of target enzymes. The method has been tested by systematically docking transition state--analogous intermediates of 12 substrates into the binding sites of 20 alpha/beta hydrolases from 15 homologous families. To evaluate the effect of side chain orientations to the docking results, 137 crystal structures were included in the analysis. A good substrate must fulfil two criteria: it must bind in a productive geometry with four hydrogen bonds between the substrate and the catalytic histidine and the oxyanion hole, and a high affinity of the enzyme-substrate complex as predicted by a high docking score. The modelling results in general reproduce experimental data on substrate specificity and stereoselectivity: the differences in substrate specificity of cholinesterases toward acetyl- and butyrylcholine, the changes of activity of lipases and esterases upon the size of the acid moieties, activity of lipases and esterases toward tertiary alcohols, and the stereopreference of lipases and esterases toward chiral secondary alcohols. Rigidity of the docking procedure was the major reason for false positive and false negative predictions, as the geometry of the complex and docking score may sensitively depend on the orientation of individual side chains. Therefore, appropriate structures have to be identified. In silico biochemical profiling provides a time efficient and cost saving protocol for virtual screening to identify the potential substrates of the members of large enzyme family from a library of molecules.

Identification of hepta-histidine as a candidate drug for Huntington’s disease by in silico-in vitro- in vivo-integrated screens of chemical libraries

NASA Astrophysics Data System (ADS)

Imamura, Tomomi; Fujita, Kyota; Tagawa, Kazuhiko; Ikura, Teikichi; Chen, Xigui; Homma, Hidenori; Tamura, Takuya; Mao, Ying; Taniguchi, Juliana Bosso; Motoki, Kazumi; Nakabayashi, Makoto; Ito, Nobutoshi; Yamada, Kazunori; Tomii, Kentaro; Okano, Hideyuki; Kaye, Julia; Finkbeiner, Steven; Okazawa, Hitoshi

2016-09-01

We identified drug seeds for treating Huntington’s disease (HD) by combining in vitro single molecule fluorescence spectroscopy, in silico molecular docking simulations, and in vivo fly and mouse HD models to screen for inhibitors of abnormal interactions between mutant Htt and physiological Ku70, an essential DNA damage repair protein in neurons whose function is known to be impaired by mutant Htt. From 19,468 and 3,010,321 chemicals in actual and virtual libraries, fifty-six chemicals were selected from combined in vitro-in silico screens; six of these were further confirmed to have an in vivo effect on lifespan in a fly HD model, and two chemicals exerted an in vivo effect on the lifespan, body weight and motor function in a mouse HD model. Two oligopeptides, hepta-histidine (7H) and Angiotensin III, rescued the morphological abnormalities of primary neurons differentiated from iPS cells of human HD patients. For these selected drug seeds, we proposed a possible common structure. Unexpectedly, the selected chemicals enhanced rather than inhibited Htt aggregation, as indicated by dynamic light scattering analysis. Taken together, these integrated screens revealed a new pathway for the molecular targeted therapy of HD.

A comprehensive characterization of rare mitochondrial DNA variants in neuroblastoma

PubMed Central

Pignataro, Piero; Lasorsa, Vito Alessandro; Hogarty, Michael D.; Castellano, Aurora; Conte, Massimo; Tonini, Gian Paolo; Iolascon, Achille; Gasparre, Giuseppe; Capasso, Mario

2016-01-01

Background Neuroblastoma, a tumor of the developing sympathetic nervous system, is a common childhood neoplasm that is often lethal. Mitochondrial DNA (mtDNA) mutations have been found in most tumors including neuroblastoma. We extracted mtDNA data from a cohort of neuroblastoma samples that had undergone Whole Exome Sequencing (WES) and also used snap-frozen samples in which mtDNA was entirely sequenced by Sanger technology. We next undertook the challenge of determining those mutations that are relevant to, or arisen during tumor development. The bioinformatics pipeline used to extract mitochondrial variants from matched tumor/blood samples was enriched by a set of filters inclusive of heteroplasmic fraction, nucleotide variability, and in silico prediction of pathogenicity. Results Our in silico multistep workflow applied both on WES and Sanger-sequenced neuroblastoma samples, allowed us to identify a limited burden of somatic and germline mitochondrial mutations with a potential pathogenic impact. Conclusions The few singleton germline and somatic mitochondrial mutations emerged, according to our in silico analysis, do not appear to impact on the development of neuroblastoma. Our findings are consistent with the hypothesis that most mitochondrial somatic mutations can be considered as ‘passengers’ and consequently have no discernible effect in this type of cancer. PMID:27351283

Identification of hepta-histidine as a candidate drug for Huntington’s disease by in silico-in vitro- in vivo-integrated screens of chemical libraries

PubMed Central

Imamura, Tomomi; Fujita, Kyota; Tagawa, Kazuhiko; Ikura, Teikichi; Chen, Xigui; Homma, Hidenori; Tamura, Takuya; Mao, Ying; Taniguchi, Juliana Bosso; Motoki, Kazumi; Nakabayashi, Makoto; Ito, Nobutoshi; Yamada, Kazunori; Tomii, Kentaro; Okano, Hideyuki; Kaye, Julia; Finkbeiner, Steven; Okazawa, Hitoshi

2016-01-01

We identified drug seeds for treating Huntington’s disease (HD) by combining in vitro single molecule fluorescence spectroscopy, in silico molecular docking simulations, and in vivo fly and mouse HD models to screen for inhibitors of abnormal interactions between mutant Htt and physiological Ku70, an essential DNA damage repair protein in neurons whose function is known to be impaired by mutant Htt. From 19,468 and 3,010,321 chemicals in actual and virtual libraries, fifty-six chemicals were selected from combined in vitro-in silico screens; six of these were further confirmed to have an in vivo effect on lifespan in a fly HD model, and two chemicals exerted an in vivo effect on the lifespan, body weight and motor function in a mouse HD model. Two oligopeptides, hepta-histidine (7H) and Angiotensin III, rescued the morphological abnormalities of primary neurons differentiated from iPS cells of human HD patients. For these selected drug seeds, we proposed a possible common structure. Unexpectedly, the selected chemicals enhanced rather than inhibited Htt aggregation, as indicated by dynamic light scattering analysis. Taken together, these integrated screens revealed a new pathway for the molecular targeted therapy of HD. PMID:27653664

In silico profiling for secondary metabolites from Lepidium meyenii (maca) by the pharmacophore and ligand-shape-based joint approach.

PubMed

Yi, Fan; Tan, Xiao-Lei; Yan, Xin; Liu, Hai-Bo

2016-01-01

Lepidium meyenii Walpers (maca) is an herb known as a traditional nutritional supplement and widely used in Peru, North America, and Europe to enhance human fertility and treat osteoporosis. The secondary metabolites of maca, namely, maca alkaloids, macaenes, and macamides, are bioactive compounds, but their targets are undefined. The pharmacophore-based PharmaDB targets database screening joint the ligand shape similarity-based WEGA validation approach is proposed to predict the targets of these unique constituents and was performed using Discovery Studio 4.5 and PharmaDB. A compounds-targets-diseases network was established using Cytoscape 3.2. These suitable targets and their genes were calculated and analyzed using ingenuity pathway analysis and GeneMANIA. Certain targets were identified in osteoporosis (8 targets), prostate cancer (9 targets), and kidney diseases (11 targets). This was the first study to identify the targets of these bioactive compounds in maca for cardiovascular diseases (29 targets). The compound with the most targets (46) was an amide alkaloid (MA-24). In silico target fishing identified maca's traditional effects on treatment and prevention of osteoporosis, prostate cancer, and kidney diseases, and its potential function of treating cardiovascular diseases, as the most important of this herb's possible activities.

RNA-Seq and Gene Network Analysis Uncover Activation of an ABA-Dependent Signalosome During the Cork Oak Root Response to Drought

PubMed Central

Magalhães, Alexandre P.; Verde, Nuno; Reis, Francisca; Martins, Inês; Costa, Daniela; Lino-Neto, Teresa; Castro, Pedro H.; Tavares, Rui M.; Azevedo, Herlânder

2016-01-01

Quercus suber (cork oak) is a West Mediterranean species of key economic interest, being extensively explored for its ability to generate cork. Like other Mediterranean plants, Q. suber is significantly threatened by climatic changes, imposing the need to quickly understand its physiological and molecular adaptability to drought stress imposition. In the present report, we uncovered the differential transcriptome of Q. suber roots exposed to long-term drought, using an RNA-Seq approach. 454-sequencing reads were used to de novo assemble a reference transcriptome, and mapping of reads allowed the identification of 546 differentially expressed unigenes. These were enriched in both effector genes (e.g., LEA, chaperones, transporters) as well as regulatory genes, including transcription factors (TFs) belonging to various different classes, and genes associated with protein turnover. To further extend functional characterization, we identified the orthologs of differentially expressed unigenes in the model species Arabidopsis thaliana, which then allowed us to perform in silico functional inference, including gene network analysis for protein function, protein subcellular localization and gene co-expression, and in silico enrichment analysis for TFs and cis-elements. Results indicated the existence of extensive transcriptional regulatory events, including activation of ABA-responsive genes and ABF-dependent signaling. We were then able to establish that a core ABA-signaling pathway involving PP2C-SnRK2-ABF components was induced in stressed Q. suber roots, identifying a key mechanism in this species’ response to drought. PMID:26793200

Micro-Environmental Signature of The Interactions between Druggable Target Protein, Dipeptidyl Peptidase-IV, and Anti-Diabetic Drugs.

PubMed

Chakraborty, Chiranjib; Mallick, Bidyut; Sharma, Ashish Ranjan; Sharma, Garima; Jagga, Supriya; Doss, C George Priya; Nam, Ju-Suk; Lee, Sang-Soo

2017-01-01

Druggability of a target protein depends on the interacting micro-environment between the target protein and drugs. Therefore, a precise knowledge of the interacting micro-environment between the target protein and drugs is requisite for drug discovery process. To understand such micro-environment, we performed in silico interaction analysis between a human target protein, Dipeptidyl Peptidase-IV (DPP-4), and three anti-diabetic drugs (saxagliptin, linagliptin and vildagliptin). During the theoretical and bioinformatics analysis of micro-environmental properties, we performed drug-likeness study, protein active site predictions, docking analysis and residual interactions with the protein-drug interface. Micro-environmental landscape properties were evaluated through various parameters such as binding energy, intermolecular energy, electrostatic energy, van der Waals'+H-bond+desolvo energy (E VHD ) and ligand efficiency (LE) using different in silico methods. For this study, we have used several servers and software, such as Molsoft prediction server, CASTp server, AutoDock software and LIGPLOT server. Through micro-environmental study, highest log P value was observed for linagliptin (1.07). Lowest binding energy was also observed for linagliptin with DPP-4 in the binding plot. We also identified the number of H-bonds and residues involved in the hydrophobic interactions between the DPP-4 and the anti-diabetic drugs. During interaction, two H-bonds and nine residues, two H-bonds and eleven residues as well as four H-bonds and nine residues were found between the saxagliptin, linagliptin as well as vildagliptin cases and DPP-4, respectively. Our in silico data obtained for drug-target interactions and micro-environmental signature demonstrates linagliptin as the most stable interacting drug among the tested anti-diabetic medicines.

In silico prediction of the pathogenic effect of a novel variant of BCKDHA leading to classical maple syrup urine disease identified using clinical exome sequencing.

PubMed

Fernández-Lainez, Cynthia; Aláez-Verson, Carmen; Ibarra-González, Isabel; Enríquez-Flores, Sergio; Carrillo-Sanchez, Karol; Flores-Lagunes, Leonardo; Guillén-López, Sara; Belmont-Martínez, Leticia; Vela-Amieva, Marcela

2018-04-16

Maple syrup urine disease (MSUD) is a metabolic disorder caused by mutations in three of the branched-chain α-keto acid dehydrogenase complex (BCKDC) genes. Classical MSUD symptom can be observed immediately after birth and include ketoacidosis, irritability, lethargy, and coma, which can lead to death or irreversible neurodevelopmental delay in survivors. The molecular diagnosis of MSUD can be time-consuming and difficult to establish using conventional Sanger sequencing because it could be due to pathogenic variants of any of the BCKDC genes. Next-generation sequencing-based methodologies have revolutionized the molecular diagnosis of inborn errors in metabolism and offer a superior approach for genotyping these patients. Here, we report an MSUD case whose molecular diagnosis was performed by clinical exome sequencing (CES), and the possible structural pathogenic effect of a novel E1α subunit pathogenic variant was analyzed using in silico analysis of α and β subunit crystallographic structure. Molecular analysis revealed a new homozygous non-sense c.1267C>T or p.Gln423Ter variant of BCKDHA. The novel BCKDHA variant is considered pathogenic because it caused a premature stop codon that probably led to the loss of the last 22 amino acid residues of the E1α subunit C-terminal end. In silico analysis of this region showed that it is in contact with several residues of the E1β subunit mainly through polar contacts, hydrogen bonds, and hydrophobic interactions. CES strategy could benefit the patients and families by offering precise and prompt diagnosis and better genetic counseling. Copyright © 2018 Elsevier B.V. All rights reserved.

Exploring root symbiotic programs in the model legume Medicago truncatula using EST analysis.

PubMed

Journet, Etienne-Pascal; van Tuinen, Diederik; Gouzy, Jérome; Crespeau, Hervé; Carreau, Véronique; Farmer, Mary-Jo; Niebel, Andreas; Schiex, Thomas; Jaillon, Olivier; Chatagnier, Odile; Godiard, Laurence; Micheli, Fabienne; Kahn, Daniel; Gianinazzi-Pearson, Vivienne; Gamas, Pascal

2002-12-15

We report on a large-scale expressed sequence tag (EST) sequencing and analysis program aimed at characterizing the sets of genes expressed in roots of the model legume Medicago truncatula during interactions with either of two microsymbionts, the nitrogen-fixing bacterium Sinorhizobium meliloti or the arbuscular mycorrhizal fungus Glomus intraradices. We have designed specific tools for in silico analysis of EST data, in relation to chimeric cDNA detection, EST clustering, encoded protein prediction, and detection of differential expression. Our 21 473 5'- and 3'-ESTs could be grouped into 6359 EST clusters, corresponding to distinct virtual genes, along with 52 498 other M.truncatula ESTs available in the dbEST (NCBI) database that were recruited in the process. These clusters were manually annotated, using a specifically developed annotation interface. Analysis of EST cluster distribution in various M.truncatula cDNA libraries, supported by a refined R test to evaluate statistical significance and by 'electronic northern' representation, enabled us to identify a large number of novel genes predicted to be up- or down-regulated during either symbiotic root interaction. These in silico analyses provide a first global view of the genetic programs for root symbioses in M.truncatula. A searchable database has been built and can be accessed through a public interface.

In vitro fatigue tests and in silico finite element analysis of dental implants with different fixture/abutment joint types using computer-aided design models.

PubMed

Yamaguchi, Satoshi; Yamanishi, Yasufumi; Machado, Lucas S; Matsumoto, Shuji; Tovar, Nick; Coelho, Paulo G; Thompson, Van P; Imazato, Satoshi

2018-01-01

The aim of this study was to evaluate fatigue resistance of dental fixtures with two different fixture-abutment connections by in vitro fatigue testing and in silico three-dimensional finite element analysis (3D FEA) using original computer-aided design (CAD) models. Dental implant fixtures with external connection (EX) or internal connection (IN) abutments were fabricated from original CAD models using grade IV titanium and step-stress accelerated life testing was performed. Fatigue cycles and loads were assessed by Weibull analysis, and fatigue cracking was observed by micro-computed tomography and a stereomicroscope with high dynamic range software. Using the same CAD models, displacement vectors of implant components were also analyzed by 3D FEA. Angles of the fractured line occurring at fixture platforms in vitro and of displacement vectors corresponding to the fractured line in silico were compared by two-way ANOVA. Fatigue testing showed significantly greater reliability for IN than EX (p<0.001). Fatigue crack initiation was primarily observed at implant fixture platforms. FEA demonstrated that crack lines of both implant systems in vitro were observed in the same direction as displacement vectors of the implant fixtures in silico. In silico displacement vectors in the implant fixture are insightful for geometric development of dental implants to reduce complex interactions leading to fatigue failure. Copyright © 2017 Japan Prosthodontic Society. Published by Elsevier Ltd. All rights reserved.

In silico analysis of a disease-causing mutation in PCDH15 gene in a consanguineous Pakistani family with Usher phenotype.

PubMed

Saleha, Shamim; Ajmal, Muhammad; Jamil, Muhammad; Nasir, Muhammad; Hameed, Abdul

2016-01-01

To map Usher phenotype in a consanguineous Pakistani family and identify disease-associated mutation in a causative gene to establish phenotype-genotype correlation. A consanguineous Pakistani family in which Usher phenotype was segregating as an autosomal recessive trait was ascertained. On the basis of results of clinical investigations of affected members of this family disease was diagnosed as Usher syndrome (USH). To identify the locus responsible for the Usher phenotype in this family, genomic DNA from blood sample of each individual was genotyped using microsatellite Short Tandem Repeat (STR) markers for the known Usher syndrome loci. Then direct sequencing was performed to find out disease associated mutations in the candidate gene. By genetic linkage analysis, the USH phenotype of this family was mapped to PCDH15 locus on chromosome 10q21.1. Three different point mutations in exon 11 of PCDH15 were identified and one of them, c.1304A>C was found to be segregating with the disease phenotype in Pakistani family with Usher phenotype. This, c.1304A>C transversion mutation predicts an amino-acid substitution of aspartic acid with an alanine at residue number 435 (p.D435A) of its protein product. Moreover, in silico analysis revealed conservation of aspartic acid at position 435 and predicated this change as pathogenic. The identification of c.1304A>C pathogenic mutation in PCDH15 gene and its association with Usher syndrome in a consanguineous Pakistani family is the first example of a missense mutation of PCDH15 causing USH1 phenotype. In previous reports, it was hypothesized that severe mutations such as truncated protein of PCDH15 led to the Usher I phenotype and that missense variants are mainly responsible for non-syndromic hearing impairment.

Enhancement of L-cysteine production by disruption of yciW in Escherichia coli.

PubMed

Kawano, Yusuke; Ohtsu, Iwao; Takumi, Kazuhiro; Tamakoshi, Ai; Nonaka, Gen; Funahashi, Eri; Ihara, Masaki; Takagi, Hiroshi

2015-02-01

Using in silico analysis, the yciW gene of Escherichia coli was identified as a novel L-cysteine regulon that may be regulated by the transcriptional activator CysB for sulfur metabolic genes. We found that overexpression of yciW conferred tolerance to L-cysteine, but disruption of yciW increased L-cysteine production in E. coli. Copyright © 2014 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

In Silico Discovery of Potential Uridine-Cytidine Kinase 2 Inhibitors from the Rhizome of Alpinia mutica.

PubMed

Malami, Ibrahim; Abdul, Ahmad Bustamam; Abdullah, Rasedee; Bt Kassim, Nur Kartinee; Waziri, Peter; Christopher Etti, Imaobong

2016-04-08

Uridine-cytidine kinase 2 is implicated in uncontrolled proliferation of abnormal cells and it is a hallmark of cancer, therefore, there is need for effective inhibitors of this key enzyme. In this study, we employed the used of in silico studies to find effective UCK2 inhibitors of natural origin using bioinformatics tools. An in vitro kinase assay was established by measuring the amount of ADP production in the presence of ATP and 5-fluorouridine as a substrate. Molecular docking studies revealed an interesting ligand interaction with the UCK2 protein for both flavokawain B and alpinetin. Both compounds were found to reduce ADP production, possibly by inhibiting UCK2 activity in vitro. In conclusion, we have identified flavokawain B and alpinetin as potential natural UCK2 inhibitors as determined by their interactions with UCK2 protein using in silico molecular docking studies. This can provide information to identify lead candidates for further drug design and development.

In Silico Identification of Highly Conserved Epitopes of Influenza A H1N1, H2N2, H3N2, and H5N1 with Diagnostic and Vaccination Potential

PubMed Central

Muñoz-Medina, José Esteban; Sánchez-Vallejo, Carlos Javier; Méndez-Tenorio, Alfonso; Monroy-Muñoz, Irma Eloísa; Angeles-Martínez, Javier; Santos Coy-Arechavaleta, Andrea; Santacruz-Tinoco, Clara Esperanza; González-Ibarra, Joaquín; Anguiano-Hernández, Yu-Mei; González-Bonilla, César Raúl; Ramón-Gallegos, Eva; Díaz-Quiñonez, José Alberto

2015-01-01

The unpredictable, evolutionary nature of the influenza A virus (IAV) is the primary problem when generating a vaccine and when designing diagnostic strategies; thus, it is necessary to determine the constant regions in viral proteins. In this study, we completed an in silico analysis of the reported epitopes of the 4 IAV proteins that are antigenically most significant (HA, NA, NP, and M2) in the 3 strains with the greatest world circulation in the last century (H1N1, H2N2, and H3N2) and in one of the main aviary subtypes responsible for zoonosis (H5N1). For this purpose, the HMMER program was used to align 3,016 epitopes reported in the Immune Epitope Database and Analysis Resource (IEDB) and distributed in 34,294 stored sequences in the Pfam database. Eighteen epitopes were identified: 8 in HA, 5 in NA, 3 in NP, and 2 in M2. These epitopes have remained constant since they were first identified (~91 years) and are present in strains that have circulated on 5 continents. These sites could be targets for vaccination design strategies based on epitopes and/or as markers in the implementation of diagnostic techniques. PMID:26346523

A novel strategy for classifying the output from an in silico vaccine discovery pipeline for eukaryotic pathogens using machine learning algorithms.

PubMed

Goodswen, Stephen J; Kennedy, Paul J; Ellis, John T

2013-11-02

An in silico vaccine discovery pipeline for eukaryotic pathogens typically consists of several computational tools to predict protein characteristics. The aim of the in silico approach to discovering subunit vaccines is to use predicted characteristics to identify proteins which are worthy of laboratory investigation. A major challenge is that these predictions are inherent with hidden inaccuracies and contradictions. This study focuses on how to reduce the number of false candidates using machine learning algorithms rather than relying on expensive laboratory validation. Proteins from Toxoplasma gondii, Plasmodium sp., and Caenorhabditis elegans were used as training and test datasets. The results show that machine learning algorithms can effectively distinguish expected true from expected false vaccine candidates (with an average sensitivity and specificity of 0.97 and 0.98 respectively), for proteins observed to induce immune responses experimentally. Vaccine candidates from an in silico approach can only be truly validated in a laboratory. Given any in silico output and appropriate training data, the number of false candidates allocated for validation can be dramatically reduced using a pool of machine learning algorithms. This will ultimately save time and money in the laboratory.

A novel strategy for classifying the output from an in silico vaccine discovery pipeline for eukaryotic pathogens using machine learning algorithms

PubMed Central

2013-01-01

Background An in silico vaccine discovery pipeline for eukaryotic pathogens typically consists of several computational tools to predict protein characteristics. The aim of the in silico approach to discovering subunit vaccines is to use predicted characteristics to identify proteins which are worthy of laboratory investigation. A major challenge is that these predictions are inherent with hidden inaccuracies and contradictions. This study focuses on how to reduce the number of false candidates using machine learning algorithms rather than relying on expensive laboratory validation. Proteins from Toxoplasma gondii, Plasmodium sp., and Caenorhabditis elegans were used as training and test datasets. Results The results show that machine learning algorithms can effectively distinguish expected true from expected false vaccine candidates (with an average sensitivity and specificity of 0.97 and 0.98 respectively), for proteins observed to induce immune responses experimentally. Conclusions Vaccine candidates from an in silico approach can only be truly validated in a laboratory. Given any in silico output and appropriate training data, the number of false candidates allocated for validation can be dramatically reduced using a pool of machine learning algorithms. This will ultimately save time and money in the laboratory. PMID:24180526

The Salmonella In Silico Typing Resource (SISTR): An Open Web-Accessible Tool for Rapidly Typing and Subtyping Draft Salmonella Genome Assemblies.

PubMed

Yoshida, Catherine E; Kruczkiewicz, Peter; Laing, Chad R; Lingohr, Erika J; Gannon, Victor P J; Nash, John H E; Taboada, Eduardo N

2016-01-01

For nearly 100 years serotyping has been the gold standard for the identification of Salmonella serovars. Despite the increasing adoption of DNA-based subtyping approaches, serotype information remains a cornerstone in food safety and public health activities aimed at reducing the burden of salmonellosis. At the same time, recent advances in whole-genome sequencing (WGS) promise to revolutionize our ability to perform advanced pathogen characterization in support of improved source attribution and outbreak analysis. We present the Salmonella In Silico Typing Resource (SISTR), a bioinformatics platform for rapidly performing simultaneous in silico analyses for several leading subtyping methods on draft Salmonella genome assemblies. In addition to performing serovar prediction by genoserotyping, this resource integrates sequence-based typing analyses for: Multi-Locus Sequence Typing (MLST), ribosomal MLST (rMLST), and core genome MLST (cgMLST). We show how phylogenetic context from cgMLST analysis can supplement the genoserotyping analysis and increase the accuracy of in silico serovar prediction to over 94.6% on a dataset comprised of 4,188 finished genomes and WGS draft assemblies. In addition to allowing analysis of user-uploaded whole-genome assemblies, the SISTR platform incorporates a database comprising over 4,000 publicly available genomes, allowing users to place their isolates in a broader phylogenetic and epidemiological context. The resource incorporates several metadata driven visualizations to examine the phylogenetic, geospatial and temporal distribution of genome-sequenced isolates. As sequencing of Salmonella isolates at public health laboratories around the world becomes increasingly common, rapid in silico analysis of minimally processed draft genome assemblies provides a powerful approach for molecular epidemiology in support of public health investigations. Moreover, this type of integrated analysis using multiple sequence-based methods of sub-typing allows for continuity with historical serotyping data as we transition towards the increasing adoption of genomic analyses in epidemiology. The SISTR platform is freely available on the web at https://lfz.corefacility.ca/sistr-app/.

Ligation site in proteins recognized in silico

PubMed Central

Brylinski, Michal; Konieczny, Leszek; Roterman, Irena

2006-01-01

Recognition of a ligation site in a protein molecule is important for identifying its biological activity. The model for in silico recognition of ligation sites in proteins is presented. The idealized hydrophobic core stabilizing protein structure is represented by a three-dimensional Gaussian function. The experimentally observed distribution of hydrophobicity compared with the theoretical distribution reveals differences. The area of high differences indicates the ligation site. Availability http://bioinformatics.cm-uj.krakow.pl/activesite PMID:17597871

Principal component analysis-based unsupervised feature extraction applied to in silico drug discovery for posttraumatic stress disorder-mediated heart disease.

PubMed

Taguchi, Y-h; Iwadate, Mitsuo; Umeyama, Hideaki

2015-04-30

Feature extraction (FE) is difficult, particularly if there are more features than samples, as small sample numbers often result in biased outcomes or overfitting. Furthermore, multiple sample classes often complicate FE because evaluating performance, which is usual in supervised FE, is generally harder than the two-class problem. Developing sample classification independent unsupervised methods would solve many of these problems. Two principal component analysis (PCA)-based FE, specifically, variational Bayes PCA (VBPCA) was extended to perform unsupervised FE, and together with conventional PCA (CPCA)-based unsupervised FE, were tested as sample classification independent unsupervised FE methods. VBPCA- and CPCA-based unsupervised FE both performed well when applied to simulated data, and a posttraumatic stress disorder (PTSD)-mediated heart disease data set that had multiple categorical class observations in mRNA/microRNA expression of stressed mouse heart. A critical set of PTSD miRNAs/mRNAs were identified that show aberrant expression between treatment and control samples, and significant, negative correlation with one another. Moreover, greater stability and biological feasibility than conventional supervised FE was also demonstrated. Based on the results obtained, in silico drug discovery was performed as translational validation of the methods. Our two proposed unsupervised FE methods (CPCA- and VBPCA-based) worked well on simulated data, and outperformed two conventional supervised FE methods on a real data set. Thus, these two methods have suggested equivalence for FE on categorical multiclass data sets, with potential translational utility for in silico drug discovery.

Robust Phagocyte Recruitment Controls the Opportunistic Fungal Pathogen Mucor circinelloides in Innate Granulomas In Vivo

PubMed Central

2018-01-01

ABSTRACT Mucormycosis is an emerging fungal infection with extremely high mortality rates in patients with defects in their innate immune response, specifically in functions mediated through phagocytes. However, we currently have a limited understanding of the molecular and cellular interactions between these innate immune effectors and mucormycete spores during the early immune response. Here, the early events of innate immune recruitment in response to infection by Mucor circinelloides spores are modeled by a combined in silico modeling approach and real-time in vivo microscopy. Phagocytes are rapidly recruited to the site of infection in a zebrafish larval model of mucormycosis. This robust early recruitment protects from disease onset in vivo. In silico analysis identified that protection is dependent on the number of phagocytes at the infection site, but not the speed of recruitment. The mathematical model highlights the role of proinflammatory signals for phagocyte recruitment and the importance of inhibition of spore germination for protection from active fungal disease. These in silico data are supported by an in vivo lack of fungal spore killing and lack of reactive oxygen burst, which together result in latent fungal infection. During this latent stage of infection, spores are controlled in innate granulomas in vivo. Disease can be reactivated by immunosuppression. Together, these data represent the first in vivo real-time analysis of innate granuloma formation during the early stages of a fungal infection. The results highlight a potential latent stage during mucormycosis that should urgently be considered for clinical management of patients. PMID:29588406

Comparative Analysis and Modeling of the Severity of Steatohepatitis in DDC-Treated Mouse Strains

PubMed Central

Pandey, Vikash; Sultan, Marc; Kashofer, Karl; Ralser, Meryem; Amstislavskiy, Vyacheslav; Starmann, Julia; Osprian, Ingrid; Grimm, Christina; Hache, Hendrik; Yaspo, Marie-Laure; Sültmann, Holger; Trauner, Michael; Denk, Helmut; Zatloukal, Kurt; Lehrach, Hans; Wierling, Christoph

2014-01-01

Background Non-alcoholic fatty liver disease (NAFLD) has a broad spectrum of disease states ranging from mild steatosis characterized by an abnormal retention of lipids within liver cells to steatohepatitis (NASH) showing fat accumulation, inflammation, ballooning and degradation of hepatocytes, and fibrosis. Ultimately, steatohepatitis can result in liver cirrhosis and hepatocellular carcinoma. Methodology and Results In this study we have analyzed three different mouse strains, A/J, C57BL/6J, and PWD/PhJ, that show different degrees of steatohepatitis when administered a 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC) containing diet. RNA-Seq gene expression analysis, protein analysis and metabolic profiling were applied to identify differentially expressed genes/proteins and perturbed metabolite levels of mouse liver samples upon DDC-treatment. Pathway analysis revealed alteration of arachidonic acid (AA) and S-adenosylmethionine (SAMe) metabolism upon other pathways. To understand metabolic changes of arachidonic acid metabolism in the light of disease expression profiles a kinetic model of this pathway was developed and optimized according to metabolite levels. Subsequently, the model was used to study in silico effects of potential drug targets for steatohepatitis. Conclusions We identified AA/eicosanoid metabolism as highly perturbed in DDC-induced mice using a combination of an experimental and in silico approach. Our analysis of the AA/eicosanoid metabolic pathway suggests that 5-hydroxyeicosatetraenoic acid (5-HETE), 15-hydroxyeicosatetraenoic acid (15-HETE) and prostaglandin D2 (PGD2) are perturbed in DDC mice. We further demonstrate that a dynamic model can be used for qualitative prediction of metabolic changes based on transcriptomics data in a disease-related context. Furthermore, SAMe metabolism was identified as being perturbed due to DDC treatment. Several genes as well as some metabolites of this module show differences between A/J and C57BL/6J on the one hand and PWD/PhJ on the other. PMID:25347188

Comparative analysis and modeling of the severity of steatohepatitis in DDC-treated mouse strains.

PubMed

Pandey, Vikash; Sultan, Marc; Kashofer, Karl; Ralser, Meryem; Amstislavskiy, Vyacheslav; Starmann, Julia; Osprian, Ingrid; Grimm, Christina; Hache, Hendrik; Yaspo, Marie-Laure; Sültmann, Holger; Trauner, Michael; Denk, Helmut; Zatloukal, Kurt; Lehrach, Hans; Wierling, Christoph

2014-01-01

Non-alcoholic fatty liver disease (NAFLD) has a broad spectrum of disease states ranging from mild steatosis characterized by an abnormal retention of lipids within liver cells to steatohepatitis (NASH) showing fat accumulation, inflammation, ballooning and degradation of hepatocytes, and fibrosis. Ultimately, steatohepatitis can result in liver cirrhosis and hepatocellular carcinoma. In this study we have analyzed three different mouse strains, A/J, C57BL/6J, and PWD/PhJ, that show different degrees of steatohepatitis when administered a 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC) containing diet. RNA-Seq gene expression analysis, protein analysis and metabolic profiling were applied to identify differentially expressed genes/proteins and perturbed metabolite levels of mouse liver samples upon DDC-treatment. Pathway analysis revealed alteration of arachidonic acid (AA) and S-adenosylmethionine (SAMe) metabolism upon other pathways. To understand metabolic changes of arachidonic acid metabolism in the light of disease expression profiles a kinetic model of this pathway was developed and optimized according to metabolite levels. Subsequently, the model was used to study in silico effects of potential drug targets for steatohepatitis. We identified AA/eicosanoid metabolism as highly perturbed in DDC-induced mice using a combination of an experimental and in silico approach. Our analysis of the AA/eicosanoid metabolic pathway suggests that 5-hydroxyeicosatetraenoic acid (5-HETE), 15-hydroxyeicosatetraenoic acid (15-HETE) and prostaglandin D2 (PGD2) are perturbed in DDC mice. We further demonstrate that a dynamic model can be used for qualitative prediction of metabolic changes based on transcriptomics data in a disease-related context. Furthermore, SAMe metabolism was identified as being perturbed due to DDC treatment. Several genes as well as some metabolites of this module show differences between A/J and C57BL/6J on the one hand and PWD/PhJ on the other.

Proposal of an in silico profiler for categorisation of repeat dose toxicity data of hair dyes.

PubMed

Nelms, M D; Ates, G; Madden, J C; Vinken, M; Cronin, M T D; Rogiers, V; Enoch, S J

2015-05-01

This study outlines the analysis of 94 chemicals with repeat dose toxicity data taken from Scientific Committee on Consumer Safety opinions for commonly used hair dyes in the European Union. Structural similarity was applied to group these chemicals into categories. Subsequent mechanistic analysis suggested that toxicity to mitochondria is potentially a key driver of repeat dose toxicity for chemicals within each of the categories. The mechanistic hypothesis allowed for an in silico profiler consisting of four mechanism-based structural alerts to be proposed. These structural alerts related to a number of important chemical classes such as quinones, anthraquinones, substituted nitrobenzenes and aromatic azos. This in silico profiler is intended for grouping chemicals into mechanism-based categories within the adverse outcome pathway paradigm.

Physical and in silico approaches identify DNA-PK in a Tax DNA-damage response interactome

PubMed Central

Ramadan, Emad; Ward, Michael; Guo, Xin; Durkin, Sarah S; Sawyer, Adam; Vilela, Marcelo; Osgood, Christopher; Pothen, Alex; Semmes, Oliver J

2008-01-01

Background We have initiated an effort to exhaustively map interactions between HTLV-1 Tax and host cellular proteins. The resulting Tax interactome will have significant utility toward defining new and understanding known activities of this important viral protein. In addition, the completion of a full Tax interactome will also help shed light upon the functional consequences of these myriad Tax activities. The physical mapping process involved the affinity isolation of Tax complexes followed by sequence identification using tandem mass spectrometry. To date we have mapped 250 cellular components within this interactome. Here we present our approach to prioritizing these interactions via an in silico culling process. Results We first constructed an in silico Tax interactome comprised of 46 literature-confirmed protein-protein interactions. This number was then reduced to four Tax-interactions suspected to play a role in DNA damage response (Rad51, TOP1, Chk2, 53BP1). The first-neighbor and second-neighbor interactions of these four proteins were assembled from available human protein interaction databases. Through an analysis of betweenness and closeness centrality measures, and numbers of interactions, we ranked proteins in the first neighborhood. When this rank list was compared to the list of physical Tax-binding proteins, DNA-PK was the highest ranked protein common to both lists. An overlapping clustering of the Tax-specific second-neighborhood protein network showed DNA-PK to be one of three bridge proteins that link multiple clusters in the DNA damage response network. Conclusion The interaction of Tax with DNA-PK represents an important biological paradigm as suggested via consensus findings in vivo and in silico. We present this methodology as an approach to discovery and as a means of validating components of a consensus Tax interactome. PMID:18922151

In silico analysis of the fucosylation-associated genome of the human blood fluke Schistosoma mansoni: cloning and characterization of the fucosyltransferase multigene family.

PubMed

Peterson, Nathan A; Anderson, Tavis K; Yoshino, Timothy P

2013-01-01

Fucosylated glycans of the parasitic flatworm Schistosoma mansoni play key roles in its development and immunobiology. In the present study we used a genome-wide homology-based bioinformatics approach to search for genes that contribute to fucosylated glycan expression in S. mansoni, specifically the α2-, α3-, and α6-fucosyltransferases (FucTs), which transfer L-fucose from a GDP-L-fucose donor to an oligosaccharide acceptor. We identified and in silico characterized several novel schistosome FucT homologs, including six α3-FucTs and six α6-FucTs, as well as two protein O-FucTs that catalyze the unrelated transfer of L-fucose to serine and threonine residues of epidermal growth factor- and thrombospondin-type repeats. No α2-FucTs were observed. Primary sequence analyses identified key conserved FucT motifs as well as characteristic transmembrane domains, consistent with their putative roles as fucosyltransferases. Most genes exhibit alternative splicing, with multiple transcript variants generated. A phylogenetic analysis demonstrated that schistosome α3- and α6-FucTs form monophyletic clades within their respective gene families, suggesting multiple gene duplications following the separation of the schistosome lineage from the main evolutionary tree. Quantitative decreases in steady-state transcript levels of some FucTs during early larval development suggest a possible mechanism for differential expression of fucosylated glycans in schistosomes. This study systematically identifies the complete repertoire of FucT homologs in S. mansoni and provides fundamental information regarding their genomic organization, genetic variation, developmental expression, and evolutionary history.

Computational Methods to Work as First-Pass Filter in Deleterious SNP Analysis of Alkaptonuria

PubMed Central

Magesh, R.; George Priya Doss, C.

2012-01-01

A major challenge in the analysis of human genetic variation is to distinguish functional from nonfunctional SNPs. Discovering these functional SNPs is one of the main goals of modern genetics and genomics studies. There is a need to effectively and efficiently identify functionally important nsSNPs which may be deleterious or disease causing and to identify their molecular effects. The prediction of phenotype of nsSNPs by computational analysis may provide a good way to explore the function of nsSNPs and its relationship with susceptibility to disease. In this context, we surveyed and compared variation databases along with in silico prediction programs to assess the effects of deleterious functional variants on protein functions. In other respects, we attempted these methods to work as first-pass filter to identify the deleterious substitutions worth pursuing for further experimental research. In this analysis, we used the existing computational methods to explore the mutation-structure-function relationship in HGD gene causing alkaptonuria. PMID:22606059

Discovery of Anti-Hypertensive Oligopeptides from Adlay Based on In Silico Proteolysis and Virtual Screening

PubMed Central

Qiao, Liansheng; Li, Bin; Chen, Yankun; Li, Lingling; Chen, Xi; Wang, Lingzhi; Lu, Fang; Luo, Ganggang; Li, Gongyu; Zhang, Yanling

2016-01-01

Adlay (Coix larchryma-jobi L.) was the commonly used Traditional Chinese Medicine (TCM) with high content of seed storage protein. The hydrolyzed bioactive oligopeptides of adlay have been proven to be anti-hypertensive effective components. However, the structures and anti-hypertensive mechanism of bioactive oligopeptides from adlay were not clear. To discover the definite anti-hypertensive oligopeptides from adlay, in silico proteolysis and virtual screening were implemented to obtain potential oligopeptides, which were further identified by biochemistry assay and molecular dynamics simulation. In this paper, ten sequences of adlay prolamins were collected and in silico hydrolyzed to construct the oligopeptide library with 134 oligopeptides. This library was reverse screened by anti-hypertensive pharmacophore database, which was constructed by our research team and contained ten anti-hypertensive targets. Angiotensin-I converting enzyme (ACE) was identified as the main potential target for the anti-hypertensive activity of adlay oligopeptides. Three crystal structures of ACE were utilized for docking studies and 19 oligopeptides were finally identified with potential ACE inhibitory activity. According to mapping features and evaluation indexes of pharmacophore and docking, three oligopeptides were selected for biochemistry assay. An oligopeptide sequence, NPATY (IC50 = 61.88 ± 2.77 µM), was identified as the ACE inhibitor by reverse-phase high performance liquid chromatography (RP-HPLC) assay. Molecular dynamics simulation of NPATY was further utilized to analyze interactive bonds and key residues. ALA354 was identified as a key residue of ACE inhibitors. Hydrophobic effect of VAL518 and electrostatic effects of HIS383, HIS387, HIS513 and Zn2+ were also regarded as playing a key role in inhibiting ACE activities. This study provides a research strategy to explore the pharmacological mechanism of Traditional Chinese Medicine (TCM) proteins based on in silico proteolysis and virtual screening, which could be beneficial to reveal the pharmacological action of TCM proteins and provide new lead compounds for peptides-based drug design. PMID:27983650

Proteome-wide identification of predominant subcellular protein localizations in a bacterial model organism.

PubMed

Stekhoven, Daniel J; Omasits, Ulrich; Quebatte, Maxime; Dehio, Christoph; Ahrens, Christian H

2014-03-17

Proteomics data provide unique insights into biological systems, including the predominant subcellular localization (SCL) of proteins, which can reveal important clues about their functions. Here we analyzed data of a complete prokaryotic proteome expressed under two conditions mimicking interaction of the emerging pathogen Bartonella henselae with its mammalian host. Normalized spectral count data from cytoplasmic, total membrane, inner and outer membrane fractions allowed us to identify the predominant SCL for 82% of the identified proteins. The spectral count proportion of total membrane versus cytoplasmic fractions indicated the propensity of cytoplasmic proteins to co-fractionate with the inner membrane, and enabled us to distinguish cytoplasmic, peripheral inner membrane and bona fide inner membrane proteins. Principal component analysis and k-nearest neighbor classification training on selected marker proteins or predominantly localized proteins, allowed us to determine an extensive catalog of at least 74 expressed outer membrane proteins, and to extend the SCL assignment to 94% of the identified proteins, including 18% where in silico methods gave no prediction. Suitable experimental proteomics data combined with straightforward computational approaches can thus identify the predominant SCL on a proteome-wide scale. Finally, we present a conceptual approach to identify proteins potentially changing their SCL in a condition-dependent fashion. The work presented here describes the first prokaryotic proteome-wide subcellular localization (SCL) dataset for the emerging pathogen B. henselae (Bhen). The study indicates that suitable subcellular fractionation experiments combined with straight-forward computational analysis approaches assessing the proportion of spectral counts observed in different subcellular fractions are powerful for determining the predominant SCL of a large percentage of the experimentally observed proteins. This includes numerous cases where in silico prediction methods do not provide any prediction. Avoiding a treatment with harsh conditions, cytoplasmic proteins tend to co-fractionate with proteins of the inner membrane fraction, indicative of close functional interactions. The spectral count proportion (SCP) of total membrane versus cytoplasmic fractions allowed us to obtain a good indication about the relative proximity of individual protein complex members to the inner membrane. Using principal component analysis and k-nearest neighbor approaches, we were able to extend the percentage of proteins with a predominant experimental localization to over 90% of all expressed proteins and identified a set of at least 74 outer membrane (OM) proteins. In general, OM proteins represent a rich source of candidates for the development of urgently needed new therapeutics in combat of resurgence of infectious disease and multi-drug resistant bacteria. Finally, by comparing the data from two infection biology relevant conditions, we conceptually explore methods to identify and visualize potential candidates that may partially change their SCL in these different conditions. The data are made available to researchers as a SCL compendium for Bhen and as an assistance in further improving in silico SCL prediction algorithms. Copyright © 2014 Elsevier B.V. All rights reserved.

Performance of in silico prediction tools for the classification of rare BRCA1/2 missense variants in clinical diagnostics.

PubMed

Ernst, Corinna; Hahnen, Eric; Engel, Christoph; Nothnagel, Michael; Weber, Jonas; Schmutzler, Rita K; Hauke, Jan

2018-03-27

The use of next-generation sequencing approaches in clinical diagnostics has led to a tremendous increase in data and a vast number of variants of uncertain significance that require interpretation. Therefore, prediction of the effects of missense mutations using in silico tools has become a frequently used approach. Aim of this study was to assess the reliability of in silico prediction as a basis for clinical decision making in the context of hereditary breast and/or ovarian cancer. We tested the performance of four prediction tools (Align-GVGD, SIFT, PolyPhen-2, MutationTaster2) using a set of 236 BRCA1/2 missense variants that had previously been classified by expert committees. However, a major pitfall in the creation of a reliable evaluation set for our purpose is the generally accepted classification of BRCA1/2 missense variants using the multifactorial likelihood model, which is partially based on Align-GVGD results. To overcome this drawback we identified 161 variants whose classification is independent of any previous in silico prediction. In addition to the performance as stand-alone tools we examined the sensitivity, specificity, accuracy and Matthews correlation coefficient (MCC) of combined approaches. PolyPhen-2 achieved the lowest sensitivity (0.67), specificity (0.67), accuracy (0.67) and MCC (0.39). Align-GVGD achieved the highest values of specificity (0.92), accuracy (0.92) and MCC (0.73), but was outperformed regarding its sensitivity (0.90) by SIFT (1.00) and MutationTaster2 (1.00). All tools suffered from poor specificities, resulting in an unacceptable proportion of false positive results in a clinical setting. This shortcoming could not be bypassed by combination of these tools. In the best case scenario, 138 families would be affected by the misclassification of neutral variants within the cohort of patients of the German Consortium for Hereditary Breast and Ovarian Cancer. We show that due to low specificities state-of-the-art in silico prediction tools are not suitable to predict pathogenicity of variants of uncertain significance in BRCA1/2. Thus, clinical consequences should never be based solely on in silico forecasts. However, our data suggests that SIFT and MutationTaster2 could be suitable to predict benignity, as both tools did not result in false negative predictions in our analysis.

An inventory of the Aspergillus niger secretome by combining in silico predictions with shotgun proteomics data.

PubMed

Braaksma, Machtelt; Martens-Uzunova, Elena S; Punt, Peter J; Schaap, Peter J

2010-10-19

The ecological niche occupied by a fungal species, its pathogenicity and its usefulness as a microbial cell factory to a large degree depends on its secretome. Protein secretion usually requires the presence of a N-terminal signal peptide (SP) and by scanning for this feature using available highly accurate SP-prediction tools, the fraction of potentially secreted proteins can be directly predicted. However, prediction of a SP does not guarantee that the protein is actually secreted and current in silico prediction methods suffer from gene-model errors introduced during genome annotation. A majority rule based classifier that also evaluates signal peptide predictions from the best homologs of three neighbouring Aspergillus species was developed to create an improved list of potential signal peptide containing proteins encoded by the Aspergillus niger genome. As a complement to these in silico predictions, the secretome associated with growth and upon carbon source depletion was determined using a shotgun proteomics approach. Overall, some 200 proteins with a predicted signal peptide were identified to be secreted proteins. Concordant changes in the secretome state were observed as a response to changes in growth/culture conditions. Additionally, two proteins secreted via a non-classical route operating in A. niger were identified. We were able to improve the in silico inventory of A. niger secretory proteins by combining different gene-model predictions from neighbouring Aspergilli and thereby avoiding prediction conflicts associated with inaccurate gene-models. The expected accuracy of signal peptide prediction for proteins that lack homologous sequences in the proteomes of related species is 85%. An experimental validation of the predicted proteome confirmed in silico predictions.

An inventory of the Aspergillus niger secretome by combining in silico predictions with shotgun proteomics data

PubMed Central

2010-01-01

Background The ecological niche occupied by a fungal species, its pathogenicity and its usefulness as a microbial cell factory to a large degree depends on its secretome. Protein secretion usually requires the presence of a N-terminal signal peptide (SP) and by scanning for this feature using available highly accurate SP-prediction tools, the fraction of potentially secreted proteins can be directly predicted. However, prediction of a SP does not guarantee that the protein is actually secreted and current in silico prediction methods suffer from gene-model errors introduced during genome annotation. Results A majority rule based classifier that also evaluates signal peptide predictions from the best homologs of three neighbouring Aspergillus species was developed to create an improved list of potential signal peptide containing proteins encoded by the Aspergillus niger genome. As a complement to these in silico predictions, the secretome associated with growth and upon carbon source depletion was determined using a shotgun proteomics approach. Overall, some 200 proteins with a predicted signal peptide were identified to be secreted proteins. Concordant changes in the secretome state were observed as a response to changes in growth/culture conditions. Additionally, two proteins secreted via a non-classical route operating in A. niger were identified. Conclusions We were able to improve the in silico inventory of A. niger secretory proteins by combining different gene-model predictions from neighbouring Aspergilli and thereby avoiding prediction conflicts associated with inaccurate gene-models. The expected accuracy of signal peptide prediction for proteins that lack homologous sequences in the proteomes of related species is 85%. An experimental validation of the predicted proteome confirmed in silico predictions. PMID:20959013

Functional examination of MLH1, MSH2, and MSH6 intronic mutations identified in Danish colorectal cancer patients.

PubMed

Petersen, Sanne M; Dandanell, Mette; Rasmussen, Lene J; Gerdes, Anne-Marie; Krogh, Lotte N; Bernstein, Inge; Okkels, Henrik; Wikman, Friedrik; Nielsen, Finn C; Hansen, Thomas V O

2013-10-03

Germ-line mutations in the DNA mismatch repair genes MLH1, MSH2, and MSH6 predispose to the development of colorectal cancer (Lynch syndrome or hereditary nonpolyposis colorectal cancer). These mutations include disease-causing frame-shift, nonsense, and splicing mutations as well as large genomic rearrangements. However, a large number of mutations, including missense, silent, and intronic variants, are classified as variants of unknown clinical significance. Intronic MLH1, MSH2, or MSH6 variants were investigated using in silico prediction tools and mini-gene assay to asses the effect on splicing. We describe in silico and in vitro characterization of nine intronic MLH1, MSH2, or MSH6 mutations identified in Danish colorectal cancer patients, of which four mutations are novel. The analysis revealed aberrant splicing of five mutations (MLH1 c.588 + 5G > A, MLH1 c.677 + 3A > T, MLH1 c.1732-2A > T, MSH2 c.1276 + 1G > T, and MSH2 c.1662-2A > C), while four mutations had no effect on splicing compared to wild type (MLH1 c.117-34A > T, MLH1 c.1039-8 T > A, MSH2 c.2459-18delT, and MSH6 c.3439-16C > T). In conclusion, we classify five MLH1/MSH2 mutations as pathogenic, whereas four MLH1/MSH2/MSH6 mutations are classified as neutral. This study supports the notion that in silico prediction tools and mini-gene assays are important for the classification of intronic variants, and thereby crucial for the genetic counseling of patients and their family members.

Reliable differentiation of Meyerozyma guilliermondii from Meyerozyma caribbica by internal transcribed spacer restriction fingerprinting.

PubMed

Romi, Wahengbam; Keisam, Santosh; Ahmed, Giasuddin; Jeyaram, Kumaraswamy

2014-02-28

Meyerozyma guilliermondii (anamorph Candida guilliermondii) and Meyerozyma caribbica (anamorph Candida fermentati) are closely related species of the genetically heterogenous M. guilliermondii complex. Conventional phenotypic methods frequently misidentify the species within this complex and also with other species of the Saccharomycotina CTG clade. Even the long-established sequencing of large subunit (LSU) rRNA gene remains ambiguous. We also faced similar problem during identification of yeast isolates of M. guilliermondii complex from indigenous bamboo shoot fermentation in North East India. There is a need for development of reliable and accurate identification methods for these closely related species because of their increasing importance as emerging infectious yeasts and associated biotechnological attributes. We targeted the highly variable internal transcribed spacer (ITS) region (ITS1-5.8S-ITS2) and identified seven restriction enzymes through in silico analysis for differentiating M. guilliermondii from M. caribbica. Fifty five isolates of M. guilliermondii complex which could not be delineated into species-specific taxonomic ranks by API 20 C AUX and LSU rRNA gene D1/D2 sequencing were subjected to ITS-restriction fragment length polymorphism (ITS-RFLP) analysis. TaqI ITS-RFLP distinctly differentiated the isolates into M. guilliermondii (47 isolates) and M. caribbica (08 isolates) with reproducible species-specific patterns similar to the in silico prediction. The reliability of this method was validated by ITS1-5.8S-ITS2 sequencing, mitochondrial DNA RFLP and electrophoretic karyotyping. We herein described a reliable ITS-RFLP method for distinct differentiation of frequently misidentified M. guilliermondii from M. caribbica. Even though in silico analysis differentiated other closely related species of M. guilliermondii complex from the above two species, it is yet to be confirmed by in vitro analysis using reference strains. This method can be used as a reliable tool for rapid and accurate identification of closely related species of M. guilliermondii complex and for differentiating emerging infectious yeasts of the Saccharomycotina CTG clade.

A comparative in silico linear B-cell epitope prediction and characterization for South American and African Trypanosoma vivax strains.

PubMed

Guedes, Rafael Lucas Muniz; Rodrigues, Carla Monadeli Filgueira; Coatnoan, Nicolas; Cosson, Alain; Cadioli, Fabiano Antonio; Garcia, Herakles Antonio; Gerber, Alexandra Lehmkuhl; Machado, Rosangela Zacarias; Minoprio, Paola Marcella Camargo; Teixeira, Marta Maria Geraldes; de Vasconcelos, Ana Tereza Ribeiro

2018-02-27

Trypanosoma vivax is a parasite widespread across Africa and South America. Immunological methods using recombinant antigens have been developed aiming at specific and sensitive detection of infections caused by T. vivax. Here, we sequenced for the first time the transcriptome of a virulent T. vivax strain (Lins), isolated from an outbreak of severe disease in South America (Brazil) and performed a computational integrated analysis of genome, transcriptome and in silico predictions to identify and characterize putative linear B-cell epitopes from African and South American T. vivax. A total of 2278, 3936 and 4062 linear B-cell epitopes were respectively characterized for the transcriptomes of T. vivax LIEM-176 (Venezuela), T. vivax IL1392 (Nigeria) and T. vivax Lins (Brazil) and 4684 for the genome of T. vivax Y486 (Nigeria). The results presented are a valuable theoretical source that may pave the way for highly sensitive and specific diagnostic tools. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Protein cleavage strategies for an improved analysis of the membrane proteome

PubMed Central

Fischer, Frank; Poetsch, Ansgar

2006-01-01

Background Membrane proteins still remain elusive in proteomic studies. This is in part due to the distribution of the amino acids lysine and arginine, which are less frequent in integral membrane proteins and almost absent in transmembrane helices. As these amino acids are cleavage targets for the commonly used protease trypsin, alternative cleavage conditions, which should improve membrane protein analysis, were tested by in silico digestion for the three organisms Saccharomyces cerevisiae, Halobacterium sp. NRC-1, and Corynebacterium glutamicum as hallmarks for eukaryotes, archea and eubacteria. Results For the membrane proteomes from all three analyzed organisms, we identified cleavage conditions that achieve better sequence and proteome coverage than trypsin. Greater improvement was obtained for bacteria than for yeast, which was attributed to differences in protein size and GRAVY. It was demonstrated for bacteriorhodopsin that the in silico predictions agree well with the experimental observations. Conclusion For all three examined organisms, it was found that a combination of chymotrypsin and staphylococcal peptidase I gave significantly better results than trypsin. As some of the improved cleavage conditions are not more elaborate than trypsin digestion and have been proven useful in practice, we suppose that the cleavage at both hydrophilic and hydrophobic amino acids should facilitate in general the analysis of membrane proteins for all organisms. PMID:16512920

Genome wide association study (GWAS) for grain yield in rice cultivated under water deficit.

PubMed

Pantalião, Gabriel Feresin; Narciso, Marcelo; Guimarães, Cléber; Castro, Adriano; Colombari, José Manoel; Breseghello, Flavio; Rodrigues, Luana; Vianello, Rosana Pereira; Borba, Tereza Oliveira; Brondani, Claudio

2016-12-01

The identification of rice drought tolerant materials is crucial for the development of best performing cultivars for the upland cultivation system. This study aimed to identify markers and candidate genes associated with drought tolerance by Genome Wide Association Study analysis, in order to develop tools for use in rice breeding programs. This analysis was made with 175 upland rice accessions (Oryza sativa), evaluated in experiments with and without water restriction, and 150,325 SNPs. Thirteen SNP markers associated with yield under drought conditions were identified. Through stepwise regression analysis, eight SNP markers were selected and validated in silico, and when tested by PCR, two out of the eight SNP markers were able to identify a group of rice genotypes with higher productivity under drought. These results are encouraging for deriving markers for the routine analysis of marker assisted selection. From the drought experiment, including the genes inherited in linkage blocks, 50 genes were identified, from which 30 were annotated, and 10 were previously related to drought and/or abiotic stress tolerance, such as the transcription factors WRKY and Apetala2, and protein kinases.

Evaluation of a genome-scale in silico metabolic model for Geobacter metallireducens by using proteomic data from a field biostimulation experiment.

PubMed

Fang, Yilin; Wilkins, Michael J; Yabusaki, Steven B; Lipton, Mary S; Long, Philip E

2012-12-01

Accurately predicting the interactions between microbial metabolism and the physical subsurface environment is necessary to enhance subsurface energy development, soil and groundwater cleanup, and carbon management. This study was an initial attempt to confirm the metabolic functional roles within an in silico model using environmental proteomic data collected during field experiments. Shotgun global proteomics data collected during a subsurface biostimulation experiment were used to validate a genome-scale metabolic model of Geobacter metallireducens-specifically, the ability of the metabolic model to predict metal reduction, biomass yield, and growth rate under dynamic field conditions. The constraint-based in silico model of G. metallireducens relates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes. Proteomic analysis showed that 180 of the 637 G. metallireducens proteins detected during the 2008 experiment were associated with specific metabolic reactions in the in silico model. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through the in silico model reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low abundances of proteins associated with amino acid transport and metabolism, revealed pathways or flux constraints in the in silico model that could be updated to more accurately predict metabolic processes that occur in the subsurface environment.

Characterizing the Grape Transcriptome. Analysis of Expressed Sequence Tags from Multiple Vitis Species and Development of a Compendium of Gene Expression during Berry Development1[w

PubMed Central

Silva, Francisco Goes da; Iandolino, Alberto; Al-Kayal, Fadi; Bohlmann, Marlene C.; Cushman, Mary Ann; Lim, Hyunju; Ergul, Ali; Figueroa, Rubi; Kabuloglu, Elif K.; Osborne, Craig; Rowe, Joan; Tattersall, Elizabeth; Leslie, Anna; Xu, Jane; Baek, JongMin; Cramer, Grant R.; Cushman, John C.; Cook, Douglas R.

2005-01-01

We report the analysis and annotation of 146,075 expressed sequence tags from Vitis species. The majority of these sequences were derived from different cultivars of Vitis vinifera, comprising an estimated 25,746 unique contig and singleton sequences that survey transcription in various tissues and developmental stages and during biotic and abiotic stress. Putatively homologous proteins were identified for over 17,752 of the transcripts, with 1,962 transcripts further subdivided into one or more Gene Ontology categories. A simple structured vocabulary, with modules for plant genotype, plant development, and stress, was developed to describe the relationship between individual expressed sequence tags and cDNA libraries; the resulting vocabulary provides query terms to facilitate data mining within the context of a relational database. As a measure of the extent to which characterized metabolic pathways were encompassed by the data set, we searched for homologs of the enzymes leading from glycolysis, through the oxidative/nonoxidative pentose phosphate pathway, and into the general phenylpropanoid pathway. Homologs were identified for 65 of these 77 enzymes, with 86% of enzymatic steps represented by paralogous genes. Differentially expressed transcripts were identified by means of a stringent believability index cutoff of ≥98.4%. Correlation analysis and two-dimensional hierarchical clustering grouped these transcripts according to similarity of expression. In the broadest analysis, 665 differentially expressed transcripts were identified across 29 cDNA libraries, representing a range of developmental and stress conditions. The groupings revealed expected associations between plant developmental stages and tissue types, with the notable exception of abiotic stress treatments. A more focused analysis of flower and berry development identified 87 differentially expressed transcripts and provides the basis for a compendium that relates gene expression and annotation to previously characterized aspects of berry development and physiology. Comparison with published results for select genes, as well as correlation analysis between independent data sets, suggests that the inferred in silico patterns of expression are likely to be an accurate representation of transcript abundance for the conditions surveyed. Thus, the combined data set reveals the in silico expression patterns for hundreds of genes in V. vinifera, the majority of which have not been previously studied within this species. PMID:16219919

Genome-Wide Identification and Transferability of Microsatellite Markers between Palmae Species

PubMed Central

Xiao, Yong; Xia, Wei; Ma, Jianwei; Mason, Annaliese S.; Fan, Haikuo; Shi, Peng; Lei, Xintao; Ma, Zilong; Peng, Ming

2016-01-01

The Palmae family contains 202 genera and approximately 2800 species. Except for Elaeis guineensis and Phoenix dactylifera, almost no genetic and genomic information is available for Palmae species. Therefore, this is an obstacle to the conservation and genetic assessment of Palmae species, especially those that are currently endangered. The study was performed to develop a large number of microsatellite markers which can be used for genetic analysis in different Palmae species. Based on the assembled genome of E. guineensis and P. dactylifera, a total of 814 383 and 371 629 microsatellites were identified. Among these microsatellites identified in E. guineensis, 734 509 primer pairs could be designed from the flanking sequences of these microsatellites. The majority (618 762) of these designed primer pairs had in silico products in the genome of E. guineensis. These 618 762 primer pairs were subsequently used to in silico amplify the genome of P. dactylifera. A total of 7 265 conserved microsatellites were identified between E. guineensis and P. dactylifera. One hundred and thirty-five primer pairs flanking the conserved SSRs were stochastically selected and validated to have high cross-genera transferability, varying from 16.7 to 93.3% with an average of 73.7%. These genome-wide conserved microsatellite markers will provide a useful tool for genetic assessment and conservation of different Palmae species in the future. PMID:27826307

Analysis of the interactome of the Ser/Thr Protein Phosphatase type 1 in Plasmodium falciparum.

PubMed

Hollin, Thomas; De Witte, Caroline; Lenne, Astrid; Pierrot, Christine; Khalife, Jamal

2016-03-17

Protein Phosphatase 1 (PP1) is an enzyme essential to cell viability in the malaria parasite Plasmodium falciparum (Pf). The activity of PP1 is regulated by the binding of regulatory subunits, of which there are up to 200 in humans, but only 3 have been so far reported for the parasite. To better understand the P. falciparum PP1 (PfPP1) regulatory network, we here report the use of three strategies to characterize the PfPP1 interactome: co-affinity purified proteins identified by mass spectrometry, yeast two-hybrid (Y2H) screening and in silico analysis of the P. falciparum predicted proteome. Co-affinity purification followed by MS analysis identified 6 PfPP1 interacting proteins (Pips) of which 3 contained the RVxF consensus binding, 2 with a Fxx[RK]x[RK] motif, also shown to be a PP1 binding motif and one with both binding motifs. The Y2H screens identified 134 proteins of which 30 present the RVxF binding motif and 20 have the Fxx[RK]x[RK] binding motif. The in silico screen of the Pf predicted proteome using a consensus RVxF motif as template revealed the presence of 55 potential Pips. As further demonstration, 35 candidate proteins were validated as PfPP1 interacting proteins in an ELISA-based assay. To the best of our knowledge, this is the first study on PfPP1 interactome. The data reports several conserved PP1 interacting proteins as well as a high number of specific interactors to PfPP1. Their analysis indicates a high diversity of biological functions for PP1 in Plasmodium. Based on the present data and on an earlier study of the Pf interactome, a potential implication of Pips in protein folding/proteolysis, transcription and pathogenicity networks is proposed. The present work provides a starting point for further studies on the structural basis of these interactions and their functions in P. falciparum.

Meta-analysis identifies six new susceptibility loci for atrial fibrillation

PubMed Central

Ellinor, Patrick T; Lunetta, Kathryn L; Albert, Christine M; Glazer, Nicole L; Ritchie, Marylyn D; Smith, Albert V; Arking, Dan E; Müller-Nurasyid, Martina; Krijthe, Bouwe P; Lubitz, Steven A; Bis, Joshua C; Chung, Mina K; Dörr, Marcus; Ozaki, Kouichi; Roberts, Jason D; Smith, J Gustav; Pfeufer, Arne; Sinner, Moritz F; Lohman, Kurt; Ding, Jingzhong; Smith, Nicholas L; Smith, Jonathan D; Rienstra, Michiel; Rice, Kenneth M; Van Wagoner, David R; Magnani, Jared W; Wakili, Reza; Clauss, Sebastian; Rotter, Jerome I; Steinbeck, Gerhard; Launer, Lenore J; Davies, Robert W; Borkovich, Matthew; Harris, Tamara B; Lin, Honghuang; Völker, Uwe; Völzke, Henry; Milan, David J; Hofman, Albert; Boerwinkle, Eric; Chen, Lin Y; Soliman, Elsayed Z; Voight, Benjamin F; Li, Guo; Chakravarti, Aravinda; Kubo, Michiaki; Tedrow, Usha B; Rose, Lynda M; Ridker, Paul M; Conen, David; Tsunoda, Tatsuhiko; Furukawa, Tetsushi; Sotoodehnia, Nona; Xu, Siyan; Kamatani, Naoyuki; Levy, Daniel; Nakamura, Yusuke; Parvez, Babar; Mahida, Saagar; Furie, Karen L; Rosand, Jonathan; Muhammad, Raafia; Psaty, Bruce M; Meitinger, Thomas; Perz, Siegfried; Wichmann, H-Erich; Witteman, Jacqueline C M; Kao, W H Linda; Kathiresan, Sekar; Roden, Dan M; Uitterlinden, Andre G; Rivadeneira, Fernando; McKnight, Barbara; Sjögren, Marketa; Newman, Anne B; Liu, Yongmei; Gollob, Michael H; Melander, Olle; Tanaka, Toshihiro; Ch Stricker, Bruno H; Felix, Stephan B; Alonso, Alvaro; Darbar, Dawood; Barnard, John; Chasman, Daniel I; Heckbert, Susan R; Benjamin, Emelia J; Gudnason, Vilmundur; Kääb, Stefan

2012-01-01

Atrial fibrillation is a highly prevalent arrhythmia and a major risk factor for stroke, heart failure and death1. We conducted a genome-wide association study (GWAS) in individuals of European ancestry, including 6,707 with and 52,426 without atrial fibrillation. Six new atrial fibrillation susceptibility loci were identified and replicated in an additional sample of individuals of European ancestry, including 5,381 subjects with and 1 0,030 subjects without atrial fibrillation (P < 5 × 10−8). Four of the loci identified in Europeans were further replicated in silico in a GWAS of Japanese individuals, including 843 individuals with and 3,350 individuals without atrial fibrillation. The identified loci implicate candidate genes that encode transcription factors related to cardiopulmonary development, cardiac-expressed ion channels and cell signaling molecules. PMID:22544366

DIANA-LncBase v2: indexing microRNA targets on non-coding transcripts

PubMed Central

Paraskevopoulou, Maria D.; Vlachos, Ioannis S.; Karagkouni, Dimitra; Georgakilas, Georgios; Kanellos, Ilias; Vergoulis, Thanasis; Zagganas, Konstantinos; Tsanakas, Panayiotis; Floros, Evangelos; Dalamagas, Theodore; Hatzigeorgiou, Artemis G.

2016-01-01

microRNAs (miRNAs) are short non-coding RNAs (ncRNAs) that act as post-transcriptional regulators of coding gene expression. Long non-coding RNAs (lncRNAs) have been recently reported to interact with miRNAs. The sponge-like function of lncRNAs introduces an extra layer of complexity in the miRNA interactome. DIANA-LncBase v1 provided a database of experimentally supported and in silico predicted miRNA Recognition Elements (MREs) on lncRNAs. The second version of LncBase (www.microrna.gr/LncBase) presents an extensive collection of miRNA:lncRNA interactions. The significantly enhanced database includes more than 70 000 low and high-throughput, (in)direct miRNA:lncRNA experimentally supported interactions, derived from manually curated publications and the analysis of 153 AGO CLIP-Seq libraries. The new experimental module presents a 14-fold increase compared to the previous release. LncBase v2 hosts in silico predicted miRNA targets on lncRNAs, identified with the DIANA-microT algorithm. The relevant module provides millions of predicted miRNA binding sites, accompanied with detailed metadata and MRE conservation metrics. LncBase v2 caters information regarding cell type specific miRNA:lncRNA regulation and enables users to easily identify interactions in 66 different cell types, spanning 36 tissues for human and mouse. Database entries are also supported by accurate lncRNA expression information, derived from the analysis of more than 6 billion RNA-Seq reads. PMID:26612864

In silico search, characterization and validation of new EST-SSR markers in the genus Prunus.

PubMed

Sorkheh, Karim; Prudencio, Angela S; Ghebinejad, Azim; Dehkordi, Mehrana Kohei; Erogul, Deniz; Rubio, Manuel; Martínez-Gómez, Pedro

2016-07-07

Simple sequence repeats (SSRs) are defined as sequence repeat units between 1 and 6 bp that occur in both coding and non-coding regions abundant in eukaryotic genomes, which may affect the expression of genes. In this study, expressed sequence tags (ESTs) of eight Prunus species were analyzed for in silico mining of EST-SSRs, protein annotation, and open reading frames (ORFs), and the identification of codon repetitions. A total of 316 SSRs were identified using MISA software. Dinucleotide SSR motifs (26.31 %) were found to be the most abundant type of repeats, followed by tri- (14.58 %), tetra- (0.53 %), and penta- (0.27 %) nucleotide motifs. An attempt was made to design primer pairs for 316 identified SSRs but these were successful for only 175 SSR sequences. The positions of SSRs with respect to ORFs were detected, and annotation of sequences containing SSRs was performed to assign function to each sequence. SSRs were also characterized (in terms of position in the reference genome and associated gene) using the two available Prunus reference genomes (mei and peach). Finally, 38 SSR markers were validated across peach, almond, plum, and apricot genotypes. This validation showed a higher transferability level of EST-SSR developed in P. mume (mei) in comparison with the rest of species analyzed. Findings will aid analysis of functionally important molecular markers and facilitate the analysis of genetic diversity.

Flux analysis and metabolomics for systematic metabolic engineering of microorganisms.

PubMed

Toya, Yoshihiro; Shimizu, Hiroshi

2013-11-01

Rational engineering of metabolism is important for bio-production using microorganisms. Metabolic design based on in silico simulations and experimental validation of the metabolic state in the engineered strain helps in accomplishing systematic metabolic engineering. Flux balance analysis (FBA) is a method for the prediction of metabolic phenotype, and many applications have been developed using FBA to design metabolic networks. Elementary mode analysis (EMA) and ensemble modeling techniques are also useful tools for in silico strain design. The metabolome and flux distribution of the metabolic pathways enable us to evaluate the metabolic state and provide useful clues to improve target productivity. Here, we reviewed several computational applications for metabolic engineering by using genome-scale metabolic models of microorganisms. We also discussed the recent progress made in the field of metabolomics and (13)C-metabolic flux analysis techniques, and reviewed these applications pertaining to bio-production development. Because these in silico or experimental approaches have their respective advantages and disadvantages, the combined usage of these methods is complementary and effective for metabolic engineering. Copyright © 2013 Elsevier Inc. All rights reserved.

In Silico Evaluation of the Potential Impact of Bioanalytical Bias Difference between Two Therapeutic Protein Formulations for Pharmacokinetic Assessment in a Biocomparability Study.

PubMed

Thway, Theingi M; Macaraeg, Chris; Eschenberg, Michael; Ma, Mark

2015-05-01

Formulation changes at later stages of biotherapeutics development require biocomparability (BC) assessment. Using simulation, this study aims to determine the potential effect of bias difference observed between the two formulations after spiking into serum in passing or failing of a critical BC study. An ELISA method with 20% total error was used to assess any bias differences between a reference (RF) and test formulations (TF) in serum. During bioanalytical comparison of these formulations, a 9% difference in bias was observed between the two formulations in sera. To determine acceptable level of bias difference between the RF and TF bioanalytically, two in silico simulations were performed. The in silico analysis showed that the likelihood of the study meeting the BC criteria was >90% when the bias difference between RF and TF in serum was 9% and the number of subjects was ≥20 per treatment arm. An additional simulation showed that when the bias difference was increased to 13% and the number of subjects was <40, the likelihood of meeting the BC criteria decreased to 80%. The result from in silico analysis allowed the bioanalytical laboratory to proceed with sample analysis using a single calibrator and quality controls made from the reference formulation. This modeling approach can be applied to other BC studies with similar situations.

In silico identification and analysis of phytoene synthase genes in plants.

PubMed

Han, Y; Zheng, Q S; Wei, Y P; Chen, J; Liu, R; Wan, H J

2015-08-14

In this study, we examined phytoene synthetase (PSY), the first key limiting enzyme in the synthesis of carotenoids and catalyzing the formation of geranylgeranyl pyrophosphate in terpenoid biosynthesis. We used known amino acid sequences of the PSY gene in tomato plants to conduct a genome-wide search and identify putative candidates in 34 sequenced plants. A total of 101 homologous genes were identified. Phylogenetic analysis revealed that PSY evolved independently in algae as well as monocotyledonous and dicotyledonous plants. Our results showed that the amino acid structures exhibited 5 motifs (motifs 1 to 5) in algae and those in higher plants were highly conserved. The PSY gene structures showed that the number of intron in algae varied widely, while the number of introns in higher plants was 4 to 5. Identification of PSY genes in plants and the analysis of the gene structure may provide a theoretical basis for studying evolutionary relationships in future analyses.

Toxicological evaluation in silico and in vivo of secondary metabolites of Cissampelos sympodialis in Mus musculus mice following inhalation.

PubMed

Alves, Mateus Feitosa; Ferreira, Larissa Adilis Maria Paiva; Gadelha, Francisco Allysson Assis Ferreira; Ferreira, Laércia Karla Diega Paiva; Felix, Mayara Barbalho; Scotti, Marcus Tullius; Scotti, Luciana; de Oliveira, Kardilândia Mendes; Dos Santos, Sócrates Golzio; Diniz, Margareth de Fátima Formiga Melo

2017-12-04

The ethanolic extract of the leaves of Cissampelos sympodialis showed great pharmacological potential, with inflammatory and immunomodulatory activities, however, it showed some toxicological effects. Therefore, this study aims to verify the toxicological potential of alkaloids of the genus Cissampelos through in silico methodologies, to develop a method in LC-MS/MS verifying the presence of alkaloids in the infusion and to evaluate the toxicity of the infusion of the leaves of C. sympodialis when inhaled by Swiss mice. Results in silico showed that alkaloid 93 presented high toxicological potential along with the products of its metabolism. LC-MS/MS results showed that the infusion of the leaves of this plant contained the alkaloids warifteine and methylwarifteine. Finally, the in vivo toxicological analysis of the C. sympodialis infusion showed results, both in biochemistry, organ weights and histological analysis, that the infusion of C. sympodialis leaves presents a low toxicity.

A Sequence in the loop domain of hepatitis C virus E2 protein identified in silico as crucial for the selective binding to human CD81

PubMed Central

Chang, Chun-Chun; Hsu, Hao-Jen; Yen, Jui-Hung; Lo, Shih-Yen

2017-01-01

Hepatitis C virus (HCV) is a species-specific pathogenic virus that infects only humans and chimpanzees. Previous studies have indicated that interactions between the HCV E2 protein and CD81 on host cells are required for HCV infection. To determine the crucial factors for species-specific interactions at the molecular level, this study employed in silico molecular docking involving molecular dynamic simulations of the binding of HCV E2 onto human and rat CD81s. In vitro experiments including surface plasmon resonance measurements and cellular binding assays were applied for simple validations of the in silico results. The in silico studies identified two binding regions on the HCV E2 loop domain, namely E2-site1 and E2-site2, as being crucial for the interactions with CD81s, with the E2-site2 as the determinant factor for human-specific binding. Free energy calculations indicated that the E2/CD81 binding process might follow a two-step model involving (i) the electrostatic interaction-driven initial binding of human-specific E2-site2, followed by (ii) changes in the E2 orientation to facilitate the hydrophobic and van der Waals interaction-driven binding of E2-site1. The sequence of the human-specific, stronger-binding E2-site2 could serve as a candidate template for the future development of HCV-inhibiting peptide drugs. PMID:28481946

Proteasix: a tool for automated and large-scale prediction of proteases involved in naturally occurring peptide generation.

PubMed

Klein, Julie; Eales, James; Zürbig, Petra; Vlahou, Antonia; Mischak, Harald; Stevens, Robert

2013-04-01

In this study, we have developed Proteasix, an open-source peptide-centric tool that can be used to predict in silico the proteases involved in naturally occurring peptide generation. We developed a curated cleavage site (CS) database, containing 3500 entries about human protease/CS combinations. On top of this database, we built a tool, Proteasix, which allows CS retrieval and protease associations from a list of peptides. To establish the proof of concept of the approach, we used a list of 1388 peptides identified from human urine samples, and compared the prediction to the analysis of 1003 randomly generated amino acid sequences. Metalloprotease activity was predominantly involved in urinary peptide generation, and more particularly to peptides associated with extracellular matrix remodelling, compared to proteins from other origins. In comparison, random sequences returned almost no results, highlighting the specificity of the prediction. This study provides a tool that can facilitate linking of identified protein fragments to predicted protease activity, and therefore into presumed mechanisms of disease. Experiments are needed to confirm the in silico hypotheses; nevertheless, this approach may be of great help to better understand molecular mechanisms of disease, and define new biomarkers, and therapeutic targets. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

ACFIS: a web server for fragment-based drug discovery

PubMed Central

Hao, Ge-Fei; Jiang, Wen; Ye, Yuan-Nong; Wu, Feng-Xu; Zhu, Xiao-Lei; Guo, Feng-Biao; Yang, Guang-Fu

2016-01-01

In order to foster innovation and improve the effectiveness of drug discovery, there is a considerable interest in exploring unknown ‘chemical space’ to identify new bioactive compounds with novel and diverse scaffolds. Hence, fragment-based drug discovery (FBDD) was developed rapidly due to its advanced expansive search for ‘chemical space’, which can lead to a higher hit rate and ligand efficiency (LE). However, computational screening of fragments is always hampered by the promiscuous binding model. In this study, we developed a new web server Auto Core Fragment in silico Screening (ACFIS). It includes three computational modules, PARA_GEN, CORE_GEN and CAND_GEN. ACFIS can generate core fragment structure from the active molecule using fragment deconstruction analysis and perform in silico screening by growing fragments to the junction of core fragment structure. An integrated energy calculation rapidly identifies which fragments fit the binding site of a protein. We constructed a simple interface to enable users to view top-ranking molecules in 2D and the binding mode in 3D for further experimental exploration. This makes the ACFIS a highly valuable tool for drug discovery. The ACFIS web server is free and open to all users at http://chemyang.ccnu.edu.cn/ccb/server/ACFIS/. PMID:27150808

ACFIS: a web server for fragment-based drug discovery.

PubMed

Hao, Ge-Fei; Jiang, Wen; Ye, Yuan-Nong; Wu, Feng-Xu; Zhu, Xiao-Lei; Guo, Feng-Biao; Yang, Guang-Fu

2016-07-08

In order to foster innovation and improve the effectiveness of drug discovery, there is a considerable interest in exploring unknown 'chemical space' to identify new bioactive compounds with novel and diverse scaffolds. Hence, fragment-based drug discovery (FBDD) was developed rapidly due to its advanced expansive search for 'chemical space', which can lead to a higher hit rate and ligand efficiency (LE). However, computational screening of fragments is always hampered by the promiscuous binding model. In this study, we developed a new web server Auto Core Fragment in silico Screening (ACFIS). It includes three computational modules, PARA_GEN, CORE_GEN and CAND_GEN. ACFIS can generate core fragment structure from the active molecule using fragment deconstruction analysis and perform in silico screening by growing fragments to the junction of core fragment structure. An integrated energy calculation rapidly identifies which fragments fit the binding site of a protein. We constructed a simple interface to enable users to view top-ranking molecules in 2D and the binding mode in 3D for further experimental exploration. This makes the ACFIS a highly valuable tool for drug discovery. The ACFIS web server is free and open to all users at http://chemyang.ccnu.edu.cn/ccb/server/ACFIS/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Systems biology study of mucopolysaccharidosis using a human metabolic reconstruction network.

PubMed

Salazar, Diego A; Rodríguez-López, Alexander; Herreño, Angélica; Barbosa, Hector; Herrera, Juliana; Ardila, Andrea; Barreto, George E; González, Janneth; Alméciga-Díaz, Carlos J

2016-02-01

Mucopolysaccharidosis (MPS) is a group of lysosomal storage diseases (LSD), characterized by the deficiency of a lysosomal enzyme responsible for the degradation of glycosaminoglycans (GAG). This deficiency leads to the lysosomal accumulation of partially degraded GAG. Nevertheless, deficiency of a single lysosomal enzyme has been associated with impairment in other cell mechanism, such as apoptosis and redox balance. Although GAG analysis represents the main biomarker for MPS diagnosis, it has several limitations that can lead to a misdiagnosis, whereby the identification of new biomarkers represents an important issue for MPS. In this study, we used a system biology approach, through the use of a genome-scale human metabolic reconstruction to understand the effect of metabolism alterations in cell homeostasis and to identify potential new biomarkers in MPS. In-silico MPS models were generated by silencing of MPS-related enzymes, and were analyzed through a flux balance and variability analysis. We found that MPS models used approximately 2286 reactions to satisfy the objective function. Impaired reactions were mainly involved in cellular respiration, mitochondrial process, amino acid and lipid metabolism, and ion exchange. Metabolic changes were similar for MPS I and II, and MPS III A to C; while the remaining MPS showed unique metabolic profiles. Eight and thirteen potential high-confidence biomarkers were identified for MPS IVB and VII, respectively, which were associated with the secondary pathologic process of LSD. In vivo evaluation of predicted intermediate confidence biomarkers (β-hexosaminidase and β-glucoronidase) for MPS IVA and VI correlated with the in-silico prediction. These results show the potential of a computational human metabolic reconstruction to understand the molecular mechanisms this group of diseases, which can be used to identify new biomarkers for MPS. Copyright © 2015. Published by Elsevier Inc.

Genetic study of the BRAF gene reveals new variants and high frequency of the V600E mutation among Iranian ameloblastoma patients.

PubMed

Soltani, Maryam; Tabatabaiefar, Mohammad Amin; Mohsenifar, Zhaleh; Pourreza, Mohammad Reza; Moridnia, Abbas; Shariati, Laleh; Razavi, Seyyed Mohammad

2018-01-01

Ameloblastoma is a benign, slow-growing and locally invasive tumor. It is one of the most prevalent odontogenic tumors, with an incidence rate of 1% of all oral tumors and approximately 18% of odontogenic tumors. A group of genes have been investigated in patients with ameloblastoma. The BRAF V600E mutation has been implicated as the most common mutation in ameloblastoma. The presence or absence of this mutation has been associated with several clinicopathological properties, including location, age at diagnosis, histology, and prognosis. Although some populations have been investigated so far, little data are available on the Iranian population. The current research was launched to study the BRAF V600E mutation among a cohort of Iranian patients with ameloblastoma. In this clinicopathological and molecular biology study, a total of 19 formalin-fixed, paraffin-embedded tissues were studied. DNA extraction was performed, followed by PCR-sequencing of exons 10 and 15 of the BRAF gene to identify mutations. In silico analysis was performed for the identified variants. Results were analyzed by T test, Chi-square, and Fisher's exact test. Totally, 12 of 19 samples (63%) harbored the p. V600E hotspot mutation. In addition, we identified several variants, two of which were novel. The c.1769T>G (p. V590G) and c.1751C>T (p.L584F) as the novel variants showed a possible damaging effect by in silico analysis. No variant was found within exon 10. Our study confirms the role of BRAF mutations in ameloblastoma in the Iranian patients studied. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

In Silico Identification of Epitopes in Mycobacterium avium subsp. paratuberculosis Proteins That Were Upregulated under Stress Conditions

PubMed Central

Gurung, Ratna B.; Purdie, Auriol C.; Begg, Douglas J.

2012-01-01

Johne's disease in ruminants is caused by Mycobacterium avium subsp. paratuberculosis. Diagnosis of M. avium subsp. paratuberculosis infection is difficult, especially in the early stages. To date, ideal antigen candidates are not available for efficient immunization or immunodiagnosis. This study reports the in silico selection and subsequent analysis of epitopes of M. avium subsp. paratuberculosis proteins that were found to be upregulated under stress conditions as a means to identify immunogenic candidate proteins. Previous studies have reported differential regulation of proteins when M. avium subsp. paratuberculosis is exposed to stressors which induce a response similar to dormancy. Dormancy may be involved in evading host defense mechanisms, and the host may also mount an immune response against these proteins. Twenty-five M. avium subsp. paratuberculosis proteins that were previously identified as being upregulated under in vitro stress conditions were analyzed for B and T cell epitopes by use of the prediction tools at the Immune Epitope Database and Analysis Resource. Major histocompatibility complex class I T cell epitopes were predicted using an artificial neural network method, and class II T cell epitopes were predicted using the consensus method. Conformational B cell epitopes were predicted from the relevant three-dimensional structure template for each protein. Based on the greatest number of predicted epitopes, eight proteins (MAP2698c [encoded by desA2], MAP2312c [encoded by fadE19], MAP3651c [encoded by fadE3_2], MAP2872c [encoded by fabG5_2], MAP3523c [encoded by oxcA], MAP0187c [encoded by sodA], and the hypothetical proteins MAP3567 and MAP1168c) were identified as potential candidates for study of antibody- and cell-mediated immune responses within infected hosts. PMID:22496492

In silico epigenetics of metal exposure and subclinical atherosclerosis in middle aged men: pilot results from the Aragon Workers Health Study.

PubMed

Riffo-Campos, Angela L; Fuentes-Trillo, Azahara; Tang, Wan Y; Soriano, Zoraida; De Marco, Griselda; Rentero-Garrido, Pilar; Adam-Felici, Victoria; Lendinez-Tortajada, Veronica; Francesconi, Kevin; Goessler, Walter; Ladd-Acosta, Christine; Leon-Latre, Montse; Casasnovas, Jose A; Chaves, F Javier; Navas-Acien, Ana; Guallar, Eliseo; Tellez-Plaza, Maria

2018-06-05

We explored the association of metal levels with subclinical atherosclerosis and epigenetic changes in relevant biological pathways. Whole blood DNA Infinium Methylation 450 K data were obtained from 23 of 73 middle age men without clinically evident cardiovascular disease (CVD) who participated in the Aragon Workers Health Study in 2009 (baseline visit) and had available baseline urinary metals and subclinical atherosclerosis measures obtained in 2010-2013 (follow-up visit). The median metal levels were 7.36 µg g -1 , 0.33 µg g -1 , 0.11 µg g -1 and 0.07 µg g -1 , for arsenic (sum of inorganic and methylated species), cadmium, antimony and tungsten, respectively. Urine cadmium and tungsten were associated with femoral and carotid intima-media thickness, respectively (Pearson's r = 0.27; p = 0.03 in both cases). Among nearest genes to identified differentially methylated regions (DMRs), 46% of metal-DMR genes overlapped with atherosclerosis-DMR genes ( p < 0.001). Pathway enrichment analysis of atherosclerosis-DMR genes showed a role in inflammatory, metabolic and transport pathways. In in silico protein-to-protein interaction networks among proteins encoded by 162 and 108 genes attributed to atherosclerosis- and metal-DMRs, respectively, with proteins known to have a role in atherosclerosis pathways, we observed hub proteins in the network associated with both atherosclerosis and metal-DMRs (e.g. SMAD3 and NOP56 ), and also hub proteins associated with metal-DMRs only but with relevant connections with atherosclerosis effectors (e.g. SSTR5 , HDAC4 , AP2A2 , CXCL12 and SSTR4 ). Our integrative in silico analysis demonstrates the feasibility of identifying epigenomic regions linked to environmental exposures and potentially involved in relevant pathways for human diseases. While our results support the hypothesis that metal exposures can influence health due to epigenetic changes, larger studies are needed to confirm our pilot results.This article is part of a discussion meeting issue 'Frontiers in epigenetic chemical biology'. © 2018 The Author(s).

Imperfect duplicate insertions type of mutations in plasmepsin V modulates binding properties of PEXEL motifs of export proteins in Indian Plasmodium vivax.

PubMed

Rawat, Manmeet; Vijay, Sonam; Gupta, Yash; Tiwari, Pramod Kumar; Sharma, Arun

2013-01-01

Plasmepsin V (PM-V) have functionally conserved orthologues across the Plasmodium genus who's binding and antigenic processing at the PEXEL motifs for export about 200-300 essential proteins is important for the virulence and viability of the causative Plasmodium species. This study was undertaken to determine P. vivax plasmepsin V Ind (PvPM-V-Ind) PEXEL motif export pathway for pathogenicity-related proteins/antigens export thereby altering plasmodium exportome during erythrocytic stages. We identify and characterize Plasmodium vivax plasmepsin-V-Ind (mutant) gene by cloning, sequence analysis, in silico bioinformatic protocols and structural modeling predictions based on docking studies on binding capacity with PEXEL motifs processing in terms of binding and accessibility of export proteins. Cloning and sequence analysis for genetic diversity demonstrates PvPM-V-Ind (mutant) gene is highly conserved among all isolates from different geographical regions of India. Imperfect duplicate insertion types of mutations (SVSE from 246-249 AA and SLSE from 266-269 AA) were identified among all Indian isolates in comparison to P.vivax Sal-1 (PvPM-V-Sal 1) isolate. In silico bioinformatics interaction studies of PEXEL peptide and active enzyme reveal that PvPM-V-Ind (mutant) is only active in endoplasmic reticulum lumen and membrane embedding is essential for activation of plasmepsin V. Structural modeling predictions based on docking studies with PEXEL motif show significant variation in substrate protein binding of these imperfect mutations with data mined PEXEL sequences. The predicted variation in the docking score and interacting amino acids of PvPM-V-Ind (mutant) proteins with PEXEL and lopinavir suggests a modulation in the activity of PvPM-V in terms of binding and accessibility at these sites. Our functional modeled validation of PvPM-V-Ind (mutant) imperfect duplicate insertions with data mined PEXEL sequences leading to altered binding and substrate accessibility of the enzyme makes it a plausible target to investigate export mechanisms for in silico virtual screening and novel pharmacophore designing.

Imperfect Duplicate Insertions Type of Mutations in Plasmepsin V Modulates Binding Properties of PEXEL Motifs of Export Proteins in Indian Plasmodium vivax

PubMed Central

Rawat, Manmeet; Vijay, Sonam; Gupta, Yash; Tiwari, Pramod Kumar; Sharma, Arun

2013-01-01

Introduction Plasmepsin V (PM-V) have functionally conserved orthologues across the Plasmodium genus who's binding and antigenic processing at the PEXEL motifs for export about 200–300 essential proteins is important for the virulence and viability of the causative Plasmodium species. This study was undertaken to determine P. vivax plasmepsin V Ind (PvPM-V-Ind) PEXEL motif export pathway for pathogenicity-related proteins/antigens export thereby altering plasmodium exportome during erythrocytic stages. Method We identify and characterize Plasmodium vivax plasmepsin-V-Ind (mutant) gene by cloning, sequence analysis, in silico bioinformatic protocols and structural modeling predictions based on docking studies on binding capacity with PEXEL motifs processing in terms of binding and accessibility of export proteins. Results Cloning and sequence analysis for genetic diversity demonstrates PvPM-V-Ind (mutant) gene is highly conserved among all isolates from different geographical regions of India. Imperfect duplicate insertion types of mutations (SVSE from 246–249 AA and SLSE from 266–269 AA) were identified among all Indian isolates in comparison to P.vivax Sal-1 (PvPM-V-Sal 1) isolate. In silico bioinformatics interaction studies of PEXEL peptide and active enzyme reveal that PvPM-V-Ind (mutant) is only active in endoplasmic reticulum lumen and membrane embedding is essential for activation of plasmepsin V. Structural modeling predictions based on docking studies with PEXEL motif show significant variation in substrate protein binding of these imperfect mutations with data mined PEXEL sequences. The predicted variation in the docking score and interacting amino acids of PvPM-V-Ind (mutant) proteins with PEXEL and lopinavir suggests a modulation in the activity of PvPM-V in terms of binding and accessibility at these sites. Conclusion/Significance Our functional modeled validation of PvPM-V-Ind (mutant) imperfect duplicate insertions with data mined PEXEL sequences leading to altered binding and substrate accessibility of the enzyme makes it a plausible target to investigate export mechanisms for in silico virtual screening and novel pharmacophore designing. PMID:23555891

In Silico Analysis of the Structural and Biochemical Features of the NMD Factor UPF1 in Ustilago maydis.

PubMed

Martínez-Montiel, Nancy; Morales-Lara, Laura; Hernández-Pérez, Julio M; Martínez-Contreras, Rebeca D

2016-01-01

The molecular mechanisms regulating the accuracy of gene expression are still not fully understood. Among these mechanisms, Nonsense-mediated Decay (NMD) is a quality control process that detects post-transcriptionally abnormal transcripts and leads them to degradation. The UPF1 protein lays at the heart of NMD as shown by several structural and functional features reported for this factor mainly for Homo sapiens and Saccharomyces cerevisiae. This process is highly conserved in eukaryotes but functional diversity can be observed in various species. Ustilago maydis is a basidiomycete and the best-known smut, which has become a model to study molecular and cellular eukaryotic mechanisms. In this study, we performed in silico analysis to investigate the structural and biochemical properties of the putative UPF1 homolog in Ustilago maydis. The putative homolog for UPF1 was recognized in the annotated genome for the basidiomycete, exhibiting 66% identity with its human counterpart at the protein level. The known structural and functional domains characteristic of UPF1 homologs were also found. Based on the crystal structures available for UPF1, we constructed different three-dimensional models for umUPF1 in order to analyze the secondary and tertiary structural features of this factor. Using these models, we studied the spatial arrangement of umUPF1 and its capability to interact with UPF2. Moreover, we identified the critical amino acids that mediate the interaction of umUPF1 with UPF2, ATP, RNA and with UPF1 itself. Mutating these amino acids in silico showed an important effect over the native structure. Finally, we performed molecular dynamic simulations for UPF1 proteins from H. sapiens and U. maydis and the results obtained show a similar behavior and physicochemical properties for the protein in both organisms. Overall, our results indicate that the putative UPF1 identified in U. maydis shows a very similar sequence, structural organization, mechanical stability, physicochemical properties and spatial organization in comparison to the NMD factor depicted for Homo sapiens. These observations strongly support the notion that human and fungal UPF1 could perform equivalent biological activities.

SpirPep: an in silico digestion-based platform to assist bioactive peptides discovery from a genome-wide database.

PubMed

Anekthanakul, Krittima; Hongsthong, Apiradee; Senachak, Jittisak; Ruengjitchatchawalya, Marasri

2018-04-20

Bioactive peptides, including biological sources-derived peptides with different biological activities, are protein fragments that influence the functions or conditions of organisms, in particular humans and animals. Conventional methods of identifying bioactive peptides are time-consuming and costly. To quicken the processes, several bioinformatics tools are recently used to facilitate screening of the potential peptides prior their activity assessment in vitro and/or in vivo. In this study, we developed an efficient computational method, SpirPep, which offers many advantages over the currently available tools. The SpirPep web application tool is a one-stop analysis and visualization facility to assist bioactive peptide discovery. The tool is equipped with 15 customized enzymes and 1-3 miscleavage options, which allows in silico digestion of protein sequences encoded by protein-coding genes from single, multiple, or genome-wide scaling, and then directly classifies the peptides by bioactivity using an in-house database that contains bioactive peptides collected from 13 public databases. With this tool, the resulting peptides are categorized by each selected enzyme, and shown in a tabular format where the peptide sequences can be tracked back to their original proteins. The developed tool and webpages are coded in PHP and HTML with CSS/JavaScript. Moreover, the tool allows protein-peptide alignment visualization by Generic Genome Browser (GBrowse) to display the region and details of the proteins and peptides within each parameter, while considering digestion design for the desirable bioactivity. SpirPep is efficient; it takes less than 20 min to digest 3000 proteins (751,860 amino acids) with 15 enzymes and three miscleavages for each enzyme, and only a few seconds for single enzyme digestion. Obviously, the tool identified more bioactive peptides than that of the benchmarked tool; an example of validated pentapeptide (FLPIL) from LC-MS/MS was demonstrated. The web and database server are available at http://spirpepapp.sbi.kmutt.ac.th . SpirPep, a web-based bioactive peptide discovery application, is an in silico-based tool with an overview of the results. The platform is a one-stop analysis and visualization facility; and offers advantages over the currently available tools. This tool may be useful for further bioactivity analysis and the quantitative discovery of desirable peptides.

In-Silico Identification Of Micro-Loops In Myelodysplastic Syndromes

NASA Astrophysics Data System (ADS)

Beck, Dominik; Brandl, Miriam; Pham, Tuan D.; Chang, Chung-Che; Zhou, Xiaobo

2011-06-01

Micro-loops are regulatory network motifs that leverage transcriptional and posttranscriptional control to effectively regulate the transcriptome. In this paper a regulatory network for Myelodysplastic Syndromes (MDSs) was constructed from the literature and publicly available data sources. The network was filtered using data from deep-sequencing of small RNAs, exon and microarrays. Motif discovery showed that micro-loops might exist in MDS. We further used the identified micro-loops and performed basic network analysis to identify the known disease gene RUNX1/AML, as well as miRNA family hsa-mir-181. This suggested that the concept of micro-loops can be applied to enhance disease gene identification and biomarker discovery.

A general framework for optimization of probes for gene expression microarray and its application to the fungus Podospora anserina.

PubMed

Bidard, Frédérique; Imbeaud, Sandrine; Reymond, Nancie; Lespinet, Olivier; Silar, Philippe; Clavé, Corinne; Delacroix, Hervé; Berteaux-Lecellier, Véronique; Debuchy, Robert

2010-06-18

The development of new microarray technologies makes custom long oligonucleotide arrays affordable for many experimental applications, notably gene expression analyses. Reliable results depend on probe design quality and selection. Probe design strategy should cope with the limited accuracy of de novo gene prediction programs, and annotation up-dating. We present a novel in silico procedure which addresses these issues and includes experimental screening, as an empirical approach is the best strategy to identify optimal probes in the in silico outcome. We used four criteria for in silico probe selection: cross-hybridization, hairpin stability, probe location relative to coding sequence end and intron position. This latter criterion is critical when exon-intron gene structure predictions for intron-rich genes are inaccurate. For each coding sequence (CDS), we selected a sub-set of four probes. These probes were included in a test microarray, which was used to evaluate the hybridization behavior of each probe. The best probe for each CDS was selected according to three experimental criteria: signal-to-noise ratio, signal reproducibility, and representative signal intensities. This procedure was applied for the development of a gene expression Agilent platform for the filamentous fungus Podospora anserina and the selection of a single 60-mer probe for each of the 10,556 P. anserina CDS. A reliable gene expression microarray version based on the Agilent 44K platform was developed with four spot replicates of each probe to increase statistical significance of analysis.

Calibration of Multiple In Silico Tools for Predicting Pathogenicity of Mismatch Repair Gene Missense Substitutions

PubMed Central

Thompson, Bryony A.; Greenblatt, Marc S.; Vallee, Maxime P.; Herkert, Johanna C.; Tessereau, Chloe; Young, Erin L.; Adzhubey, Ivan A.; Li, Biao; Bell, Russell; Feng, Bingjian; Mooney, Sean D.; Radivojac, Predrag; Sunyaev, Shamil R.; Frebourg, Thierry; Hofstra, Robert M.W.; Sijmons, Rolf H.; Boucher, Ken; Thomas, Alun; Goldgar, David E.; Spurdle, Amanda B.; Tavtigian, Sean V.

2015-01-01

Classification of rare missense substitutions observed during genetic testing for patient management is a considerable problem in clinical genetics. The Bayesian integrated evaluation of unclassified variants is a solution originally developed for BRCA1/2. Here, we take a step toward an analogous system for the mismatch repair (MMR) genes (MLH1, MSH2, MSH6, and PMS2) that confer colon cancer susceptibility in Lynch syndrome by calibrating in silico tools to estimate prior probabilities of pathogenicity for MMR gene missense substitutions. A qualitative five-class classification system was developed and applied to 143 MMR missense variants. This identified 74 missense substitutions suitable for calibration. These substitutions were scored using six different in silico tools (Align-Grantham Variation Grantham Deviation, multivariate analysis of protein polymorphisms [MAPP], Mut-Pred, PolyPhen-2.1, Sorting Intolerant From Tolerant, and Xvar), using curated MMR multiple sequence alignments where possible. The output from each tool was calibrated by regression against the classifications of the 74 missense substitutions; these calibrated outputs are interpretable as prior probabilities of pathogenicity. MAPP was the most accurate tool and MAPP + PolyPhen-2.1 provided the best-combined model (R2 = 0.62 and area under receiver operating characteristic = 0.93). The MAPP + PolyPhen-2.1 output is sufficiently predictive to feed as a continuous variable into the quantitative Bayesian integrated evaluation for clinical classification of MMR gene missense substitutions. PMID:22949387

Structural and functional analysis of rare missense mutations in human chorionic gonadotrophin β-subunit

PubMed Central

Nagirnaja, Liina; Venclovas, Česlovas; Rull, Kristiina; Jonas, Kim C.; Peltoketo, Hellevi; Christiansen, Ole B.; Kairys, Visvaldas; Kivi, Gaily; Steffensen, Rudi; Huhtaniemi, Ilpo T.; Laan, Maris

2012-01-01

Heterodimeric hCG is one of the key hormones determining early pregnancy success. We have previously identified rare missense mutations in hCGβ genes with potential pathophysiological importance. The present study assessed the impact of these mutations on the structure and function of hCG by applying a combination of in silico (sequence and structure analysis, molecular dynamics) and in vitro (co-immunoprecipitation, immuno- and bioassays) approaches. The carrier status of each mutation was determined for 1086 North-Europeans [655 patients with recurrent miscarriage (RM)/431 healthy controls from Estonia, Finland and Denmark] using PCR-restriction fragment length polymorphism. The mutation CGB5 p.Val56Leu (rs72556325) was identified in a single heterozygous RM patient and caused a structural hindrance in the formation of the hCGα/β dimer. Although the amount of the mutant hCGβ assembled into secreted intact hCG was only 10% compared with the wild-type, a stronger signaling response was triggered upon binding to its receptor, thus compensating the effect of poor dimerization. The mutation CGB8 p.Pro73Arg (rs72556345) was found in five heterozygotes (three RM cases and two control individuals) and was inherited by two of seven studied live born children. The mutation caused ∼50% of secreted β-subunits to acquire an alternative conformation, but did not affect its biological activity. For the CGB8 p.Arg8Trp (rs72556341) substitution, the applied in vitro methods revealed no alterations in the assembly of intact hCG as also supported by an in silico analysis. In summary, the accumulated data indicate that only mutations with neutral or mild functional consequences might be tolerated in the major hCGβ genes CGB5 and CGB8. PMID:22554618

Complete mitochondrial genome of Concholepas concholepas inferred by 454 pyrosequencing and mtDNA expression in two mollusc populations.

PubMed

Núñez-Acuña, Gustavo; Aguilar-Espinoza, Andrea; Gallardo-Escárate, Cristian

2013-03-01

Despite the great relevance of mitochondrial genome analysis in evolutionary studies, there is scarce information on how the transcripts associated with the mitogenome are expressed and their role in the genetic structuring of populations. This work reports the complete mitochondrial genome of the marine gastropod Concholepas concholepas, obtained by 454 pryosequencing, and an analysis of mitochondrial transcripts of two populations 1000 km apart along the Chilean coast. The mitochondrion of C. concholepas is 15,495 base pairs (bp) in size and contains the 37 subunits characteristic of metazoans, as well as a non-coding region of 330 bp. In silico analysis of mitochondrial gene variability showed significant differences among populations. In terms of levels of relative abundance of transcripts associated with mitochondrion in the two populations (assessed by qPCR), the genes associated with complexes III and IV of the mitochondrial genome had the highest levels of expression in the northern population while transcripts associated with the ATP synthase complex had the highest levels of expression in the southern population. Moreover, fifteen polymorphic SNPs were identified in silico between the mitogenomes of the two populations. Four of these markers implied different amino acid substitutions (non-synonymous SNPs). This work contributes novel information regarding the mitochondrial genome structure and mRNA expression levels of C. concholepas. Copyright © 2012 Elsevier Inc. All rights reserved.

Genome-Wide Search Identifies 1.9 Mb from the Polar Bear Y Chromosome for Evolutionary Analyses

PubMed Central

Bidon, Tobias; Schreck, Nancy; Hailer, Frank; Nilsson, Maria A.; Janke, Axel

2015-01-01

The male-inherited Y chromosome is the major haploid fraction of the mammalian genome, rendering Y-linked sequences an indispensable resource for evolutionary research. However, despite recent large-scale genome sequencing approaches, only a handful of Y chromosome sequences have been characterized to date, mainly in model organisms. Using polar bear (Ursus maritimus) genomes, we compare two different in silico approaches to identify Y-linked sequences: 1) Similarity to known Y-linked genes and 2) difference in the average read depth of autosomal versus sex chromosomal scaffolds. Specifically, we mapped available genomic sequencing short reads from a male and a female polar bear against the reference genome and identify 112 Y-chromosomal scaffolds with a combined length of 1.9 Mb. We verified the in silico findings for the longer polar bear scaffolds by male-specific in vitro amplification, demonstrating the reliability of the average read depth approach. The obtained Y chromosome sequences contain protein-coding sequences, single nucleotide polymorphisms, microsatellites, and transposable elements that are useful for evolutionary studies. A high-resolution phylogeny of the polar bear patriline shows two highly divergent Y chromosome lineages, obtained from analysis of the identified Y scaffolds in 12 previously published male polar bear genomes. Moreover, we find evidence of gene conversion among ZFX and ZFY sequences in the giant panda lineage and in the ancestor of ursine and tremarctine bears. Thus, the identification of Y-linked scaffold sequences from unordered genome sequences yields valuable data to infer phylogenomic and population-genomic patterns in bears. PMID:26019166

Evaluation of a Genome-Scale In Silico Metabolic Model for Geobacter metallireducens Using Proteomic Data from a Field Biostimulation Experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fang, Yilin; Wilkins, Michael J.; Yabusaki, Steven B.

2012-12-12

Biomass and shotgun global proteomics data that reflected relative protein abundances from samples collected during the 2008 experiment at the U.S. Department of Energy Integrated Field-Scale Subsurface Research Challenge site in Rifle, Colorado, provided an unprecedented opportunity to validate a genome-scale metabolic model of Geobacter metallireducens and assess its performance with respect to prediction of metal reduction, biomass yield, and growth rate under dynamic field conditions. Reconstructed from annotated genomic sequence, biochemical, and physiological data, the constraint-based in silico model of G. metallireducens relates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes.more » Proteomic analysis showed that 180 of the 637 G. metallireducens proteins detected during the 2008 experiment were associated with specific metabolic reactions in the in silico model. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through the in silico model reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low fluxes through amino acid transport and metabolism, revealed pathways or flux constraints in the in silico model that could be updated to more accurately predict metabolic processes that occur in the subsurface environment.« less

In vitro and in silico studies on the anticancer and apoptosis-inducing activities of the sterols identified from the soft coral, subergorgia reticulata

PubMed Central

Byju, Kuniyil; Anuradha, Vattoni; Vasundhara, Gopalakrishnapai; Nair, S. Muraleedharan; Kumar, N. Chandramohana

2014-01-01

Background: Gorgonians and other octocorals are known to possess a huge array of secondary metabolites in which sterols are the major group of secondary metabolites apart from sesquiterpenes and diterpenes, and the bioactive metabolites could show marked biomedical potential for future drug discovery. Objective: This study was intended for the isolation and identification of sterols from the octocoral Subergorgia reticulata and to evaluate the anticancer and apoptosis-inducing activities of the identified sterols through in vitro and in silico approach. Materials and Methods: The organism was collected from Lakshadweep Island. The isolated sterols were identified using Gas chromatography-mass spectrometry (GC-MS). The structure was confirmed by using comparison of their spectra those in National Institute of Standard Technology (NIST) library. The apoptosis inducing effect of identified sterols were determined by PASS online prediction. In vitro cytotoxity studies were carried out using Dalton's lymphoma ascites cells (DLA) and the cell viability was determined by trypan blue exclusion method. Results: Six sterols were identified from the soft coral S. reticulata. They are Cholesta-5,22-diene-3ol (3β), Ergosta-5-22-dien-3ol (3β,22E 24S), Cholesterol, 26,26-Dimethyl-5,24(28)-ergostadien-3β-ol. β-sitosterol, and Fucosterol. In silico predictions showed that the identified sterols exhibited remarkable apoptosis agonist activity. The probability of apoptosis agonist activity were found maximum for 26,26-Dimethyl-5,24 (28)-S. reticulata sterol fractions isolated were found to be having anticancer activity. Conclusions: These findings suggest that S. reticulata contained biologically active sterol compounds that may be useful in the treatment of cancer. PMID:24914311

Prediction and analysis of promiscuous T cell-epitopes derived from the vaccine candidate antigens of Leishmania donovani binding to MHC class-II alleles using in silico approach.

PubMed

Kashyap, Manju; Jaiswal, Varun; Farooq, Umar

2017-09-01

Visceral leishmaniasis is a dreadful infectious disease and caused by the intracellular protozoan parasites, Leishmania donovani and Leishmania infantum. Despite extensive efforts for developing effective prophylactic vaccine, still no vaccine is available against leishmaniasis. However, advancement in immunoinformatics methods generated new dimension in peptide based vaccine development. The present study was aimed to identify T-cell epitopes from the vaccine candidate antigens like Lipophosphogylcan-3(LPG-3) and Nucleoside hydrolase (NH) from the L. donovani using in silico methods. Available best tools were used for the identification of promiscuous peptides for MHC class-II alleles. A total of 34 promiscuous peptides from LPG-3, 3 from NH were identified on the basis of their 100% binding affinity towards all six HLA alleles, taken in this study. These peptides were further checked computationally to know their IFN-γ and IL4 inducing potential and nine peptides were identified. Peptide binding interactions with predominant HLA alleles were done by docking. Out of nine docked promiscuous peptides, only two peptides (QESRILRVIKKKLVR, RILRVIKKKLVRKTL), from LPG-3 and one peptide (FDKFWCLVIDALKRI) from NH showed lowest binding energy with all six alleles. These promiscuous T-cell epitopes were predicted on the basis of their antigenicity, hydrophobicity, potential immune response and docking scores. The immunogenicity of predicted promiscuous peptides might be used for subunit vaccine development with immune-modulating adjuvants. Copyright © 2017 Elsevier B.V. All rights reserved.

New milk protein-derived peptides with potential antimicrobial activity: an approach based on bioinformatic studies.

PubMed

Dziuba, Bartłomiej; Dziuba, Marta

2014-08-20

New peptides with potential antimicrobial activity, encrypted in milk protein sequences, were searched for with the use of bioinformatic tools. The major milk proteins were hydrolyzed in silico by 28 enzymes. The obtained peptides were characterized by the following parameters: molecular weight, isoelectric point, composition and number of amino acid residues, net charge at pH 7.0, aliphatic index, instability index, Boman index, and GRAVY index, and compared with those calculated for known 416 antimicrobial peptides including 59 antimicrobial peptides (AMPs) from milk proteins listed in the BIOPEP database. A simple analysis of physico-chemical properties and the values of biological activity indicators were insufficient to select potentially antimicrobial peptides released in silico from milk proteins by proteolytic enzymes. The final selection was made based on the results of multidimensional statistical analysis such as support vector machines (SVM), random forest (RF), artificial neural networks (ANN) and discriminant analysis (DA) available in the Collection of Anti-Microbial Peptides (CAMP database). Eleven new peptides with potential antimicrobial activity were selected from all peptides released during in silico proteolysis of milk proteins.

New Milk Protein-Derived Peptides with Potential Antimicrobial Activity: An Approach Based on Bioinformatic Studies

PubMed Central

Dziuba, Bartłomiej; Dziuba, Marta

2014-01-01

New peptides with potential antimicrobial activity, encrypted in milk protein sequences, were searched for with the use of bioinformatic tools. The major milk proteins were hydrolyzed in silico by 28 enzymes. The obtained peptides were characterized by the following parameters: molecular weight, isoelectric point, composition and number of amino acid residues, net charge at pH 7.0, aliphatic index, instability index, Boman index, and GRAVY index, and compared with those calculated for known 416 antimicrobial peptides including 59 antimicrobial peptides (AMPs) from milk proteins listed in the BIOPEP database. A simple analysis of physico-chemical properties and the values of biological activity indicators were insufficient to select potentially antimicrobial peptides released in silico from milk proteins by proteolytic enzymes. The final selection was made based on the results of multidimensional statistical analysis such as support vector machines (SVM), random forest (RF), artificial neural networks (ANN) and discriminant analysis (DA) available in the Collection of Anti-Microbial Peptides (CAMP database). Eleven new peptides with potential antimicrobial activity were selected from all peptides released during in silico proteolysis of milk proteins. PMID:25141106

Identification and the molecular mechanism of a novel myosin-derived ACE inhibitory peptide.

PubMed

Yu, Zhipeng; Wu, Sijia; Zhao, Wenzhu; Ding, Long; Shiuan, David; Chen, Feng; Li, Jianrong; Liu, Jingbo

2018-01-24

The objective of this work was to identify a novel ACE inhibitory peptide from myosin using a number of in silico methods. Myosin was evaluated as a substrate for use in the generation of ACE inhibitory peptides using BIOPEP and ExPASy PeptideCutter. Then the ACE inhibitory activity prediction of peptides in silico was evaluated using the program peptide ranker, following the database search of known and unknown peptides using the program BIOPEP. In addition, the interaction mechanisms of the peptide and ACE were evaluated by DS. All of the tripeptides were predicted to be nontoxic. Results suggested that the tripeptide NCW exerted potent ACE inhibitory activity with an IC 50 value of 35.5 μM. Furthermore, the results suggested that the peptide NCW comes into contact with Zn 701, Tyr 523, His 383, Glu 384, Glu 411, and His 387. The potential molecular mechanism of the NCW/ACE interaction was investigated. Results confirmed that the higher inhibitory potency of NCW might be attributed to the formation of more hydrogen bonds with the ACE's active site. Therefore, the in silico method is effective to predict and identify novel ACE inhibitory peptides from protein hydrolysates.

in silico identification of cross affinity towards Cry1Ac pesticidal protein with receptor enzyme in Bos taurus and sequence, structure analysis of crystal proteins for stability.

PubMed

Ebenezer, King Solomon; Nachimuthu, Ramesh; Thiagarajan, Prabha; Velu, Rajesh Kannan

2013-01-01

Any novel protein introduced into the GM crops need to be evaluated for cross affinity on living organisms. Many researchers are currently focusing on the impact of Bacillus thuringiensis cotton on soil and microbial diversity by field experiments. In spite of this, in silico approach might be helpful to elucidate the impact of cry genes. The crystal a protein which was produced by Bt at the time of sporulation has been used as a biological pesticide to target the insectivorous pests like Cry1Ac for Helicoverpa armigera and Cry2Ab for Spodoptera sp. and Heliothis sp. Here, we present the comprehensive in silico analysis of Cry1Ac and Cry2Ab proteins with available in silico tools, databases and docking servers. Molecular docking of Cry1Ac with procarboxypeptidase from Helicoverpa armigera and Cry1Ac with Leucine aminopeptidase from Bos taurus has showed the 125(th) amino acid position to be the preference site of Cry1Ac protein. The structures were compared with each other and it showed 5% of similarity. The cross affinity of this toxin that have confirmed the earlier reports of ill effects of Bt cotton consumed by cattle.

Prospecting Biotechnologically-Relevant Monooxygenases from Cold Sediment Metagenomes: An In Silico Approach

DOE PAGES

Musumeci, Matias A.; Lozada, Mariana; Rial, Daniela V.; ...

2017-04-09

The goal of this work was to identify sequences encoding monooxygenase biocatalysts with novel features by in silico mining an assembled metagenomic dataset of polar and subpolar marine sediments. The targeted enzyme sequences were Baeyer-Villiger and bacterial cytochrome P450 monooxygenases (CYP153). These enzymes have wide-ranging applications, from the synthesis of steroids, antibiotics, mycotoxins and pheromones to the synthesis of monomers for polymerization and anticancer precursors, due to their extraordinary enantio-, regio-, and chemo- selectivity that are valuable features for organic synthesis. Phylogenetic analyses were used to select the most divergent sequences affiliated to these enzyme families among the 264 putativemore » monooxygenases recovered from the ~14 million protein-coding sequences in the assembled metagenome dataset. Three-dimensional structure modeling and docking analysis suggested features useful in biotechnological applications in five metagenomic sequences, such as wide substrate range, novel substrate specificity or regioselectivity. Further analysis revealed structural features associated with psychrophilic enzymes, such as broader substrate accessibility, larger catalytic pockets or low domain interactions, suggesting that they could be applied in biooxidations at room or low temperatures, saving costs inherent to energy consumption. As a result, this work allowed the identification of putative enzyme candidates with promising features from metagenomes, providing a suitable starting point for further developments.« less

Prospecting Biotechnologically-Relevant Monooxygenases from Cold Sediment Metagenomes: An In Silico Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Musumeci, Matias A.; Lozada, Mariana; Rial, Daniela V.

The goal of this work was to identify sequences encoding monooxygenase biocatalysts with novel features by in silico mining an assembled metagenomic dataset of polar and subpolar marine sediments. The targeted enzyme sequences were Baeyer-Villiger and bacterial cytochrome P450 monooxygenases (CYP153). These enzymes have wide-ranging applications, from the synthesis of steroids, antibiotics, mycotoxins and pheromones to the synthesis of monomers for polymerization and anticancer precursors, due to their extraordinary enantio-, regio-, and chemo- selectivity that are valuable features for organic synthesis. Phylogenetic analyses were used to select the most divergent sequences affiliated to these enzyme families among the 264 putativemore » monooxygenases recovered from the ~14 million protein-coding sequences in the assembled metagenome dataset. Three-dimensional structure modeling and docking analysis suggested features useful in biotechnological applications in five metagenomic sequences, such as wide substrate range, novel substrate specificity or regioselectivity. Further analysis revealed structural features associated with psychrophilic enzymes, such as broader substrate accessibility, larger catalytic pockets or low domain interactions, suggesting that they could be applied in biooxidations at room or low temperatures, saving costs inherent to energy consumption. As a result, this work allowed the identification of putative enzyme candidates with promising features from metagenomes, providing a suitable starting point for further developments.« less

Prospecting Biotechnologically-Relevant Monooxygenases from Cold Sediment Metagenomes: An In Silico Approach.

PubMed

Musumeci, Matías A; Lozada, Mariana; Rial, Daniela V; Mac Cormack, Walter P; Jansson, Janet K; Sjöling, Sara; Carroll, JoLynn; Dionisi, Hebe M

2017-04-09

The goal of this work was to identify sequences encoding monooxygenase biocatalysts with novel features by in silico mining an assembled metagenomic dataset of polar and subpolar marine sediments. The targeted enzyme sequences were Baeyer-Villiger and bacterial cytochrome P450 monooxygenases (CYP153). These enzymes have wide-ranging applications, from the synthesis of steroids, antibiotics, mycotoxins and pheromones to the synthesis of monomers for polymerization and anticancer precursors, due to their extraordinary enantio-, regio-, and chemo- selectivity that are valuable features for organic synthesis. Phylogenetic analyses were used to select the most divergent sequences affiliated to these enzyme families among the 264 putative monooxygenases recovered from the ~14 million protein-coding sequences in the assembled metagenome dataset. Three-dimensional structure modeling and docking analysis suggested features useful in biotechnological applications in five metagenomic sequences, such as wide substrate range, novel substrate specificity or regioselectivity. Further analysis revealed structural features associated with psychrophilic enzymes, such as broader substrate accessibility, larger catalytic pockets or low domain interactions, suggesting that they could be applied in biooxidations at room or low temperatures, saving costs inherent to energy consumption. This work allowed the identification of putative enzyme candidates with promising features from metagenomes, providing a suitable starting point for further developments.

Prospecting Biotechnologically-Relevant Monooxygenases from Cold Sediment Metagenomes: An In Silico Approach

PubMed Central

Musumeci, Matías A.; Lozada, Mariana; Rial, Daniela V.; Mac Cormack, Walter P.; Jansson, Janet K.; Sjöling, Sara; Carroll, JoLynn; Dionisi, Hebe M.

2017-01-01

The goal of this work was to identify sequences encoding monooxygenase biocatalysts with novel features by in silico mining an assembled metagenomic dataset of polar and subpolar marine sediments. The targeted enzyme sequences were Baeyer–Villiger and bacterial cytochrome P450 monooxygenases (CYP153). These enzymes have wide-ranging applications, from the synthesis of steroids, antibiotics, mycotoxins and pheromones to the synthesis of monomers for polymerization and anticancer precursors, due to their extraordinary enantio-, regio-, and chemo- selectivity that are valuable features for organic synthesis. Phylogenetic analyses were used to select the most divergent sequences affiliated to these enzyme families among the 264 putative monooxygenases recovered from the ~14 million protein-coding sequences in the assembled metagenome dataset. Three-dimensional structure modeling and docking analysis suggested features useful in biotechnological applications in five metagenomic sequences, such as wide substrate range, novel substrate specificity or regioselectivity. Further analysis revealed structural features associated with psychrophilic enzymes, such as broader substrate accessibility, larger catalytic pockets or low domain interactions, suggesting that they could be applied in biooxidations at room or low temperatures, saving costs inherent to energy consumption. This work allowed the identification of putative enzyme candidates with promising features from metagenomes, providing a suitable starting point for further developments. PMID:28397770

Training needs for toxicity testing in the 21st century: a survey-informed analysis.

PubMed

Lapenna, Silvia; Gabbert, Silke; Worth, Andrew

2012-12-01

Current training needs on the use of alternative methods in predictive toxicology, including new approaches based on mode-of-action (MoA) and adverse outcome pathway (AOP) concepts, are expected to evolve rapidly. In order to gain insight into stakeholder preferences for training, the European Commission's Joint Research Centre (JRC) conducted a single-question survey with twelve experts in regulatory agencies, industry, national research organisations, NGOs and consultancies. Stakeholder responses were evaluated by means of theory-based qualitative data analysis. Overall, a set of training topics were identified that relate both to general background information and to guidance for applying alternative testing methods. In particular, for the use of in silico methods, stakeholders emphasised the need for training on data integration and evaluation, in order to increase confidence in applying these methods for regulatory purposes. Although the survey does not claim to offer an exhaustive overview of the training requirements, its findings support the conclusion that the development of well-targeted and tailor-made training opportunities that inform about the usefulness of alternative methods, in particular those that offer practical experience in the application of in silico methods, deserves more attention. This should be complemented by transparent information and guidance on the interpretation of the results generated by these methods and software tools. 2012 FRAME.

In silico study of breast cancer associated gene 3 using LION Target Engine and other tools.

PubMed

León, Darryl A; Cànaves, Jaume M

2003-12-01

Sequence analysis of individual targets is an important step in annotation and validation. As a test case, we investigated human breast cancer associated gene 3 (BCA3) with LION Target Engine and with other bioinformatics tools. LION Target Engine confirmed that the BCA3 gene is located on 11p15.4 and that the two most likely splice variants (lacking exon 3 and exons 3 and 5, respectively) exist. Based on our manual curation of sequence data, it is proposed that an additional variant (missing only exon 5) published in a public sequence repository, is a prediction artifact. A significant number of new orthologs were also identified, and these were the basis for a high-quality protein secondary structure prediction. Moreover, our research confirmed several distinct functional domains as described in earlier reports. Sequence conservation from multiple sequence alignments, splice variant identification, secondary structure predictions, and predicted phosphorylation sites suggest that the removal of interaction sites through alternative splicing might play a modulatory role in BCA3. This in silico approach shows the depth and relevance of an analysis that can be accomplished by including a variety of publicly available tools with an integrated and customizable life science informatics platform.

Combining structure-based pharmacophore modeling, virtual screening, and in silico ADMET analysis to discover novel tetrahydro-quinoline based pyruvate kinase isozyme M2 activators with antitumor activity

PubMed Central

Chen, Can; Wang, Ting; Wu, Fengbo; Huang, Wei; He, Gu; Ouyang, Liang; Xiang, Mingli; Peng, Cheng; Jiang, Qinglin

2014-01-01

Compared with normal differentiated cells, cancer cells upregulate the expression of pyruvate kinase isozyme M2 (PKM2) to support glycolytic intermediates for anabolic processes, including the synthesis of nucleic acids, amino acids, and lipids. In this study, a combination of the structure-based pharmacophore modeling and a hybrid protocol of virtual screening methods comprised of pharmacophore model-based virtual screening, docking-based virtual screening, and in silico ADMET (absorption, distribution, metabolism, excretion and toxicity) analysis were used to retrieve novel PKM2 activators from commercially available chemical databases. Tetrahydroquinoline derivatives were identified as potential scaffolds of PKM2 activators. Thus, the hybrid virtual screening approach was applied to screen the focused tetrahydroquinoline derivatives embedded in the ZINC database. Six hit compounds were selected from the final hits and experimental studies were then performed. Compound 8 displayed a potent inhibitory effect on human lung cancer cells. Following treatment with Compound 8, cell viability, apoptosis, and reactive oxygen species (ROS) production were examined in A549 cells. Finally, we evaluated the effects of Compound 8 on mice xenograft tumor models in vivo. These results may provide important information for further research on novel PKM2 activators as antitumor agents. PMID:25214764

New antimicrobial peptides against foodborne pathogens: From in silico design to experimental evidence.

PubMed

Palmieri, Gianna; Balestrieri, Marco; Proroga, Yolande T R; Falcigno, Lucia; Facchiano, Angelo; Riccio, Alessia; Capuano, Federico; Marrone, Raffaele; Neglia, Gianluca; Anastasio, Aniello

2016-11-15

Recently there has been growing interest in the discovery of new antimicrobial agents to increase safety and shelf-life of food products. Here, we developed an innovative approach by introducing the concept that mitochondrial targeting peptides (MTP) can interact and disrupt bacterial membranes, acting as antimicrobial agents. As proof-of-principle, we used a multidisciplinary strategy by combining in silico predictions, docking simulations and antimicrobial assays, to identify two peptides, MTP1 and MTP2, which were structurally and functionally characterized. Both compounds appeared effective against Listeria monocytogenes, one of the most important foodborne pathogens. Specifically, a significant bactericidal activity was evidenced with EC50 values of 16.8±1.2μM for MTP1 and 109±7.0μM for MTP2. Finally, NMR structure determinations suggested that MTP1 would be oriented into the membrane bilayer, while the molecular shape of MTP2 could indicate porin-mediated antimicrobial mechanisms, as predicted using molecular docking analysis. Therefore, MTPs represent alternative sources to design new potential bio-preservatives. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comprehensive predictions of target proteins based on protein-chemical interaction using virtual screening and experimental verifications.

PubMed

Kobayashi, Hiroki; Harada, Hiroko; Nakamura, Masaomi; Futamura, Yushi; Ito, Akihiro; Yoshida, Minoru; Iemura, Shun-Ichiro; Shin-Ya, Kazuo; Doi, Takayuki; Takahashi, Takashi; Natsume, Tohru; Imoto, Masaya; Sakakibara, Yasubumi

2012-04-05

Identification of the target proteins of bioactive compounds is critical for elucidating the mode of action; however, target identification has been difficult in general, mostly due to the low sensitivity of detection using affinity chromatography followed by CBB staining and MS/MS analysis. We applied our protocol of predicting target proteins combining in silico screening and experimental verification for incednine, which inhibits the anti-apoptotic function of Bcl-xL by an unknown mechanism. One hundred eighty-two target protein candidates were computationally predicted to bind to incednine by the statistical prediction method, and the predictions were verified by in vitro binding of incednine to seven proteins, whose expression can be confirmed in our cell system.As a result, 40% accuracy of the computational predictions was achieved successfully, and we newly found 3 incednine-binding proteins. This study revealed that our proposed protocol of predicting target protein combining in silico screening and experimental verification is useful, and provides new insight into a strategy for identifying target proteins of small molecules.

BRCA1/2 missense mutations and the value of in-silico analyses.

PubMed

Sadowski, Carolin E; Kohlstedt, Daniela; Meisel, Cornelia; Keller, Katja; Becker, Kerstin; Mackenroth, Luisa; Rump, Andreas; Schröck, Evelin; Wimberger, Pauline; Kast, Karin

2017-11-01

The clinical implications of genetic variants in BRCA1/2 in healthy and affected individuals are considerable. Variant interpretation, however, is especially challenging for missense variants. The majority of them are classified as variants of unknown clinical significance (VUS). Computational (in-silico) predictive programs are easy to access, but represent only one tool out of a wide range of complemental approaches to classify VUS. With this single-center study, we aimed to evaluate the impact of in-silico analyses in a spectrum of different BRCA1/2 missense variants. We conducted mutation analysis of BRCA1/2 in 523 index patients with suspected hereditary breast and ovarian cancer (HBOC). Classification of the genetic variants was performed according to the German Consortium (GC)-HBOC database. Additionally, all missense variants were classified by the following three in-silico prediction tools: SIFT, Mutation Taster (MT2) and PolyPhen2 (PPH2). Overall 201 different variants, 68 of which constituted missense variants were ranked as pathogenic, neutral, or unknown. The classification of missense variants by in-silico tools resulted in a higher amount of pathogenic mutations (25% vs. 13.2%) compared to the GC-HBOC-classification. Altogether, more than fifty percent (38/68, 55.9%) of missense variants were ranked differently. Sensitivity of in-silico-tools for mutation prediction was 88.9% (PPH2), 100% (SIFT) and 100% (MT2). We found a relevant discrepancy in variant classification by using in-silico prediction tools, resulting in potential overestimation and/or underestimation of cancer risk. More reliable, notably gene-specific, prediction tools and functional tests are needed to improve clinical counseling. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Genome-Wide Comparative In Silico Analysis of the RNA Helicase Gene Family in Zea mays and Glycine max: A Comparison with Arabidopsis and Oryza sativa

PubMed Central

Huang, Jinguang; Zheng, Chengchao

2013-01-01

RNA helicases are enzymes that are thought to unwind double-stranded RNA molecules in an energy-dependent fashion through the hydrolysis of NTP. RNA helicases are associated with all processes involving RNA molecules, including nuclear transcription, editing, splicing, ribosome biogenesis, RNA export, and organelle gene expression. The involvement of RNA helicase in response to stress and in plant growth and development has been reported previously. While their importance in Arabidopsis and Oryza sativa has been partially studied, the function of RNA helicase proteins is poorly understood in Zea mays and Glycine max. In this study, we identified a total of RNA helicase genes in Arabidopsis and other crop species genome by genome-wide comparative in silico analysis. We classified the RNA helicase genes into three subfamilies according to the structural features of the motif II region, such as DEAD-box, DEAH-box and DExD/H-box, and different species showed different patterns of alternative splicing. Secondly, chromosome location analysis showed that the RNA helicase protein genes were distributed across all chromosomes with different densities in the four species. Thirdly, phylogenetic tree analyses identified the relevant homologs of DEAD-box, DEAH-box and DExD/H-box RNA helicase proteins in each of the four species. Fourthly, microarray expression data showed that many of these predicted RNA helicase genes were expressed in different developmental stages and different tissues under normal growth conditions. Finally, real-time quantitative PCR analysis showed that the expression levels of 10 genes in Arabidopsis and 13 genes in Zea mays were in close agreement with the microarray expression data. To our knowledge, this is the first report of a comparative genome-wide analysis of the RNA helicase gene family in Arabidopsis, Oryza sativa, Zea mays and Glycine max. This study provides valuable information for understanding the classification and putative functions of the RNA helicase gene family in crop growth and development. PMID:24265739

Genome-wide comparative in silico analysis of the RNA helicase gene family in Zea mays and Glycine max: a comparison with Arabidopsis and Oryza sativa.

PubMed

Xu, Ruirui; Zhang, Shizhong; Huang, Jinguang; Zheng, Chengchao

2013-01-01

RNA helicases are enzymes that are thought to unwind double-stranded RNA molecules in an energy-dependent fashion through the hydrolysis of NTP. RNA helicases are associated with all processes involving RNA molecules, including nuclear transcription, editing, splicing, ribosome biogenesis, RNA export, and organelle gene expression. The involvement of RNA helicase in response to stress and in plant growth and development has been reported previously. While their importance in Arabidopsis and Oryza sativa has been partially studied, the function of RNA helicase proteins is poorly understood in Zea mays and Glycine max. In this study, we identified a total of RNA helicase genes in Arabidopsis and other crop species genome by genome-wide comparative in silico analysis. We classified the RNA helicase genes into three subfamilies according to the structural features of the motif II region, such as DEAD-box, DEAH-box and DExD/H-box, and different species showed different patterns of alternative splicing. Secondly, chromosome location analysis showed that the RNA helicase protein genes were distributed across all chromosomes with different densities in the four species. Thirdly, phylogenetic tree analyses identified the relevant homologs of DEAD-box, DEAH-box and DExD/H-box RNA helicase proteins in each of the four species. Fourthly, microarray expression data showed that many of these predicted RNA helicase genes were expressed in different developmental stages and different tissues under normal growth conditions. Finally, real-time quantitative PCR analysis showed that the expression levels of 10 genes in Arabidopsis and 13 genes in Zea mays were in close agreement with the microarray expression data. To our knowledge, this is the first report of a comparative genome-wide analysis of the RNA helicase gene family in Arabidopsis, Oryza sativa, Zea mays and Glycine max. This study provides valuable information for understanding the classification and putative functions of the RNA helicase gene family in crop growth and development.

In silico prediction of cytochrome P450-mediated drug metabolism.

PubMed

Zhang, Tao; Chen, Qi; Li, Li; Liu, Limin Angela; Wei, Dong-Qing

2011-06-01

The application of combinatorial chemistry and high-throughput screening technique enables the large number of chemicals to be generated and tested simultaneously, which will facilitate the drug development and discovery. At the same time, it brings about a challenge of how to efficiently identify the potential drug candidates from thousands of compounds. A way used to deal with the challenge is to consider the drug pharmacokinetic properties, such as absorption, distribution, metabolism and excretion (ADME), in the early stage of drug development. Among ADME properties, metabolism is of importance due to the strong association with efficacy and safety of drug. The review will focus on in silico approaches for prediction of Cytochrome P450-mediated drug metabolism. We will describe these predictive methods from two aspects, structure-based and data-based. Moreover, the applications and limitations of various methods will be discussed. Finally, we provide further direction toward improving the predictive accuracy of these in silico methods.

In silico discovery of metal-organic frameworks for precombustion CO2 capture using a genetic algorithm

PubMed Central

Chung, Yongchul G.; Gómez-Gualdrón, Diego A.; Li, Peng; Leperi, Karson T.; Deria, Pravas; Zhang, Hongda; Vermeulen, Nicolaas A.; Stoddart, J. Fraser; You, Fengqi; Hupp, Joseph T.; Farha, Omar K.; Snurr, Randall Q.

2016-01-01

Discovery of new adsorbent materials with a high CO2 working capacity could help reduce CO2 emissions from newly commissioned power plants using precombustion carbon capture. High-throughput computational screening efforts can accelerate the discovery of new adsorbents but sometimes require significant computational resources to explore the large space of possible materials. We report the in silico discovery of high-performing adsorbents for precombustion CO2 capture by applying a genetic algorithm to efficiently search a large database of metal-organic frameworks (MOFs) for top candidates. High-performing MOFs identified from the in silico search were synthesized and activated and show a high CO2 working capacity and a high CO2/H2 selectivity. One of the synthesized MOFs shows a higher CO2 working capacity than any MOF reported in the literature under the operating conditions investigated here. PMID:27757420

Identification of expressed sequences in the coffee genome potentially associated with somatic embryogenesis.

PubMed

Silva, A T; Paiva, L V; Andrade, A C; Barduche, D

2013-05-21

Brazil possesses the most modern and productive coffee growing farms in the world, but technological development is desired to cope with the increasing world demand. One way to increase Brazilian coffee growing productivity is wide scale production of clones with superior genotypes, which can be obtained with in vitro propagation technique, or from tissue culture. These procedures can generate thousands of clones. However, the methodologies for in vitro cultivation are genotype-dependent, which leads to an almost empirical development of specific protocols for each species. Therefore, molecular markers linked to the biochemical events of somatic embryogenesis would greatly facilitate the development of such protocols. In this context, sequences potentially involved in embryogenesis processes in the coffee plant were identified in silico from libraries generated by the Brazilian Coffee Genome Project. Through these in silico analyses, we identified 15 EST-contigs related to the embryogenesis process. Among these, 5 EST-contigs (3605, 9850, 13686, 17240, and 17265) could readily be associated with plant embryogenesis. Sequence analysis of EST-contig 3605, 9850, and 17265 revealed similarity to a polygalacturonase, to a cysteine-proteinase, and to an allergenine, respectively. Results also show that EST-contig 17265 sequences presented similarity to an expansin. Finally, analysis of EST-contig 17240 revealed similarity to a protein of unknown function, but it grouped in the similarity dendrogram with the WUSCHEL transcription factor. The data suggest that these EST-contigs are related to the embryogenic process and have potential as molecular markers to increase methodological efficiency in obtaining coffee plant embryogenic materials.

DIANA-LncBase v2: indexing microRNA targets on non-coding transcripts.

PubMed

Paraskevopoulou, Maria D; Vlachos, Ioannis S; Karagkouni, Dimitra; Georgakilas, Georgios; Kanellos, Ilias; Vergoulis, Thanasis; Zagganas, Konstantinos; Tsanakas, Panayiotis; Floros, Evangelos; Dalamagas, Theodore; Hatzigeorgiou, Artemis G

2016-01-04

microRNAs (miRNAs) are short non-coding RNAs (ncRNAs) that act as post-transcriptional regulators of coding gene expression. Long non-coding RNAs (lncRNAs) have been recently reported to interact with miRNAs. The sponge-like function of lncRNAs introduces an extra layer of complexity in the miRNA interactome. DIANA-LncBase v1 provided a database of experimentally supported and in silico predicted miRNA Recognition Elements (MREs) on lncRNAs. The second version of LncBase (www.microrna.gr/LncBase) presents an extensive collection of miRNA:lncRNA interactions. The significantly enhanced database includes more than 70 000 low and high-throughput, (in)direct miRNA:lncRNA experimentally supported interactions, derived from manually curated publications and the analysis of 153 AGO CLIP-Seq libraries. The new experimental module presents a 14-fold increase compared to the previous release. LncBase v2 hosts in silico predicted miRNA targets on lncRNAs, identified with the DIANA-microT algorithm. The relevant module provides millions of predicted miRNA binding sites, accompanied with detailed metadata and MRE conservation metrics. LncBase v2 caters information regarding cell type specific miRNA:lncRNA regulation and enables users to easily identify interactions in 66 different cell types, spanning 36 tissues for human and mouse. Database entries are also supported by accurate lncRNA expression information, derived from the analysis of more than 6 billion RNA-Seq reads. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Gene signature associated with benign neurofibroma transformation to malignant peripheral nerve sheath tumors

PubMed Central

Sorzano, Carlos O. S.; Pascual-Montano, Alberto; Carazo, Jose M.

2017-01-01

Benign neurofibromas, the main phenotypic manifestations of the rare neurological disorder neurofibromatosis type 1, degenerate to malignant tumors associated to poor prognosis in about 10% of patients. Despite efforts in the field of (epi)genomics, the lack of prognostic biomarkers with which to predict disease evolution frustrates the adoption of appropriate early therapeutic measures. To identify potential biomarkers of malignant neurofibroma transformation, we integrated four human experimental studies and one for mouse, using a gene score-based meta-analysis method, from which we obtained a score-ranked signature of 579 genes. Genes with the highest absolute scores were classified as promising disease biomarkers. By grouping genes with similar neurofibromatosis-related profiles, we derived panels of potential biomarkers. The addition of promoter methylation data to gene profiles indicated a panel of genes probably silenced by hypermethylation. To identify possible therapeutic treatments, we used the gene signature to query drug expression databases. Trichostatin A and other histone deacetylase inhibitors, as well as cantharidin and tamoxifen, were retrieved as putative therapeutic means to reverse the aberrant regulation that drives to malignant cell proliferation and metastasis. This in silico prediction corroborated reported experimental results that suggested the inclusion of these compounds in clinical trials. This experimental validation supported the suitability of the meta-analysis method used to integrate several sources of public genomic information, and the reliability of the gene signature associated to the malignant evolution of neurofibromas to generate working hypotheses for prognostic and drug-responsive biomarkers or therapeutic measures, thus showing the potential of this in silico approach for biomarker discovery. PMID:28542306

Understanding mechanism of in vitro maturation, fertilization and culture of sheep embryoes through in silico analysis.

PubMed

Sreenivas, Dulam; Kaladhar, Dowluru Svgk; Samy, A Palni; Kumar, R Sangeeth

2012-01-01

Protein interations are presently required to understand the mechanisms of in vitro maturation, fertilization and culture of sheep embryoes through in silico analysis. The present work has been conducted on TCM-199 supplemented with epidermal growth factor (EGF), fetal bovine serum (FBS) or wheat peptones The maturation rate of oocyte was significantly higher in the FBS supplemented group when compared with BSA and wheat peptone supplemented groups. The in silico protein interaction studies has shown that the proteins EGFR (epidermal growth factor receptor), CCK (cholecystokinin)- a peptide hormone, Alb - a serum albumin, ESR- estrogen receptor 1, TGFA- transforming growth factor, STAT- signal transducer and FN1- fibronectin 1 has direct interaction and produces cell growth in in vitro culture. Alb is directly activates EGF and promotes MAPK3 that mediates diverse biological functions such as cell growth, adhesion and proliferation. Alb may also involve in stress response signalling and may be in cell cycle control.

Safety assessment and functional properties of four enterococci strains isolated from regional Argentinean cheese.

PubMed

Martino, Gabriela P; Espariz, Martín; Gallina Nizo, Gabriel; Esteban, Luis; Blancato, Víctor S; Magni, Christian

2018-07-20

The members of the Enterococcus genus are widely distributed in nature. Its strains have been extensively reported to be present in plant surfaces, soil, water and food. In an attempt to assess their potential application in food industry, four Enterococcus faecium group-strains recently isolated from Argentinean regional cheese products were evaluated using a combination of whole genome analyses and in vivo assays. In order to identify these microorganisms at species level, in silico analyses using their newly reported sequences were conducted. The average nucleotide identity (ANI), in silico DNA-DNA hybridization, and phylogenomic trees constructed using core genome data allowed IQ110, GM70 and GM75 strains to be classified as E. faecium while IQ23 strain was identified as E. durans. Besides their common origin, the strains showed differences in their genetic structure and mobile genetic element content. Furthermore, it was possible to determine the absence or presence of specific features related to growth in milk, cheese ripening, probiotic capability and gut adaptation including sugar, amino acid, and peptides utilization, flavor compound production, bile salt tolerance as well as biogenic amine production. Remarkably, all strains encoded for peptide permeases, maltose utilization, bile salt tolerance, diacetyl and tyramine production genes. On the other hand, some variability was observed regarding citrate and lactose utilization, esterase, and cell wall-associated proteinase. In addition, while strains were predicted to be non-human pathogens by the in silico inspection of pathogenicity and virulence factors, only the GM70 strain proved to be non-virulent in Galleria mellonella model. In conclusion, we propose that, in order to improve the rational selection of strains for industrial applications, a holistic approach involving a comparative genomic analysis of positive and negative features as well as in vivo evaluation of virulence behavior should be performed. Copyright © 2018 Elsevier B.V. All rights reserved.

A Comprehensive in vitro and in silico Analysis of Antibiotics that Activate PXR and Induce CYP3A4 in Liver and Intestine

PubMed Central

Yasuda, Kazuto; Ranade, Aarati; Venkataramanan, Raman; Strom, Stephen; Chupka, Jonathan; Ekins, Sean; Schuetz, Erin; Bachmann, Kenneth

2015-01-01

We have investigated several in silico and in vitro methods in order to improve our ability to predict potential drug interactions of antibiotics. Our focus was to identify those antibiotics that activate PXR and induce CYP3A4 in human hepatocytes and intestinal cells. Human PXR activation was screened using reporter assays in HepG2 cells, kinetic measurements of PXR activation were made in DPX-2 cells, and induction of CYP3A4 expression and activity was verified by quantitative PCR, immunoblotting and testosterone 6β-hydroxylation in primary human hepatocytes and LS180 cells. We found that in HepG2 cells CYP3A4 transcription was activated strongly (>10-fold) by rifampin and troleandomycin; moderately (> 7-fold) by dicloxacillin, tetracycline, clindamycin, griseofulvin and (> 4-fold) by erythromycin; weakly (>2.4-fold) by nafcillin, cefaclor and sulfisoxazole; and (>2-fold) by cefadroxil and penicillin V. Similar though not identical results were obtained in DPX-2 cells. CYP3A4 mRNA and protein expression were induced by these antibiotics to differing extents in both liver and intestinal cells. CYP3A4 activity was significantly increased by rifampin (9.7-fold), nafcillin and dicloxacillin (5.9-fold), and weakly induced (2-fold) by tetracycline, sufisoxazole, troleandomycin and clindamycin. Multiple pharmacophore models and docking indicated a good fit for dicloxacillin and nafcillin in PXR. These results suggest that in vitro and in silico methods can help to prioritize and identify antibiotics that are most likely to reduce exposures of medications (such as oral contraceptive agents) which interact with enzymes and transporters regulated by PXR. In summary, nafcillin, dicloxacillin, cephradine, tetracycline, sulfixoxazole, erythromycin, clindamycin, and griseofulvin exhibit a clear propensity to induce CYP3A4 and warrant further clinical investigation. PMID:18505790

Propagating annotations of molecular networks using in silico fragmentation

PubMed Central

da Silva, Ricardo R.; Wang, Mingxun; Fox, Evan; Balunas, Marcy J.; Klassen, Jonathan L.; Dorrestein, Pieter C.

2018-01-01

The annotation of small molecules is one of the most challenging and important steps in untargeted mass spectrometry analysis, as most of our biological interpretations rely on structural annotations. Molecular networking has emerged as a structured way to organize and mine data from untargeted tandem mass spectrometry (MS/MS) experiments and has been widely applied to propagate annotations. However, propagation is done through manual inspection of MS/MS spectra connected in the spectral networks and is only possible when a reference library spectrum is available. One of the alternative approaches used to annotate an unknown fragmentation mass spectrum is through the use of in silico predictions. One of the challenges of in silico annotation is the uncertainty around the correct structure among the predicted candidate lists. Here we show how molecular networking can be used to improve the accuracy of in silico predictions through propagation of structural annotations, even when there is no match to a MS/MS spectrum in spectral libraries. This is accomplished through creating a network consensus of re-ranked structural candidates using the molecular network topology and structural similarity to improve in silico annotations. The Network Annotation Propagation (NAP) tool is accessible through the GNPS web-platform https://gnps.ucsd.edu/ProteoSAFe/static/gnps-theoretical.jsp. PMID:29668671

Propagating annotations of molecular networks using in silico fragmentation.

PubMed

da Silva, Ricardo R; Wang, Mingxun; Nothias, Louis-Félix; van der Hooft, Justin J J; Caraballo-Rodríguez, Andrés Mauricio; Fox, Evan; Balunas, Marcy J; Klassen, Jonathan L; Lopes, Norberto Peporine; Dorrestein, Pieter C

2018-04-01

The annotation of small molecules is one of the most challenging and important steps in untargeted mass spectrometry analysis, as most of our biological interpretations rely on structural annotations. Molecular networking has emerged as a structured way to organize and mine data from untargeted tandem mass spectrometry (MS/MS) experiments and has been widely applied to propagate annotations. However, propagation is done through manual inspection of MS/MS spectra connected in the spectral networks and is only possible when a reference library spectrum is available. One of the alternative approaches used to annotate an unknown fragmentation mass spectrum is through the use of in silico predictions. One of the challenges of in silico annotation is the uncertainty around the correct structure among the predicted candidate lists. Here we show how molecular networking can be used to improve the accuracy of in silico predictions through propagation of structural annotations, even when there is no match to a MS/MS spectrum in spectral libraries. This is accomplished through creating a network consensus of re-ranked structural candidates using the molecular network topology and structural similarity to improve in silico annotations. The Network Annotation Propagation (NAP) tool is accessible through the GNPS web-platform https://gnps.ucsd.edu/ProteoSAFe/static/gnps-theoretical.jsp.

Genome-wide association meta-analysis highlights light-induced signaling as a driver for refractive error.

PubMed

Tedja, Milly S; Wojciechowski, Robert; Hysi, Pirro G; Eriksson, Nicholas; Furlotte, Nicholas A; Verhoeven, Virginie J M; Iglesias, Adriana I; Meester-Smoor, Magda A; Tompson, Stuart W; Fan, Qiao; Khawaja, Anthony P; Cheng, Ching-Yu; Höhn, René; Yamashiro, Kenji; Wenocur, Adam; Grazal, Clare; Haller, Toomas; Metspalu, Andres; Wedenoja, Juho; Jonas, Jost B; Wang, Ya Xing; Xie, Jing; Mitchell, Paul; Foster, Paul J; Klein, Barbara E K; Klein, Ronald; Paterson, Andrew D; Hosseini, S Mohsen; Shah, Rupal L; Williams, Cathy; Teo, Yik Ying; Tham, Yih Chung; Gupta, Preeti; Zhao, Wanting; Shi, Yuan; Saw, Woei-Yuh; Tai, E-Shyong; Sim, Xue Ling; Huffman, Jennifer E; Polašek, Ozren; Hayward, Caroline; Bencic, Goran; Rudan, Igor; Wilson, James F; Joshi, Peter K; Tsujikawa, Akitaka; Matsuda, Fumihiko; Whisenhunt, Kristina N; Zeller, Tanja; van der Spek, Peter J; Haak, Roxanna; Meijers-Heijboer, Hanne; van Leeuwen, Elisabeth M; Iyengar, Sudha K; Lass, Jonathan H; Hofman, Albert; Rivadeneira, Fernando; Uitterlinden, André G; Vingerling, Johannes R; Lehtimäki, Terho; Raitakari, Olli T; Biino, Ginevra; Concas, Maria Pina; Schwantes-An, Tae-Hwi; Igo, Robert P; Cuellar-Partida, Gabriel; Martin, Nicholas G; Craig, Jamie E; Gharahkhani, Puya; Williams, Katie M; Nag, Abhishek; Rahi, Jugnoo S; Cumberland, Phillippa M; Delcourt, Cécile; Bellenguez, Céline; Ried, Janina S; Bergen, Arthur A; Meitinger, Thomas; Gieger, Christian; Wong, Tien Yin; Hewitt, Alex W; Mackey, David A; Simpson, Claire L; Pfeiffer, Norbert; Pärssinen, Olavi; Baird, Paul N; Vitart, Veronique; Amin, Najaf; van Duijn, Cornelia M; Bailey-Wilson, Joan E; Young, Terri L; Saw, Seang-Mei; Stambolian, Dwight; MacGregor, Stuart; Guggenheim, Jeremy A; Tung, Joyce Y; Hammond, Christopher J; Klaver, Caroline C W

2018-06-01

Refractive errors, including myopia, are the most frequent eye disorders worldwide and an increasingly common cause of blindness. This genome-wide association meta-analysis in 160,420 participants and replication in 95,505 participants increased the number of established independent signals from 37 to 161 and showed high genetic correlation between Europeans and Asians (>0.78). Expression experiments and comprehensive in silico analyses identified retinal cell physiology and light processing as prominent mechanisms, and also identified functional contributions to refractive-error development in all cell types of the neurosensory retina, retinal pigment epithelium, vascular endothelium and extracellular matrix. Newly identified genes implicate novel mechanisms such as rod-and-cone bipolar synaptic neurotransmission, anterior-segment morphology and angiogenesis. Thirty-one loci resided in or near regions transcribing small RNAs, thus suggesting a role for post-transcriptional regulation. Our results support the notion that refractive errors are caused by a light-dependent retina-to-sclera signaling cascade and delineate potential pathobiological molecular drivers.

Identification of trans-acting factors regulating SamDC expression in Oryza sativa

DOE Office of Scientific and Technical Information (OSTI.GOV)

Basu, Supratim, E-mail: supratim_genetics@yahoo.co.in; Division of Plant Biology, Bose Institute, Kolkata; Roychoudhury, Aryadeep

2014-03-07

Highlights: • Identification of cis elements responsible for SamDC expression by in silico analysis. • qPCR analysis of SamDC expression to abiotic and biotic stress treatments. • Detection of SamDC regulators using identified cis-elements as probe by EMSA. • Southwestern Blot analysis to predict the size of the trans-acting factors. - Abstract: Abiotic stress affects the growth and productivity of crop plants; to cope with the adverse environmental conditions, plants have developed efficient defense machinery comprising of antioxidants like phenolics and flavonoids, and osmolytes like polyamines. SamDC is a key enzyme in the polyamine biosynthesis pathway in plants. In ourmore » present communication we have done in silico analysis of the promoter region of SamDC to look for the presence of different cis-regulatory elements contributing to its expression. Based on the presence of different cis-regulatory elements we completed comparative analysis of SamDC gene expression in rice lamina of IR-29 and Nonabokra by qPCR in response to the abiotic stress treatments of salinity, drought, cold and the biotic stress treatments of ABA and light. Additionally, to explore the role of the cis-regulatory elements in regulating the expression of SamDC gene in plants we comparatively analyzed the binding of rice nuclear proteins prepared from IR-29 and Nonabokra undergoing various stress treatments. The intensity of the complex formed was low and inducible in IR-29 in contrast to Nonabokra. Southwestern blot analysis helped in predicting the size of the trans-acting factors binding to these cis-elements. To our knowledge this is the first report on the comprehensive analysis of SamDC gene expression in rice and identification of the trans-acting factors regulating its expression.« less

CAPSAICIN: ITS BIOLOGICAL ACTIVITIES AND IN SILICO TARGET FISHING.

PubMed

Akhtar, Fahad; Muhammad Sharif, Hajra; Arshad Mallick, Muhammad; Zahoor, Fareeha; Abdulmalik, Attiya; Baig, Warda; Shujaat, Nodia; Gul, Sundas; Bibi, Gulfam; Ramzan, Rahdia; Murtaza, Ghulam

2017-03-01

Capsicum annuum L. is a rich source of capsaicin, an alkaloid, which is a very pungent compound. Due to ever growing need of capsaicin, an extensive research on its efficient cultivation as well as chemical synthesis is underway. Owing to the pungent nature of capsaicin, its analogous molecules without pungent effect are being explored. The objective of this descriptive review is to comprehensively present the updates on the bioactivities of capsaicin. Additionally, the in silico target fishing approach has been used to identify the possible protein targets of capsaicin. This article will definitely provide future perspectives of research on capsaicin.

Nimbolide targets BCL2 and induces apoptosis in preclinical models of Waldenströms macroglobulinemia

PubMed Central

Chitta, K; Paulus, A; Caulfield, T R; Akhtar, S; Blake, M-KK; Ailawadhi, S; Knight, J; Heckman, M G; Pinkerton, A; Chanan-Khan, A

2014-01-01

Neem leaf extract (NLE) has medicinal properties, which have been attributed to its limonoid content. We identified the NLE tetranorterpenoid, nimbolide, as being the key limonoid responsible for the cytotoxicity of NLE in various preclinical models of human B-lymphocyte cancer. Of the models tested, Waldenströms macroglobulinemia (WM) cells were most sensitive to nimbolide, undergoing significant mitochondrial mediated apoptosis. Notably, nimbolide toxicity was also observed in drug-resistant (bortezomib or ibrutinib) WM cells. To identify putative targets of nimbolide, relevant in WM, we used chemoinformatics-based approaches comprised of virtual in silico screening, molecular modeling and target–ligand reverse docking. In silico analysis revealed the antiapoptotic protein BCL2 was the preferential binding partner of nimbolide. The significance of this finding was further tested in vitro in RS4;11 (BCL2-dependent) tumor cells, in which nimbolide induced significantly more apoptosis compared with BCL2 mutated (Jurkat BCL2Ser70-Ala) cells. Lastly, intraperitoneal administration of nimbolide in WM tumor xenografted mice, significantly reduced tumor growth and IgM secretion in vivo, while modulating the expression of several proteins as seen on immunohistochemistry. Overall, our data demonstrate that nimbolide is highly active in WM cells, as well as other B-cell cancers, and engages BCL2 to exert its cytotoxic activity. PMID:25382610

Molecular mechanisms underlying variations in lung function: a systems genetics analysis

PubMed Central

Obeidat, Ma’en; Hao, Ke; Bossé, Yohan; Nickle, David C; Nie, Yunlong; Postma, Dirkje S; Laviolette, Michel; Sandford, Andrew J; Daley, Denise D; Hogg, James C; Elliott, W Mark; Fishbane, Nick; Timens, Wim; Hysi, Pirro G; Kaprio, Jaakko; Wilson, James F; Hui, Jennie; Rawal, Rajesh; Schulz, Holger; Stubbe, Beate; Hayward, Caroline; Polasek, Ozren; Järvelin, Marjo-Riitta; Zhao, Jing Hua; Jarvis, Deborah; Kähönen, Mika; Franceschini, Nora; North, Kari E; Loth, Daan W; Brusselle, Guy G; Smith, Albert Vernon; Gudnason, Vilmundur; Bartz, Traci M; Wilk, Jemma B; O’Connor, George T; Cassano, Patricia A; Tang, Wenbo; Wain, Louise V; Artigas, María Soler; Gharib, Sina A; Strachan, David P; Sin, Don D; Tobin, Martin D; London, Stephanie J; Hall, Ian P; Paré, Peter D

2016-01-01

Summary Background Lung function measures reflect the physiological state of the lung, and are essential to the diagnosis of chronic obstructive pulmonary disease (COPD). The SpiroMeta-CHARGE consortium undertook the largest genome-wide association study (GWAS) so far (n=48 201) for forced expiratory volume in 1 s (FEV1) and the ratio of FEV1 to forced vital capacity (FEV1/FVC) in the general population. The lung expression quantitative trait loci (eQTLs) study mapped the genetic architecture of gene expression in lung tissue from 1111 individuals. We used a systems genetics approach to identify single nucleotide polymorphisms (SNPs) associated with lung function that act as eQTLs and change the level of expression of their target genes in lung tissue; termed eSNPs. Methods The SpiroMeta-CHARGE GWAS results were integrated with lung eQTLs to map eSNPs and the genes and pathways underlying the associations in lung tissue. For comparison, a similar analysis was done in peripheral blood. The lung mRNA expression levels of the eSNP-regulated genes were tested for associations with lung function measures in 727 individuals. Additional analyses identified the pleiotropic effects of eSNPs from the published GWAS catalogue, and mapped enrichment in regulatory regions from the ENCODE project. Finally, the Connectivity Map database was used to identify potential therapeutics in silico that could reverse the COPD lung tissue gene signature. Findings SNPs associated with lung function measures were more likely to be eQTLs and vice versa. The integration mapped the specific genes underlying the GWAS signals in lung tissue. The eSNP-regulated genes were enriched for developmental and inflammatory pathways; by comparison, SNPs associated with lung function that were eQTLs in blood, but not in lung, were only involved in inflammatory pathways. Lung function eSNPs were enriched for regulatory elements and were over-represented among genes showing differential expression during fetal lung development. An mRNA gene expression signature for COPD was identified in lung tissue and compared with the Connectivity Map. This in-silico drug repurposing approach suggested several compounds that reverse the COPD gene expression signature, including a nicotine receptor antagonist. These findings represent novel therapeutic pathways for COPD. Interpretation The system genetics approach identified lung tissue genes driving the variation in lung function and susceptibility to COPD. The identification of these genes and the pathways in which they are enriched is essential to understand the pathophysiology of airway obstruction and to identify novel therapeutic targets and biomarkers for COPD, including drugs that reverse the COPD gene signature in silico. Funding The research reported in this article was not specifically funded by any agency. See Acknowledgments for a full list of funders of the lung eQTL study and the Spiro-Meta CHARGE GWAS. PMID:26404118

Identification of a 'Candidatus Phytoplasma hispanicum'-related strain, associated with yellows-type diseases, in smoke-tree sharpshooter (Homalodisca liturata Ball).

PubMed

Servín-Villegas, Rosalía; Caamal-Chan, Maria Goretty; Chavez-Medina, Alicia; Loera-Muro, Abraham; Barraza, Aarón; Medina-Hernández, Diana; Holguín-Peña, Ramón Jaime

2018-04-11

The 16SrXIII group from phytoplasma bacteria were identified in salivary glands from Homalodisca liturata, which were collected in El Comitán on the Baja California peninsula in Mexico. We were able to positively identify 15 16S rRNA gene sequences with the corresponding signature sequence of 'CandidatusPhytoplasma' (CAAGAYBATKATGTKTAGCYGGDCT) and in silico restriction fragment length polymorphism (RFLP) profiles (F value estimations) coupled with a phylogenetic analysis to confirm their relatedness to 'CandidatusPhytoplasma hispanicum', which in turn belongs to the 16SrXIII group. A restriction analysis was carried out with AluI and EcoRI to confirm that the five sequences belongs to subgroup D. The rest of the sequences did not exhibit any known RFLP profile related to a subgroup reported in the 16SrXIII group.

Identification of lethal reactions in the Esherichia coli metabolic network: Graph theory approach

NASA Astrophysics Data System (ADS)

Ghim, C.-M.; Goh, K.-I.; Kahng, B.; Kim, D.

2004-03-01

As a first step toward holistic modeling of cells, we analyze the biochemical reactions occurring in the genome-scale metabolism of Esherichia coli. To this end, we construct a directed bipartite graph by assigning metabolite or reaction to each node. We apply various measures of centrality, a well-known concept in the graph theory, and their modifications to the metabolic network, finding that there exist lethal reactions involved in the central metabolism. Such lethal reactions or associated enzymes under diverse environments in silico are identified and compared with earlier results obtained from flux balance analysis.

Genome-wide association study identifies a novel locus contributing to type 2 diabetes susceptibility in Sikhs of Punjabi origin from India.

PubMed

Saxena, Richa; Saleheen, Danish; Been, Latonya F; Garavito, Martha L; Braun, Timothy; Bjonnes, Andrew; Young, Robin; Ho, Weang Kee; Rasheed, Asif; Frossard, Philippe; Sim, Xueling; Hassanali, Neelam; Radha, Venkatesan; Chidambaram, Manickam; Liju, Samuel; Rees, Simon D; Ng, Daniel Peng-Keat; Wong, Tien-Yin; Yamauchi, Toshimasa; Hara, Kazuo; Tanaka, Yasushi; Hirose, Hiroshi; McCarthy, Mark I; Morris, Andrew P; Basit, Abdul; Barnett, Anthony H; Katulanda, Prasad; Matthews, David; Mohan, Viswanathan; Wander, Gurpreet S; Singh, Jai Rup; Mehra, Narinder K; Ralhan, Sarju; Kamboh, M Ilyas; Mulvihill, John J; Maegawa, Hiroshi; Tobe, Kazuyuki; Maeda, Shiro; Cho, Yoon S; Tai, E Shyong; Kelly, M Ann; Chambers, John C; Kooner, Jaspal S; Kadowaki, Takashi; Deloukas, Panos; Rader, Daniel J; Danesh, John; Sanghera, Dharambir K

2013-05-01

We performed a genome-wide association study (GWAS) and a multistage meta-analysis of type 2 diabetes (T2D) in Punjabi Sikhs from India. Our discovery GWAS in 1,616 individuals (842 case subjects) was followed by in silico replication of the top 513 independent single nucleotide polymorphisms (SNPs) (P < 10⁻³) in Punjabi Sikhs (n = 2,819; 801 case subjects). We further replicated 66 SNPs (P < 10⁻⁴) through genotyping in a Punjabi Sikh sample (n = 2,894; 1,711 case subjects). On combined meta-analysis in Sikh populations (n = 7,329; 3,354 case subjects), we identified a novel locus in association with T2D at 13q12 represented by a directly genotyped intronic SNP (rs9552911, P = 1.82 × 10⁻⁸) in the SGCG gene. Next, we undertook in silico replication (stage 2b) of the top 513 signals (P < 10⁻³) in 29,157 non-Sikh South Asians (10,971 case subjects) and de novo genotyping of up to 31 top signals (P < 10⁻⁴) in 10,817 South Asians (5,157 case subjects) (stage 3b). In combined South Asian meta-analysis, we observed six suggestive associations (P < 10⁻⁵ to < 10⁻⁷), including SNPs at HMG1L1/CTCFL, PLXNA4, SCAP, and chr5p11. Further evaluation of 31 top SNPs in 33,707 East Asians (16,746 case subjects) (stage 3c) and 47,117 Europeans (8,130 case subjects) (stage 3d), and joint meta-analysis of 128,127 individuals (44,358 case subjects) from 27 multiethnic studies, did not reveal any additional loci nor was there any evidence of replication for the new variant. Our findings provide new evidence on the presence of a population-specific signal in relation to T2D, which may provide additional insights into T2D pathogenesis.

Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk.

PubMed

Warren, Helen R; Evangelou, Evangelos; Cabrera, Claudia P; Gao, He; Ren, Meixia; Mifsud, Borbala; Ntalla, Ioanna; Surendran, Praveen; Liu, Chunyu; Cook, James P; Kraja, Aldi T; Drenos, Fotios; Loh, Marie; Verweij, Niek; Marten, Jonathan; Karaman, Ibrahim; Lepe, Marcelo P Segura; O'Reilly, Paul F; Knight, Joanne; Snieder, Harold; Kato, Norihiro; He, Jiang; Tai, E Shyong; Said, M Abdullah; Porteous, David; Alver, Maris; Poulter, Neil; Farrall, Martin; Gansevoort, Ron T; Padmanabhan, Sandosh; Mägi, Reedik; Stanton, Alice; Connell, John; Bakker, Stephan J L; Metspalu, Andres; Shields, Denis C; Thom, Simon; Brown, Morris; Sever, Peter; Esko, Tõnu; Hayward, Caroline; van der Harst, Pim; Saleheen, Danish; Chowdhury, Rajiv; Chambers, John C; Chasman, Daniel I; Chakravarti, Aravinda; Newton-Cheh, Christopher; Lindgren, Cecilia M; Levy, Daniel; Kooner, Jaspal S; Keavney, Bernard; Tomaszewski, Maciej; Samani, Nilesh J; Howson, Joanna M M; Tobin, Martin D; Munroe, Patricia B; Ehret, Georg B; Wain, Louise V

2017-03-01

Elevated blood pressure is the leading heritable risk factor for cardiovascular disease worldwide. We report genetic association of blood pressure (systolic, diastolic, pulse pressure) among UK Biobank participants of European ancestry with independent replication in other cohorts, and robust validation of 107 independent loci. We also identify new independent variants at 11 previously reported blood pressure loci. In combination with results from a range of in silico functional analyses and wet bench experiments, our findings highlight new biological pathways for blood pressure regulation enriched for genes expressed in vascular tissues and identify potential therapeutic targets for hypertension. Results from genetic risk score models raise the possibility of a precision medicine approach through early lifestyle intervention to offset the impact of blood pressure-raising genetic variants on future cardiovascular disease risk.

Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk

PubMed Central

Ntalla, Ioanna; Surendran, Praveen; Liu, Chunyu; Cook, James P; Kraja, Aldi T; Drenos, Fotios; Loh, Marie; Verweij, Niek; Marten, Jonathan; Karaman, Ibrahim; Segura Lepe, Marcelo P; O’Reilly, Paul F; Knight, Joanne; Snieder, Harold; Kato, Norihiro; He, Jiang; Tai, E Shyong; Said, M Abdullah; Porteous, David; Alver, Maris; Poulter, Neil; Farrall, Martin; Gansevoort, Ron T; Padmanabhan, Sandosh; Mägi, Reedik; Stanton, Alice; Connell, John; Bakker, Stephan J L; Metspalu, Andres; Shields, Denis C; Thom, Simon; Brown, Morris; Sever, Peter; Esko, Tõnu; Hayward, Caroline; van der Harst, Pim; Saleheen, Danish; Chowdhury, Rajiv; Chambers, John C; Chasman, Daniel I; Chakravarti, Aravinda; Newton-Cheh, Christopher; Lindgren, Cecilia M; Levy, Daniel; Kooner, Jaspal S; Keavney, Bernard; Tomaszewski, Maciej; Samani, Nilesh J; Howson, Joanna M M; Tobin, Martin D; Munroe, Patricia B; Ehret, Georg B; Wain, Louise V

2017-01-01

Elevated blood pressure is the leading heritable risk factor for cardiovascular disease worldwide. We report genetic association of blood pressure (systolic, diastolic, pulse pressure) among UK Biobank participants of European ancestry with independent replication in other cohorts, and robust validation of 107 independent loci. We also identify new independent variants at 11 previously reported blood pressure loci. Combined with results from a range of in silico functional analyses and wet bench experiments, our findings highlight new biological pathways for blood pressure regulation enriched for genes expressed in vascular tissues and identify potential therapeutic targets for hypertension. Results from genetic risk score models raise the possibility of a precision medicine approach through early lifestyle intervention to offset the impact of blood pressure raising genetic variants on future cardiovascular disease risk. PMID:28135244

A general framework for optimization of probes for gene expression microarray and its application to the fungus Podospora anserina

PubMed Central

2010-01-01

Background The development of new microarray technologies makes custom long oligonucleotide arrays affordable for many experimental applications, notably gene expression analyses. Reliable results depend on probe design quality and selection. Probe design strategy should cope with the limited accuracy of de novo gene prediction programs, and annotation up-dating. We present a novel in silico procedure which addresses these issues and includes experimental screening, as an empirical approach is the best strategy to identify optimal probes in the in silico outcome. Findings We used four criteria for in silico probe selection: cross-hybridization, hairpin stability, probe location relative to coding sequence end and intron position. This latter criterion is critical when exon-intron gene structure predictions for intron-rich genes are inaccurate. For each coding sequence (CDS), we selected a sub-set of four probes. These probes were included in a test microarray, which was used to evaluate the hybridization behavior of each probe. The best probe for each CDS was selected according to three experimental criteria: signal-to-noise ratio, signal reproducibility, and representative signal intensities. This procedure was applied for the development of a gene expression Agilent platform for the filamentous fungus Podospora anserina and the selection of a single 60-mer probe for each of the 10,556 P. anserina CDS. Conclusions A reliable gene expression microarray version based on the Agilent 44K platform was developed with four spot replicates of each probe to increase statistical significance of analysis. PMID:20565839

Rational design of small-molecule stabilizers of spermine synthase dimer by virtual screening and free energy-based approach.

PubMed

Zhang, Zhe; Martiny, Virginie; Lagorce, David; Ikeguchi, Yoshihiko; Alexov, Emil; Miteva, Maria A

2014-01-01

Snyder-Robinson Syndrome (SRS) is a rare mental retardation disorder which is caused by the malfunctioning of an enzyme, the spermine synthase (SMS), which functions as a homo-dimer. The malfunctioning of SMS in SRS patients is associated with several identified missense mutations that occur away from the active site. This investigation deals with a particular SRS-causing mutation, the G56S mutation, which was shown computationally and experimentally to destabilize the SMS homo-dimer and thus to abolish SMS enzymatic activity. As a proof-of-concept, we explore the possibility to restore the enzymatic activity of the malfunctioning SMS mutant G56S by stabilizing the dimer through small molecule binding at the mutant homo-dimer interface. For this purpose, we designed an in silico protocol that couples virtual screening and a free binding energy-based approach to identify potential small-molecule binders on the destabilized G56S dimer, with the goal to stabilize it and thus to increase SMS G56S mutant activity. The protocol resulted in extensive list of plausible stabilizers, among which we selected and tested 51 compounds experimentally for their capability to increase SMS G56S mutant enzymatic activity. In silico analysis of the experimentally identified stabilizers suggested five distinctive chemical scaffolds. This investigation suggests that druggable pockets exist in the vicinity of the mutation sites at protein-protein interfaces which can be used to alter the disease-causing effects by small molecule binding. The identified chemical scaffolds are drug-like and can serve as original starting points for development of lead molecules to further rescue the disease-causing effects of the Snyder-Robinson syndrome for which no efficient treatment exists up to now.

Genome-Wide Search Identifies 1.9 Mb from the Polar Bear Y Chromosome for Evolutionary Analyses.

PubMed

Bidon, Tobias; Schreck, Nancy; Hailer, Frank; Nilsson, Maria A; Janke, Axel

2015-05-27

The male-inherited Y chromosome is the major haploid fraction of the mammalian genome, rendering Y-linked sequences an indispensable resource for evolutionary research. However, despite recent large-scale genome sequencing approaches, only a handful of Y chromosome sequences have been characterized to date, mainly in model organisms. Using polar bear (Ursus maritimus) genomes, we compare two different in silico approaches to identify Y-linked sequences: 1) Similarity to known Y-linked genes and 2) difference in the average read depth of autosomal versus sex chromosomal scaffolds. Specifically, we mapped available genomic sequencing short reads from a male and a female polar bear against the reference genome and identify 112 Y-chromosomal scaffolds with a combined length of 1.9 Mb. We verified the in silico findings for the longer polar bear scaffolds by male-specific in vitro amplification, demonstrating the reliability of the average read depth approach. The obtained Y chromosome sequences contain protein-coding sequences, single nucleotide polymorphisms, microsatellites, and transposable elements that are useful for evolutionary studies. A high-resolution phylogeny of the polar bear patriline shows two highly divergent Y chromosome lineages, obtained from analysis of the identified Y scaffolds in 12 previously published male polar bear genomes. Moreover, we find evidence of gene conversion among ZFX and ZFY sequences in the giant panda lineage and in the ancestor of ursine and tremarctine bears. Thus, the identification of Y-linked scaffold sequences from unordered genome sequences yields valuable data to infer phylogenomic and population-genomic patterns in bears. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Genome-Wide Association Study of the Genetic Determinants of Emphysema Distribution.

PubMed

Boueiz, Adel; Lutz, Sharon M; Cho, Michael H; Hersh, Craig P; Bowler, Russell P; Washko, George R; Halper-Stromberg, Eitan; Bakke, Per; Gulsvik, Amund; Laird, Nan M; Beaty, Terri H; Coxson, Harvey O; Crapo, James D; Silverman, Edwin K; Castaldi, Peter J; DeMeo, Dawn L

2017-03-15

Emphysema has considerable variability in the severity and distribution of parenchymal destruction throughout the lungs. Upper lobe-predominant emphysema has emerged as an important predictor of response to lung volume reduction surgery. Yet, aside from alpha-1 antitrypsin deficiency, the genetic determinants of emphysema distribution remain largely unknown. To identify the genetic influences of emphysema distribution in non-alpha-1 antitrypsin-deficient smokers. A total of 11,532 subjects with complete genotype and computed tomography densitometry data in the COPDGene (Genetic Epidemiology of Chronic Obstructive Pulmonary Disease [COPD]; non-Hispanic white and African American), ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints), and GenKOLS (Genetics of Chronic Obstructive Lung Disease) studies were analyzed. Two computed tomography scan emphysema distribution measures (difference between upper-third and lower-third emphysema; ratio of upper-third to lower-third emphysema) were tested for genetic associations in all study subjects. Separate analyses in each study population were followed by a fixed effect metaanalysis. Single-nucleotide polymorphism-, gene-, and pathway-based approaches were used. In silico functional evaluation was also performed. We identified five loci associated with emphysema distribution at genome-wide significance. These loci included two previously reported associations with COPD susceptibility (4q31 near HHIP and 15q25 near CHRNA5) and three new associations near SOWAHB, TRAPPC9, and KIAA1462. Gene set analysis and in silico functional evaluation revealed pathways and cell types that may potentially contribute to the pathogenesis of emphysema distribution. This multicohort genome-wide association study identified new genomic loci associated with differential emphysematous destruction throughout the lungs. These findings may point to new biologic pathways on which to expand diagnostic and therapeutic approaches in chronic obstructive pulmonary disease. Clinical trial registered with www.clinicaltrials.gov (NCT 00608764).

Evaluation of Bioinformatic Programmes for the Analysis of Variants within Splice Site Consensus Regions

PubMed Central

Tang, Rongying; Prosser, Debra O.; Love, Donald R.

2016-01-01

The increasing diagnostic use of gene sequencing has led to an expanding dataset of novel variants that lie within consensus splice junctions. The challenge for diagnostic laboratories is the evaluation of these variants in order to determine if they affect splicing or are merely benign. A common evaluation strategy is to use in silico analysis, and it is here that a number of programmes are available online; however, currently, there are no consensus guidelines on the selection of programmes or protocols to interpret the prediction results. Using a collection of 222 pathogenic mutations and 50 benign polymorphisms, we evaluated the sensitivity and specificity of four in silico programmes in predicting the effect of each variant on splicing. The programmes comprised Human Splice Finder (HSF), Max Entropy Scan (MES), NNSplice, and ASSP. The MES and ASSP programmes gave the highest performance based on Receiver Operator Curve analysis, with an optimal cut-off of score reduction of 10%. The study also showed that the sensitivity of prediction is affected by the level of conservation of individual positions, with in silico predictions for variants at positions −4 and +7 within consensus splice sites being largely uninformative. PMID:27313609

In silico simulations of experimental protocols for cardiac modeling.

PubMed

Carro, Jesus; Rodriguez, Jose Felix; Pueyo, Esther

2014-01-01

A mathematical model of the AP involves the sum of different transmembrane ionic currents and the balance of intracellular ionic concentrations. To each ionic current corresponds an equation involving several effects. There are a number of model parameters that must be identified using specific experimental protocols in which the effects are considered as independent. However, when the model complexity grows, the interaction between effects becomes increasingly important. Therefore, model parameters identified considering the different effects as independent might be misleading. In this work, a novel methodology consisting in performing in silico simulations of the experimental protocol and then comparing experimental and simulated outcomes is proposed for parameter model identification and validation. The potential of the methodology is demonstrated by validating voltage-dependent L-type calcium current (ICaL) inactivation in recently proposed human ventricular AP models with different formulations. Our results show large differences between ICaL inactivation as calculated from the model equation and ICaL inactivation from the in silico simulations due to the interaction between effects and/or to the experimental protocol. Our results suggest that, when proposing any new model formulation, consistency between such formulation and the corresponding experimental data that is aimed at being reproduced needs to be first verified considering all involved factors.

Differentiation of Toxocara canis and Toxocara cati based on PCR-RFLP analyses of rDNA-ITS and mitochondrial cox1 and nad1 regions.

PubMed

Mikaeili, Fattaneh; Mathis, Alexander; Deplazes, Peter; Mirhendi, Hossein; Barazesh, Afshin; Ebrahimi, Sepideh; Kia, Eshrat Beigom

2017-09-26

The definitive genetic identification of Toxocara species is currently based on PCR/sequencing. The objectives of the present study were to design and conduct an in silico polymerase chain reaction-restriction fragment length polymorphism method for identification of Toxocara species. In silico analyses using the DNASIS and NEBcutter softwares were performed with rDNA internal transcribed spacers, and mitochondrial cox1 and nad1 sequences obtained in our previous studies along with relevant sequences deposited in GenBank. Consequently, RFLP profiles were designed and all isolates of T. canis and T. cati collected from dogs and cats in different geographical areas of Iran were investigated with the RFLP method using some of the identified suitable enzymes. The findings of in silico analyses predicted that on the cox1 gene only the MboII enzyme is appropriate for PCR-RFLP to reliably distinguish the two species. No suitable enzyme for PCR-RFLP on the nad1 gene was identified that yields the same pattern for all isolates of a species. DNASIS software showed that there are 241 suitable restriction enzymes for the differentiation of T. canis from T. cati based on ITS sequences. RsaI, MvaI and SalI enzymes were selected to evaluate the reliability of the in silico PCR-RFLP. The sizes of restriction fragments obtained by PCR-RFLP of all samples consistently matched the expected RFLP patterns. The ITS sequences are usually conserved and the PCR-RFLP approach targeting the ITS sequence is recommended for the molecular differentiation of Toxocara species and can provide a reliable tool for identification purposes particularly at the larval and egg stages.

Biological interaction of newly synthesized astaxanthin-s-allyl cysteine biconjugate with Saccharomyces cerevisiae and mammalian α-glucosidase: In vitro kinetics and in silico docking analysis.

PubMed

Penislusshiyan, Sakayanathan; Chitra, Loganathan; Ancy, Iruthayaraj; Premkumar, Periyasamy; Kumaradhas, Poomani; Viswanathamurthi, Periasamy; Palvannan, Thayumanavan

2018-06-06

In humans, alpha-glucosidase activity is present in sucrase-isomaltase (SI) and maltase-glucoamylase (MGAM). α-glucosidase is involved in the hydrolyses of disaccharide into monosaccharides and results in hyperglycemia. Subsequently chronic hyperglycemia induces oxidative stress and ultimately leads to the secondary complications of diabetes. Hence, identifying compounds with dual beneficial activity such as efficient antioxidant and α-glucosidase inhibition property has attracted the attention in recent years. Keeping these views, in the present study astaxanthin (AST; a natural antioxidant present in marine microalgae) was biconjugated with allyl sulfur amino acid such as s-allyl cysteine (SAC). The synthesized AST-SAC (with molecular weight of 883.28) was characterized using UV-visible spectrophotometer, ESI-MS, and NMR analysis. AST-SAC showed potent antioxidant property in vitro. AST-SAC inhibited Saccharomyces cerevisiae α-glucosidase (IC 50  = 3.98 μM; Ki = 1 μM) and mammalian α-glucosidase [rat intestinal maltase (IC 50  = 6.4 μM; Ki = 1.3 μM) and sucrase (IC 50  = 1.6 μM; Ki = 0.18 μM)] enzyme activity in a dose-dependent manner. Kinetic analysis revealed that AST-SAC inhibited all the α-glucosidases in a competitive mode. In silico analysis determined the interaction of AST-SAC with the amino acids present in the active site of S. cerevisiae and human (MGAM and SI) α-glucosidases. Copyright © 2017. Published by Elsevier B.V.

Integration of Molecular Networking and In-Silico MS/MS Fragmentation for Natural Products Dereplication.

PubMed

Allard, Pierre-Marie; Péresse, Tiphaine; Bisson, Jonathan; Gindro, Katia; Marcourt, Laurence; Pham, Van Cuong; Roussi, Fanny; Litaudon, Marc; Wolfender, Jean-Luc

2016-03-15

Dereplication represents a key step for rapidly identifying known secondary metabolites in complex biological matrices. In this context, liquid-chromatography coupled to high resolution mass spectrometry (LC-HRMS) is increasingly used and, via untargeted data-dependent MS/MS experiments, massive amounts of detailed information on the chemical composition of crude extracts can be generated. An efficient exploitation of such data sets requires automated data treatment and access to dedicated fragmentation databases. Various novel bioinformatics approaches such as molecular networking (MN) and in-silico fragmentation tools have emerged recently and provide new perspective for early metabolite identification in natural products (NPs) research. Here we propose an innovative dereplication strategy based on the combination of MN with an extensive in-silico MS/MS fragmentation database of NPs. Using two case studies, we demonstrate that this combined approach offers a powerful tool to navigate through the chemistry of complex NPs extracts, dereplicate metabolites, and annotate analogues of database entries.

Advancing Peptide-Based Biorecognition Elements for Biosensors Using in-Silico Evolution.

PubMed

Xiao, Xingqing; Kuang, Zhifeng; Slocik, Joseph M; Tadepalli, Sirimuvva; Brothers, Michael; Kim, Steve; Mirau, Peter A; Butkus, Claire; Farmer, Barry L; Singamaneni, Srikanth; Hall, Carol K; Naik, Rajesh R

2018-05-25

Sensors for human health and performance monitoring require biological recognition elements (BREs) at device interfaces for the detection of key molecular biomarkers that are measurable biological state indicators. BREs, including peptides, antibodies, and nucleic acids, bind to biomarkers in the vicinity of the sensor surface to create a signal proportional to the biomarker concentration. The discovery of BREs with the required sensitivity and selectivity to bind biomarkers at low concentrations remains a fundamental challenge. In this study, we describe an in-silico approach to evolve higher sensitivity peptide-based BREs for the detection of cardiac event marker protein troponin I (cTnI) from a previously identified BRE as the parental affinity peptide. The P2 affinity peptide, evolved using our in-silico method, was found to have ∼16-fold higher affinity compared to the parent BRE and ∼10 fM (0.23 pg/mL) limit of detection. The approach described here can be applied towards designing BREs for other biomarkers for human health monitoring.

GeneNetWeaver: in silico benchmark generation and performance profiling of network inference methods.

PubMed

Schaffter, Thomas; Marbach, Daniel; Floreano, Dario

2011-08-15

Over the last decade, numerous methods have been developed for inference of regulatory networks from gene expression data. However, accurate and systematic evaluation of these methods is hampered by the difficulty of constructing adequate benchmarks and the lack of tools for a differentiated analysis of network predictions on such benchmarks. Here, we describe a novel and comprehensive method for in silico benchmark generation and performance profiling of network inference methods available to the community as an open-source software called GeneNetWeaver (GNW). In addition to the generation of detailed dynamical models of gene regulatory networks to be used as benchmarks, GNW provides a network motif analysis that reveals systematic prediction errors, thereby indicating potential ways of improving inference methods. The accuracy of network inference methods is evaluated using standard metrics such as precision-recall and receiver operating characteristic curves. We show how GNW can be used to assess the performance and identify the strengths and weaknesses of six inference methods. Furthermore, we used GNW to provide the international Dialogue for Reverse Engineering Assessments and Methods (DREAM) competition with three network inference challenges (DREAM3, DREAM4 and DREAM5). GNW is available at http://gnw.sourceforge.net along with its Java source code, user manual and supporting data. Supplementary data are available at Bioinformatics online. dario.floreano@epfl.ch.

TLR and IMD signaling pathways from Caligus rogercresseyi (Crustacea: Copepoda): in silico gene expression and SNPs discovery.

PubMed

Valenzuela-Muñoz, V; Gallardo-Escárate, C

2014-02-01

The Toll and IMD signaling pathways represent one of the first lines of innate immune defense in invertebrates like Drosophila. However, for crustaceans like Caligus rogercresseyi, there is very little genomic information and, consequently, understanding of immune mechanisms. Massive sequencing data obtained for three developmental stages of C. rogercresseyi were used to evaluate in silico the expression patterns and presence of SNPs variants in genes involved in the Toll and IMD pathways. Through RNA-seq analysis, which used 20 contigs corresponding to relevant genes of the Toll and IMD pathways, an overexpression of genes linked to the Toll pathway, such as toll3 and Dorsal, were observed in the copepod stage. For the chalimus and adult stages, overexpression of genes in both pathways, such as Akirin and Tollip and IAP and Toll9, respectively, were observed. On the other hand, PCA statistical analysis inferred that in the chalimus and adult stages, the immune response mechanism was more developed, as evidenced by a relation between these two stages and the genes of both pathways. Moreover, 136 SNPs were identified for 20 contigs in genes of the Toll and IMD pathways. This study provides transcriptomic information about the immune response mechanisms of Caligus, thus providing a foundation for the development of new control strategies through blocking the innate immune response. Copyright © 2013 Elsevier Ltd. All rights reserved.

Association of endothelial nitric oxide synthase gene variants (-786 T>C, intron 4 b/a VNTR and 894 G>T) with idiopathic recurrent pregnancy loss: A case-control study with haplotype and in silico analysis.

PubMed

Azani, Alireza; Hosseinzadeh, Asghar; Azadkhah, Roya; Zonouzi, Ali Akbar Poursadegh; Zonouzi, Ahmad Poursadegh; Aftabi, Younes; Khani, Hourieh; Heidary, Leida; Danaii, Shahla; Bargahi, Nasrin; Pouladi, Nasser; Hosseini, Sayed Mostafa

2017-08-01

Many lines of evidence suggest that reduced production of nitric oxide (NO) due to single nucleotide polymorphisms in endothelial nitric oxide synthase (eNOS) gene may affect the implantation and maintenance of pregnancy. Accordingly, our objective was to investigate whether the eNOS polymorphisms (-786 T>C, intron 4 b/a VNTR and 894 G>T) and haplotypes may be associated with increased susceptibility to recurrent pregnancy loss (RPL). A total of 130 women with a history of two or more unexplained consecutive first trimester miscarriages and 110 ethnically matched women with at least two normal pregnancies and no history of pregnancy loss were included in the study as cases and controls, respectively. To identify the genotypes, we used polymerase chain reaction (PCR) and PCR-restriction fragment length polymorphism (PCR-RFLP) methods In addition, an in silico analysis was conducted to predict the possible effects of the eNOS 894 G>T polymorphism on the structure and function of eNOS mRNA and protein using prediction servers. Our findings revealed that the prevalence of eNOS -786 T>C polymorphism, eNOS -786C allele and TC+CC genotype in cases were significantly higher than those in healthy controls (p<0.05). Also, the combination genotypes -786TT/4b4a and -786TT/894GG were significantly associated with reduced risk of RPL. We also found that the C-4a-G haplotype of the eNOS gene studied polymorphisms was significantly associated with a predisposition to RPL (odds ratio, 3.219; 95% confidence interval, 1.649-6.282; p=0.0003). The in silico analysis showed that the eNOS 894 G>T polymorphism couldn't affects eNOS mRNA and protein significantly. Our findings provide evidence to support the hypothesis that eNOS -786 T>C polymorphism and the -786C-4a-894G haplotype are associated with the high risk of RPL. Copyright © 2017 Elsevier B.V. All rights reserved.

Human induced pluripotent stem cell‐derived versus adult cardiomyocytes: an in silico electrophysiological study on effects of ionic current block

PubMed Central

Paci, M; Hyttinen, J; Rodriguez, B

2015-01-01

Background and Purpose Two new technologies are likely to revolutionize cardiac safety and drug development: in vitro experiments on human‐induced pluripotent stem cell‐derived cardiomyocytes (hiPSC‐CMs) and in silico human adult ventricular cardiomyocyte (hAdultV‐CM) models. Their combination was recently proposed as a potential replacement for the present hERG‐based QT study for pharmacological safety assessments. Here, we systematically compared in silico the effects of selective ionic current block on hiPSC‐CM and hAdultV‐CM action potentials (APs), to identify similarities/differences and to illustrate the potential of computational models as supportive tools for evaluating new in vitro technologies. Experimental Approach In silico AP models of ventricular‐like and atrial‐like hiPSC‐CMs and hAdultV‐CM were used to simulate the main effects of four degrees of block of the main cardiac transmembrane currents. Key Results Qualitatively, hiPSC‐CM and hAdultV‐CM APs showed similar responses to current block, consistent with results from experiments. However, quantitatively, hiPSC‐CMs were more sensitive to block of (i) L‐type Ca2+ currents due to the overexpression of the Na+/Ca2+ exchanger (leading to shorter APs) and (ii) the inward rectifier K+ current due to reduced repolarization reserve (inducing diastolic potential depolarization and repolarization failure). Conclusions and Implications In silico hiPSC‐CMs and hAdultV‐CMs exhibit a similar response to selective current blocks. However, overall hiPSC‐CMs show greater sensitivity to block, which may facilitate in vitro identification of drug‐induced effects. Extrapolation of drug effects from hiPSC‐CM to hAdultV‐CM and pro‐arrhythmic risk assessment can be facilitated by in silico predictions using biophysically‐based computational models. PMID:26276951

Mutations in the LHX2 gene are not a frequent cause of micro/anophthalmia

PubMed Central

Desmaison, Annaïck; Vigouroux, Adeline; Rieubland, Claudine; Peres, Christine; Calvas, Patrick

2010-01-01

Purpose Microphthalmia and anophthalmia are at the severe end of the spectrum of abnormalities in ocular development. A few genes (orthodenticle homeobox 2 [OTX2], retina and anterior neural fold homeobox [RAX], SRY-box 2 [SOX2], CEH10 homeodomain-containing homolog [CHX10], and growth differentiation factor 6 [GDF6]) have been implicated mainly in isolated micro/anophthalmia but causative mutations of these genes explain less than a quarter of these developmental defects. The essential role of the LIM homeobox 2 (LHX2) transcription factor in early eye development has recently been documented. We postulated that mutations in this gene could lead to micro/anophthalmia, and thus performed molecular screening of its sequence in patients having micro/anophthalmia. Methods Seventy patients having non-syndromic forms of colobomatous microphthalmia (n=25), isolated microphthalmia (n=18), or anophthalmia (n=17), and syndromic forms of micro/anophthalmia (n=10) were included in this study after negative molecular screening for OTX2, RAX, SOX2, and CHX10 mutations. Mutation screening of LHX2 was performed by direct sequencing of the coding sequences and intron/exon boundaries. Results Two heterozygous variants of unknown significance (c.128C>G [p.Pro43Arg]; c.776C>A [p.Pro259Gln]) were identified in LHX2 among the 70 patients. These variations were not identified in a panel of 100 control patients of mixed origins. The variation c.776C>A (p.Pro259Gln) was considered as non pathogenic by in silico analysis, while the variation c.128C>G (p.Pro43Arg) considered as deleterious by in silico analysis and was inherited from the asymptomatic father. Conclusions Mutations in LHX2 do not represent a frequent cause of micro/anophthalmia. PMID:21203406

Mutations in the LHX2 gene are not a frequent cause of micro/anophthalmia.

PubMed

Desmaison, Annaïck; Vigouroux, Adeline; Rieubland, Claudine; Peres, Christine; Calvas, Patrick; Chassaing, Nicolas

2010-12-18

Microphthalmia and anophthalmia are at the severe end of the spectrum of abnormalities in ocular development. A few genes (orthodenticle homeobox 2 [OTX2], retina and anterior neural fold homeobox [RAX], SRY-box 2 [SOX2], CEH10 homeodomain-containing homolog [CHX10], and growth differentiation factor 6 [GDF6]) have been implicated mainly in isolated micro/anophthalmia but causative mutations of these genes explain less than a quarter of these developmental defects. The essential role of the LIM homeobox 2 (LHX2) transcription factor in early eye development has recently been documented. We postulated that mutations in this gene could lead to micro/anophthalmia, and thus performed molecular screening of its sequence in patients having micro/anophthalmia. Seventy patients having non-syndromic forms of colobomatous microphthalmia (n=25), isolated microphthalmia (n=18), or anophthalmia (n=17), and syndromic forms of micro/anophthalmia (n=10) were included in this study after negative molecular screening for OTX2, RAX, SOX2, and CHX10 mutations. Mutation screening of LHX2 was performed by direct sequencing of the coding sequences and intron/exon boundaries. Two heterozygous variants of unknown significance (c.128C>G [p.Pro43Arg]; c.776C>A [p.Pro259Gln]) were identified in LHX2 among the 70 patients. These variations were not identified in a panel of 100 control patients of mixed origins. The variation c.776C>A (p.Pro259Gln) was considered as non pathogenic by in silico analysis, while the variation c.128C>G (p.Pro43Arg) considered as deleterious by in silico analysis and was inherited from the asymptomatic father. Mutations in LHX2 do not represent a frequent cause of micro/anophthalmia.

Identification of Brucella melitensis Rev.1 vaccine-strain genetic markers: Towards understanding the molecular mechanism behind virulence attenuation.

PubMed

Issa, Mohammad Nouh; Ashhab, Yaqoub

2016-09-22

Brucella melitensis Rev.1 is an avirulent strain that is widely used as a live vaccine to control brucellosis in small ruminants. Although an assembled draft version of Rev.1 genome has been available since 2009, this genome has not been investigated to characterize this important vaccine. In the present work, we used the draft genome of Rev.1 to perform a thorough genomic comparison and sequence analysis to identify and characterize the panel of its unique genetic markers. The draft genome of Rev.1 was compared with genome sequences of 36 different Brucella melitensis strains from the Brucella project of the Broad Institute of MIT and Harvard. The comparative analyses revealed 32 genetic alterations (30 SNPs, 1 single-bp insertion and 1 single-bp deletion) that are exclusively present in the Rev.1 genome. In silico analyses showed that 9 out of the 17 non-synonymous mutations are deleterious. Three ABC transporters are among the disrupted genes that can be linked to virulence attenuation. Out of the 32 mutations, 11 Rev.1 specific markers were selected to test their potential to discriminate Rev.1 using a bi-directional allele-specific PCR assay. Six markers were able to distinguish between Rev.1 and a set of control strains. We succeeded in identifying a panel of 32 genome-specific markers of the B. melitensis Rev.1 vaccine strain. Extensive in silico analysis showed that a considerable number of these mutations could severely affect the function of the associated genes. In addition, some of the discovered markers were able to discriminate Rev.1 strain from a group of control strains using practical PCR tests that can be applied in resource-limited settings. Copyright © 2016 Elsevier Ltd. All rights reserved.

Antimicrobial Peptides of Meat Origin - An In silico and In vitro Analysis.

PubMed

Keska, Paulina; Stadnik, Joanna

2017-01-01

The aim of this study was to evaluate the antimicrobial activity of meat protein-derived peptides against selected Gram-positive and Gram-negative bacteria. The in silico and in vitro approach was combined to determine the potency of antimicrobial peptides derived from pig (Sus scrofa) and cow (Bos taurus) proteins. The in silico studies consisted of an analysis of the amino acid composition of peptides obtained from the CAMPR database, their molecular weight and other physicochemical properties (isoelectric point, molar extinction coefficient, instability index, aliphatic index, hydropathy index and net charge). The degree of similarity was estimated between the antimicrobial peptide sequences derived from the slaughtered animals and the main meat proteins. Antimicrobial activity of peptides isolated from dry-cured meat products was analysed (in vitro) against two strains of pathogenic bacteria using the disc diffusion method. There was no evidence of growthinhibitory properties of peptides isolated from dry-cured meat products against Escherichia coli K12 ATCC 10798 and Staphylococcus aureus ATCC 25923. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Enhanced hexose fermentation by Saccharomyces cerevisiae through integration of stoichiometric modeling and genetic screening.

PubMed

Quarterman, Josh; Kim, Soo Rin; Kim, Pan-Jun; Jin, Yong-Su

2015-01-20

In order to determine beneficial gene deletions for ethanol production by the yeast Saccharomyces cerevisiae, we performed an in silico gene deletion experiment based on a genome-scale metabolic model. Genes coding for two oxidative phosphorylation reactions (cytochrome c oxidase and ubiquinol cytochrome c reductase) were identified by the model-based simulation as potential deletion targets for enhancing ethanol production and maintaining acceptable overall growth rate in oxygen-limited conditions. Since the two target enzymes are composed of multiple subunits, we conducted a genetic screening study to evaluate the in silico results and compare the effect of deleting various portions of the respiratory enzyme complexes. Over two-thirds of the knockout mutants identified by the in silico study did exhibit experimental behavior in qualitative agreement with model predictions, but the exceptions illustrate the limitation of using a purely stoichiometric model-based approach. Furthermore, there was a substantial quantitative variation in phenotype among the various respiration-deficient mutants that were screened in this study, and three genes encoding respiratory enzyme subunits were identified as the best knockout targets for improving hexose fermentation in microaerobic conditions. Specifically, deletion of either COX9 or QCR9 resulted in higher ethanol production rates than the parental strain by 37% and 27%, respectively, with slight growth disadvantages. Also, deletion of QCR6 led to improved ethanol production rate by 24% with no growth disadvantage. The beneficial effects of these gene deletions were consistently demonstrated in different strain backgrounds and with four common hexoses. The combination of stoichiometric modeling and genetic screening using a systematic knockout collection was useful for narrowing a large set of gene targets and identifying targets of interest. Copyright © 2014 Elsevier B.V. All rights reserved.

In silico prediction of Tetrahymena pyriformis toxicity for diverse industrial chemicals with substructure pattern recognition and machine learning methods.

PubMed

Cheng, Feixiong; Shen, Jie; Yu, Yue; Li, Weihua; Liu, Guixia; Lee, Philip W; Tang, Yun

2011-03-01

There is an increasing need for the rapid safety assessment of chemicals by both industries and regulatory agencies throughout the world. In silico techniques are practical alternatives in the environmental hazard assessment. It is especially true to address the persistence, bioaccumulative and toxicity potentials of organic chemicals. Tetrahymena pyriformis toxicity is often used as a toxic endpoint. In this study, 1571 diverse unique chemicals were collected from the literature and composed of the largest diverse data set for T. pyriformis toxicity. Classification predictive models of T. pyriformis toxicity were developed by substructure pattern recognition and different machine learning methods, including support vector machine (SVM), C4.5 decision tree, k-nearest neighbors and random forest. The results of a 5-fold cross-validation showed that the SVM method performed better than other algorithms. The overall predictive accuracies of the SVM classification model with radial basis functions kernel was 92.2% for the 5-fold cross-validation and 92.6% for the external validation set, respectively. Furthermore, several representative substructure patterns for characterizing T. pyriformis toxicity were also identified via the information gain analysis methods. Copyright © 2010 Elsevier Ltd. All rights reserved.

A practical guidance for Cramer class determination.

PubMed

Roberts, David W; Aptula, Aynur; Schultz, Terry W; Shen, Jie; Api, Anne Marie; Bhatia, Sneha; Kromidas, Lambros

2015-12-01

Expanded use of the Threshold of Toxicological Concern (TTC) methodology has brought into discussion the intent of the original questions used in the Cramer scheme or Cramer decision tree. We have analysed, both manually and by Toxtree software, a large dataset of fragrance ingredients and identified several issues with the original Cramer questions. Some relate to definitions and wording of questions; others relate to in silico interpretation of the questions. We have endeavoured to address all of these inconsistencies and misinterpretations without changing the basic structure and principles of the original decision tree. Based on the analysis of a large data set of over 2500 fragrance ingredients, we found that most of the 33 questions in the original Cramer scheme are straightforward. Through repeated examination each of the 33 questions, we found 14 where the logic underlying the development of the rule is unclear. These questions are well served by minor wording changes and/or further explanation designed to capture what we perceive to be the intent of the original decision tree. The findings reported here could be used as a guidance for conducting Cramer classification and provide advices for the improvement of the in silico tools. Copyright © 2015 Elsevier Inc. All rights reserved.

A Petri net model of granulomatous inflammation: implications for IL-10 mediated control of Leishmania donovani infection.

PubMed

Albergante, Luca; Timmis, Jon; Beattie, Lynette; Kaye, Paul M

2013-01-01

Experimental visceral leishmaniasis, caused by infection of mice with the protozoan parasite Leishmania donovani, is characterized by focal accumulation of inflammatory cells in the liver, forming discrete "granulomas" within which the parasite is eventually eliminated. To shed new light on fundamental aspects of granuloma formation and function, we have developed an in silico Petri net model that simulates hepatic granuloma development throughout the course of infection. The model was extensively validated by comparison with data derived from experimental studies in mice, and the model robustness was assessed by a sensitivity analysis. The model recapitulated the progression of disease as seen during experimental infection and also faithfully predicted many of the changes in cellular composition seen within granulomas over time. By conducting in silico experiments, we have identified a previously unappreciated level of inter-granuloma diversity in terms of the development of anti-leishmanial activity. Furthermore, by simulating the impact of IL-10 gene deficiency in a variety of lymphocyte and myeloid cell populations, our data suggest a dominant local regulatory role for IL-10 produced by infected Kupffer cells at the core of the granuloma.

A Petri Net Model of Granulomatous Inflammation: Implications for IL-10 Mediated Control of Leishmania donovani Infection

PubMed Central

Albergante, Luca; Timmis, Jon; Beattie, Lynette; Kaye, Paul M.

2013-01-01

Experimental visceral leishmaniasis, caused by infection of mice with the protozoan parasite Leishmania donovani, is characterized by focal accumulation of inflammatory cells in the liver, forming discrete “granulomas” within which the parasite is eventually eliminated. To shed new light on fundamental aspects of granuloma formation and function, we have developed an in silico Petri net model that simulates hepatic granuloma development throughout the course of infection. The model was extensively validated by comparison with data derived from experimental studies in mice, and the model robustness was assessed by a sensitivity analysis. The model recapitulated the progression of disease as seen during experimental infection and also faithfully predicted many of the changes in cellular composition seen within granulomas over time. By conducting in silico experiments, we have identified a previously unappreciated level of inter-granuloma diversity in terms of the development of anti-leishmanial activity. Furthermore, by simulating the impact of IL-10 gene deficiency in a variety of lymphocyte and myeloid cell populations, our data suggest a dominant local regulatory role for IL-10 produced by infected Kupffer cells at the core of the granuloma. PMID:24363630

Typing clinical and animal environment Aspergillus fumigatus gliotoxin producer strains isolated from Brazil by PCR-RFLP markers.

PubMed

Soleiro, C A; Pena, G A; Cavaglieri, L R; Coelho, I; Keller, L M; Dalcero, A M; Rosa, C A R

2013-12-01

Aspergillus fumigatus, a well-known human and animal pathogen causing aspergillosis, has been historically identified by morphological and microscopic features. However, recent studies have shown that species identification on the basis of morphology alone is problematic. The aim of this work was to confirm the taxonomic state at specie level of a set of clinical (human and animal) and animal environment A. fumigatus strains identified by morphological criteria applying a PCR-RFLP assay by an in silico and in situ analysis with three restriction enzymes. The A. fumigatus gliotoxin-producing ability was also determined. Previous to the in situ PCR-RFLP analysis, an in silico assay with BccI, MspI and Sau3AI restriction enzymes was carried out. After that, these enzymes were used for in situ assay. All A. fumigatus strains isolated from corn silage, human aspergillosis and bovine mastitis and high per cent of the strains isolated from cereals, animal feedstuff and sorghum silage were able to produce high gliotoxin levels. Also, all these strains identified by morphological criteria as A. fumigatus, regardless of its isolation source, had band patterns according to A. fumigatus sensu stricto by PCR-RFLP markers. Aspergillus fumigatus is a well-known human and animal pathogen causing aspergillosis. In this study, clinical (human and animal) and animal environment strains were able to produce high gliotoxin levels and had band profiles according to A. fumigatus sensu stricto by PCR-RFLP markers. The results obtained here suggest that strains involved in human and animal aspergillosis could come from the animal environment in which A. fumigatus is frequently found. Its presence in animal environments could affect animal health and productivity; in addition, there are risks of contamination for rural workers during handling and storage of animal feedstuffs. © 2013 The Society for Applied Microbiology.

Genome-wide association study using a high-density SNP-array and case-control design identifies a novel essential hypertension susceptibility locus in the promoter region of eNOS

PubMed Central

Salvi, Erika; Kutalik, Zoltán; Glorioso, Nicola; Benaglio, Paola; Frau, Francesca; Kuznetsova, Tatiana; Arima, Hisatomi; Hoggart, Clive; Tichet, Jean; Nikitin, Yury P.; Conti, Costanza; Seidlerova, Jitka; Tikhonoff, Valérie; Stolarz-Skrzypek, Katarzyna; Johnson, Toby; Devos, Nabila; Zagato, Laura; Guarrera, Simonetta; Zaninello, Roberta; Calabria, Andrea; Stancanelli, Benedetta; Troffa, Chiara; Thijs, Lutgarde; Rizzi, Federica; Simonova, Galina; Lupoli, Sara; Argiolas, Giuseppe; Braga, Daniele; D’Alessio, Maria C.; Ortu, Maria F.; Ricceri, Fulvio; Mercurio, Maurizio; Descombes, Patrick; Marconi, Maurizio; Chalmers, John; Harrap, Stephen; Filipovsky, Jan; Bochud, Murielle; Iacoviello, Licia; Ellis, Justine; Stanton, Alice V.; Laan, Maris; Padmanabhan, Sandosh; Dominiczak, Anna F.; Samani, Nilesh J.; Melander, Olle; Jeunemaitre, Xavier; Manunta, Paolo; Shabo, Amnon; Vineis, Paolo; Cappuccio, Francesco P.; Caulfield, Mark J.; Matullo, Giuseppe; Rivolta, Carlo; Munroe, Patricia B.; Barlassina, Cristina; Staessen, Jan A; Beckmann, Jacques S.; Cusi, Daniele

2012-01-01

Essential hypertension is a multi-factorial disorder and is the main risk factor for renal and cardiovascular complications. The research on the genetics of hypertension has been frustrated by the small predictive value of the discovered genetic variants. The HYPERGENES Project investigated associations between genetic variants and essential hypertension pursuing a two-stage study by recruiting cases and controls from extensively characterized cohorts recruited over many years in different European regions. The discovery phase consisted of 1,865 cases and 1,750 controls genotyped with 1M Illumina array. Best hits were followed up in a validation panel of 1,385 cases and 1,246 controls that were genotyped with a custom array of 14,055 markers. We identified a new hypertension susceptibility locus (rs3918226) in the promoter region of the endothelial nitric oxide synthase (eNOS) gene (odds ratio 1.54; 95% CI 1.37-1.73; combined p=2.58·10−13). A meta-analysis, using other in-silico/de novo genotyping data for a total of 21714 subjects, resulted in an overall odds ratio of 1.34 (95% CI 1.25-1.44, p=1.032·10−14). The quantitative analysis on a population-based sample revealed an effect size of 1.91 (95% CI 0.16-3.66) for systolic and 1.40 (95% CI 0.25-2.55) for diastolic blood pressure. We identified in-silico a potential binding site for ETS transcription-factors directly next to rs3918226, suggesting a potential modulation of eNOS expression. Biological evidence links eNOS with hypertension, as it is a critical mediator of cardiovascular homeostasis and blood pressure control via vascular tone regulation. This finding supports the hypothesis that there may be a causal genetic variation at this locus. PMID:22184326

Analysis and design of a genetic circuit for dynamic metabolic engineering.

PubMed

Anesiadis, Nikolaos; Kobayashi, Hideki; Cluett, William R; Mahadevan, Radhakrishnan

2013-08-16

Recent advances in synthetic biology have equipped us with new tools for bioprocess optimization at the genetic level. Previously, we have presented an integrated in silico design for the dynamic control of gene expression based on a density-sensing unit and a genetic toggle switch. In the present paper, analysis of a serine-producing Escherichia coli mutant shows that an instantaneous ON-OFF switch leads to a maximum theoretical productivity improvement of 29.6% compared to the mutant. To further the design, global sensitivity analysis is applied here to a mathematical model of serine production in E. coli coupled with a genetic circuit. The model of the quorum sensing and the toggle switch involves 13 parameters of which 3 are identified as having a significant effect on serine concentration. Simulations conducted in this reduced parameter space further identified the optimal ranges for these 3 key parameters to achieve productivity values close to the maximum theoretical values. This analysis can now be used to guide the experimental implementation of a dynamic metabolic engineering strategy and reduce the time required to design the genetic circuit components.

Meta-analysis identifies common variants associated with body mass index in East Asians

PubMed Central

Wen, Wanqing; Cho, Yoon Shin; Zheng, Wei; Dorajoo, Rajkumar; Kato, Norihiro; Qi, Lu; Chen, Chien-Hsiun; Delahanty, Ryan J.; Okada, Yukinori; Tabara, Yasuharu; Gu, Dongfeng; Zhu, Dingliang; Haiman, Christopher A.; Mo, Zengnan; Gao, Yu-Tang; Saw, Seang Mei; Go, Min Jin; Takeuchi, Fumihiko; Chang, Li-Ching; Kokubo, Yoshihiro; Liang, Jun; Hao, Mei; Marchand, Loic Le; Zhang, Yi; Hu, Yanling; Wong, Tien Yin; Long, Jirong; Han, Bok-Ghee; Kubo, Michiaki; Yamamoto, Ken; Su, Mei-Hsin; Miki, Tetsuro; Henderson, Brian E.; Song, Huaidong; Tan, Aihua; He, Jiang; Ng, Daniel P.-K.; Cai, Qiuyin; Tsunoda, Tatsuhiko; Tsai, Fuu-Jen; Iwai, Naoharu; Chen, Gary K.; Shi, Jiajun; Xu, Jianfeng; Sim, Xueling; Xiang, Yong-Bing; Maeda, Shiro; Ong, Rick T.H.; Li, Chun; Nakamura, Yusuke; Aung, Tin; Kamatani, Naoyuki; Liu, Jian Jun; Lu, Wei; Yokota, Mitsuhiro; Seielstad, Mark; Fann, Cathy S.J.; Wu, Jer-Yuarn; Lee, Jong-Young; Hu, Frank B.; Tanaka, Toshihiro; Tai, E. Shyong; Shu, Xiao Ou

2012-01-01

Multiple genetic loci associated with obesity or body mass index (BMI) have been identified through genome-wide association studies conducted predominantly in populations of European ancestry. We conducted a meta-analysis of associations between BMI and approximately 2.4 million SNPs in 27,715 East Asians, followed by in silico and de novo replication in 37,691 and 17,642 additional East Asians, respectively. We identified ten BMI-associated loci at the genome-wide significance level (P<5.0×10−8), including seven previously identified loci (FTO, SEC16B, MC4R, GIPR/QPCTL, ADCY3/RBJ, BDNF, and MAP2K5) and three novel loci in or near the CDKAL1,PCSK1, and GP2 genes. Three additional loci nearly reached the genome-wide significance threshold, including two previously identified loci in the GNPDA2 and TFAP2B genes and a new locus near PAX6, which all had P<5.0×10−7. Findings from this study may shed light on new pathways involved in obesity and demonstrate the value of conducting genetic studies in non-European populations. PMID:22344219

Peroxisomal lactate dehydrogenase is generated by translational readthrough in mammals

PubMed Central

Schueren, Fabian; Lingner, Thomas; George, Rosemol; Hofhuis, Julia; Dickel, Corinna; Gärtner, Jutta; Thoms, Sven

2014-01-01

Translational readthrough gives rise to low abundance proteins with C-terminal extensions beyond the stop codon. To identify functional translational readthrough, we estimated the readthrough propensity (RTP) of all stop codon contexts of the human genome by a new regression model in silico, identified a nucleotide consensus motif for high RTP by using this model, and analyzed all readthrough extensions in silico with a new predictor for peroxisomal targeting signal type 1 (PTS1). Lactate dehydrogenase B (LDHB) showed the highest combined RTP and PTS1 probability. Experimentally we show that at least 1.6% of the total cellular LDHB is targeted to the peroxisome by a conserved hidden PTS1. The readthrough-extended lactate dehydrogenase subunit LDHBx can also co-import LDHA, the other LDH subunit, into peroxisomes. Peroxisomal LDH is conserved in mammals and likely contributes to redox equivalent regeneration in peroxisomes. DOI: http://dx.doi.org/10.7554/eLife.03640.001 PMID:25247702

Flow-Based Network Analysis of the Caenorhabditis elegans Connectome

PubMed Central

Bacik, Karol A.; Schaub, Michael T.; Billeh, Yazan N.; Barahona, Mauricio

2016-01-01

We exploit flow propagation on the directed neuronal network of the nematode C. elegans to reveal dynamically relevant features of its connectome. We find flow-based groupings of neurons at different levels of granularity, which we relate to functional and anatomical constituents of its nervous system. A systematic in silico evaluation of the full set of single and double neuron ablations is used to identify deletions that induce the most severe disruptions of the multi-resolution flow structure. Such ablations are linked to functionally relevant neurons, and suggest potential candidates for further in vivo investigation. In addition, we use the directional patterns of incoming and outgoing network flows at all scales to identify flow profiles for the neurons in the connectome, without pre-imposing a priori categories. The four flow roles identified are linked to signal propagation motivated by biological input-response scenarios. PMID:27494178

Identification and in silico characterization of p.G380R substitution in FGFR3, associated with achondroplasia in a non-consanguineous Pakistani family.

PubMed

Ajmal, Muhammad; Mir, Asif; Shoaib, Muhammad; Malik, Salman Akbar; Nasir, Muhammad

2017-07-05

The dimerization efficiency of FGFR3 transmembrane domain plays a critical role in the formation of a normal skeleton through the negative regulation of bone development. Recently, gain-of-function mutations in the transmembrane domain of FGFR3 has been described associated with an aberrant negative regulation, leading to the development of achondroplasia-group disorders, including achondroplasia (ACH), hypochondroplasia (HCH) and thanatophoric dysplasia (TD). Here, we describe a non-consanguineous Pakistani family with achondroplasia to explain hereditary basis of the disease. PCR-based linkage analysis using microsatellite markers was employed to localize the disease gene. Gene specific intronic primers were used to amplify the genomic DNA from all affected as well as phenotypically healthy individuals. Amplified PCR products were then subjected to Sanger sequencing and RFLP analysis to identify a potentially pathogenic mutation. The impact of identified mutation on FGFR3 protein's structure and stability was highlighted through different bioinformatics tools. Genetic screening of the family revealed a previously reported heterozygous c.1138 G > A (p.G380R) mutation in the coding exon 8 of FGFR3 gene. Identified genetic variation was confirmed in all affected individuals while healthy individuals and controls were found genotypically normal. The results were further validated by RFLP analysis as c.1138 G > A substitution generates a unique recognition site for SfcI endonuclease. Following SfcI digestion, the electrophoretic pattern of three bands/DNA fragments for each patient is indicative of heterozygous status of the disease allele. In silico studies of the mutant FGFR3 protein predicted to adversely affect the stability of FGFR3 protein. Mutation in the transmembrane domain may adversely affect the dimerization efficiency and overall stability of the FGFR3, leading to a constitutively active protein. As a result, an uncontrolled intracellular signaling or negative bone growth regulation leads to achondroplasia. Our findings support the fact that p.G380R is a common mutation among diverse population of the world and like other countries, can be used as a molecular diagnosis marker for achondroplasia in Pakistan.

In Vitro vs In Silico Detected SNPs for the Development of a Genotyping Array: What Can We Learn from a Non-Model Species?

PubMed Central

Lepoittevin, Camille; Frigerio, Jean-Marc; Garnier-Géré, Pauline; Salin, Franck; Cervera, María-Teresa; Vornam, Barbara; Harvengt, Luc; Plomion, Christophe

2010-01-01

Background There is considerable interest in the high-throughput discovery and genotyping of single nucleotide polymorphisms (SNPs) to accelerate genetic mapping and enable association studies. This study provides an assessment of EST-derived and resequencing-derived SNP quality in maritime pine (Pinus pinaster Ait.), a conifer characterized by a huge genome size (∼23.8 Gb/C). Methodology/Principal Findings A 384-SNPs GoldenGate genotyping array was built from i/ 184 SNPs originally detected in a set of 40 re-sequenced candidate genes (in vitro SNPs), chosen on the basis of functionality scores, presence of neighboring polymorphisms, minor allele frequencies and linkage disequilibrium and ii/ 200 SNPs screened from ESTs (in silico SNPs) selected based on the number of ESTs used for SNP detection, the SNP minor allele frequency and the quality of SNP flanking sequences. The global success rate of the assay was 66.9%, and a conversion rate (considering only polymorphic SNPs) of 51% was achieved. In vitro SNPs showed significantly higher genotyping-success and conversion rates than in silico SNPs (+11.5% and +18.5%, respectively). The reproducibility was 100%, and the genotyping error rate very low (0.54%, dropping down to 0.06% when removing four SNPs showing elevated error rates). Conclusions/Significance This study demonstrates that ESTs provide a resource for SNP identification in non-model species, which do not require any additional bench work and little bio-informatics analysis. However, the time and cost benefits of in silico SNPs are counterbalanced by a lower conversion rate than in vitro SNPs. This drawback is acceptable for population-based experiments, but could be dramatic in experiments involving samples from narrow genetic backgrounds. In addition, we showed that both the visual inspection of genotyping clusters and the estimation of a per SNP error rate should help identify markers that are not suitable to the GoldenGate technology in species characterized by a large and complex genome. PMID:20543950

Scheffersomyces stipitis: a comparative systems biology study with the Crabtree positive yeast Saccharomyces cerevisiae

PubMed Central

2012-01-01

Background Scheffersomyces stipitis is a Crabtree negative yeast, commonly known for its capacity to ferment pentose sugars. Differently from Crabtree positive yeasts such as Saccharomyces cerevisiae, the onset of fermentation in S. stipitis is not dependent on the sugar concentration, but is regulated by a decrease in oxygen levels. Even though S. stipitis has been extensively studied due to its potential application in pentoses fermentation, a limited amount of information is available about its metabolism during aerobic growth on glucose. Here, we provide a systems biology based comparison between the two yeasts, uncovering the metabolism of S. stipitis during aerobic growth on glucose under batch and chemostat cultivations. Results Starting from the analysis of physiological data, we confirmed through 13C-based flux analysis the fully respiratory metabolism of S. stipitis when growing both under glucose limited or glucose excess conditions. The patterns observed showed similarity to the fully respiratory metabolism observed for S. cerevisiae under chemostat cultivations however, intracellular metabolome analysis uncovered the presence of several differences in metabolite patterns. To describe gene expression levels under the two conditions, we performed RNA sequencing and the results were used to quantify transcript abundances of genes from the central carbon metabolism and compared with those obtained with S. cerevisiae. Interestingly, genes involved in central pathways showed different patterns of expression, suggesting different regulatory networks between the two yeasts. Efforts were focused on identifying shared and unique families of transcription factors between the two yeasts through in silico transcription factors analysis, suggesting a different regulation of glycolytic and glucoenogenic pathways. Conclusions The work presented addresses the impact of high-throughput methods in describing and comparing the physiology of Crabtree positive and Crabtree negative yeasts. Based on physiological data and flux analysis we identified the presence of one metabolic condition for S. stipitis under aerobic batch and chemostat cultivations, which shows similarities to the oxidative metabolism observed for S. cerevisiae under chemostat cultivations. Through metabolome analysis and genome-wide transcriptomic analysis several differences were identified. Interestingly, in silico analysis of transciption factors was useful to address a different regulation of mRNAs of genes involved in the central carbon metabolism. To our knowledge, this is the first time that the metabolism of S. stiptis is investigated in details and is compared to S. cerevisiae. Our study provides useful results and allows for the possibility to incorporate these data into recently developed genome-scaled metabolic, thus contributing to improve future industrial applications of S. stipitis as cell factory. PMID:23043429

In-Silico Screening of Ligand Based Pharmacophore, Database Mining and Molecular Docking on 2, 5-Diaminopyrimidines Azapurines as Potential Inhibitors of Glycogen Synthase Kinase-3β.

PubMed

Mishra, Pooja; Kesar, Seema; Paliwal, Sarvesh K; Chauhan, Monika; Madan, Kirtika

2018-05-29

Glycogen synthase kinase-3β plays a significant role in the regulation of various pathological pathways relating to central nervous system (CNS). Dysregulation of Glycogen synthase kinase 3 (GSK-3) activity gives a rise to numerous neuroinflammation and neurodegenerative related disorders that affect the whole central nervous system. By the sequential application of in-silico tools, efforts have been attempted to design the novel GSK-3β inhibitors. Owing to the potential role of GSK-3β in nervous disorders, we have attempted to develop the quantitative four featured pharmacophore model comprising two hydrogen bond acceptors (HBA), one ring aromatic (RA), and one hydrophobe (HY), which were further affirmed by cost-function analysis, rm2 matrices, internal and external test set validation and Güner-Henry (GH) scoring analysis. Validated pharmacophoric model was used for virtual screening and out of 345 compounds, two potential virtual hits were finalized that were on the basis of fit value, estimated activity and Lipinski's violation. The chosen compounds were subjected to dock within the active site of GSK-3β Result: Four essential features, i.e., two hydrogen bond acceptors(HBA), one ring aromatic(RA), and one hydrophobe(HY), were subjected to build the pharmacophoric model and showed good correlation coefficient, RMSD and cost difference values of 0.91, 0.94 and 42.9 respectively and further model was validated employing cost-function analysis, rm2-matrices, internal and external test set prediction with r2 value of 0.77 and 0.84. Docked conformations showed potential interactions in between the features of the identified hits (NCI 4296, NCI 3034) and the amino acids present in the active site. In line with the overhead discussion, and through our stepwise computational approaches, we have identified novel, structurally diverse glycogen synthase kinase inhibitors. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

The secrets of Oriental panacea: Panax ginseng.

PubMed

Colzani, Mara; Altomare, Alessandra; Caliendo, Matteo; Aldini, Giancarlo; Righetti, Pier Giorgio; Fasoli, Elisa

2016-01-01

The Panax ginseng root proteome has been investigated via capture with combinatorial peptide ligand libraries (CPLL) at three different pH values. Proteomic characterization by SDS-PAGE and nLC–MS/MS analysis, via LTQ-Orbitrap XL, led to the identification of a total of 207 expressed proteins. This quite large number of identifications was achieved by consulting two different plant databases: P. ginseng and Arabidopsis thaliana. The major groups of identified proteins were associated to structural species (19.2%), oxidoreductase (19.5%), dehydrogenases (7.6%) and synthases (9.0%). For the first time, an exploration of protein–protein interactions was performed by merging all recognized proteins and building an interactomic map, characterized by 196 nodes and 1554 interactions. Finally a peptidomic analysis was developed combining different in-silico enzymatic digestions to simulate the human gastrointestinal process: from 661 generated peptides, 95 were identified as possible bioactives and in particular 6 of them were characterized by antimicrobial activity. The present report offers new insight for future investigations focused on elucidation of biological properties of P. ginseng proteome and peptidome. Ginseng is a traditional oriental herbal remedy whose use is very diffused in all the world for its numerous pharmacological effects. However, the exact mechanism of action of ginseng components, both ginsenosides and proteins, is still unidentified. So the common use of ginseng requires strict investigations to assess both its efficiency and its safety. Although many reports have been published regarding the pharmacological effects of ginseng, little is known about the biochemical pathways of root. Proteomics analysis could be useful to elucidate the physiological pathways. In this manuscript, an integrated approach to proteomics and peptidomics will usher in exploration of Panax ginseng proteins and proteolytic peptides, obtained by in-silico gastrointestinal digestion, characterized by antimicrobial action. The present research would pave the way for better knowledge of metabolic functions connected with ginseng proteome and provide with new information necessary to understand better antimicrobial activity of P. ginseng.

Mapping the epitopes of a neutralizing antibody fragment directed against the lethal factor of Bacillus anthracis and cross-reacting with the homologous edema factor.

PubMed

Thullier, Philippe; Avril, Arnaud; Mathieu, Jacques; Behrens, Christian K; Pellequer, Jean-Luc; Pelat, Thibaut

2013-01-01

The lethal toxin (LT) of Bacillus anthracis, composed of the protective antigen (PA) and the lethal factor (LF), plays an essential role in anthrax pathogenesis. PA also interacts with the edema factor (EF, 20% identity with LF) to form the edema toxin (ET), which has a lesser role in anthrax pathogenesis. The first recombinant antibody fragment directed against LF was scFv 2LF; it neutralizes LT by blocking the interaction between PA and LF. Here, we report that scFv 2LF cross-reacts with EF and cross-neutralizes ET, and we present an in silico method taking advantage of this cross-reactivity to map the epitope of scFv 2LF on both LF and EF. This method identified five epitope candidates on LF, constituted of a total of 32 residues, which were tested experimentally by mutating the residues to alanine. This combined approach precisely identified the epitope of scFv 2LF on LF as five residues (H229, R230, Q234, L235 and Y236), of which three were missed by the consensus epitope candidate identified by pre-existing in silico methods. The homolog of this epitope on EF (H253, R254, E258, L259 and Y260) was experimentally confirmed to constitute the epitope of scFv 2LF on EF. Other inhibitors, including synthetic molecules, could be used to target these epitopes for therapeutic purposes. The in silico method presented here may be of more general interest.

Merging in-silico and in vitro salivary protein complex partners using the STRING database: A tutorial.

PubMed

Crosara, Karla Tonelli Bicalho; Moffa, Eduardo Buozi; Xiao, Yizhi; Siqueira, Walter Luiz

2018-01-16

Protein-protein interaction is a common physiological mechanism for protection and actions of proteins in an organism. The identification and characterization of protein-protein interactions in different organisms is necessary to better understand their physiology and to determine their efficacy. In a previous in vitro study using mass spectrometry, we identified 43 proteins that interact with histatin 1. Six previously documented interactors were confirmed and 37 novel partners were identified. In this tutorial, we aimed to demonstrate the usefulness of the STRING database for studying protein-protein interactions. We used an in-silico approach along with the STRING database (http://string-db.org/) and successfully performed a fast simulation of a novel constructed histatin 1 protein-protein network, including both the previously known and the predicted interactors, along with our newly identified interactors. Our study highlights the advantages and importance of applying bioinformatics tools to merge in-silico tactics with experimental in vitro findings for rapid advancement of our knowledge about protein-protein interactions. Our findings also indicate that bioinformatics tools such as the STRING protein network database can help predict potential interactions between proteins and thus serve as a guide for future steps in our exploration of the Human Interactome. Our study highlights the usefulness of the STRING protein database for studying protein-protein interactions. The STRING database can collect and integrate data about known and predicted protein-protein associations from many organisms, including both direct (physical) and indirect (functional) interactions, in an easy-to-use interface. Copyright © 2017 Elsevier B.V. All rights reserved.

Studies on interaction of insect repellent compounds with odorant binding receptor proteins by in silico molecular docking approach.

PubMed

Gopal, J Vinay; Kannabiran, K

2013-12-01

The aim of the study was to identify the interactions between insect repellent compounds and target olfactory proteins. Four compounds, camphor (C10H16O), carvacrol (C10H14O), oleic acid (C18H34O2) and firmotox (C22H28O5) were chosen as ligands. Seven olfactory proteins of insects with PDB IDs: 3K1E, 1QWV, 1TUJ, 1OOF, 2ERB, 3R1O and OBP1 were chosen for docking analysis. Patch dock was used and pymol for visualizing the structures. The interactions of these ligands with few odorant binding proteins showed binding energies. The ligand camphor had showed a binding energy of -136 kcal/mol with OBP1 protein. The ligand carvacrol interacted with 1QWV and 1TUJ proteins with a least binding energy of -117.45 kcal/mol and -21.78 kcal/mol respectively. The ligand oleic acid interacted with 1OOF, 2ERB, 3R1O and OBP1 with least binding energies. Ligand firmotox interacted with OBP1 and showed least binding energies. Three ligands (camphor, oleic acid and firmotox) had one, two, three interactions with a single protein OBP1 of Nilaparvatha lugens (Rice pest). From this in silico study we identified the interaction patterns for insect repellent compounds with the target insect odarant proteins. The results of our study revealed that the chosen ligands showed hydrogen bond interactions with the target olfactory receptor proteins.

Centromeric chromatin and its dynamics in plants.

PubMed

Lermontova, Inna; Sandmann, Michael; Mascher, Martin; Schmit, Anne-Catherine; Chabouté, Marie-Edith

2015-07-01

Centromeres are chromatin structures that are required for proper separation of chromosomes during mitosis and meiosis. The centromere is composed of centromeric DNA, often enriched in satellite repeats, and kinetochore complex proteins. To date, over 100 kinetochore components have been identified in various eukaryotes. Kinetochore assembly begins with incorporation of centromeric histone H3 variant CENH3 into centromeric nucleosomes. Protein components of the kinetochore are either present at centromeres throughout the cell cycle or localize to centromeres transiently, prior to attachment of microtubules to each kinetochore in prometaphase of mitotic cells. This is the case for the spindle assembly checkpoint (SAC) proteins in animal cells. The SAC complex ensures equal separation of chromosomes between daughter nuclei by preventing anaphase onset before metaphase is complete, i.e. the sister kinetochores of all chromosomes are attached to spindle fibers from opposite poles. In this review, we focus on the organization of centromeric DNA and the kinetochore assembly in plants. We summarize recent advances regarding loading of CENH3 into the centromere, and the subcellular localization and protein-protein interactions of Arabidopsis thaliana proteins involved in kinetochore assembly and function. We describe the transcriptional activity of corresponding genes based on in silico analysis of their promoters and cell cycle-dependent expression. Additionally, barley homologs of all selected A. thaliana proteins have been identified in silico, and their sequences and domain structures are presented. © 2015 The Authors The Plant Journal © 2015 John Wiley & Sons Ltd.

Stability-indicating HPLC-DAD/UV-ESI/MS impurity profiling of the anti-malarial drug lumefantrine.

PubMed

Verbeken, Mathieu; Suleman, Sultan; Baert, Bram; Vangheluwe, Elien; Van Dorpe, Sylvia; Burvenich, Christian; Duchateau, Luc; Jansen, Frans H; De Spiegeleer, Bart

2011-02-28

Lumefantrine (benflumetol) is a fluorene derivative belonging to the aryl amino alcohol class of anti-malarial drugs and is commercially available in fixed combination products with β-artemether. Impurity characterization of such drugs, which are widely consumed in tropical countries for malaria control programmes, is of paramount importance. However, until now, no exhaustive impurity profile of lumefantrine has been established, encompassing process-related and degradation impurities in active pharmaceutical ingredients (APIs) and finished pharmaceutical products (FPPs). Using HPLC-DAD/UV-ESI/ion trap/MS, a comprehensive impurity profile was established based upon analysis of market samples as well as stress, accelerated and long-term stability results. In-silico toxicological predictions for these lumefantrine related impurities were made using Toxtree® and Derek®. Several new impurities are identified, of which the desbenzylketo derivative (DBK) is proposed as a new specified degradant. DBK and the remaining unspecified lumefantrine related impurities are predicted, using Toxtree® and Derek®, to have a toxicity risk comparable to the toxicity risk of the API lumefantrine itself. From unstressed, stressed and accelerated stability samples of lumefantrine API and FPPs, nine compounds were detected and characterized to be lumefantrine related impurities. One new lumefantrine related compound, DBK, was identified and characterized as a specified degradation impurity of lumefantrine in real market samples (FPPs). The in-silico toxicological investigation (Toxtree® and Derek®) indicated overall a toxicity risk for lumefantrine related impurities comparable to that of the API lumefantrine itself.

Designing and conducting in silico analysis for identifying of Echinococcus spp. with discrimination of novel haplotypes: an approach to better understanding of parasite taxonomic.

PubMed

Spotin, Adel; Gholami, Shirzad; Nasab, Abbas Najafi; Fallah, Esmaeil; Oskouei, Mahmoud Mahami; Semnani, Vahid; Shariatzadeh, Seyyed Ali; Shahbazi, Abbas

2015-04-01

The definitive identification of Echinococcus species is currently carried out by sequencing and phylogenetic strategies. However, the application of polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) patterns is not broadly used as a result of heterogeneity traits of Echinococcus genome in different regions of the world. Therefore, designing and conducting a standardized pattern should indigenously be considered in under-studied areas. In this investigation, an in silico mapping was designed and developed for eight Echinococcus spp. on the basis of regional sequences in Iran and the world. The numbers of 60 Echinococcus isolates were collected from the liver and lungs of 15 human, 15 sheep, 15 cattle, and 15 camel cases in Semnan province, Central Iran. DNA samples were extracted and examined by polymerase chain reaction of ribosomal DNA (rDNA) internal transcribed spacer 1 (ITS1) and PCR-RFLP via Rsa1 endonuclease enzyme. Moreover, 15 amplicons of cytochrome oxidase 1 (Cox1) were directly sequenced in order to identify the strains/haplotypes. PCR-RFLP and phylogenetic analyses revealed firmly the presence of the G1 and G6 genotypes with heterogeneity (three novel haplotypes) of Cox1 gene although no other expected genotypes were found in the region. Finding shows that the identification of novel haplotypes along with discrimination of Echinococcus spp. through regional patterns can unambiguously illustrate the real taxonomic status of parasite in Central Iran.

Mass spectrometry analysis and in silico prediction of allergenicity of peptides in tryptic hydrolysates of the proteins from Ruditapes philippinarum.

PubMed

Yu, Yue; Liu, Hongwei; Tu, Maolin; Qiao, Meiling; Wang, Zhenyu; Du, Ming

2017-12-01

Ruditapes philippinarum is nutrient-rich and widely-distributed, but little attention has been paid to the identification and characterization of the bioactive peptides in the bivalve. In the present study, we evaluated the peptides of the R. philippinarum that were enzymolysised by trypsin using a combination of ultra-performance liquid chromatography separation and electrospray ionization quadrupole time-of-flight tandem mass spectrometry, followed by data processing and sequence-similarity database searching. The potential allergenicity of the peptides was assessed in silico. The enzymolysis was performed under the conditions: E:S 3:100 (w/w), pH 9.0, 45 °C for 4 h. After separation and detection, the Swiss-Prot database and a Ruditapes philippinarum sequence database were used: 966 unique peptides were identified by non-error tolerant database searching; 173 peptides matching 55 precursor proteins comprised highly conserved cytoskeleton proteins. The remaining 793 peptides were identified from the R. philippinarum sequence database. The results showed that 510 peptides were labeled as allergens and 31 peptides were potential allergens; 425 peptides were predicted to be nonallergenic. The abundant peptide information contributes to further investigations of the structure and potential function of R. philippinarum. Additional in vitro studies are required to demonstrate and ensure the correct production of the hydrolysates for use in the food industry with respect to R. philippinarum. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Theoretical investigation on the microstructure of triethylene glycol based deep eutectic solvents: COSMO-RS and TURBOMOLE prediction

NASA Astrophysics Data System (ADS)

Aissaoui, Tayeb; Benguerba, Yacine; AlNashef, Inas M.

2017-08-01

The in-silico combination mechanism of triethylene glycol based DESs has been studied. COSMO-RS and graphical user interface TmoleX software were used to predict the interaction mechanism of hydrogen bond donors (HBDs) with hydrogen bond acceptors (HBA) to form DESs. The predicted IR results were compared with the previously reported experimental FT-IR analysis for the same studied DESs. The sigma profiles for the HBD, HBAs and formed DESs were interpreted to identify qualitatively molecular properties like polarity or hydrogen bonding donor and acceptor abilities. The predicted physicochemical properties reported in this study were in good agreement with experimental ones.

In silico analysis of Schmidtea mediterranea TIR domain-containing proteins.

PubMed

Tsoumtsa, Landry Laure; Sougoufora, Seynabou; Torre, Cedric; Lemichez, Emmanuel; Pontarotti, Pierre; Ghigo, Eric

2018-09-01

While genetic evidence points towards an absence of Toll-Like Receptors (TLRs) in Platyhelminthes, the Toll/IL-1 Receptor (TIR)-domains that drive the assembly of signalling complexes downstream TLR are present in these organisms. Here, we undertook the characterisation of the repertoire of TIR-domain containing proteins in Schmidtea mediterranea in order to gain valuable information on TLR evolution in metazoan. We report the presence of twenty proteins containing between one and two TIR domains. In addition, our phylogenetic-based reconstruction approach identified Smed-SARM and Smed-MyD88 as conserved TLR adaptors. Copyright © 2018 Elsevier Ltd. All rights reserved.

Lack of Detectable Allergenicity in Genetically Modified Maize Containing “Cry” Proteins as Compared to Native Maize Based on In Silico & In Vitro Analysis

PubMed Central

Mathur, Chandni; Kathuria, Pooran C.; Dahiya, Pushpa; Singh, Anand B.

2015-01-01

Background Genetically modified, (GM) crops with potential allergens must be evaluated for safety and endogenous IgE binding pattern compared to native variety, prior to market release. Objective To compare endogenous IgE binding proteins of three GM maize seeds containing Cry 1Ab,1Ac,1C transgenic proteins with non GM maize. Methods An integrated approach of in silico & in vitro methods was employed. Cry proteins were tested for presence of allergen sequence by FASTA in allergen databases. Biochemical assays for maize extracts were performed. Specific IgE (sIgE) and Immunoblot using food sensitized patients sera (n = 39) to non GM and GM maize antigens was performed. Results In silico approaches, confirmed for non sequence similarity of stated transgenic proteins in allergen databases. An insignificant (p> 0.05) variation in protein content between GM and non GM maize was observed. Simulated Gastric Fluid (SGF) revealed reduced number of stable protein fractions in GM then non GM maize which might be due to shift of constituent protein expression. Specific IgE values from patients showed insignificant difference in non GM and GM maize extracts. Five maize sensitized cases, recognized same 7 protein fractions of 88-28 kD as IgE bindng in both GM and non-GM maize, signifying absence of variation. Four of the reported IgE binding proteins were also found to be stable by SGF. Conclusion Cry proteins did not indicate any significant similarity of >35% in allergen databases. Immunoassays also did not identify appreciable differences in endogenous IgE binding in GM and non GM maize. PMID:25706412

Pregnancy-induced gingivitis and OMICS in dentistry: in silico modeling and in vivo prospective validation of estradiol-modulated inflammatory biomarkers.

PubMed

Gürsoy, Mervi; Zeidán-Chuliá, Fares; Könönen, Eija; Moreira, José C F; Liukkonen, Joonas; Sorsa, Timo; Gürsoy, Ulvi K

2014-09-01

Pregnancy-associated gingivitis is a bacterial-induced inflammatory disease with a remarkably high prevalence ranging from 35% to 100% across studies. Yet little is known about the attendant mechanisms or diagnostic biomarkers that can help predict individual susceptibility for rational personalized medicine. We aimed to define inflammatory proteins in saliva, induced or inhibited by estradiol, as early diagnostic biomarkers or target proteins in relation to pregnancy-associated gingivitis. An in silico gene/protein interaction network model was developed by using the STITCH 3.1 with "experiments" and "databases" as input options and a confidence score of 0.700 (high confidence). Salivary estradiol, interleukin (IL)-1β and -8, myeloperoxidase (MPO), matrix metalloproteinase (MMP)-2, -8, and -9, and tissue inhibitor of matrix metalloproteinase (TIMP)-1 levels from 30 women were measured prospectively three times during pregnancy and twice during postpartum. In silico analysis revealed that estradiol interacts with IL-1β and -8 by an activation link when the "actions view" was consulted. In saliva, estradiol concentrations associated positively with TIMP-1 and negatively with MPO and MMP-8 concentrations. When the gingival bleeding on probing percentage (BOP%) was included in the model as an effect modifier, the only association, a negative one, was found between estradiol and MMP-8. Throughout gestation, estradiol modulates the inflammatory response by inhibiting neutrophilic enzymes, such as MMP-8. The interactions between salivary degradative enzymes and proinflammatory cytokines during pregnancy suggest promising ways to identify candidate biomarkers for pregnancy-associated gingivitis, and for personalized medicine in the field of dentistry. Finally, we call for greater investments in, and action for biomarker research in periodontology and dentistry that have surprisingly lagged behind in personalized medicine compared to other fields, such as cancer research.

Antinociceptive Activity of Borreria verticillata: In vivo and In silico Studies

PubMed Central

Silva, Rosa H. M.; Lima, Nathália de Fátima M.; Lopes, Alberto J. O.; Vasconcelos, Cleydlenne C.; de Mesquita, José W. C.; de Mesquita, Ludmilla S. S.; Lima, Fernando C. V. M.; Ribeiro, Maria N. de S.; Ramos, Ricardo M.; Cartágenes, Maria do Socorro de S.; Garcia, João B. S.

2017-01-01

Borreria verticillata (L.) G. Mey. known vassourinha has antibacterial, antimalarial, hepatoprotective, antioxidative, analgesic, and anti-inflammatory, however, its antinociceptive action requires further studies. Aim of the study evaluated the antinociceptive activity of B. verticillata hydroalcoholic extract (EHBv) and ethyl acetate fraction (FAc) by in vivo and in silico studies. In vivo assessment included the paw edema test, writhing test, formalin test and tail flick test. Wistar rats and Swiss mice were divided into 6 groups and given the following treatments oral: 0.9% NaCl control group (CTRL), 10 mg/kg memantine (MEM), 10 mg/kg indomethacin (INDO), 500 mg/kg EHBv (EHBv 500), 25 mg/kg FAc (FAc 25) and 50 mg/kg FAc (FAc 50). EHBv, FAc 25 and 50 treatments exhibited anti-edematous and peripheral antinociceptive effects. For in silico assessment, compounds identified in FAc were subjected to molecular docking with COX-2, GluN1a and GluN2B. Ursolic acid (UA) was the compound with best affinity parameters (binding energy and inhibition constant) for COX-2, GluN1a, GluN2B, and was selected for further analysis with molecular dynamics (MD) simulations. In MD simulations, UA exhibited highly frequent interactions with residues Arg120 and Glu524 in the COX-2 active site and NMDA, whereby it might prevent COX-2 and NMDA receptor activation. Treatment with UA 10 mg/Kg showed peripheral and central antinociceptive effect. The antinociceptive effect of B. verticillata might be predominantly attributed to peripheral actions, including the participation of anti-inflammatory components. Ursolic acid is the main active component and seems to be a promising source of COX-2 inhibitors and NMDA receptor antagonists. PMID:28588488

Characterization of anti-leukemia components from Indigo naturalis using comprehensive two-dimensional K562/cell membrane chromatography and in silico target identification.

PubMed

Wu, Xunxun; Chen, Xiaofei; Dan, Jia; Cao, Yan; Gao, Shouhong; Guo, Zhiying; Zerbe, Philipp; Chai, Yifeng; Diao, Yong; Zhang, Lei

2016-05-06

Traditional Chinese Medicine (TCM) has been developed for thousands of years and has formed an integrated theoretical system based on a large amount of clinical practice. However, essential ingredients in TCM herbs have not been fully identified, and their precise mechanisms and targets are not elucidated. In this study, a new strategy combining comprehensive two-dimensional K562/cell membrane chromatographic system and in silico target identification was established to characterize active components from Indigo naturalis, a famous TCM herb that has been widely used for the treatment of leukemia in China, and their targets. Three active components, indirubin, tryptanthrin and isorhamnetin, were successfully characterized and their anti-leukemia effects were validated by cell viability and cell apoptosis assays. Isorhamnetin, with undefined cancer related targets, was selected for in silico target identification. Proto-oncogene tyrosine-protein kinase (Src) was identified as its membrane target and the dissociation constant (Kd) between Src and isorhamnetin was 3.81 μM. Furthermore, anti-leukemia effects of isorhamnetin were mediated by Src through inducing G2/M cell cycle arrest. The results demonstrated that the integrated strategy could efficiently characterize active components in TCM and their targets, which may bring a new light for a better understanding of the complex mechanism of herbal medicines.

Characterization of anti-leukemia components from Indigo naturalis using comprehensive two-dimensional K562/cell membrane chromatography and in silico target identification

PubMed Central

Wu, Xunxun; Chen, Xiaofei; Dan, Jia; Cao, Yan; Gao, Shouhong; Guo, Zhiying; Zerbe, Philipp; Chai, Yifeng; Diao, Yong; Zhang, Lei

2016-01-01

Traditional Chinese Medicine (TCM) has been developed for thousands of years and has formed an integrated theoretical system based on a large amount of clinical practice. However, essential ingredients in TCM herbs have not been fully identified, and their precise mechanisms and targets are not elucidated. In this study, a new strategy combining comprehensive two-dimensional K562/cell membrane chromatographic system and in silico target identification was established to characterize active components from Indigo naturalis, a famous TCM herb that has been widely used for the treatment of leukemia in China, and their targets. Three active components, indirubin, tryptanthrin and isorhamnetin, were successfully characterized and their anti-leukemia effects were validated by cell viability and cell apoptosis assays. Isorhamnetin, with undefined cancer related targets, was selected for in silico target identification. Proto-oncogene tyrosine-protein kinase (Src) was identified as its membrane target and the dissociation constant (Kd) between Src and isorhamnetin was 3.81 μM. Furthermore, anti-leukemia effects of isorhamnetin were mediated by Src through inducing G2/M cell cycle arrest. The results demonstrated that the integrated strategy could efficiently characterize active components in TCM and their targets, which may bring a new light for a better understanding of the complex mechanism of herbal medicines. PMID:27150638

Pathway-based predictive approaches for non-animal assessment of acute inhalation toxicity.

PubMed

Clippinger, Amy J; Allen, David; Behrsing, Holger; BéruBé, Kelly A; Bolger, Michael B; Casey, Warren; DeLorme, Michael; Gaça, Marianna; Gehen, Sean C; Glover, Kyle; Hayden, Patrick; Hinderliter, Paul; Hotchkiss, Jon A; Iskandar, Anita; Keyser, Brian; Luettich, Karsta; Ma-Hock, Lan; Maione, Anna G; Makena, Patrudu; Melbourne, Jodie; Milchak, Lawrence; Ng, Sheung P; Paini, Alicia; Page, Kathryn; Patlewicz, Grace; Prieto, Pilar; Raabe, Hans; Reinke, Emily N; Roper, Clive; Rose, Jane; Sharma, Monita; Spoo, Wayne; Thorne, Peter S; Wilson, Daniel M; Jarabek, Annie M

2018-06-20

New approaches are needed to assess the effects of inhaled substances on human health. These approaches will be based on mechanisms of toxicity, an understanding of dosimetry, and the use of in silico modeling and in vitro test methods. In order to accelerate wider implementation of such approaches, development of adverse outcome pathways (AOPs) can help identify and address gaps in our understanding of relevant parameters for model input and mechanisms, and optimize non-animal approaches that can be used to investigate key events of toxicity. This paper describes the AOPs and the toolbox of in vitro and in silico models that can be used to assess the key events leading to toxicity following inhalation exposure. Because the optimal testing strategy will vary depending on the substance of interest, here we present a decision tree approach to identify an appropriate non-animal integrated testing strategy that incorporates consideration of a substance's physicochemical properties, relevant mechanisms of toxicity, and available in silico models and in vitro test methods. This decision tree can facilitate standardization of the testing approaches. Case study examples are presented to provide a basis for proof-of-concept testing to illustrate the utility of non-animal approaches to inform hazard identification and risk assessment of humans exposed to inhaled substances. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

An evaluation of selected in silico models for the assessment ...

EPA Pesticide Factsheets

Skin sensitization remains an important endpoint for consumers, manufacturers and regulators. Although the development of alternative approaches to assess skin sensitization potential has been extremely active over many years, the implication of regulations such as REACH and the Cosmetics Directive in EU has provided a much stronger impetus to actualize this research into practical tools for decision making. Thus there has been considerable focus on the development, evaluation, and integration of alternative approaches for skin sensitization hazard and risk assessment. This includes in silico approaches such as (Q)SARs and expert systems. This study aimed to evaluate the predictive performance of a selection of in silico models and then to explore whether combining those models led to an improvement in accuracy. A dataset of 473 substances that had been tested in the local lymph node assay (LLNA) was compiled. This comprised 295 sensitizers and 178 non-sensitizers. Four freely available models were identified - 2 statistical models VEGA and MultiCASE model A33 for skin sensitization (MCASE A33) from the Danish National Food Institute and two mechanistic models Toxtree’s Skin sensitization Reaction domains (Toxtree SS Rxn domains) and the OASIS v1.3 protein binding alerts for skin sensitization from the OECD Toolbox (OASIS). VEGA and MCASE A33 aim to predict sensitization as a binary score whereas the mechanistic models identified reaction domains or structura

An in silico model for identification of small RNAs in whole bacterial genomes: characterization of antisense RNAs in pathogenic Escherichia coli and Streptococcus agalactiae strains.

PubMed

Pichon, Christophe; du Merle, Laurence; Caliot, Marie Elise; Trieu-Cuot, Patrick; Le Bouguénec, Chantal

2012-04-01

Characterization of small non-coding ribonucleic acids (sRNA) among the large volume of data generated by high-throughput RNA-seq or tiling microarray analyses remains a challenge. Thus, there is still a need for accurate in silico prediction methods to identify sRNAs within a given bacterial species. After years of effort, dedicated software were developed based on comparative genomic analyses or mathematical/statistical models. Although these genomic analyses enabled sRNAs in intergenic regions to be efficiently identified, they all failed to predict antisense sRNA genes (asRNA), i.e. RNA genes located on the DNA strand complementary to that which encodes the protein. The statistical models enabled any genomic region to be analyzed theorically but not efficiently. We present a new model for in silico identification of sRNA and asRNA candidates within an entire bacterial genome. This model was successfully used to analyze the Gram-negative Escherichia coli and Gram-positive Streptococcus agalactiae. In both bacteria, numerous asRNAs are transcribed from the complementary strand of genes located in pathogenicity islands, strongly suggesting that these asRNAs are regulators of the virulence expression. In particular, we characterized an asRNA that acted as an enhancer-like regulator of the type 1 fimbriae production involved in the virulence of extra-intestinal pathogenic E. coli.

An in silico model for identification of small RNAs in whole bacterial genomes: characterization of antisense RNAs in pathogenic Escherichia coli and Streptococcus agalactiae strains

PubMed Central

Pichon, Christophe; du Merle, Laurence; Caliot, Marie Elise; Trieu-Cuot, Patrick; Le Bouguénec, Chantal

2012-01-01

Characterization of small non-coding ribonucleic acids (sRNA) among the large volume of data generated by high-throughput RNA-seq or tiling microarray analyses remains a challenge. Thus, there is still a need for accurate in silico prediction methods to identify sRNAs within a given bacterial species. After years of effort, dedicated software were developed based on comparative genomic analyses or mathematical/statistical models. Although these genomic analyses enabled sRNAs in intergenic regions to be efficiently identified, they all failed to predict antisense sRNA genes (asRNA), i.e. RNA genes located on the DNA strand complementary to that which encodes the protein. The statistical models enabled any genomic region to be analyzed theorically but not efficiently. We present a new model for in silico identification of sRNA and asRNA candidates within an entire bacterial genome. This model was successfully used to analyze the Gram-negative Escherichia coli and Gram-positive Streptococcus agalactiae. In both bacteria, numerous asRNAs are transcribed from the complementary strand of genes located in pathogenicity islands, strongly suggesting that these asRNAs are regulators of the virulence expression. In particular, we characterized an asRNA that acted as an enhancer-like regulator of the type 1 fimbriae production involved in the virulence of extra-intestinal pathogenic E. coli. PMID:22139924

In Silico Constraint-Based Strain Optimization Methods: the Quest for Optimal Cell Factories

PubMed Central

Maia, Paulo; Rocha, Miguel

2015-01-01

SUMMARY Shifting from chemical to biotechnological processes is one of the cornerstones of 21st century industry. The production of a great range of chemicals via biotechnological means is a key challenge on the way toward a bio-based economy. However, this shift is occurring at a pace slower than initially expected. The development of efficient cell factories that allow for competitive production yields is of paramount importance for this leap to happen. Constraint-based models of metabolism, together with in silico strain design algorithms, promise to reveal insights into the best genetic design strategies, a step further toward achieving that goal. In this work, a thorough analysis of the main in silico constraint-based strain design strategies and algorithms is presented, their application in real-world case studies is analyzed, and a path for the future is discussed. PMID:26609052

Comparative genomics of grass EST libraries reveals previously uncharacterized splicing events in crop plants.

PubMed

Chuang, Trees-Juen; Yang, Min-Yu; Lin, Chuang-Chieh; Hsieh, Ping-Hung; Hung, Li-Yuan

2015-02-05

Crop plants such as rice, maize and sorghum play economically-important roles as main sources of food, fuel, and animal feed. However, current genome annotations of crop plants still suffer false-positive predictions; a more comprehensive registry of alternative splicing (AS) events is also in demand. Comparative genomics of crop plants is largely unexplored. We performed a large-scale comparative analysis (ExonFinder) of the expressed sequence tag (EST) library from nine grass plants against three crop genomes (rice, maize, and sorghum) and identified 2,879 previously-unannotated exons (i.e., novel exons) in the three crops. We validated 81% of the tested exons by RT-PCR-sequencing, supporting the effectiveness of our in silico strategy. Evolutionary analysis reveals that the novel exons, comparing with their flanking annotated ones, are generally under weaker selection pressure at the protein level, but under stronger pressure at the RNA level, suggesting that most of the novel exons also represent novel alternatively spliced variants (ASVs). However, we also observed the consistency of evolutionary rates between certain novel exons and their flanking exons, which provided further evidence of their co-occurrence in the transcripts, suggesting that previously-annotated isoforms might be subject to erroneous predictions. Our validation showed that 54% of the tested genes expressed the newly-identified isoforms that contained the novel exons, rather than the previously-annotated isoforms that excluded them. The consistent results were steadily observed across cultivated (Oryza sativa and O. glaberrima) and wild (O. rufipogon and O. nivara) rice species, asserting the necessity of our curation of the crop genome annotations. Our comparative analyses also inferred the common ancestral transcriptome of grass plants and gain- and loss-of-ASV events. We have reannotated the rice, maize, and sorghum genomes, and showed that evolutionary rates might serve as an indicator for determining whether the identified exons were alternatively spliced. This study not only presents an effective in silico strategy for the improvement of plant annotations, but also provides further insights into the role of AS events in the evolution and domestication of crop plants. ExonFinder and the novel exons/ASVs identified are publicly accessible at http://exonfinder.sourceforge.net/ .

Human In Silico Drug Trials Demonstrate Higher Accuracy than Animal Models in Predicting Clinical Pro-Arrhythmic Cardiotoxicity.

PubMed

Passini, Elisa; Britton, Oliver J; Lu, Hua Rong; Rohrbacher, Jutta; Hermans, An N; Gallacher, David J; Greig, Robert J H; Bueno-Orovio, Alfonso; Rodriguez, Blanca

2017-01-01

Early prediction of cardiotoxicity is critical for drug development. Current animal models raise ethical and translational questions, and have limited accuracy in clinical risk prediction. Human-based computer models constitute a fast, cheap and potentially effective alternative to experimental assays, also facilitating translation to human. Key challenges include consideration of inter-cellular variability in drug responses and integration of computational and experimental methods in safety pharmacology. Our aim is to evaluate the ability of in silico drug trials in populations of human action potential (AP) models to predict clinical risk of drug-induced arrhythmias based on ion channel information, and to compare simulation results against experimental assays commonly used for drug testing. A control population of 1,213 human ventricular AP models in agreement with experimental recordings was constructed. In silico drug trials were performed for 62 reference compounds at multiple concentrations, using pore-block drug models (IC 50 /Hill coefficient). Drug-induced changes in AP biomarkers were quantified, together with occurrence of repolarization/depolarization abnormalities. Simulation results were used to predict clinical risk based on reports of Torsade de Pointes arrhythmias, and further evaluated in a subset of compounds through comparison with electrocardiograms from rabbit wedge preparations and Ca 2+ -transient recordings in human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs). Drug-induced changes in silico vary in magnitude depending on the specific ionic profile of each model in the population, thus allowing to identify cell sub-populations at higher risk of developing abnormal AP phenotypes. Models with low repolarization reserve (increased Ca 2+ /late Na + currents and Na + /Ca 2+ -exchanger, reduced Na + /K + -pump) are highly vulnerable to drug-induced repolarization abnormalities, while those with reduced inward current density (fast/late Na + and Ca 2+ currents) exhibit high susceptibility to depolarization abnormalities. Repolarization abnormalities in silico predict clinical risk for all compounds with 89% accuracy. Drug-induced changes in biomarkers are in overall agreement across different assays: in silico AP duration changes reflect the ones observed in rabbit QT interval and hiPS-CMs Ca 2+ -transient, and simulated upstroke velocity captures variations in rabbit QRS complex. Our results demonstrate that human in silico drug trials constitute a powerful methodology for prediction of clinical pro-arrhythmic cardiotoxicity, ready for integration in the existing drug safety assessment pipelines.

In Silico and in Vitro Screening for P-Glycoprotein Interaction with Tenofovir, Darunavir, and Dapivirine: An Antiretroviral Drug Combination for Topical Prevention of Colorectal HIV Transmission.

PubMed

Swedrowska, Magda; Jamshidi, Shirin; Kumar, Abhinav; Kelly, Charles; Rahman, Khondaker Miraz; Forbes, Ben

2017-08-07

The aim of the study was to use in silico and in vitro techniques to evaluate whether a triple formulation of antiretroviral drugs (tenofovir, darunavir, and dapivirine) interacted with P-glycoprotein (P-gp) or exhibited any other permeability-altering drug-drug interactions in the colorectal mucosa. Potential drug interactions with P-gp were screened initially using molecular docking, followed by molecular dynamics simulations to analyze the identified drug-transporter interaction more mechanistically. The transport of tenofovir, darunavir, and dapivirine was investigated in the Caco-2 cell models and colorectal tissue, and their apparent permeability coefficient (P app ), efflux ratio (ER), and the effect of transporter inhibitors were evaluated. In silico, dapivirine and darunavir showed strong affinity for P-gp with similar free energy of binding; dapivirine exhibiting a ΔG PB value -38.24 kcal/mol, darunavir a ΔG PB value -36.84 kcal/mol. The rank order of permeability of the compounds in vitro was tenofovir < darunavir < dapivirine. The P app for tenofovir in Caco-2 cell monolayers was 0.10 ± 0.02 × 10 -6 cm/s, ER = 1. For dapivirine, P app was 32.2 ± 3.7 × 10 -6 cm/s, but the ER = 1.3 was lower than anticipated based on the in silico findings. Neither tenofovir nor dapivirine transport was influenced by P-gp inhibitors. The absorptive permeability of darunavir (P app = 6.4 ± 0.9 × 10 -6 cm/s) was concentration dependent with ER = 6.3, which was reduced by verapamil to 1.2. Administration of the drugs in combination did not alter their permeability compared to administration as single agents. In conclusion, in silico modeling, cell culture, and tissue-based assays showed that tenofovir does not interact with P-gp and is poorly permeable, consistent with a paracellular transport mechanism. In silico modeling predicted that darunavir and dapivirine were P-gp substrates, but only darunavir showed P-gp-dependent permeability in the biological models, illustrating that in silico modeling requires experimental validation. When administered in combination, the disposition of the proposed triple-therapy antiretroviral drugs in the colorectal mucosa will depend on their distinctly different permeability, but was not interdependent.

Genome-wide analysis identifies chickpea (Cicer arietinum) heat stress transcription factors (Hsfs) responsive to heat stress at the pod development stage.

PubMed

Chidambaranathan, Parameswaran; Jagannadham, Prasanth Tej Kumar; Satheesh, Viswanathan; Kohli, Deshika; Basavarajappa, Santosh Halasabala; Chellapilla, Bharadwaj; Kumar, Jitendra; Jain, Pradeep Kumar; Srinivasan, R

2018-05-01

The heat stress transcription factors (Hsfs) play a prominent role in thermotolerance and eliciting the heat stress response in plants. Identification and expression analysis of Hsfs gene family members in chickpea would provide valuable information on heat stress responsive Hsfs. A genome-wide analysis of Hsfs gene family resulted in the identification of 22 Hsf genes in chickpea in both desi and kabuli genome. Phylogenetic analysis distinctly separated 12 A, 9 B, and 1 C class Hsfs, respectively. An analysis of cis-regulatory elements in the upstream region of the genes identified many stress responsive elements such as heat stress elements (HSE), abscisic acid responsive element (ABRE) etc. In silico expression analysis showed nine and three Hsfs were also expressed in drought and salinity stresses, respectively. Q-PCR expression analysis of Hsfs under heat stress at pod development and at 15 days old seedling stage showed that CarHsfA2, A6, and B2 were significantly upregulated in both the stages of crop growth and other four Hsfs (CarHsfA2, A6a, A6c, B2a) showed early transcriptional upregulation for heat stress at seedling stage of chickpea. These subclasses of Hsfs identified in this study can be further evaluated as candidate genes in the characterization of heat stress response in chickpea.

In silico structural analysis of group 3, 6 and 9 allergens from Dermatophagoides farinae.

PubMed

Teng, Feixiang; Yu, Lili; Bian, Yonghua; Sun, Jinxia; Wu, Juansong; Ling, Cunbao; Yang, Li; Wang, Yungang; Cui, Yubao

2015-05-01

Dermatophagoides farinae (Hughes; Acari: Pyroglyphidae) are the predominant source of dust mite allergens, which provoke allergic diseases, such as rhinitis, asthma and eczema. Of the 30 allergen groups produced by D. farinae, the Der f 3, Der f 6 and Der f 9 allergens are all trypsin‑associated proteins, however little else is currently known about them. The present study used in silico tools to compare the amino acid sequences, and predict the secondary and tertiary structures of Der f 3, Der f 6 and Der f 9 allergens. Protein sequence alignment detected ~46% identity between Der f 3, Der f 6 and Der f 9. Furthermore, each protein was shown to contain three active sites and two highly conserved trypsin functional domains. Predictions of the secondary and tertiary structure identified α‑helices, β‑sheets and random coils. The active sites of the three proteins appeared to fold onto each other in a three‑dimensional model, constituting the active site of the enzyme. Epitope analysis demonstrated that Der f 3, Der f 6 and Der f 9 have 4‑5 potential epitopes located in random coils, and the epitope sequences of Der f 3, Der f 6 and Der f 9 were shown to overlap in two domains (at amino acids 83‑87 and 179‑180); however the residues in these two domains were not identical. The present study aimed to conduct a biochemical and genetic analysis of these three allergens, and to potentially contribute to the development of vaccines for allergen‑specific immunotherapy.

Application of Genomic Technologies to the Breeding of Trees

PubMed Central

Badenes, Maria L.; Fernández i Martí, Angel; Ríos, Gabino; Rubio-Cabetas, María J.

2016-01-01

The recent introduction of next generation sequencing (NGS) technologies represents a major revolution in providing new tools for identifying the genes and/or genomic intervals controlling important traits for selection in breeding programs. In perennial fruit trees with long generation times and large sizes of adult plants, the impact of these techniques is even more important. High-throughput DNA sequencing technologies have provided complete annotated sequences in many important tree species. Most of the high-throughput genotyping platforms described are being used for studies of genetic diversity and population structure. Dissection of complex traits became possible through the availability of genome sequences along with phenotypic variation data, which allow to elucidate the causative genetic differences that give rise to observed phenotypic variation. Association mapping facilitates the association between genetic markers and phenotype in unstructured and complex populations, identifying molecular markers for assisted selection and breeding. Also, genomic data provide in silico identification and characterization of genes and gene families related to important traits, enabling new tools for molecular marker assisted selection in tree breeding. Deep sequencing of transcriptomes is also a powerful tool for the analysis of precise expression levels of each gene in a sample. It consists in quantifying short cDNA reads, obtained by NGS technologies, in order to compare the entire transcriptomes between genotypes and environmental conditions. The miRNAs are non-coding short RNAs involved in the regulation of different physiological processes, which can be identified by high-throughput sequencing of RNA libraries obtained by reverse transcription of purified short RNAs, and by in silico comparison with known miRNAs from other species. All together, NGS techniques and their applications have increased the resources for plant breeding in tree species, closing the former gap of genetic tools between trees and annual species. PMID:27895664

In silico investigation into the interactions between murine 5-HT3 receptor and the principle active compounds of ginger (Zingiber officinale).

PubMed

Lohning, Anna E; Marx, Wolfgang; Isenring, Liz

2016-11-01

Gingerols and shogaols are the primary non-volatile actives within ginger (Zingiber officinale). These compounds have demonstrated in vitro to exert 5-HT 3 receptor antagonism which could benefit chemotherapy-induced nausea and vomiting (CINV). The site and mechanism of action by which these compounds interact with the 5-HT 3 receptor is not fully understood although research indicates they may bind to a currently unidentified allosteric binding site. Using in silico techniques, such as molecular docking and GRID analysis, we have characterized the recently available murine 5-HT 3 receptor by identifying sites of strong interaction with particular functional groups at both the orthogonal (serotonin) site and a proposed allosteric binding site situated at the interface between the transmembrane region and the extracellular domain. These were assessed concurrently with the top-scoring poses of the docked ligands and included key active gingerols, shogaols and dehydroshogaols as well as competitive antagonists (e.g. setron class of pharmacologically active drugs), serotonin and its structural analogues, curcumin and capsaicin, non-competitive antagonists and decoys. Unexpectedly, we found that the ginger compounds and their structural analogs generally outscored other ligands at both sites. Our results correlated well with previous site-directed mutagenesis studies in identifying key binding site residues. We have identified new residues important for binding the ginger compounds. Overall, the results suggest that the ginger compounds and their structural analogues possess a high binding affinity to both sites. Notwithstanding the limitations of such theoretical analyses, these results suggest that the ginger compounds could act both competitively or non-competitively as has been shown for palonosetron and other modulators of CYS loop receptors. Copyright © 2016 Elsevier Inc. All rights reserved.

Application of Genomic Technologies to the Breeding of Trees.

PubMed

Badenes, Maria L; Fernández I Martí, Angel; Ríos, Gabino; Rubio-Cabetas, María J

2016-01-01

The recent introduction of next generation sequencing (NGS) technologies represents a major revolution in providing new tools for identifying the genes and/or genomic intervals controlling important traits for selection in breeding programs. In perennial fruit trees with long generation times and large sizes of adult plants, the impact of these techniques is even more important. High-throughput DNA sequencing technologies have provided complete annotated sequences in many important tree species. Most of the high-throughput genotyping platforms described are being used for studies of genetic diversity and population structure. Dissection of complex traits became possible through the availability of genome sequences along with phenotypic variation data, which allow to elucidate the causative genetic differences that give rise to observed phenotypic variation. Association mapping facilitates the association between genetic markers and phenotype in unstructured and complex populations, identifying molecular markers for assisted selection and breeding. Also, genomic data provide in silico identification and characterization of genes and gene families related to important traits, enabling new tools for molecular marker assisted selection in tree breeding. Deep sequencing of transcriptomes is also a powerful tool for the analysis of precise expression levels of each gene in a sample. It consists in quantifying short cDNA reads, obtained by NGS technologies, in order to compare the entire transcriptomes between genotypes and environmental conditions. The miRNAs are non-coding short RNAs involved in the regulation of different physiological processes, which can be identified by high-throughput sequencing of RNA libraries obtained by reverse transcription of purified short RNAs, and by in silico comparison with known miRNAs from other species. All together, NGS techniques and their applications have increased the resources for plant breeding in tree species, closing the former gap of genetic tools between trees and annual species.

Unique CD44 intronic SNP is associated with tumor grade in breast cancer: a case control study and in silico analysis.

PubMed

Esmaeili, Rezvan; Abdoli, Nasrin; Yadegari, Fatemeh; Neishaboury, Mohamadreza; Farahmand, Leila; Kaviani, Ahmad; Majidzadeh-A, Keivan

2018-01-01

CD44 encoded by a single gene is a cell surface transmembrane glycoprotein. Exon 2 is one of the important exons to bind CD44 protein to hyaluronan. Experimental evidences show that hyaluronan-CD44 interaction intensifies the proliferation, migration, and invasion of breast cancer cells. Therefore, the current study aimed at investigating the association between specific polymorphisms in exon 2 and its flanking region of CD44 with predisposition to breast cancer. In the current study, 175 Iranian female patients with breast cancer and 175 age-matched healthy controls were recruited in biobank, Breast Cancer Research Center, Tehran, Iran. Single nucleotide polymorphisms of CD44 exon 2 and its flanking were analyzed via polymerase chain reaction and gene sequencing techniques. Association between the observed variation with breast cancer risk and clinico-pathological characteristics were studied. Subsequently, bioinformatics analysis was conducted to predict potential exonic splicing enhancer (ESE) motifs changed as the result of a mutation. A unique polymorphism of the gene encoding CD44 was identified at position 14 nucleotide upstream of exon 2 (A37692→G) by the sequencing method. The A > G polymorphism exhibited a significant association with higher-grades of breast cancer, although no significant relation was found between this polymorphism and breast cancer risk. Finally, computational analysis revealed that the intronic mutation generated a new consensus-binding motif for the splicing factor, SC35, within intron 1. The current study results indicated that A > G polymorphism was associated with breast cancer development; in addition, in silico analysis with ESE finder prediction software showed that the change created a new SC35 binding site.

Label-free proteomic analysis to confirm the predicted proteome of Corynebacterium pseudotuberculosis under nitrosative stress mediated by nitric oxide.

PubMed

Silva, Wanderson M; Carvalho, Rodrigo D; Soares, Siomar C; Bastos, Isabela Fs; Folador, Edson L; Souza, Gustavo Hmf; Le Loir, Yves; Miyoshi, Anderson; Silva, Artur; Azevedo, Vasco

2014-12-04

Corynebacterium pseudotuberculosis biovar ovis is a facultative intracellular pathogen, and the etiological agent of caseous lymphadenitis in small ruminants. During the infection process, the bacterium is subjected to several stress conditions, including nitrosative stress, which is caused by nitric oxide (NO). In silico analysis of the genome of C. pseudotuberculosis ovis 1002 predicted several genes that could influence the resistance of this pathogen to nitrosative stress. Here, we applied high-throughput proteomics using high definition mass spectrometry to characterize the functional genome of C. pseudotuberculosis ovis 1002 in the presence of NO-donor Diethylenetriamine/nitric oxide adduct (DETA/NO), with the aim of identifying proteins involved in nitrosative stress resistance. We characterized 835 proteins, representing approximately 41% of the predicted proteome of C. pseudotuberculosis ovis 1002, following exposure to nitrosative stress. In total, 102 proteins were exclusive to the proteome of DETA/NO-induced cells, and a further 58 proteins were differentially regulated between the DETA/NO and control conditions. An interactomic analysis of the differential proteome of C. pseudotuberculosis in response to nitrosative stress was also performed. Our proteomic data set suggested the activation of both a general stress response and a specific nitrosative stress response, as well as changes in proteins involved in cellular metabolism, detoxification, transcriptional regulation, and DNA synthesis and repair. Our proteomic analysis validated previously-determined in silico data for C. pseudotuberculosis ovis 1002. In addition, proteomic screening performed in the presence of NO enabled the identification of a set of factors that can influence the resistance and survival of C. pseudotuberculosis during exposure to nitrosative stress.

Identification of ageing-associated naturally occurring peptides in human urine

PubMed Central

Nkuipou-Kenfack, Esther; Bhat, Akshay; Klein, Julie; Jankowski, Vera; Mullen, William; Vlahou, Antonia; Dakna, Mohammed; Koeck, Thomas; Schanstra, Joost P.; Zürbig, Petra; Rudolph, Karl L.; Schumacher, Björn; Pich, Andreas; Mischak, Harald

2015-01-01

To assess normal and pathological peptidomic changes that may lead to an improved understanding of molecular mechanisms underlying ageing, urinary peptidomes of 1227 healthy and 10333 diseased individuals between 20 and 86 years of age were investigated. The diseases thereby comprised diabetes mellitus, renal and cardiovascular diseases. Using age as a continuous variable, 116 peptides were identified that significantly (p < 0.05; |ρ|≥0.2) correlated with age in the healthy cohort. The same approach was applied to the diseased cohort. Upon comparison of the peptide patterns of the two cohorts 112 common age-correlated peptides were identified. These 112 peptides predominantly originated from collagen, uromodulin and fibrinogen. While most fibrillar and basement membrane collagen fragments showed a decreased age-related excretion, uromodulin, beta-2-microglobulin and fibrinogen fragments showed an increase. Peptide-based in silico protease analysis was performed and 32 proteases, including matrix metalloproteinases and cathepsins, were predicted to be involved in ageing. Identified peptides, predicted proteases and patient information were combined in a systems biology pathway analysis to identify molecular pathways associated with normal and/or pathological ageing. While perturbations in collagen homeostasis, trafficking of toll-like receptors and endosomal pathways were commonly identified, degradation of insulin-like growth factor-binding proteins was uniquely identified in pathological ageing. PMID:26431327

In silico profiling of Escherichia coli and Saccharomyces cerevisiae as terpenoid factories

PubMed Central

2013-01-01

Background Heterologous microbial production of rare plant terpenoids of medicinal or industrial interest is attracting more and more attention but terpenoid yields are still low. Escherichia coli and Saccharomyces cerevisiae are the most widely used heterologous hosts; a direct comparison of both hosts based on experimental data is difficult though. Hence, the terpenoid pathways of E. coli (via 1-deoxy-D-xylulose 5-phosphate, DXP) and S. cerevisiae (via mevalonate, MVA), the impact of the respective hosts metabolism as well as the impact of different carbon sources were compared in silico by means of elementary mode analysis. The focus was set on the yield of isopentenyl diphosphate (IPP), the general terpenoid precursor, to identify new metabolic engineering strategies for an enhanced terpenoid yield. Results Starting from the respective precursor metabolites of the terpenoid pathways (pyruvate and glyceraldehyde-3-phosphate for the DXP pathway and acetyl-CoA for the MVA pathway) and considering only carbon stoichiometry, the two terpenoid pathways are identical with respect to carbon yield. However, with glucose as substrate, the MVA pathway has a lower potential to supply terpenoids in high yields than the DXP pathway if the formation of the required precursors is taken into account, due to the carbon loss in the formation of acetyl-CoA. This maximum yield is further reduced in both hosts when the required energy and reduction equivalents are considered. Moreover, the choice of carbon source (glucose, xylose, ethanol or glycerol) has an effect on terpenoid yield with non-fermentable carbon sources being more promising. Both hosts have deficiencies in energy and redox equivalents for high yield terpenoid production leading to new overexpression strategies (heterologous enzymes/pathways) for an enhanced terpenoid yield. Finally, several knockout strategies are identified using constrained minimal cut sets enforcing a coupling of growth to a terpenoid yield which is higher than any yield published in scientific literature so far. Conclusions This study provides for the first time a comprehensive and detailed in silico comparison of the most prominent heterologous hosts E. coli and S. cerevisiae as terpenoid factories giving an overview on several promising metabolic engineering strategies paving the way for an enhanced terpenoid yield. PMID:24059635

DNA barcoding coupled to HRM analysis as a new and simple tool for the authentication of Gadidae fish species.

PubMed

Fernandes, Telmo J R; Costa, Joana; Oliveira, M Beatriz P P; Mafra, Isabel

2017-09-01

This work aimed to exploit the use of DNA mini-barcodes combined with high resolution melting (HRM) for the authentication of gadoid species: Atlantic cod (Gadus morhua), Pacific cod (Gadus macrocephalus), Alaska pollock (Theragra chalcogramma) and saithe (Pollachius virens). Two DNA barcode regions, namely cytochrome c oxidase subunit I (COI) and cytochrome b (cytb), were analysed in silico to identify genetic variability among the four species and used, subsequently, to develop a real-time PCR method coupled with HRM analysis. The cytb mini-barcode enabled best discrimination of the target species with a high level of confidence (99.3%). The approach was applied successfully to identify gadoid species in 30 fish-containing foods, 30% of which were not as declared on the label. Herein, a novel approach for rapid, simple and cost-effective discrimination/clustering, as a tool to authenticate Gadidae fish species, according to their genetic relationship, is proposed. Copyright © 2017 Elsevier Ltd. All rights reserved.

WEbcoli: an interactive and asynchronous web application for in silico design and analysis of genome-scale E.coli model.

PubMed

Jung, Tae-Sung; Yeo, Hock Chuan; Reddy, Satty G; Cho, Wan-Sup; Lee, Dong-Yup

2009-11-01

WEbcoli is a WEb application for in silico designing, analyzing and engineering Escherichia coli metabolism. It is devised and implemented using advanced web technologies, thereby leading to enhanced usability and dynamic web accessibility. As a main feature, the WEbcoli system provides a user-friendly rich web interface, allowing users to virtually design and synthesize mutant strains derived from the genome-scale wild-type E.coli model and to customize pathways of interest through a graph editor. In addition, constraints-based flux analysis can be conducted for quantifying metabolic fluxes and charactering the physiological and metabolic states under various genetic and/or environmental conditions. WEbcoli is freely accessible at http://webcoli.org. cheld@nus.edu.sg.

An enhanced genome-scale metabolic reconstruction of Streptomyces clavuligerus identifies novel strain improvement strategies.

PubMed

Toro, León; Pinilla, Laura; Avignone-Rossa, Claudio; Ríos-Estepa, Rigoberto

2018-05-01

In this work, we expanded and updated a genome-scale metabolic model of Streptomyces clavuligerus. The model includes 1021 genes and 1494 biochemical reactions; genome-reaction information was curated and new features related to clavam metabolism and to the biomass synthesis equation were incorporated. The model was validated using experimental data from the literature and simulations were performed to predict cellular growth and clavulanic acid biosynthesis. Flux balance analysis (FBA) showed that limiting concentrations of phosphate and an excess of ammonia accumulation are unfavorable for growth and clavulanic acid biosynthesis. The evaluation of different objective functions for FBA showed that maximization of ATP yields the best predictions for cellular behavior in continuous cultures, while the maximization of growth rate provides better predictions for batch cultures. Through gene essentiality analysis, 130 essential genes were found using a limited in silico media, while 100 essential genes were identified in amino acid-supplemented media. Finally, a strain design was carried out to identify candidate genes to be overexpressed or knocked out so as to maximize antibiotic biosynthesis. Interestingly, potential metabolic engineering targets, identified in this study, have not been tested experimentally.

In Silico and Fluorescence In Situ Hybridization Mapping Reveals Collinearity between the Pennisetum squamulatum Apomixis Carrier-Chromosome and Chromosome 2 of Sorghum and Foxtail Millet.

PubMed

Sapkota, Sirjan; Conner, Joann A; Hanna, Wayne W; Simon, Bindu; Fengler, Kevin; Deschamps, Stéphane; Cigan, Mark; Ozias-Akins, Peggy

2016-01-01

Apomixis, or clonal propagation through seed, is a trait identified within multiple species of the grass family (Poaceae). The genetic locus controlling apomixis in Pennisetum squamulatum (syn Cenchrus squamulatus) and Cenchrus ciliaris (syn Pennisetum ciliare, buffelgrass) is the apospory-specific genomic region (ASGR). Previously, the ASGR was shown to be highly conserved but inverted in marker order between P. squamulatum and C. ciliaris based on fluorescence in situ hybridization (FISH) and varied in both karyotype and position of the ASGR on the ASGR-carrier chromosome among other apomictic Cenchrus/Pennisetum species. Using in silico transcript mapping and verification of physical positions of some of the transcripts via FISH, we discovered that the ASGR-carrier chromosome from P. squamulatum is collinear with chromosome 2 of foxtail millet and sorghum outside of the ASGR. The in silico ordering of the ASGR-carrier chromosome markers, previously unmapped in P. squamulatum, allowed for the identification of a backcross line with structural changes to the P. squamulatum ASGR-carrier chromosome derived from gamma irradiated pollen.

In Silico and Fluorescence In Situ Hybridization Mapping Reveals Collinearity between the Pennisetum squamulatum Apomixis Carrier-Chromosome and Chromosome 2 of Sorghum and Foxtail Millet

PubMed Central

Sapkota, Sirjan; Conner, Joann A.; Hanna, Wayne W.; Simon, Bindu; Fengler, Kevin; Deschamps, Stéphane; Cigan, Mark; Ozias-Akins, Peggy

2016-01-01

Apomixis, or clonal propagation through seed, is a trait identified within multiple species of the grass family (Poaceae). The genetic locus controlling apomixis in Pennisetum squamulatum (syn Cenchrus squamulatus) and Cenchrus ciliaris (syn Pennisetum ciliare, buffelgrass) is the apospory-specific genomic region (ASGR). Previously, the ASGR was shown to be highly conserved but inverted in marker order between P. squamulatum and C. ciliaris based on fluorescence in situ hybridization (FISH) and varied in both karyotype and position of the ASGR on the ASGR-carrier chromosome among other apomictic Cenchrus/Pennisetum species. Using in silico transcript mapping and verification of physical positions of some of the transcripts via FISH, we discovered that the ASGR-carrier chromosome from P. squamulatum is collinear with chromosome 2 of foxtail millet and sorghum outside of the ASGR. The in silico ordering of the ASGR-carrier chromosome markers, previously unmapped in P. squamulatum, allowed for the identification of a backcross line with structural changes to the P. squamulatum ASGR-carrier chromosome derived from gamma irradiated pollen. PMID:27031857

FutureTox II: In vitro Data and In Silico Models for Predictive Toxicology

PubMed Central

Knudsen, Thomas B.; Keller, Douglas A.; Sander, Miriam; Carney, Edward W.; Doerrer, Nancy G.; Eaton, David L.; Fitzpatrick, Suzanne Compton; Hastings, Kenneth L.; Mendrick, Donna L.; Tice, Raymond R.; Watkins, Paul B.; Whelan, Maurice

2015-01-01

FutureTox II, a Society of Toxicology Contemporary Concepts in Toxicology workshop, was held in January, 2014. The meeting goals were to review and discuss the state of the science in toxicology in the context of implementing the NRC 21st century vision of predicting in vivo responses from in vitro and in silico data, and to define the goals for the future. Presentations and discussions were held on priority concerns such as predicting and modeling of metabolism, cell growth and differentiation, effects on sensitive subpopulations, and integrating data into risk assessment. Emerging trends in technologies such as stem cell-derived human cells, 3D organotypic culture models, mathematical modeling of cellular processes and morphogenesis, adverse outcome pathway development, and high-content imaging of in vivo systems were discussed. Although advances in moving towards an in vitro/in silico based risk assessment paradigm were apparent, knowledge gaps in these areas and limitations of technologies were identified. Specific recommendations were made for future directions and research needs in the areas of hepatotoxicity, cancer prediction, developmental toxicity, and regulatory toxicology. PMID:25628403

[Pulmonary arterial hypertension associated with human immunodeficiency virus infection: study of 4 cases].

PubMed

Pousada, Guillermo; Baloira, Adolfo; Castro-Añón, Olalla; Valverde, Diana

2016-04-15

Pulmonary arterial hypertension (PAH) is a rare and progressive disease that can be inherited as autosomal dominant form. The BMPR2, ACVRL1 and ENG genes are main genes involved in the pathology. PAH associated to human immunodeficiency virus (HIV) is another rare disease with a low incidence, prevalence and survival. The main objective of this analysis was to study the clinical and molecular characteristics of PAH associated to HIV patients. We present 4 cases of HIV patients who developed PAH and have been treated with ambrisentan. Pathogenic mutations have been identify in analyzed genes in 3 of the four analyzed patients. In addition, these patients present other changes classified as benign after a thorough in silico analysis. We identified some changes in genetic modifiers that predispose to these patients to more severe phenotype. The clinical analysis can help to define monitoring for these patients and the administration of appropriate treatment. These patients also have shown several pathogenic mutations. Copyright © 2016 Elsevier España, S.L.U. All rights reserved.

A two-dimensional electrophoretic profile of the proteins secreted by Herbaspirillum seropedicae strain Z78.

PubMed

Chaves, Daniela Fojo Seixas; de Souza, Emanuel Maltempi; Monteiro, Rose Adele; de Oliveira Pedrosa, Fábio

2009-11-02

Herbaspirillum seropedicae is an endophytic bacterium that associates with rice, sugarcane and other economically important crops. Secreted proteins play a key role in the plant-bacterial interaction. Using 2D electrophoresis and peptide mass fingerprint mass spectrometry, 63 protein spots representing 41 different secreted proteins were identified during growth of H. seropedicae under nitrogen-sufficient conditions. In silico analysis showed that 25.4% of the proteins had signal peptides and 15.9% were predicted to be non-classically secreted. Among the most abundant were flagellar components and ABC-type transport system proteins. Nine secreted proteins had also been identified in the cellular proteome, suggesting that they also play a role in the extracellular environment. No type III secreted proteins were detected by comparison of the wild type strain with an hrcN mutant strain.

[Molecular cloning and characterization in silico of phospholipase A(2) transcript isolated from Lachesis muta peruvian snake venom].

PubMed

Jimenez, Karim L; Zavaleta, Amparo I; Izaguirre, Victor; Yarleque, Armando; Inga, Rosio R

2010-01-01

Isolate and characterize in silico gene phospholipase A(2) (PLA(2)) isolated from Lachesis muta venom of the Peruvian Amazon. Technique RT-PCR from total RNA was using specific primers, the amplified DNA product was inserted into the pGEM vector for subsequent sequencing. By bioinformatic analysis identified an open reading frame of 414 nucleotides that encoded 138 amino acids including a signal peptide of 16 aminoacids, molecular weight and pI were 13,976 kDa and 5.66 respectively. The aminoacid sequence was called Lm-PLA(2)-Peru, contains an aspartate at position 49, this aminoacid in conjunction with other conserved residues such as Tyr-28, Gly-30, Gly-32, His-48, Tyr52, Asp99 are important for enzymatic activity. The comparison with the amino acid sequence data banks showed of similarity between PLA(2) from Lachesis stenophrys (93%) and other PLA(2) snake venoms and over 80% of other sPLA(2) family Viperidae venoms. A phylogenetic analysis showed that Lm-PLA(2)-Peru grouped with other acidic [Asp(49)] sPLA(2) previously isolated from Bothriechis schlegelii venom showing 89 % nucleotide sequence identity. Finally, the computer modeling indicated that enzyme had the characteristic structure of sPLA(2) group II that consisted of three α-helices, a β-wing, a short helix and a calcium-binding loop. The nucleotide sequence corresponding to the first transcript of gene from PLA(2) cloned of Lachesis muta venom, snake from the Peruvian rainforest.

In silico designing of power conversion efficient organic lead dyes for solar cells using todays innovative approaches to assure renewable energy for future

NASA Astrophysics Data System (ADS)

Kar, Supratik; Roy, Juganta K.; Leszczynski, Jerzy

2017-06-01

Advances in solar cell technology require designing of new organic dye sensitizers for dye-sensitized solar cells with high power conversion efficiency to circumvent the disadvantages of silicon-based solar cells. In silico studies including quantitative structure-property relationship analysis combined with quantum chemical analysis were employed to understand the primary electron transfer mechanism and photo-physical properties of 273 arylamine organic dyes from 11 diverse chemical families explicit to iodine electrolyte. The direct quantitative structure-property relationship models enable identification of the essential electronic and structural attributes necessary for quantifying the molecular prerequisites of 11 classes of arylamine organic dyes, responsible for high power conversion efficiency of dye-sensitized solar cells. Tetrahydroquinoline, N,N'-dialkylaniline and indoline have been least explored classes under arylamine organic dyes for dye-sensitized solar cells. Therefore, the identified properties from the corresponding quantitative structure-property relationship models of the mentioned classes were employed in designing of "lead dyes". Followed by, a series of electrochemical and photo-physical parameters were computed for designed dyes to check the required variables for electron flow of dye-sensitized solar cells. The combined computational techniques yielded seven promising lead dyes each for all three chemical classes considered. Significant (130, 183, and 46%) increment in predicted %power conversion efficiency was observed comparing with the existing dye with highest experimental %power conversion efficiency value for tetrahydroquinoline, N,N'-dialkylaniline and indoline, respectively maintaining required electrochemical parameters.

Isolation and characterization of full-length putative alcohol dehydrogenase genes from polygonum minus

NASA Astrophysics Data System (ADS)

Hamid, Nur Athirah Abd; Ismail, Ismanizan

2013-11-01

Polygonum minus, locally named as Kesum is an aromatic herb which is high in secondary metabolite content. Alcohol dehydrogenase is an important enzyme that catalyzes the reversible oxidation of alcohol and aldehyde with the presence of NAD(P)(H) as co-factor. The main focus of this research is to identify the gene of ADH. The total RNA was extracted from leaves of P. minus which was treated with 150 μM Jasmonic acid. Full-length cDNA sequence of ADH was isolated via rapid amplification cDNA end (RACE). Subsequently, in silico analysis was conducted on the full-length cDNA sequence and PCR was done on genomic DNA to determine the exon and intron organization. Two sequences of ADH, designated as PmADH1 and PmADH2 were successfully isolated. Both sequences have ORF of 801 bp which encode 266 aa residues. Nucleotide sequence comparison of PmADH1 and PmADH2 indicated that both sequences are highly similar at the ORF region but divergent in the 3' untranslated regions (UTR). The amino acid is differ at the 107 residue; PmADH1 contains Gly (G) residue while PmADH2 contains Cys (C) residue. The intron-exon organization pattern of both sequences are also same, with 3 introns and 4 exons. Based on in silico analysis, both sequences contain "classical" short chain alcohol dehydrogenases/reductases ((c) SDRs) conserved domain. The results suggest that both sequences are the members of short chain alcohol dehydrogenase family.

Evolutionary distance from human homologs reflects allergenicity of animal food proteins.

PubMed

Jenkins, John A; Breiteneder, Heimo; Mills, E N Clare

2007-12-01

In silico analysis of allergens can identify putative relationships among protein sequence, structure, and allergenic properties. Such systematic analysis reveals that most plant food allergens belong to a restricted number of protein superfamilies, with pollen allergens behaving similarly. We have investigated the structural relationships of animal food allergens and their evolutionary relatedness to human homologs to define how closely a protein must resemble a human counterpart to lose its allergenic potential. Profile-based sequence homology methods were used to classify animal food allergens into Pfam families, and in silico analyses of their evolutionary and structural relationships were performed. Animal food allergens could be classified into 3 main families--tropomyosins, EF-hand proteins, and caseins--along with 14 minor families each composed of 1 to 3 allergens. The evolutionary relationships of each of these allergen superfamilies showed that in general, proteins with a sequence identity to a human homolog above approximately 62% were rarely allergenic. Single substitutions in otherwise highly conserved regions containing IgE epitopes in EF-hand parvalbumins may modulate allergenicity. These data support the premise that certain protein structures are more allergenic than others. Contrasting with plant food allergens, animal allergens, such as the highly conserved tropomyosins, challenge the capability of the human immune system to discriminate between foreign and self-proteins. Such immune responses run close to becoming autoimmune responses. Exploiting the closeness between animal allergens and their human homologs in the development of recombinant allergens for immunotherapy will need to consider the potential for developing unanticipated autoimmune responses.

Meta-analysis of genome-wide association studies in East Asian-ancestry populations identifies four new loci for body mass index

PubMed Central

Wen, Wanqing; Zheng, Wei; Okada, Yukinori; Takeuchi, Fumihiko; Tabara, Yasuharu; Hwang, Joo-Yeon; Dorajoo, Rajkumar; Li, Huaixing; Tsai, Fuu-Jen; Yang, Xiaobo; He, Jiang; Wu, Ying; He, Meian; Zhang, Yi; Liang, Jun; Guo, Xiuqing; Sheu, Wayne Huey-Herng; Delahanty, Ryan; Guo, Xingyi; Kubo, Michiaki; Yamamoto, Ken; Ohkubo, Takayoshi; Go, Min Jin; Liu, Jian Jun; Gan, Wei; Chen, Ching-Chu; Gao, Yong; Li, Shengxu; Lee, Nanette R.; Wu, Chen; Zhou, Xueya; Song, Huaidong; Yao, Jie; Lee, I-Te; Long, Jirong; Tsunoda, Tatsuhiko; Akiyama, Koichi; Takashima, Naoyuki; Cho, Yoon Shin; Ong, Rick TH; Lu, Ling; Chen, Chien-Hsiun; Tan, Aihua; Rice, Treva K; Adair, Linda S.; Gui, Lixuan; Allison, Matthew; Lee, Wen-Jane; Cai, Qiuyin; Isomura, Minoru; Umemura, Satoshi; Kim, Young Jin; Seielstad, Mark; Hixson, James; Xiang, Yong-Bing; Isono, Masato; Kim, Bong-Jo; Sim, Xueling; Lu, Wei; Nabika, Toru; Lee, Juyoung; Lim, Wei-Yen; Gao, Yu-Tang; Takayanagi, Ryoichi; Kang, Dae-Hee; Wong, Tien Yin; Hsiung, Chao Agnes; Wu, I-Chien; Juang, Jyh-Ming Jimmy; Shi, Jiajun; Choi, Bo Youl; Aung, Tin; Hu, Frank; Kim, Mi Kyung; Lim, Wei Yen; Wang, Tzung-Dao; Shin, Min-Ho; Lee, Jeannette; Ji, Bu-Tian; Lee, Young-Hoon; Young, Terri L.; Shin, Dong Hoon; Chun, Byung-Yeol; Cho, Myeong-Chan; Han, Bok-Ghee; Hwu, Chii-Min; Assimes, Themistocles L.; Absher, Devin; Yan, Xiaofei; Kim, Eric; Kuo, Jane Z.; Kwon, Soonil; Taylor, Kent D.; Chen, Yii-Der I.; Rotter, Jerome I.; Qi, Lu; Zhu, Dingliang; Wu, Tangchun; Mohlke, Karen L.; Gu, Dongfeng; Mo, Zengnan; Wu, Jer-Yuarn; Lin, Xu; Miki, Tetsuro; Tai, E. Shyong; Lee, Jong-Young; Kato, Norihiro; Shu, Xiao-Ou; Tanaka, Toshihiro

2014-01-01

Recent genetic association studies have identified 55 genetic loci associated with obesity or body mass index (BMI). The vast majority, 51 loci, however, were identified in European-ancestry populations. We conducted a meta-analysis of associations between BMI and ∼2.5 million genotyped or imputed single nucleotide polymorphisms among 86 757 individuals of Asian ancestry, followed by in silico and de novo replication among 7488–47 352 additional Asian-ancestry individuals. We identified four novel BMI-associated loci near the KCNQ1 (rs2237892, P = 9.29 × 10−13), ALDH2/MYL2 (rs671, P = 3.40 × 10−11; rs12229654, P = 4.56 × 10−9), ITIH4 (rs2535633, P = 1.77 × 10−10) and NT5C2 (rs11191580, P = 3.83 × 10−8) genes. The association of BMI with rs2237892, rs671 and rs12229654 was significantly stronger among men than among women. Of the 51 BMI-associated loci initially identified in European-ancestry populations, we confirmed eight loci at the genome-wide significance level (P < 5.0 × 10−8) and an additional 14 at P < 1.0 × 10−3 with the same direction of effect as reported previously. Findings from this analysis expand our knowledge of the genetic basis of obesity. PMID:24861553

Computational analysis of ribonomics datasets identifies long non-coding RNA targets of γ-herpesviral miRNAs.

PubMed

Sethuraman, Sunantha; Thomas, Merin; Gay, Lauren A; Renne, Rolf

2018-05-29

Ribonomics experiments involving crosslinking and immuno-precipitation (CLIP) of Ago proteins have expanded the understanding of the miRNA targetome of several organisms. These techniques, collectively referred to as CLIP-seq, have been applied to identifying the mRNA targets of miRNAs expressed by Kaposi's Sarcoma-associated herpes virus (KSHV) and Epstein-Barr virus (EBV). However, these studies focused on identifying only those RNA targets of KSHV and EBV miRNAs that are known to encode proteins. Recent studies have demonstrated that long non-coding RNAs (lncRNAs) are also targeted by miRNAs. In this study, we performed a systematic re-analysis of published datasets from KSHV- and EBV-driven cancers. We used CLIP-seq data from lymphoma cells or EBV-transformed B cells, and a crosslinking, ligation and sequencing of hybrids dataset from KSHV-infected endothelial cells, to identify novel lncRNA targets of viral miRNAs. Here, we catalog the lncRNA targetome of KSHV and EBV miRNAs, and provide a detailed in silico analysis of lncRNA-miRNA binding interactions. Viral miRNAs target several hundred lncRNAs, including a subset previously shown to be aberrantly expressed in human malignancies. In addition, we identified thousands of lncRNAs to be putative targets of human miRNAs, suggesting that miRNA-lncRNA interactions broadly contribute to the regulation of gene expression.

Systems Toxicology of Embryo Development (9th Copenhagen Workshop)

EPA Science Inventory

An important consideration for predictive toxicology is to identify developmental hazards utilizing mechanism-based in vitro assays (e.g., ToxCast) and in silico multiscale models. Steady progress has been made with agent-based models that recapitulate morphogenetic drivers for a...

Toward the Rational Use of Exposure Information in Mixtures Toxicology

EPA Science Inventory

Of all the disciplines of toxicology, perhaps none is as dependent on exposure information as Mixtures Toxicology. Identifying real world mixtures and replicating them in the laboratory (or in silico) is critical to understanding their risks. Complex mixtures such as cigarett...

In silico environmental chemical science: properties and processes from statistical and computational modelling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tratnyek, Paul G.; Bylaska, Eric J.; Weber, Eric J.

2017-01-01

Quantitative structure–activity relationships (QSARs) have long been used in the environmental sciences. More recently, molecular modeling and chemoinformatic methods have become widespread. These methods have the potential to expand and accelerate advances in environmental chemistry because they complement observational and experimental data with “in silico” results and analysis. The opportunities and challenges that arise at the intersection between statistical and theoretical in silico methods are most apparent in the context of properties that determine the environmental fate and effects of chemical contaminants (degradation rate constants, partition coefficients, toxicities, etc.). The main example of this is the calibration of QSARs usingmore » descriptor variable data calculated from molecular modeling, which can make QSARs more useful for predicting property data that are unavailable, but also can make them more powerful tools for diagnosis of fate determining pathways and mechanisms. Emerging opportunities for “in silico environmental chemical science” are to move beyond the calculation of specific chemical properties using statistical models and toward more fully in silico models, prediction of transformation pathways and products, incorporation of environmental factors into model predictions, integration of databases and predictive models into more comprehensive and efficient tools for exposure assessment, and extending the applicability of all the above from chemicals to biologicals and materials.« less

In vitro, in vivo and in silico analysis of the anticancer and estrogen-like activity of guava leaf extracts.

PubMed

Rizzo, L Y; Longato, G B; Ruiz, A Lt G; Tinti, S V; Possenti, A; Vendramini-Costa, D B; Sartoratto, A; Figueira, G M; Silva, F L N; Eberlin, M N; Souza, T A C B; Murakami, M T; Rizzo, E; Foglio, M A; Kiessling, F; Lammers, T; Carvalho, J E

2014-01-01

Anticancer drug research based on natural compounds enabled the discovery of many drugs currently used in cancer therapy. Here, we report the in vitro, in vivo and in silico anticancer and estrogen-like activity of Psidium guajava L. (guava) extracts and enriched mixture containing the meroterpenes guajadial, psidial A and psiguadial A and B. All samples were evaluated in vitro for anticancer activity against nine human cancer lines: K562 (leukemia), MCF7 (breast), NCI/ADR-RES (resistant ovarian cancer), NCI-H460 (lung), UACC-62 (melanoma), PC-3 (prostate), HT-29 (colon), OVCAR-3 (ovarian) and 786-0 (kidney). Psidium guajava's active compounds displayed similar physicochemical properties to estradiol and tamoxifen, as in silico molecular docking studies demonstrated that they fit into the estrogen receptors (ERs). The meroterpene-enriched fraction was also evaluated in vivo in a Solid Ehrlich murine breast adenocarcinoma model, and showed to be highly effective in inhibiting tumor growth, also demonstrating uterus increase in comparison to negative controls. The ability of guajadial, psidial A and psiguadials A and B to reduce tumor growth and stimulate uterus proliferation, as well as their in silico docking similarity to tamoxifen, suggest that these compounds may act as Selective Estrogen Receptors Modulators (SERMs), therefore holding significant potential for anticancer therapy.

In silico comparative analysis of SSR markers in plants

PubMed Central

2011-01-01

Background The adverse environmental conditions impose extreme limitation to growth and plant development, restricting the genetic potential and reflecting on plant yield losses. The progress obtained by classic plant breeding methods aiming at increasing abiotic stress tolerances have not been enough to cope with increasing food demands. New target genes need to be identified to reach this goal, which requires extensive studies of the related biological mechanisms. Comparative analyses in ancestral plant groups can help to elucidate yet unclear biological processes. Results In this study, we surveyed the occurrence patterns of expressed sequence tag-derived microsatellite markers for model plants. A total of 13,133 SSR markers were discovered using the SSRLocator software in non-redundant EST databases made for all eleven species chosen for this study. The dimer motifs are more frequent in lower plant species, such as green algae and mosses, and the trimer motifs are more frequent for the majority of higher plant groups, such as monocots and dicots. With this in silico study we confirm several microsatellite plant survey results made with available bioinformatics tools. Conclusions The comparative studies of EST-SSR markers among all plant lineages is well suited for plant evolution studies as well as for future studies of transferability of molecular markers. PMID:21247422

An in silico pan-genomic probe for the molecular traits behind Lactobacillus ruminis gut autochthony.

PubMed

Kant, Ravi; Palva, Airi; von Ossowski, Ingemar

2017-01-01

As an ecological niche, the mammalian intestine provides the ideal habitat for a variety of bacterial microorganisms. Purportedly, some commensal genera and species offer a beneficial mix of metabolic, protective, and structural processes that help sustain the natural digestive health of the host. Among these sort of gut inhabitants is the Gram-positive lactic acid bacterium Lactobacillus ruminis, a strict anaerobe with both pili and flagella on its cell surface, but also known for being autochthonous (indigenous) to the intestinal environment. Given that the molecular basis of gut autochthony for this species is largely unexplored and unknown, we undertook a study at the genome level to pinpoint some of the adaptive traits behind its colonization behavior. In our pan-genomic probe of L. ruminis, the genomes of nine different strains isolated from human, bovine, porcine, and equine host guts were compiled and compared for in silico analysis. For this, we conducted a geno-phenotypic assessment of protein-coding genes, with an emphasis on those products involved with cell-surface morphology and anaerobic fermentation and respiration. We also categorized and examined the core and accessory genes that define the L. ruminis species and its strains. Here, we made an attempt to identify those genes having ecologically relevant phenotypes that might support or bring about intestinal indigenousness.

In Silico Characterization of miRNA and Long Non-Coding RNA Interplay in Multiple Myeloma

PubMed Central

Ronchetti, Domenica; Manzoni, Martina; Todoerti, Katia; Neri, Antonino; Agnelli, Luca

2016-01-01

The identification of deregulated microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) in multiple myeloma (MM) has progressively added a further level of complexity to MM biology. In addition, the cross-regulation between lncRNAs and miRNAs has begun to emerge, and theoretical and experimental studies have demonstrated the competing endogenous RNA (ceRNA) activity of lncRNAs as natural miRNA decoys in pathophysiological conditions, including cancer. Currently, information concerning lncRNA and miRNA interplay in MM is virtually absent. Herein, we investigated in silico the lncRNA and miRNA relationship in a representative datasets encompassing 95 MM and 30 plasma cell leukemia patients at diagnosis and in four normal controls, whose expression profiles were generated by a custom annotation pipeline to detect specific lncRNAs. We applied target prediction analysis based on miRanda and RNA22 algorithms to 235 lncRNAs and 459 miRNAs selected with a potential pivotal role in the pathology of MM. Among pairs that showed a significant correlation between lncRNA and miRNA expression levels, we identified 11 lncRNA–miRNA relationships suggestive of a novel ceRNA network with relevance in MM. PMID:27916857

Discovering novel phenotypes with automatically inferred dynamic models: a partial melanocyte conversion in Xenopus

NASA Astrophysics Data System (ADS)

Lobo, Daniel; Lobikin, Maria; Levin, Michael

2017-01-01

Progress in regenerative medicine requires reverse-engineering cellular control networks to infer perturbations with desired systems-level outcomes. Such dynamic models allow phenotypic predictions for novel perturbations to be rapidly assessed in silico. Here, we analyzed a Xenopus model of conversion of melanocytes to a metastatic-like phenotype only previously observed in an all-or-none manner. Prior in vivo genetic and pharmacological experiments showed that individual animals either fully convert or remain normal, at some characteristic frequency after a given perturbation. We developed a Machine Learning method which inferred a model explaining this complex, stochastic all-or-none dataset. We then used this model to ask how a new phenotype could be generated: animals in which only some of the melanocytes converted. Systematically performing in silico perturbations, the model predicted that a combination of altanserin (5HTR2 inhibitor), reserpine (VMAT inhibitor), and VP16-XlCreb1 (constitutively active CREB) would break the all-or-none concordance. Remarkably, applying the predicted combination of three reagents in vivo revealed precisely the expected novel outcome, resulting in partial conversion of melanocytes within individuals. This work demonstrates the capability of automated analysis of dynamic models of signaling networks to discover novel phenotypes and predictively identify specific manipulations that can reach them.

Degradation of Aflatoxins by Means of Laccases from Trametes versicolor: An In Silico Insight.

PubMed

Dellafiora, Luca; Galaverna, Gianni; Reverberi, Massimo; Dall'Asta, Chiara

2017-01-01

Mycotoxins are secondary metabolites of fungi that contaminate food and feed, and are involved in a series of foodborne illnesses and disorders in humans and animals. The mitigation of mycotoxin content via enzymatic degradation is a strategy to ensure safer food and feed, and to address the forthcoming issues in view of the global trade and sustainability. Nevertheless, the search for active enzymes is still challenging and time-consuming. The in silico analysis may strongly support the research by providing the evidence-based hierarchization of enzymes for a rational design of more effective experimental trials. The present work dealt with the degradation of aflatoxin B₁ and M₁ by laccase enzymes from Trametes versicolor . The enzymes-substrate interaction for various enzyme isoforms was investigated through 3D molecular modeling techniques. Structural differences among the isoforms have been pinpointed, which may cause different patterns of interaction between aflatoxin B₁ and M₁. The possible formation of different products of degradation can be argued accordingly. Moreover, the laccase gamma isoform was identified as the most suitable for protein engineering aimed at ameliorating the substrate specificity. Overall, 3D modeling proved to be an effective analytical tool to assess the enzyme-substrate interaction and provided a solid foothold for supporting the search of degrading enzyme at the early stage.

Distinct profiling of antimicrobial peptide families

PubMed Central

Khamis, Abdullah M.; Essack, Magbubah; Gao, Xin; Bajic, Vladimir B.

2015-01-01

Motivation: The increased prevalence of multi-drug resistant (MDR) pathogens heightens the need to design new antimicrobial agents. Antimicrobial peptides (AMPs) exhibit broad-spectrum potent activity against MDR pathogens and kills rapidly, thus giving rise to AMPs being recognized as a potential substitute for conventional antibiotics. Designing new AMPs using current in-silico approaches is, however, challenging due to the absence of suitable models, large number of design parameters, testing cycles, production time and cost. To date, AMPs have merely been categorized into families according to their primary sequences, structures and functions. The ability to computationally determine the properties that discriminate AMP families from each other could help in exploring the key characteristics of these families and facilitate the in-silico design of synthetic AMPs. Results: Here we studied 14 AMP families and sub-families. We selected a specific description of AMP amino acid sequence and identified compositional and physicochemical properties of amino acids that accurately distinguish each AMP family from all other AMPs with an average sensitivity, specificity and precision of 92.88%, 99.86% and 95.96%, respectively. Many of our identified discriminative properties have been shown to be compositional or functional characteristics of the corresponding AMP family in literature. We suggest that these properties could serve as guides for in-silico methods in design of novel synthetic AMPs. The methodology we developed is generic and has a potential to be applied for characterization of any protein family. Contact: vladimir.bajic@kaust.edu.sa Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25388148

Investigation of protein selectivity in multimodal chromatography using in silico designed Fab fragment variants.

PubMed

Karkov, Hanne Sophie; Krogh, Berit Olsen; Woo, James; Parimal, Siddharth; Ahmadian, Haleh; Cramer, Steven M

2015-11-01

In this study, a unique set of antibody Fab fragments was designed in silico and produced to examine the relationship between protein surface properties and selectivity in multimodal chromatographic systems. We hypothesized that multimodal ligands containing both hydrophobic and charged moieties would interact strongly with protein surface regions where charged groups and hydrophobic patches were in close spatial proximity. Protein surface property characterization tools were employed to identify the potential multimodal ligand binding regions on the Fab fragment of a humanized antibody and to evaluate the impact of mutations on surface charge and hydrophobicity. Twenty Fab variants were generated by site-directed mutagenesis, recombinant expression, and affinity purification. Column gradient experiments were carried out with the Fab variants in multimodal, cation-exchange, and hydrophobic interaction chromatographic systems. The results clearly indicated that selectivity in the multimodal system was different from the other chromatographic modes examined. Column retention data for the reduced charge Fab variants identified a binding site comprising light chain CDR1 as the main electrostatic interaction site for the multimodal and cation-exchange ligands. Furthermore, the multimodal ligand binding was enhanced by additional hydrophobic contributions as evident from the results obtained with hydrophobic Fab variants. The use of in silico protein surface property analyses combined with molecular biology techniques, protein expression, and chromatographic evaluations represents a previously undescribed and powerful approach for investigating multimodal selectivity with complex biomolecules. © 2015 Wiley Periodicals, Inc.

Mechanistic modeling of developmental defects through computational embryology (WC10th)

EPA Science Inventory

Abstract: An important consideration for 3Rs is to identify developmental hazards utilizing mechanism-based in vitro assays (e.g., ToxCast) and in silico predictive models. Steady progress has been made with agent-based models that recapitulate morphogenetic drivers for angiogen...

Systematic Identification of Combinatorial Drivers and Targets in Cancer Cell Lines

PubMed Central

Tabchy, Adel; Eltonsy, Nevine; Housman, David E.; Mills, Gordon B.

2013-01-01

There is an urgent need to elicit and validate highly efficacious targets for combinatorial intervention from large scale ongoing molecular characterization efforts of tumors. We established an in silico bioinformatic platform in concert with a high throughput screening platform evaluating 37 novel targeted agents in 669 extensively characterized cancer cell lines reflecting the genomic and tissue-type diversity of human cancers, to systematically identify combinatorial biomarkers of response and co-actionable targets in cancer. Genomic biomarkers discovered in a 141 cell line training set were validated in an independent 359 cell line test set. We identified co-occurring and mutually exclusive genomic events that represent potential drivers and combinatorial targets in cancer. We demonstrate multiple cooperating genomic events that predict sensitivity to drug intervention independent of tumor lineage. The coupling of scalable in silico and biologic high throughput cancer cell line platforms for the identification of co-events in cancer delivers rational combinatorial targets for synthetic lethal approaches with a high potential to pre-empt the emergence of resistance. PMID:23577104

Systematic identification of combinatorial drivers and targets in cancer cell lines.

PubMed

Tabchy, Adel; Eltonsy, Nevine; Housman, David E; Mills, Gordon B

2013-01-01

There is an urgent need to elicit and validate highly efficacious targets for combinatorial intervention from large scale ongoing molecular characterization efforts of tumors. We established an in silico bioinformatic platform in concert with a high throughput screening platform evaluating 37 novel targeted agents in 669 extensively characterized cancer cell lines reflecting the genomic and tissue-type diversity of human cancers, to systematically identify combinatorial biomarkers of response and co-actionable targets in cancer. Genomic biomarkers discovered in a 141 cell line training set were validated in an independent 359 cell line test set. We identified co-occurring and mutually exclusive genomic events that represent potential drivers and combinatorial targets in cancer. We demonstrate multiple cooperating genomic events that predict sensitivity to drug intervention independent of tumor lineage. The coupling of scalable in silico and biologic high throughput cancer cell line platforms for the identification of co-events in cancer delivers rational combinatorial targets for synthetic lethal approaches with a high potential to pre-empt the emergence of resistance.

Genome-Wide Association Study of the Genetic Determinants of Emphysema Distribution

PubMed Central

Boueiz, Adel; Lutz, Sharon M.; Cho, Michael H.; Hersh, Craig P.; Bowler, Russell P.; Washko, George R.; Halper-Stromberg, Eitan; Bakke, Per; Gulsvik, Amund; Laird, Nan M.; Beaty, Terri H.; Coxson, Harvey O.; Crapo, James D.; Silverman, Edwin K.; Castaldi, Peter J.

2017-01-01

Rationale: Emphysema has considerable variability in the severity and distribution of parenchymal destruction throughout the lungs. Upper lobe–predominant emphysema has emerged as an important predictor of response to lung volume reduction surgery. Yet, aside from alpha-1 antitrypsin deficiency, the genetic determinants of emphysema distribution remain largely unknown. Objectives: To identify the genetic influences of emphysema distribution in non–alpha-1 antitrypsin–deficient smokers. Methods: A total of 11,532 subjects with complete genotype and computed tomography densitometry data in the COPDGene (Genetic Epidemiology of Chronic Obstructive Pulmonary Disease [COPD]; non-Hispanic white and African American), ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints), and GenKOLS (Genetics of Chronic Obstructive Lung Disease) studies were analyzed. Two computed tomography scan emphysema distribution measures (difference between upper-third and lower-third emphysema; ratio of upper-third to lower-third emphysema) were tested for genetic associations in all study subjects. Separate analyses in each study population were followed by a fixed effect metaanalysis. Single-nucleotide polymorphism–, gene-, and pathway-based approaches were used. In silico functional evaluation was also performed. Measurements and Main Results: We identified five loci associated with emphysema distribution at genome-wide significance. These loci included two previously reported associations with COPD susceptibility (4q31 near HHIP and 15q25 near CHRNA5) and three new associations near SOWAHB, TRAPPC9, and KIAA1462. Gene set analysis and in silico functional evaluation revealed pathways and cell types that may potentially contribute to the pathogenesis of emphysema distribution. Conclusions: This multicohort genome-wide association study identified new genomic loci associated with differential emphysematous destruction throughout the lungs. These findings may point to new biologic pathways on which to expand diagnostic and therapeutic approaches in chronic obstructive pulmonary disease. Clinical trial registered with www.clinicaltrials.gov (NCT 00608764). PMID:27669027

Altered retinal microRNA expression profiles in early diabetic retinopathy: an in silico analysis.

PubMed

Xiong, Fen; Du, Xinhua; Hu, Jianyan; Li, Tingting; Du, Shanshan; Wu, Qiang

2014-07-01

MicroRNAs (miRNAs) - as negative regulators of target genes - are associated with various human diseases, but their precise role(s) in diabetic retinopathy (DR) remains to be elucidated. The aim of this study was to elucidate the involvement of miRNAs in early DR using in silico analysis to explore their gene expression patterns. We used the streptozotocin (STZ)-induced diabetic rat to investigate the roles of miRNAs in early DR. Retinal miRNA expression profiles from diabetic versus healthy control rats were examined by miRNA array analysis. Based on several bioinformatic systems, specifically, gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, we identified signatures of the potential pathological processes, gene functions, and signaling pathways that are influenced by dysregulated miRNAs. We used quantitative real-time polymerase chain reaction (qRT-PCR) to validate six (i.e. those with significant changes in expression levels) of the 17 miRNAs that were detected in the miRNA array. We also describe the significant role of the miRNA-gene network, which is based on the interactions between miRNAs and target genes. GO analysis of the 17 miRNAs detected in the miRNA array analysis revealed the most prevalent miRNAs to be those related to biological processes, olfactory bulb development and axonogenesis. These miRNAs also exert significant influence on additional pathways, including the mitogen-activated protein and calcium signaling pathways. Six of the seventeen miRNAs were chosen for qRT-PCR validation. With the exception of a slight difference in miRNA-350, our results are in close agreement with the differential expressions detected by array analysis. This study, which describes miRNA expression during the early developmental phases of DR, revealed extensive miRNA interactions. Based on both their target genes and signaling pathways, we suggest that miRNAs perform critical regulatory functions during the early stages of DR evolution.

Hybrid In Silico/In Vitro Approaches for the Identification of Functional Cholesterol-Binding Domains in Membrane Proteins.

PubMed

Di Scala, Coralie; Fantini, Jacques

2017-01-01

In eukaryotic cells, cholesterol is an important regulator of a broad range of membrane proteins, including receptors, transporters, and ion channels. Understanding how cholesterol interacts with membrane proteins is a difficult task because structural data of these proteins complexed with cholesterol are scarce. Here, we describe a dual approach based on in silico studies of protein-cholesterol interactions, combined with physico-chemical measurements of protein insertion into cholesterol-containing monolayers. Our algorithm is validated through careful analysis of the effect of key mutations within and outside the predicted cholesterol-binding site. Our method is illustrated by a complete analysis of cholesterol-binding to Alzheimer's β-amyloid peptide, a protein that penetrates the plasma membrane of brain cells through a cholesterol-dependent process.

PTGER4 Expression-Modulating Polymorphisms in the 5p13.1 Region Predispose to Crohn's Disease and Affect NF-κB and XBP1 Binding Sites

PubMed Central

Czamara, Darina; Pasciuto, Giulia; Diegelmann, Julia; Wetzke, Martin; Olszak, Torsten; Wolf, Christiane; Müller-Myhsok, Bertram; Balschun, Tobias; Achkar, Jean-Paul; Kamboh, M. Ilyas; Franke, Andre; Duerr, Richard H.; Brand, Stephan

2012-01-01

Background Genome-wide association studies identified a PTGER4 expression-modulating region on chromosome 5p13.1 as Crohn's disease (CD) susceptibility region. The study aim was to test this association in a large cohort of patients with inflammatory bowel disease (IBD) and to elucidate genotypic and phenotypic interactions with other IBD genes. Methodology/Principal Findings A total of 7073 patients and controls were genotyped: 844 CD and 471 patients with ulcerative colitis and 1488 controls were analyzed for the single nucleotide polymorphisms (SNPs) rs4495224 and rs7720838 on chromosome 5p13.1. The study included two replication cohorts of North American (CD: n = 684; controls: n = 1440) and of German origin (CD: n = 1098; controls: n = 1048). Genotype-phenotype, epistasis and transcription factor binding analyses were performed. In the discovery cohort, an association of rs4495224 (p = 4.10×10−5; 0.76 [0.67–0.87]) and of rs7720838 (p = 6.91×10−4; 0.81 [0.71–0.91]) with susceptibility to CD was demonstrated. These associations were confirmed in both replication cohorts. In silico analysis predicted rs4495224 and rs7720838 as essential parts of binding sites for the transcription factors NF-κB and XBP1 with higher binding scores for carriers of the CD risk alleles, providing an explanation of how these SNPs might contribute to increased PTGER4 expression. There was no association of the PTGER4 SNPs with IBD phenotypes. Epistasis detected between 5p13.1 and ATG16L1 for CD susceptibility in the discovery cohort (p = 5.99×10−7 for rs7720838 and rs2241880) could not be replicated in both replication cohorts arguing against a major role of this gene-gene interaction in the susceptibility to CD. Conclusions/Significance We confirmed 5p13.1 as a major CD susceptibility locus and demonstrate by in silico analysis rs4495224 and rs7720838 as part of binding sites for NF-κB and XBP1. Further functional studies are necessary to confirm the results of our in silico analysis and to analyze if changes in PTGER4 expression modulate CD susceptibility. PMID:23300802

PTGER4 expression-modulating polymorphisms in the 5p13.1 region predispose to Crohn's disease and affect NF-κB and XBP1 binding sites.

PubMed

Glas, Jürgen; Seiderer, Julia; Czamara, Darina; Pasciuto, Giulia; Diegelmann, Julia; Wetzke, Martin; Olszak, Torsten; Wolf, Christiane; Müller-Myhsok, Bertram; Balschun, Tobias; Achkar, Jean-Paul; Kamboh, M Ilyas; Franke, Andre; Duerr, Richard H; Brand, Stephan

2012-01-01

Genome-wide association studies identified a PTGER4 expression-modulating region on chromosome 5p13.1 as Crohn's disease (CD) susceptibility region. The study aim was to test this association in a large cohort of patients with inflammatory bowel disease (IBD) and to elucidate genotypic and phenotypic interactions with other IBD genes. A total of 7073 patients and controls were genotyped: 844 CD and 471 patients with ulcerative colitis and 1488 controls were analyzed for the single nucleotide polymorphisms (SNPs) rs4495224 and rs7720838 on chromosome 5p13.1. The study included two replication cohorts of North American (CD: n = 684; controls: n = 1440) and of German origin (CD: n = 1098; controls: n = 1048). Genotype-phenotype, epistasis and transcription factor binding analyses were performed. In the discovery cohort, an association of rs4495224 (p = 4.10×10⁻⁵; 0.76 [0.67-0.87]) and of rs7720838 (p = 6.91×10⁻⁴; 0.81 [0.71-0.91]) with susceptibility to CD was demonstrated. These associations were confirmed in both replication cohorts. In silico analysis predicted rs4495224 and rs7720838 as essential parts of binding sites for the transcription factors NF-κB and XBP1 with higher binding scores for carriers of the CD risk alleles, providing an explanation of how these SNPs might contribute to increased PTGER4 expression. There was no association of the PTGER4 SNPs with IBD phenotypes. Epistasis detected between 5p13.1 and ATG16L1 for CD susceptibility in the discovery cohort (p = 5.99×10⁻⁷ for rs7720838 and rs2241880) could not be replicated in both replication cohorts arguing against a major role of this gene-gene interaction in the susceptibility to CD. We confirmed 5p13.1 as a major CD susceptibility locus and demonstrate by in silico analysis rs4495224 and rs7720838 as part of binding sites for NF-κB and XBP1. Further functional studies are necessary to confirm the results of our in silico analysis and to analyze if changes in PTGER4 expression modulate CD susceptibility.

Robust Phagocyte Recruitment Controls the Opportunistic Fungal Pathogen Mucor circinelloides in Innate Granulomas In Vivo.

PubMed

Inglesfield, Sarah; Jasiulewicz, Aleksandra; Hopwood, Matthew; Tyrrell, James; Youlden, George; Mazon-Moya, Maria; Millington, Owain R; Mostowy, Serge; Jabbari, Sara; Voelz, Kerstin

2018-03-27

Mucormycosis is an emerging fungal infection with extremely high mortality rates in patients with defects in their innate immune response, specifically in functions mediated through phagocytes. However, we currently have a limited understanding of the molecular and cellular interactions between these innate immune effectors and mucormycete spores during the early immune response. Here, the early events of innate immune recruitment in response to infection by Mucor circinelloides spores are modeled by a combined in silico modeling approach and real-time in vivo microscopy. Phagocytes are rapidly recruited to the site of infection in a zebrafish larval model of mucormycosis. This robust early recruitment protects from disease onset in vivo In silico analysis identified that protection is dependent on the number of phagocytes at the infection site, but not the speed of recruitment. The mathematical model highlights the role of proinflammatory signals for phagocyte recruitment and the importance of inhibition of spore germination for protection from active fungal disease. These in silico data are supported by an in vivo lack of fungal spore killing and lack of reactive oxygen burst, which together result in latent fungal infection. During this latent stage of infection, spores are controlled in innate granulomas in vivo Disease can be reactivated by immunosuppression. Together, these data represent the first in vivo real-time analysis of innate granuloma formation during the early stages of a fungal infection. The results highlight a potential latent stage during mucormycosis that should urgently be considered for clinical management of patients. IMPORTANCE Mucormycosis is a dramatic fungal infection frequently leading to the death of patients. We know little about the immune response to the fungus causing this infection, although evidence points toward defects in early immune events after infection. Here, we dissect this early immune response to infectious fungal spores. We show that specialized white blood cells (phagocytes) rapidly respond to these spores and accumulate around the fungus. However, we demonstrate that the mechanisms that enable phagocytes to kill the fungus fail, allowing for survival of spores. Instead a cluster of phagocytes resembling an early granuloma is formed around spores to control the latent infection. This study is the first detailed analysis of early granuloma formation during a fungal infection highlighting a latent stage that needs to be considered for clinical management of patients. Copyright © 2018 Inglesfield et al.

Identification of Interactions between Abscisic Acid and Ribulose-1,5-Bisphosphate Carboxylase/Oxygenase

PubMed Central

Galka, Marek M.; Rajagopalan, Nandhakishore; Buhrow, Leann M.; Nelson, Ken M.; Switala, Jacek; Cutler, Adrian J.; Palmer, David R. J.; Loewen, Peter C.; Abrams, Suzanne R.; Loewen, Michele C.

2015-01-01

Abscisic acid ((+)-ABA) is a phytohormone involved in the modulation of developmental processes and stress responses in plants. A chemical proteomics approach using an ABA mimetic probe was combined with in vitro assays, isothermal titration calorimetry (ITC), x-ray crystallography and in silico modelling to identify putative (+)-ABA binding-proteins in crude extracts of Arabidopsis thaliana. Ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) was identified as a putative ABA-binding protein. Radiolabelled-binding assays yielded a Kd of 47 nM for (+)-ABA binding to spinach Rubisco, which was validated by ITC, and found to be similar to reported and experimentally derived values for the native ribulose-1,5-bisphosphate (RuBP) substrate. Functionally, (+)-ABA caused only weak inhibition of Rubisco catalytic activity (Ki of 2.1 mM), but more potent inhibition of Rubisco activation (Ki of ~ 130 μM). Comparative structural analysis of Rubisco in the presence of (+)-ABA with RuBP in the active site revealed only a putative low occupancy (+)-ABA binding site on the surface of the large subunit at a location distal from the active site. However, subtle distortions in electron density in the binding pocket and in silico docking support the possibility of a higher affinity (+)-ABA binding site in the RuBP binding pocket. Overall we conclude that (+)-ABA interacts with Rubisco. While the low occupancy (+)-ABA binding site and weak non-competitive inhibition of catalysis may not be relevant, the high affinity site may allow ABA to act as a negative effector of Rubisco activation. PMID:26197050

Identification of Interactions between Abscisic Acid and Ribulose-1,5-Bisphosphate Carboxylase/Oxygenase.

PubMed

Galka, Marek M; Rajagopalan, Nandhakishore; Buhrow, Leann M; Nelson, Ken M; Switala, Jacek; Cutler, Adrian J; Palmer, David R J; Loewen, Peter C; Abrams, Suzanne R; Loewen, Michele C

2015-01-01

Abscisic acid ((+)-ABA) is a phytohormone involved in the modulation of developmental processes and stress responses in plants. A chemical proteomics approach using an ABA mimetic probe was combined with in vitro assays, isothermal titration calorimetry (ITC), x-ray crystallography and in silico modelling to identify putative (+)-ABA binding-proteins in crude extracts of Arabidopsis thaliana. Ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) was identified as a putative ABA-binding protein. Radiolabelled-binding assays yielded a Kd of 47 nM for (+)-ABA binding to spinach Rubisco, which was validated by ITC, and found to be similar to reported and experimentally derived values for the native ribulose-1,5-bisphosphate (RuBP) substrate. Functionally, (+)-ABA caused only weak inhibition of Rubisco catalytic activity (Ki of 2.1 mM), but more potent inhibition of Rubisco activation (Ki of ~ 130 μM). Comparative structural analysis of Rubisco in the presence of (+)-ABA with RuBP in the active site revealed only a putative low occupancy (+)-ABA binding site on the surface of the large subunit at a location distal from the active site. However, subtle distortions in electron density in the binding pocket and in silico docking support the possibility of a higher affinity (+)-ABA binding site in the RuBP binding pocket. Overall we conclude that (+)-ABA interacts with Rubisco. While the low occupancy (+)-ABA binding site and weak non-competitive inhibition of catalysis may not be relevant, the high affinity site may allow ABA to act as a negative effector of Rubisco activation.

Functional Coding Variation in Recombinant Inbred Mouse Lines Reveals Novel Serotonin Transporter-Associated Phenotypes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carneiro, Ana; Airey, David; Thompson, Brent

The human serotonin (5-hydroxytryptamine, 5-HT) transporter (hSERT, SLC6A4) figures prominently in the etiology or treatment of many prevalent neurobehavioral disorders including anxiety, alcoholism, depression, autism and obsessive-compulsive disorder (OCD). Here we utilize naturally occurring polymorphisms in recombinant inbred (RI) lines to identify novel phenotypes associated with altered SERT function. The widely used mouse strain C57BL/6J, harbors a SERT haplotype defined by two nonsynonymous coding variants (Gly39 and Lys152 (GK)). At these positions, many other mouse lines, including DBA/2J, encode Glu39 and Arg152 (ER haplotype), assignments found also in hSERT. Synaptosomal 5-HT transport studies revealed reduced uptake associated with the GKmore » variant. Heterologous expression studies confirmed a reduced SERT turnover rate for the GK variant. Experimental and in silico approaches using RI lines (C57Bl/6J X DBA/2J=BXD) identifies multiple anatomical, biochemical and behavioral phenotypes specifically impacted by GK/ER variation. Among our findings are multiple traits associated with anxiety and alcohol consumption, as well as of the control of dopamine (DA) signaling. Further bioinformatic analysis of BXD phenotypes, combined with biochemical evaluation of SERT knockout mice, nominates SERT-dependent 5-HT signaling as a major determinant of midbrain iron homeostasis that, in turn, dictates ironregulated DA phenotypes. Our studies provide a novel example of the power of coordinated in vitro, in vivo and in silico approaches using murine RI lines to elucidate and quantify the system-level impact of gene variation.« less

In Silico Identification of OncomiRs in Different Cancer Types

NASA Astrophysics Data System (ADS)

Bhattacharyya, Malay; Bandyopadhyay, Sanghamitra

2012-03-01

The diagnosis, prognosis and therapeutics of various kinds of cancers are challenging domains of research. Current landmark of cancer research at the molecular level mainly focuses on the regulation of genes for studying cancer pathways. Recent investigations highlight that there is a significant association of a class of short RNAs in the progression of different types of cancer. In this paper, the involvement of microRNAs (miRNAs), a type of small endogenous RNAs, is explored in two categories of cancers in human, one tumor-based and another non-tumorous. A new approach of in silico identification of the miRNAs that might be associated with these cancer types is proposed. The oncomiRs, miRNAs associated with cancer, are identified by analyzing the differentially co-expressed miRNAs and further exploring how they cooperate with each other. Extensive computational analysis on miRNA expression profiles for the discovery of novel oncomiRs is pursued. The results are found to be promising by going deep into the regulatory information available on oncogenes from the up-to-date literature. Some of the miRNAs as oncogenic are identified by the approach like hsa-miR-186 and hsa-miR-154 for leukemia and prostate cancer, respectively, which are not included in standard databases. However, some of the emerging studies give evidences to these findings. Statistical and biological studies, on the other hand, strengthen the effectiveness of the proposed method in futuristic investigations for the exploration of undiscovered oncomiRs. On the whole, these analyses provide insight into the discovery of miRNA markers.

Identification of potential inhibitors for oncogenic target of dihydroorotate dehydrogenase using in silico approaches

NASA Astrophysics Data System (ADS)

Surekha, Kanagarajan; Nachiappan, Mutharasappan; Prabhu, Dhamodharan; Choubey, Sanjay Kumar; Biswal, Jayashree; Jeyakanthan, Jeyaraman

2017-01-01

Dihydroorotate dehydrogenase (DHODH) plays a major role in the rate limiting step of de novo pyrimidine biosynthesis pathway and it is pronounced as a novel target for drug development of cancer. The currently available drugs against DHODH are ineffective and bear various side effects. Three-dimensional structure of the targeted protein was constructed using molecular modeling approach followed by 100 ns molecular dynamics simulations. In this study, High Throughput Virtual Screening (HTVS) was performed using various compound libraries to identify pharmacologically potential molecules. The top four identified lead molecules includes NCI_47074, HitFinder_7630, Binding_66981 and Specs_108872 with high docking score of -9.45, -8.29, -8.04 and -8.03 kcal/mol and the corresponding binding free energy were -16.25, -56.37, -26.93 and -48.04 kcal/mol respectively. Arg122, Arg185, Glu255 and Gly257 are the key residues found to be interacting with the ligands. Molecular dynamics simulations of DHODH-inhibitors complexes were performed to assess the stability of various conformations from complex structures of TtDHODH. Furthermore, stereoelectronic features of the ligands were explored to facilitate charge transfer during the protein-ligand interactions using Density Functional Theoretical approach. Based on in silico analysis, the ligand NCI_47074 ((2Z)-3-({6-[(2Z)-3-carboxylatoprop-2-enamido]pyridin-2-yl}carbamoyl)prop-2-enoate) was found to be the most potent lead molecule which was validated using energetic and electronic parameters and it could serve as a template for designing effective anticancerous drug molecule.

hfAIM: A reliable bioinformatics approach for in silico genome-wide identification of autophagy-associated Atg8-interacting motifs in various organisms

PubMed Central

Xie, Qingjun; Tzfadia, Oren; Levy, Matan; Weithorn, Efrat; Peled-Zehavi, Hadas; Van Parys, Thomas; Van de Peer, Yves; Galili, Gad

2016-01-01

ABSTRACT Most of the proteins that are specifically turned over by selective autophagy are recognized by the presence of short Atg8 interacting motifs (AIMs) that facilitate their association with the autophagy apparatus. Such AIMs can be identified by bioinformatics methods based on their defined degenerate consensus F/W/Y-X-X-L/I/V sequences in which X represents any amino acid. Achieving reliability and/or fidelity of the prediction of such AIMs on a genome-wide scale represents a major challenge. Here, we present a bioinformatics approach, high fidelity AIM (hfAIM), which uses additional sequence requirements—the presence of acidic amino acids and the absence of positively charged amino acids in certain positions—to reliably identify AIMs in proteins. We demonstrate that the use of the hfAIM method allows for in silico high fidelity prediction of AIMs in AIM-containing proteins (ACPs) on a genome-wide scale in various organisms. Furthermore, by using hfAIM to identify putative AIMs in the Arabidopsis proteome, we illustrate a potential contribution of selective autophagy to various biological processes. More specifically, we identified 9 peroxisomal PEX proteins that contain hfAIM motifs, among which AtPEX1, AtPEX6 and AtPEX10 possess evolutionary-conserved AIMs. Bimolecular fluorescence complementation (BiFC) results verified that AtPEX6 and AtPEX10 indeed interact with Atg8 in planta. In addition, we show that mutations occurring within or nearby hfAIMs in PEX1, PEX6 and PEX10 caused defects in the growth and development of various organisms. Taken together, the above results suggest that the hfAIM tool can be used to effectively perform genome-wide in silico screens of proteins that are potentially regulated by selective autophagy. The hfAIM system is a web tool that can be accessed at link: http://bioinformatics.psb.ugent.be/hfAIM/. PMID:27071037

In Silico Systems Biology Analysis of Variants of Uncertain Significance in Lynch Syndrome Supports the Prioritization of Functional Molecular Validation.

PubMed

Borras, Ester; Chang, Kyle; Pande, Mala; Cuddy, Amanda; Bosch, Jennifer L; Bannon, Sarah A; Mork, Maureen E; Rodriguez-Bigas, Miguel A; Taggart, Melissa W; Lynch, Patrick M; You, Y Nancy; Vilar, Eduardo

2017-10-01

Lynch syndrome (LS) is a genetic condition secondary to germline alterations in the DNA mismatch repair (MMR) genes with 30% of changes being variants of uncertain significance (VUS). Our aim was to perform an in silico reclassification of VUS from a large single institutional cohort that will help prioritizing functional validation. A total of 54 VUS were detected with 33 (61%) novel variants. We integrated family history, pathology, and genetic information along with supporting evidence from eight different in silico tools at the RNA and protein level. Our assessment allowed us to reclassify 54% (29/54) of the VUS as probably damaging, 13% (7/54) as possibly damaging, and 28% (15/54) as probably neutral. There are more than 1,000 VUS reported in MMR genes and our approach facilitates the prioritization of further functional efforts to assess the pathogenicity to those classified as probably damaging. Cancer Prev Res; 10(10); 580-7. ©2017 AACR . ©2017 American Association for Cancer Research.

Binding Patterns Associated Aß-HSP60 p458 Conjugate to HLA-DR-DRB Allele of Human in Alzheimer's Disease: An In Silico Approach.

PubMed

Padmadas, Naveen; Panda, Pritam Kumar; Durairaj, Sudarsanam

2018-03-01

Alzheimer's disease (AD) is a complex, irreversible, progressive brain disorder, which diminishes memory in a slow pace and thinking skills; ranked third by experts. It is a complex disorder that involves numerous cellular and subcellular alterations. The pathogenesis of AD is still unknown, but for better understanding, we proposed an in silico analysis to find out the binding patterns associated with HSP60. Several experimental conclusions have been drawn to understand the actual mechanism behind the forming of aggregation due to misfolding. Protein misfolding disorder is experimentally identified by the accumulation of protein aggregates at the intracellular or extracellular region of brain that adversely affects the cell functioning by disrupting the connection between the cells and ultimately leading to cell death. To unravel the mystery behind the mechanism of AD through computational approach, the current proposal shows the designing of Aß-HSP60 p458 conjugate followed by secondary structure analysis, which is further targeted to HLA-DR-DRB allele of human. The antigenicity of Aß (1-42) peptide is the major concern in our study predicted through PVS server, which provides an insight into the immunogenic behavior of Aß peptide. The mechanism involved in the interaction of HSP60-Aß conjugate with HLA-DR-DRB allele considering the fact that Aß (1-42) is highly immunogenic in human and interactions evoked highly robust T-cell response through MHC class II binding predictions. It was assisted by molecular dynamics simulation of predicted HSP60 structure followed by validation through Ramachandran plot analysis and protein-protein interaction of Aß (1-42) with HSP60.

In-silico mining, type and frequency analysis of genic microsatellites of finger millet (Eleusine coracana (L.) Gaertn.): a comparative genomic analysis of NBS-LRR regions of finger millet with rice.

PubMed

Kalyana Babu, B; Pandey, Dinesh; Agrawal, P K; Sood, Salej; Kumar, Anil

2014-05-01

In recent years, the increased availability of the DNA sequences has given the possibility to develop and explore the expressed sequence tags (ESTs) derived SSR markers. In the present study, a total of 1956 ESTs of finger millet were used to find the microsatellite type, distribution, frequency and developed a total of 545 primer pairs from the ESTs of finger millet. Thirty-two EST sequences had more than two microsatellites and 1357 sequences did not have any SSR repeats. The most frequent type of repeats was trimeric motif, however the second place was occupied by dimeric motif followed by tetra-, hexa- and penta repeat motifs. The most common dimer repeat motif was GA and in case of trimeric SSRs, it was CGG. The EST sequences of NBS-LRR region of finger millet and rice showed higher synteny and were found on nearly same positions on the rice chromosome map. A total of eight, out of 15 EST based SSR primers were polymorphic among the selected resistant and susceptible finger millet genotypes. The primer FMBLEST5 could able to differentiate them into resistant and susceptible genotypes. The alleles specific to the resistant and susceptible genotypes were sequenced using the ABI 3130XL genetic analyzer and found similarity to NBS-LRR regions of rice and finger millet and contained the characteristic kinase-2 and kinase 3a motifs of plant R-genes belonged to NBS-LRR region. The In-silico and comparative analysis showed that the genes responsible for blast resistance can be identified, mapped and further introgressed through molecular breeding approaches for enhancing the blast resistance in finger millet.

Development and in silico evaluation of large-scale metabolite identification methods using functional group detection for metabolomics

PubMed Central

Mitchell, Joshua M.; Fan, Teresa W.-M.; Lane, Andrew N.; Moseley, Hunter N. B.

2014-01-01

Large-scale identification of metabolites is key to elucidating and modeling metabolism at the systems level. Advances in metabolomics technologies, particularly ultra-high resolution mass spectrometry (MS) enable comprehensive and rapid analysis of metabolites. However, a significant barrier to meaningful data interpretation is the identification of a wide range of metabolites including unknowns and the determination of their role(s) in various metabolic networks. Chemoselective (CS) probes to tag metabolite functional groups combined with high mass accuracy provide additional structural constraints for metabolite identification and quantification. We have developed a novel algorithm, Chemically Aware Substructure Search (CASS) that efficiently detects functional groups within existing metabolite databases, allowing for combined molecular formula and functional group (from CS tagging) queries to aid in metabolite identification without a priori knowledge. Analysis of the isomeric compounds in both Human Metabolome Database (HMDB) and KEGG Ligand demonstrated a high percentage of isomeric molecular formulae (43 and 28%, respectively), indicating the necessity for techniques such as CS-tagging. Furthermore, these two databases have only moderate overlap in molecular formulae. Thus, it is prudent to use multiple databases in metabolite assignment, since each major metabolite database represents different portions of metabolism within the biosphere. In silico analysis of various CS-tagging strategies under different conditions for adduct formation demonstrate that combined FT-MS derived molecular formulae and CS-tagging can uniquely identify up to 71% of KEGG and 37% of the combined KEGG/HMDB database vs. 41 and 17%, respectively without adduct formation. This difference between database isomer disambiguation highlights the strength of CS-tagging for non-lipid metabolite identification. However, unique identification of complex lipids still needs additional information. PMID:25120557

Proteome analysis in the assessment of ageing.

PubMed

Nkuipou-Kenfack, Esther; Koeck, Thomas; Mischak, Harald; Pich, Andreas; Schanstra, Joost P; Zürbig, Petra; Schumacher, Björn

2014-11-01

Based on demographic trends, the societies in many developed countries are facing an increasing number and proportion of people over the age of 65. The raise in elderly populations along with improved health-care will be concomitant with an increased prevalence of ageing-associated chronic conditions like cardiovascular, renal, and respiratory diseases, arthritis, dementia, and diabetes mellitus. This is expected to pose unprecedented challenges both for individuals and societies and their health care systems. An ultimate goal of ageing research is therefore the understanding of physiological ageing and the achievement of 'healthy' ageing by decreasing age-related pathologies. However, on a molecular level, ageing is a complex multi-mechanistic process whose contributing factors may vary individually, partly overlap with pathological alterations, and are often poorly understood. Proteome analysis potentially allows modelling of these multifactorial processes. This review summarises recent proteomic research on age-related changes identified in animal models and human studies. We combined this information with pathway analysis to identify molecular mechanisms associated with ageing. We identified some molecular pathways that are affected in most or even all organs and others that are organ-specific. However, appropriately powered studies are needed to confirm these findings based in in silico evaluation. Copyright © 2014 Elsevier B.V. All rights reserved.

Hybridization-based antibody cDNA recovery for the production of recombinant antibodies identified by repertoire sequencing.

PubMed

Valdés-Alemán, Javier; Téllez-Sosa, Juan; Ovilla-Muñoz, Marbella; Godoy-Lozano, Elizabeth; Velázquez-Ramírez, Daniel; Valdovinos-Torres, Humberto; Gómez-Barreto, Rosa E; Martinez-Barnetche, Jesús

2014-01-01

High-throughput sequencing of the antibody repertoire is enabling a thorough analysis of B cell diversity and clonal selection, which may improve the novel antibody discovery process. Theoretically, an adequate bioinformatic analysis could allow identification of candidate antigen-specific antibodies, requiring their recombinant production for experimental validation of their specificity. Gene synthesis is commonly used for the generation of recombinant antibodies identified in silico. Novel strategies that bypass gene synthesis could offer more accessible antibody identification and validation alternatives. We developed a hybridization-based recovery strategy that targets the complementarity-determining region 3 (CDRH3) for the enrichment of cDNA of candidate antigen-specific antibody sequences. Ten clonal groups of interest were identified through bioinformatic analysis of the heavy chain antibody repertoire of mice immunized with hen egg white lysozyme (HEL). cDNA from eight of the targeted clonal groups was recovered efficiently, leading to the generation of recombinant antibodies. One representative heavy chain sequence from each clonal group recovered was paired with previously reported anti-HEL light chains to generate full antibodies, later tested for HEL-binding capacity. The recovery process proposed represents a simple and scalable molecular strategy that could enhance antibody identification and specificity assessment, enabling a more cost-efficient generation of recombinant antibodies.

Transcriptomic analysis of Ruditapes philippinarum hemocytes reveals cytoskeleton disruption after in vitro Vibrio tapetis challenge.

PubMed

Brulle, Franck; Jeffroy, Fanny; Madec, Stéphanie; Nicolas, Jean-Louis; Paillard, Christine

2012-10-01

The Manila clam, Ruditapes philippinarum, is an economically-important, commercial shellfish; harvests are diminished in some European waters by a pathogenic bacterium, Vibrio tapetis, that causes Brown Ring disease. To identify molecular characteristics associated with susceptibility or resistance to Brown Ring disease, Suppression Subtractive Hybridization (SSH) analyzes were performed to construct cDNA libraries enriched in up- or down-regulated transcripts from clam immune cells, hemocytes, after a 3-h in vitro challenge with cultured V. tapetis. Nine hundred and ninety eight sequences from the two libraries were sequenced, and an in silico analysis identified 235 unique genes. BLAST and "Gene ontology" classification analyzes revealed that 60.4% of the Expressed Sequence Tags (ESTs) have high similarities with genes involved in various physiological functions, such as immunity, apoptosis and cytoskeleton organization; whereas, 39.6% remain unidentified. From the 235 unique genes, we selected 22 candidates based upon physiological function and redundancy in the libraries. Then, Real-Time PCR analysis identified 3 genes related to cytoskeleton organization showing significant variation in expression attributable to V. tapetis exposure. Disruption in regulation of these genes is consistent with the etiologic agent of Brown Ring disease in Manila clams. Copyright © 2012 Elsevier Ltd. All rights reserved.

Screening of mutations affecting protein stability and dynamics of FGFR1—A simulation analysis

PubMed Central

Doss, C. George Priya; Rajith, B.; Garwasis, Nimisha; Mathew, Pretty Raju; Raju, Anand Solomon; Apoorva, K.; William, Denise; Sadhana, N.R.; Himani, Tanwar; Dike, IP.

2012-01-01

Single amino acid substitutions in Fibroblast Growth Factor Receptor 1 (FGFR1) destabilize protein and have been implicated in several genetic disorders like various forms of cancer, Kallamann syndrome, Pfeiffer syndrome, Jackson Weiss syndrome, etc. In order to gain functional insight into mutation caused by amino acid substitution to protein function and expression, special emphasis was laid on molecular dynamics simulation techniques in combination with in silico tools such as SIFT, PolyPhen 2.0, I-Mutant 3.0 and SNAP. It has been estimated that 68% nsSNPs were predicted to be deleterious by I-Mutant, slightly higher than SIFT (37%), PolyPhen 2.0 (61%) and SNAP (58%). From the observed results, P722S mutation was found to be most deleterious by comparing results of all in silico tools. By molecular dynamics approach, we have shown that P722S mutation leads to increase in flexibility, and deviated more from the native structure which was supported by the decrease in the number of hydrogen bonds. In addition, biophysical analysis revealed a clear insight of stability loss due to P722S mutation in FGFR1 protein. Majority of mutations predicted by these in silico tools were in good concordance with the experimental results. PMID:27896051

Screening of mutations affecting protein stability and dynamics of FGFR1-A simulation analysis.

PubMed

Doss, C George Priya; Rajith, B; Garwasis, Nimisha; Mathew, Pretty Raju; Raju, Anand Solomon; Apoorva, K; William, Denise; Sadhana, N R; Himani, Tanwar; Dike, I P

2012-12-01

Single amino acid substitutions in Fibroblast Growth Factor Receptor 1 ( FGFR1 ) destabilize protein and have been implicated in several genetic disorders like various forms of cancer, Kallamann syndrome, Pfeiffer syndrome, Jackson Weiss syndrome, etc. In order to gain functional insight into mutation caused by amino acid substitution to protein function and expression, special emphasis was laid on molecular dynamics simulation techniques in combination with in silico tools such as SIFT, PolyPhen 2.0, I-Mutant 3.0 and SNAP. It has been estimated that 68% nsSNPs were predicted to be deleterious by I-Mutant, slightly higher than SIFT (37%), PolyPhen 2.0 (61%) and SNAP (58%). From the observed results, P722S mutation was found to be most deleterious by comparing results of all in silico tools. By molecular dynamics approach, we have shown that P722S mutation leads to increase in flexibility, and deviated more from the native structure which was supported by the decrease in the number of hydrogen bonds. In addition, biophysical analysis revealed a clear insight of stability loss due to P722S mutation in FGFR1 protein. Majority of mutations predicted by these in silico tools were in good concordance with the experimental results.

UNCLES: method for the identification of genes differentially consistently co-expressed in a specific subset of datasets.

PubMed

Abu-Jamous, Basel; Fa, Rui; Roberts, David J; Nandi, Asoke K

2015-06-04

Collective analysis of the increasingly emerging gene expression datasets are required. The recently proposed binarisation of consensus partition matrices (Bi-CoPaM) method can combine clustering results from multiple datasets to identify the subsets of genes which are consistently co-expressed in all of the provided datasets in a tuneable manner. However, results validation and parameter setting are issues that complicate the design of such methods. Moreover, although it is a common practice to test methods by application to synthetic datasets, the mathematical models used to synthesise such datasets are usually based on approximations which may not always be sufficiently representative of real datasets. Here, we propose an unsupervised method for the unification of clustering results from multiple datasets using external specifications (UNCLES). This method has the ability to identify the subsets of genes consistently co-expressed in a subset of datasets while being poorly co-expressed in another subset of datasets, and to identify the subsets of genes consistently co-expressed in all given datasets. We also propose the M-N scatter plots validation technique and adopt it to set the parameters of UNCLES, such as the number of clusters, automatically. Additionally, we propose an approach for the synthesis of gene expression datasets using real data profiles in a way which combines the ground-truth-knowledge of synthetic data and the realistic expression values of real data, and therefore overcomes the problem of faithfulness of synthetic expression data modelling. By application to those datasets, we validate UNCLES while comparing it with other conventional clustering methods, and of particular relevance, biclustering methods. We further validate UNCLES by application to a set of 14 real genome-wide yeast datasets as it produces focused clusters that conform well to known biological facts. Furthermore, in-silico-based hypotheses regarding the function of a few previously unknown genes in those focused clusters are drawn. The UNCLES method, the M-N scatter plots technique, and the expression data synthesis approach will have wide application for the comprehensive analysis of genomic and other sources of multiple complex biological datasets. Moreover, the derived in-silico-based biological hypotheses represent subjects for future functional studies.

Is Increased Susceptibility to Balkan Endemic Nephropathy in Carriers of Common GSTA1 (*A/*B) Polymorphism Linked with the Catalytic Role of GSTA1 in Ochratoxin A Biotransformation? Serbian Case Control Study and In Silico Analysis

PubMed Central

Reljic, Zorica; Zlatovic, Mario; Savic-Radojevic, Ana; Pekmezovic, Tatjana; Djukanovic, Ljubica; Matic, Marija; Pljesa-Ercegovac, Marija; Mimic-Oka, Jasmina; Opsenica, Dejan; Simic, Tatjana

2014-01-01

Although recent data suggest aristolochic acid as a putative cause of Balkan endemic nephropathy (BEN), evidence also exists in favor of ochratoxin A (OTA) exposure as risk factor for the disease. The potential role of xenobiotic metabolizing enzymes, such as the glutathione transferases (GSTs), in OTA biotransformation is based on OTA glutathione adducts (OTHQ-SG and OTB-SG) in blood and urine of BEN patients. We aimed to analyze the association between common GSTA1, GSTM1, GSTT1, and GSTP1 polymorphisms and BEN susceptibility, and thereafter performed an in silico simulation of particular GST enzymes potentially involved in OTA transformations. GSTA1, GSTM1, GSTT1 and GSTP1 genotypes were determined in 207 BEN patients and 138 non-BEN healthy individuals from endemic regions by polymerase chain reaction (PCR). Molecular modeling in silico was performed for GSTA1 protein. Among the GST polymorphisms tested, only GSTA1 was significantly associated with a higher risk of BEN. Namely, carriers of the GSTA1*B gene variant, associated with lower transcriptional activation, were at a 1.6-fold higher BEN risk than those carrying the homozygous GSTA1*A/*A genotype (OR = 1.6; p = 0.037). In in silico modeling, we found four structures, two OTB-SG and two OTHQ-SG, bound in a GSTA1 monomer. We found that GSTA1 polymorphism was associated with increased risk of BEN, and suggested, according to the in silico simulation, that GSTA1-1 might be involved in catalyzing the formation of OTHQ-SG and OTB-SG conjugates. PMID:25111321

Prediction of pharmacokinetic and toxicological parameters of a 4-phenylcoumarin isolated from geopropolis: In silico and in vitro approaches.

PubMed

da Cunha, Marcos Guilherme; Franco, Gilson César Nobre; Franchin, Marcelo; Beutler, John A; de Alencar, Severino Matias; Ikegaki, Masaharu; Rosalen, Pedro Luiz

2016-11-30

In silico and in vitro methodologies have been used as important tools in the drug discovery process, including from natural sources. The aim of this study was to predict pharmacokinetic and toxicity (ADME/Tox) properties of a coumarin isolated from geopropolis using in silico and in vitro approaches. Cinnamoyloxy-mammeisin (CNM) isolated from Brazilian M. scutellaris geopropolis was evaluated for its pharmacokinetic parameters by in silico models (ACD/Percepta™ and MetaDrug™ software). Genotoxicity was assessed by in vitro DNA damage signaling PCR array. CNM did not pass all parameters of Lipinski's rule of five, with a predicted low oral bioavailability and high plasma protein binding, but with good predicted blood brain barrier penetration. CNM was predicted to show low affinity to cytochrome P450 family members. Furthermore, the predicted Ames test indicated potential mutagenicity of CNM. Also, the probability of toxicity for organs and tissues was classified as moderate and high for liver and kidney, and moderate and low for skin and eye irritation, respectively. The PCR array analysis showed that CNM significantly upregulated about 7% of all DNA damage-related genes. By exploring the biological function of these genes, it was found that the predicted CNM genotoxicity is likely to be mediated by apoptosis. The predicted ADME/Tox profile suggests that external use of CNM may be preferable to systemic exposure, while its genotoxicity was characterized by the upregulation of apoptosis-related genes after treatment. The combined use of in silico and in vitro approaches to evaluate these parameters generated useful hypotheses to guide further preclinical studies. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

High throughput screening: an in silico solubility parameter approach for lipids and solvents in SLN preparations.

PubMed

Shah, Malay; Agrawal, Yadvendra

2013-01-01

The present paper describes an in silico solubility behavior of drug and lipids, an essential screening study in preparation of solid lipid nanoparticles (SLN). Ciprofloxacin HCl was selected as a model drug along with 11 lipids and 5 organic solvents. In silico miscibility study of drug/lipid/solvent was performed using Hansen solubility parameter approach calculated by group contribution method of Van Krevelen and Hoftyzer. Predicted solubility was validated by determining solubility of lipids in various solvent at different temperature range, while miscibility of drug in lipids was determined by apparent solubility study and partition experiment. The presence of oxygen and OH functionality increases the polarity and hydrogen bonding possibilities of the compound which has reflected the highest solubility parameter values for Geleol and Capmul MCM C8. Ethyl acetate, Geleol and Capmul MCM C8 was identified as suitable organic solvent, solid lipid and liquid lipid respectively based on a solubility parameter approach which was in agreement with the result of an apparent solubility study and partition coefficient. These works demonstrate the validity of solubility parameter approach and provide a feasible predictor to the rational selection of excipients in designing SLN formulation.

In silico analysis sheds light on the structural basis underlying the ribotoxicity of trichothecenes-A tool for supporting the hazard identification process.

PubMed

Dellafiora, Luca; Galaverna, Gianni; Dall'Asta, Chiara

2017-03-15

Deoxynivalenol is a food borne mycotoxin belonging to the trichothecenes family that may cause severe injuries in human and animals. The inhibition of protein synthesis via the interaction with the ribosome has been identified as a crucial mechanism underlying toxic action. However, it is not still fully understood how and to what extent compounds belonging to trichothecenes family affect human and animal health. In turn, this scenario causes delay in managing the related health risk. Aimed at supporting the hazard identification process, the in silico analysis may be a straightforward tool to investigate the structure-activity relationship of trichothecenes, finding out molecules of possible concern to carry forth in the risk assessment process. In this framework, this work investigated through a molecular modeling approach the structural basis underlying the interaction with the ribosome under a structure-activity relationship perspective. To identify further forms possibly involved in the total trichothecenes-dependent ribotoxic load, the model was challenged with a set of 16 trichothecene modified forms found in plants, fungi and animals, including also compounds never tested before for the capability to bind and inhibit the ribosome. Among them, only the regiospecific glycosylation in the position 3 of the sesquiterpenoid scaffold (i.e. T-2 toxin-3-glucuronide, α and β isomers of T-2 toxin-3-glucoside and deoxynivalenol-3-glucuronide) was found impairing the interaction with the ribosome, while the other compounds tested (i.e. neosolaniol, nivalenol, fusarenon-X, diacetoxyscirpenol, NT-1 toxin, HT-2 toxin, 19- and 20-hydroxy-T-2 toxin, T-2 toxin triol and tetraol, and 15-deacetyl-T-2 toxin), were found potentially able to inhibit the ribosome. Accordingly, they should be included with high priority in further risk assessment studies in order to better characterize the trichothecenes-related hazard. Copyright © 2017 Elsevier B.V. All rights reserved.

Unc-51 like kinase 1 (ULK1) in silico analysis for biomarker identification: a vital component of autophagy.

PubMed

Randhawa, Rohit; Sehgal, Manika; Singh, Tiratha Raj; Duseja, Ajay; Changotra, Harish

2015-05-10

Autophagy is a degradation pathway involving lysosomal machinery for degradation of damaged organelles like the endoplasmic reticulum and mitochondria into their building blocks to maintain homeostasis within the cell. ULK1, a serine/threonine kinase, is conserved across species, from yeasts to mammals, and plays a central role in autophagy pathway. It receives signals from upstream modulators such as TIP60, mTOR and AMPK and relays them to its downstream substrates like Ambra1 and ZIP kinase. The activity of this complex is regulated through protein-protein interactions and post-translational modifications. Applying in silico analysis we identified (i) conserved patterns of ULK1 that showed its evolutionary relationship between the species which were closely related in a family compared to others. (ii) A total of 23 TFBS distributed throughout ULK1 and nuclear factor (erythroid-derived) 2 (NFE2) is of utmost significance because of its high importance rate. NEF2 has already been shown experimentally to play a role in the autophagy pathway. Most of these were of zinc coordinating class and we suggest that this information could be utilized to modulate this pathway by modifying interactions of these TFs with ULK1. (iii) CATTT haplotype was prominently found with frequency 0.774 in the studied population and nsSNPs which could have harmful effect on ULK1 protein and these could further be tested. (iv) A total of 83 phosphorylation sites were identified; 26 are already known and 57 are new that include one at tyrosine residue which could further be studied for its involvement in ULK1 regulation and hence autophagy. Furthermore, 4 palmitoylation sites at positions 426, 927, 1003 and 1049 were also found which could further be studied for protein-protein interactions as well as in trafficking. Copyright © 2015 Elsevier B.V. All rights reserved.

Fine-Scale Variation and Genetic Determinants of Alternative Splicing across Individuals

PubMed Central

Coulombe-Huntington, Jasmin; Lam, Kevin C. L.; Dias, Christel; Majewski, Jacek

2009-01-01

Recently, thanks to the increasing throughput of new technologies, we have begun to explore the full extent of alternative pre–mRNA splicing (AS) in the human transcriptome. This is unveiling a vast layer of complexity in isoform-level expression differences between individuals. We used previously published splicing sensitive microarray data from lymphoblastoid cell lines to conduct an in-depth analysis on splicing efficiency of known and predicted exons. By combining publicly available AS annotation with a novel algorithm designed to search for AS, we show that many real AS events can be detected within the usually unexploited, speculative majority of the array and at significance levels much below standard multiple-testing thresholds, demonstrating that the extent of cis-regulated differential splicing between individuals is potentially far greater than previously reported. Specifically, many genes show subtle but significant genetically controlled differences in splice-site usage. PCR validation shows that 42 out of 58 (72%) candidate gene regions undergo detectable AS, amounting to the largest scale validation of isoform eQTLs to date. Targeted sequencing revealed a likely causative SNP in most validated cases. In all 17 incidences where a SNP affected a splice-site region, in silico splice-site strength modeling correctly predicted the direction of the micro-array and PCR results. In 13 other cases, we identified likely causative SNPs disrupting predicted splicing enhancers. Using Fst and REHH analysis, we uncovered significant evidence that 2 putative causative SNPs have undergone recent positive selection. We verified the effect of five SNPs using in vivo minigene assays. This study shows that splicing differences between individuals, including quantitative differences in isoform ratios, are frequent in human populations and that causative SNPs can be identified using in silico predictions. Several cases affected disease-relevant genes and it is likely some of these differences are involved in phenotypic diversity and susceptibility to complex diseases. PMID:20011102

In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen

PubMed Central

Plouffe, David; Brinker, Achim; McNamara, Case; Henson, Kerstin; Kato, Nobutaka; Kuhen, Kelli; Nagle, Advait; Adrián, Francisco; Matzen, Jason T.; Anderson, Paul; Nam, Tae-gyu; Gray, Nathanael S.; Chatterjee, Arnab; Janes, Jeff; Yan, S. Frank; Trager, Richard; Caldwell, Jeremy S.; Schultz, Peter G.; Zhou, Yingyao; Winzeler, Elizabeth A.

2008-01-01

The growing resistance to current first-line antimalarial drugs represents a major health challenge. To facilitate the discovery of new antimalarials, we have implemented an efficient and robust high-throughput cell-based screen (1,536-well format) based on proliferation of Plasmodium falciparum (Pf) in erythrocytes. From a screen of ≈1.7 million compounds, we identified a diverse collection of ≈6,000 small molecules comprised of >530 distinct scaffolds, all of which show potent antimalarial activity (<1.25 μM). Most known antimalarials were identified in this screen, thus validating our approach. In addition, we identified many novel chemical scaffolds, which likely act through both known and novel pathways. We further show that in some cases the mechanism of action of these antimalarials can be determined by in silico compound activity profiling. This method uses large datasets from unrelated cellular and biochemical screens and the guilt-by-association principle to predict which cellular pathway and/or protein target is being inhibited by select compounds. In addition, the screening method has the potential to provide the malaria community with many new starting points for the development of biological probes and drugs with novel antiparasitic activities. PMID:18579783

Identification and functional analysis of the aspergillic acid gene cluster in Aspergillus flavus

USDA-ARS?s Scientific Manuscript database

Aspergillus flavus can colonize important food staples and produces aflatoxins, toxic and carcinogenic secondary metabolites. In silico analysis of the A. flavus genome revealed 56 gene clusters encoding for secondary metabolites. How these many of these metabolites affect fungal development, surviv...

Identification of drought-responsive genes in roots of upland rice (Oryza sativa L)

PubMed Central

Rabello, Aline R; Guimarães, Cléber M; Rangel, Paulo HN; da Silva, Felipe R; Seixas, Daniela; de Souza, Emanuel; Brasileiro, Ana CM; Spehar, Carlos R; Ferreira, Márcio E; Mehta, Ângela

2008-01-01

Background Rice (Oryza sativa L.) germplasm represents an extraordinary source of genes that control traits of agronomic importance such as drought tolerance. This diversity is the basis for the development of new cultivars better adapted to water restriction conditions, in particular for upland rice, which is grown under rainfall. The analyses of subtractive cDNA libraries and differential protein expression of drought tolerant and susceptible genotypes can contribute to the understanding of the genetic control of water use efficiency in rice. Results Two subtractive libraries were constructed using cDNA of drought susceptible and tolerant genotypes submitted to stress against cDNA of well-watered plants. In silico analysis revealed 463 reads, which were grouped into 282 clusters. Several genes expressed exclusively in the tolerant or susceptible genotypes were identified. Additionally, proteome analysis of roots from stressed plants was performed and 22 proteins putatively associated to drought tolerance were identified by mass spectrometry. Conclusion Several genes and proteins involved in drought-response, as well as genes with no described homologs were identified. Genes exclusively expressed in the tolerant genotype were, in general, related to maintenance of turgor and cell integrity. In contrast, in the susceptible genotype, expression of genes involved in protection against cell damage was not detected. Several protein families identified in the proteomic analysis were not detected in the cDNA analysis. There is an indication that the mechanisms of susceptibility to drought in upland rice are similar to those of lowland varieties. PMID:18922162

Domain-Specific QSAR Model for Identifying Potential Estrogenic Activity of Phenols (ASCCT annual meeting)

EPA Science Inventory

Humans are potentially exposed to tens of thousands of man-made chemicals in the environment, some of which may mimic natural endocrine hormones and thus have the potential to be endocrine disruptors. Predictive in silico tools can be used to quickly and efficiently evaluate thes...

Discovery of secondary metabolites from Bacillus spp. biocontrol strains using genome mining and mass spectroscopy

USDA-ARS?s Scientific Manuscript database

Genome sequencing, data mining and mass spectrometry were used to identify secondary metabolites produced by several Bacillus spp. biocontrol strains. These biocontrol strains have shown promise in managing Fusarium head blight in wheat. Draft genomes were produced and screened in silico using genom...

EDC testing in the future: Exploring roles of pathway-based in silico, in vitro and in vivo methods

EPA Science Inventory

Many thoroughly validated, robust tests with both mammalian and non-mammalian models have been developed to identify chemicals with the potential to impact endocrine pathways associated with the hypothalamic-pituitary-gonadal (HPG) and thyroidal axes. In the US, for example, the...

LC-MS-Based Lipidomics and Automated Identification of Lipids Using the LipidBlast In-Silico MS/MS Library.

PubMed

Cajka, Tomas; Fiehn, Oliver

2017-01-01

This protocol describes the analysis, specifically the identification, of blood plasma lipids. Plasma lipids are extracted using methyl tert-butyl ether (MTBE), methanol, and water followed by separation and data acquisition of isolated lipids using reversed-phase liquid chromatography coupled to quadrupole/time-of-flight mass spectrometry (RPLC-QTOFMS) operated in MS/MS mode. For lipid identification, acquired MS/MS spectra are converted to the mascot generic format (MGF) followed by library search using the in-silico MS/MS library LipidBlast. Using this approach, lipid classes, carbon-chain lengths, and degree of unsaturation of fatty-acid components are annotated.

The hOGG1 Ser326Cys Gene Polymorphism and Breast Cancer Risk in Saudi Population.

PubMed

Alanazi, Mohammed; Pathan, Akbar Ali Khan; Shaik, Jilani P; Alhadheq, Abdullah; Khan, Zahid; Khan, Wajahatullah; Al Naeem, Abdulrahman; Parine, Narasimha Reddy

2017-07-01

The purpose of this study was to test the association between human 8-oxoguanine glycosylase 1 (hOGG1) gene polymorphisms and susceptibility to breast cancer in Saudi population. We have also aimed to screen the hOGG1 Ser326Cys polymorphism effect on structural and functional properties of the hOGG1 protein using in silico tools. We have analyzed four SNPs of hOGG1 gene among Saudi breast cancer patients along with healthy controls. Genotypes were screened using TaqMan SNP genotype analysis method. Experimental data was analyzed using Chi-square, t test and logistic regression analysis using SPSS software (v.16). In silco analysis was conducted using discovery studio and HOPE program. Genotypic analysis showed that hOGG1 rs1052133 (Ser326Cys) is significantly associated with breast cancer samples in Saudi population, however rs293795 (T >C), rs2072668 (C>G) and rs2075747 (G >A) did not show any association with breast cancer. The hOGG1 SNP rs1052133 (Ser326Cys) minor allele T showed a significant association with breast cancer samples (OR = 1.78, χ2 = 7.86, p = 0.02024). In silico structural analysis was carried out to compare the wild type (Ser326) and mutant (Cys326) protein structures. The structural prediction studies revealed that Ser326Cys variant may destabilize the protein structure and it may disturb the hOGG1 function. Taken together this is the first In silico study report to confirm Ser326Cys variant effect on structural and functional properties of hOGG1 gene and Ser326Cys role in breast cancer susceptibility in Saudi population.

In-silico and in-vivo analyses of EST databases unveil conserved miRNAs from Carthamus tinctorius and Cynara cardunculus

PubMed Central

2012-01-01

Background MicroRNAs (miRNAs) are small RNAs (21-24 bp) providing an RNA-based system of gene regulation highly conserved in plants and animals. In plants, miRNAs control mRNA degradation or restrain translation, affecting development and responses to stresses. Plant miRNAs show imperfect but extensive complementarity to mRNA targets, making their computational prediction possible, useful when data mining is applied on different species. In this study we used a comparative approach to identify both miRNAs and their targets, in artichoke and safflower. Results Two complete expressed sequence tags (ESTs) datasets from artichoke (3.6·104 entries) and safflower (4.2·104), were analysed with a bioinformatic pipeline and in vitro experiments, identifying 17 potential miRNAs. For each EST, using RNAhybrid program and 953 non redundant miRNA mature sequences, available in mirBase as reference, we searched matching putative targets. 8730 out of 42011 ESTs from safflower and 7145 of 36323 ESTs from artichoke showed at least one predicted miRNA target. BLAST analysis showed that 75% of all ESTs shared at least a common homologous region (E-value < 10-4) and about 50% of these displayed 400 bp or longer aligned sequences as conserved homologous/orthologous (COS) regions. 960 and 890 ESTs of safflower and artichoke organized in COS shared 79 different miRNA targets, considered functionally conserved, and statistically significant when compared with random sequences (signal to noise ratio > 2 and specificity ≥ 0.85). Four highly significant miRNAs selected from in silico data were experimentally validated in globe artichoke leaves. Conclusions Mature miRNAs and targets were predicted within EST sequences of safflower and artichoke. Most of the miRNA targets appeared highly/moderately conserved, highlighting an important and conserved function. In this study we introduce a stringent parameter for the comparative sequence analysis, represented by the identification of the same target in the COS region. After statistical analysis 79 targets, found on the COS regions and belonging to 60 miRNA families, have a signal to noise ratio > 2, with ≥ 0.85 specificity. The putative miRNAs identified belong to 55 dicotyledon plants and to 24 families only in monocotyledon. PMID:22536958

Understanding the mode-of-action of Cassia auriculata via in silico and in vivo studies towards validating it as a long term therapy for type II diabetes.

PubMed

Mohd Fauzi, Fazlin; John, Cini Mathew; Karunanidhi, Arunkumar; Mussa, Hamse Y; Ramasamy, Rajesh; Adam, Aishah; Bender, Andreas

2017-02-02

Cassia auriculata (CA) is used as an antidiabetic therapy in Ayurvedic and Siddha practice. This study aimed to understand the mode-of-action of CA via combined cheminformatics and in vivo biological analysis. In particular, the effect of 10 polyphenolic constituents of CA in modulating insulin and immunoprotective pathways were studied. In silico target prediction was first employed to predict the probability of the polyphenols interacting with key protein targets related to insulin signalling, based on a model trained on known bioactivity data and chemical similarity considerations. Next, CA was investigated in in vivo studies where induced type 2 diabetic rats were treated with CA for 28 days and the expression levels of genes regulating insulin signalling pathway, glucose transporters of hepatic (GLUT2) and muscular (GLUT4) tissue, insulin receptor substrate (IRS), phosphorylated insulin receptor (AKT), gluconeogenesis (G6PC and PCK-1), along with inflammatory mediators genes (NF-κB, IL-6, IFN-γ and TNF-α) and peroxisome proliferators-activated receptor gamma (PPAR-γ) were determined by qPCR. In silico analysis shows that several of the top 20 enriched targets predicted for the constituents of CA are involved in insulin signalling pathways e.g. PTPN1, PCK-α, AKT2, PI3K-γ. Some of the predictions were supported by scientific literature such as the prediction of PI3K for epigallocatechin gallate. Based on the in silico and in vivo findings, we hypothesized that CA may enhance glucose uptake and glucose transporter expressions via the IRS signalling pathway. This is based on AKT2 and PI3K-γ being listed in the top 20 enriched targets. In vivo analysis shows significant increase in the expression of IRS, AKT, GLUT2 and GLUT4. CA may also affect the PPAR-γ signalling pathway. This is based on the CA-treated groups showing significant activation of PPAR-γ in the liver compared to control. PPAR-γ was predicted by the in silico target prediction with high normalisation rate although it was not in the top 20 most enriched targets. CA may also be involved in the gluconeogenesis and glycogenolysis in the liver based on the downregulation of G6PC and PCK-1 genes seen in CA-treated groups. In addition, CA-treated groups also showed decreased cholesterol, triglyceride, glucose, CRP and Hb1Ac levels, and increased insulin and C-peptide levels. These findings demonstrate the insulin secretagogue and sensitizer effect of CA. Based on both an in silico and in vivo analysis, we propose here that CA mediates glucose/lipid metabolism via the PI3K signalling pathway, and influence AKT thereby causing insulin secretion and insulin sensitivity in peripheral tissues. CA enhances glucose uptake and expression of glucose transporters in particular via the upregulation of GLUT2 and GLUT4. Thus, based on its ability to modulate immunometabolic pathways, CA appears as an attractive long term therapy for T2DM even at relatively low doses. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Computational approach to analyze isolated ssDNA aptamers against angiotensin II.

PubMed

Heiat, Mohammad; Najafi, Ali; Ranjbar, Reza; Latifi, Ali Mohammad; Rasaee, Mohammad Javad

2016-07-20

Aptamers are oligonucleotides with highly structured molecules that can bind to their targets through specific 3-D conformation. Commonly, not all the nucleotides such as primer binding fixed region and some other sequences are vital for aptamers folding and interaction. Elimination of unnecessary regions needs trustworthy prediction tools to reduce experimental efforts and errors. Here we introduced a manipulated in-silico approach to predict the 3-D structure of aptamers and their target interactions. To design an approach for computational analysis of isolated ssDNA aptamers (FLC112, FLC125 and their truncated core region including CRC112 and CRC125), their secondary and tertiary structures were modeled by Mfold and RNA composer respectively. Output PDB files were modified from RNA to DNA in the discovery studio visualizer software. Using ZDOCK server, the aptamer-target interactions were predicted. Finally, the interaction scores were compared with the experimental results. In-silico interaction scores and the experimental outcomes were in the same descending arrangement of FLC112>CRC125>CRC112>FLC125 with similar intensity. The consistent results of innovative in-silico method with experimental outputs, affirmed that the present method may be a reliable approach. Also, it showed that the exact in-silico predictions can be utilized as a credible reference to find aptameric fragments binding potency. Copyright © 2016 Elsevier B.V. All rights reserved.

In Silico Analysis of Gene Expression Network Components Underlying Pigmentation Phenotypes in the Python Identified Evolutionarily Conserved Clusters of Transcription Factor Binding Sites

PubMed Central

2016-01-01

Color variation provides the opportunity to investigate the genetic basis of evolution and selection. Reptiles are less studied than mammals. Comparative genomics approaches allow for knowledge gained in one species to be leveraged for use in another species. We describe a comparative vertebrate analysis of conserved regulatory modules in pythons aimed at assessing bioinformatics evidence that transcription factors important in mammalian pigmentation phenotypes may also be important in python pigmentation phenotypes. We identified 23 python orthologs of mammalian genes associated with variation in coat color phenotypes for which we assessed the extent of pairwise protein sequence identity between pythons and mouse, dog, horse, cow, chicken, anole lizard, and garter snake. We next identified a set of melanocyte/pigment associated transcription factors (CREB, FOXD3, LEF-1, MITF, POU3F2, and USF-1) that exhibit relatively conserved sequence similarity within their DNA binding regions across species based on orthologous alignments across multiple species. Finally, we identified 27 evolutionarily conserved clusters of transcription factor binding sites within ~200-nucleotide intervals of the 1500-nucleotide upstream regions of AIM1, DCT, MC1R, MITF, MLANA, OA1, PMEL, RAB27A, and TYR from Python bivittatus. Our results provide insight into pigment phenotypes in pythons. PMID:27698666

In Silico Analysis of Gene Expression Network Components Underlying Pigmentation Phenotypes in the Python Identified Evolutionarily Conserved Clusters of Transcription Factor Binding Sites.

PubMed

Irizarry, Kristopher J L; Bryden, Randall L

2016-01-01

Color variation provides the opportunity to investigate the genetic basis of evolution and selection. Reptiles are less studied than mammals. Comparative genomics approaches allow for knowledge gained in one species to be leveraged for use in another species. We describe a comparative vertebrate analysis of conserved regulatory modules in pythons aimed at assessing bioinformatics evidence that transcription factors important in mammalian pigmentation phenotypes may also be important in python pigmentation phenotypes. We identified 23 python orthologs of mammalian genes associated with variation in coat color phenotypes for which we assessed the extent of pairwise protein sequence identity between pythons and mouse, dog, horse, cow, chicken, anole lizard, and garter snake. We next identified a set of melanocyte/pigment associated transcription factors (CREB, FOXD3, LEF-1, MITF, POU3F2, and USF-1) that exhibit relatively conserved sequence similarity within their DNA binding regions across species based on orthologous alignments across multiple species. Finally, we identified 27 evolutionarily conserved clusters of transcription factor binding sites within ~200-nucleotide intervals of the 1500-nucleotide upstream regions of AIM1, DCT, MC1R, MITF, MLANA, OA1, PMEL, RAB27A, and TYR from Python bivittatus . Our results provide insight into pigment phenotypes in pythons.

A proteomic analysis of the chromoplasts isolated from sweet orange fruits [Citrus sinensis (L.) Osbeck].

PubMed

Zeng, Yunliu; Pan, Zhiyong; Ding, Yuduan; Zhu, Andan; Cao, Hongbo; Xu, Qiang; Deng, Xiuxin

2011-11-01

Here, a comprehensive proteomic analysis of the chromoplasts purified from sweet orange using Nycodenz density gradient centrifugation is reported. A GeLC-MS/MS shotgun approach was used to identify the proteins of pooled chromoplast samples. A total of 493 proteins were identified from purified chromoplasts, of which 418 are putative plastid proteins based on in silico sequence homology and functional analyses. Based on the predicted functions of these identified plastid proteins, a large proportion (∼60%) of the chromoplast proteome of sweet orange is constituted by proteins involved in carbohydrate metabolism, amino acid/protein synthesis, and secondary metabolism. Of note, HDS (hydroxymethylbutenyl 4-diphosphate synthase), PAP (plastid-lipid-associated protein), and psHSPs (plastid small heat shock proteins) involved in the synthesis or storage of carotenoid and stress response are among the most abundant proteins identified. A comparison of chromoplast proteomes between sweet orange and tomato suggested a high level of conservation in a broad range of metabolic pathways. However, the citrus chromoplast was characterized by more extensive carotenoid synthesis, extensive amino acid synthesis without nitrogen assimilation, and evidence for lipid metabolism concerning jasmonic acid synthesis. In conclusion, this study provides an insight into the major metabolic pathways as well as some unique characteristics of the sweet orange chromoplasts at the whole proteome level.

Evaluation of in silico tools to predict the skin sensitization potential of chemicals.

PubMed

Verheyen, G R; Braeken, E; Van Deun, K; Van Miert, S

2017-01-01

Public domain and commercial in silico tools were compared for their performance in predicting the skin sensitization potential of chemicals. The packages were either statistical based (Vega, CASE Ultra) or rule based (OECD Toolbox, Toxtree, Derek Nexus). In practice, several of these in silico tools are used in gap filling and read-across, but here their use was limited to make predictions based on presence/absence of structural features associated to sensitization. The top 400 ranking substances of the ATSDR 2011 Priority List of Hazardous Substances were selected as a starting point. Experimental information was identified for 160 chemically diverse substances (82 positive and 78 negative). The prediction for skin sensitization potential was compared with the experimental data. Rule-based tools perform slightly better, with accuracies ranging from 0.6 (OECD Toolbox) to 0.78 (Derek Nexus), compared with statistical tools that had accuracies ranging from 0.48 (Vega) to 0.73 (CASE Ultra - LLNA weak model). Combining models increased the performance, with positive and negative predictive values up to 80% and 84%, respectively. However, the number of substances that were predicted positive or negative for skin sensitization in both models was low. Adding more substances to the dataset will increase the confidence in the conclusions reached. The insights obtained in this evaluation are incorporated in a web database www.asopus.weebly.com that provides a potential end user context for the scope and performance of different in silico tools with respect to a common dataset of curated skin sensitization data.

Meta-analysis of genome-wide association studies in East Asian-ancestry populations identifies four new loci for body mass index.

PubMed

Wen, Wanqing; Zheng, Wei; Okada, Yukinori; Takeuchi, Fumihiko; Tabara, Yasuharu; Hwang, Joo-Yeon; Dorajoo, Rajkumar; Li, Huaixing; Tsai, Fuu-Jen; Yang, Xiaobo; He, Jiang; Wu, Ying; He, Meian; Zhang, Yi; Liang, Jun; Guo, Xiuqing; Sheu, Wayne Huey-Herng; Delahanty, Ryan; Guo, Xingyi; Kubo, Michiaki; Yamamoto, Ken; Ohkubo, Takayoshi; Go, Min Jin; Liu, Jian Jun; Gan, Wei; Chen, Ching-Chu; Gao, Yong; Li, Shengxu; Lee, Nanette R; Wu, Chen; Zhou, Xueya; Song, Huaidong; Yao, Jie; Lee, I-Te; Long, Jirong; Tsunoda, Tatsuhiko; Akiyama, Koichi; Takashima, Naoyuki; Cho, Yoon Shin; Ong, Rick Th; Lu, Ling; Chen, Chien-Hsiun; Tan, Aihua; Rice, Treva K; Adair, Linda S; Gui, Lixuan; Allison, Matthew; Lee, Wen-Jane; Cai, Qiuyin; Isomura, Minoru; Umemura, Satoshi; Kim, Young Jin; Seielstad, Mark; Hixson, James; Xiang, Yong-Bing; Isono, Masato; Kim, Bong-Jo; Sim, Xueling; Lu, Wei; Nabika, Toru; Lee, Juyoung; Lim, Wei-Yen; Gao, Yu-Tang; Takayanagi, Ryoichi; Kang, Dae-Hee; Wong, Tien Yin; Hsiung, Chao Agnes; Wu, I-Chien; Juang, Jyh-Ming Jimmy; Shi, Jiajun; Choi, Bo Youl; Aung, Tin; Hu, Frank; Kim, Mi Kyung; Lim, Wei Yen; Wang, Tzung-Dao; Shin, Min-Ho; Lee, Jeannette; Ji, Bu-Tian; Lee, Young-Hoon; Young, Terri L; Shin, Dong Hoon; Chun, Byung-Yeol; Cho, Myeong-Chan; Han, Bok-Ghee; Hwu, Chii-Min; Assimes, Themistocles L; Absher, Devin; Yan, Xiaofei; Kim, Eric; Kuo, Jane Z; Kwon, Soonil; Taylor, Kent D; Chen, Yii-Der I; Rotter, Jerome I; Qi, Lu; Zhu, Dingliang; Wu, Tangchun; Mohlke, Karen L; Gu, Dongfeng; Mo, Zengnan; Wu, Jer-Yuarn; Lin, Xu; Miki, Tetsuro; Tai, E Shyong; Lee, Jong-Young; Kato, Norihiro; Shu, Xiao-Ou; Tanaka, Toshihiro

2014-10-15

Recent genetic association studies have identified 55 genetic loci associated with obesity or body mass index (BMI). The vast majority, 51 loci, however, were identified in European-ancestry populations. We conducted a meta-analysis of associations between BMI and ∼2.5 million genotyped or imputed single nucleotide polymorphisms among 86 757 individuals of Asian ancestry, followed by in silico and de novo replication among 7488-47 352 additional Asian-ancestry individuals. We identified four novel BMI-associated loci near the KCNQ1 (rs2237892, P = 9.29 × 10(-13)), ALDH2/MYL2 (rs671, P = 3.40 × 10(-11); rs12229654, P = 4.56 × 10(-9)), ITIH4 (rs2535633, P = 1.77 × 10(-10)) and NT5C2 (rs11191580, P = 3.83 × 10(-8)) genes. The association of BMI with rs2237892, rs671 and rs12229654 was significantly stronger among men than among women. Of the 51 BMI-associated loci initially identified in European-ancestry populations, we confirmed eight loci at the genome-wide significance level (P < 5.0 × 10(-8)) and an additional 14 at P < 1.0 × 10(-3) with the same direction of effect as reported previously. Findings from this analysis expand our knowledge of the genetic basis of obesity. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Elucidating Rice Cell Metabolism under Flooding and Drought Stresses Using Flux-Based Modeling and Analysis1[C][W][OPEN

PubMed Central

Lakshmanan, Meiyappan; Zhang, Zhaoyang; Mohanty, Bijayalaxmi; Kwon, Jun-Young; Choi, Hong-Yeol; Nam, Hyung-Jin; Kim, Dong-Il; Lee, Dong-Yup

2013-01-01

Rice (Oryza sativa) is one of the major food crops in world agriculture, especially in Asia. However, the possibility of subsequent occurrence of flood and drought is a major constraint to its production. Thus, the unique behavior of rice toward flooding and drought stresses has required special attention to understand its metabolic adaptations. However, despite several decades of research investigations, the cellular metabolism of rice remains largely unclear. In this study, in order to elucidate the physiological characteristics in response to such abiotic stresses, we reconstructed what is to our knowledge the first metabolic/regulatory network model of rice, representing two tissue types: germinating seeds and photorespiring leaves. The phenotypic behavior and metabolic states simulated by the model are highly consistent with our suspension culture experiments as well as previous reports. The in silico simulation results of seed-derived rice cells indicated (1) the characteristic metabolic utilization of glycolysis and ethanolic fermentation based on oxygen availability and (2) the efficient sucrose breakdown through sucrose synthase instead of invertase. Similarly, flux analysis on photorespiring leaf cells elucidated the crucial role of plastid-cytosol and mitochondrion-cytosol malate transporters in recycling the ammonia liberated during photorespiration and in exporting the excess redox cofactors, respectively. The model simulations also unraveled the essential role of mitochondrial respiration during drought stress. In the future, the combination of experimental and in silico analyses can serve as a promising approach to understand the complex metabolism of rice and potentially help in identifying engineering targets for improving its productivity as well as enabling stress tolerance. PMID:23753178

In silico genotoxicity of coumarins: application of the Phenol-Explorer food database to functional food science.

PubMed

Guardado Yordi, E; Matos, M J; Pérez Martínez, A; Tornes, A C; Santana, L; Molina, E; Uriarte, E

2017-08-01

Coumarins are a group of phytochemicals that may be beneficial or harmful to health depending on their type and dosage and the matrix that contains them. Some of these compounds have been proven to display pro-oxidant and clastogenic activities. Therefore, in the current work, we have studied the coumarins that are present in food sources extracted from the Phenol-Explorer database in order to predict their clastogenic activity and identify the structure-activity relationships and genotoxic structural alerts using alternative methods in the field of computational toxicology. It was necessary to compile information on the type and amount of coumarins in different food sources through the analysis of databases of food composition available online. A virtual screening using a clastogenic model and different software, such as MODESLAB, ChemDraw and STATISTIC, was performed. As a result, a table of food composition was prepared and qualitative information from this data was extracted. The virtual screening showed that the esterified substituents inactivate molecules, while the methoxyl and hydroxyl substituents contribute to their activity and constitute, together with the basic structures of the studied subclasses, clastogenic structural alerts. Chemical subclasses of simple coumarins and furocoumarins were classified as active (xanthotoxin, isopimpinellin, esculin, scopoletin, scopolin and bergapten). In silico genotoxicity was mainly predicted for coumarins found in beer, sherry, dried parsley, fresh parsley and raw celery stalks. The results obtained can be interesting for the future design of functional foods and dietary supplements. These studies constitute a reference for the genotoxic chemoinformatic analysis of bioactive compounds present in databases of food composition.

Splice-site mutations identified in PDE6A responsible for retinitis pigmentosa in consanguineous Pakistani families

PubMed Central

Khan, Shahid Y.; Ali, Shahbaz; Naeem, Muhammad Asif; Khan, Shaheen N.; Husnain, Tayyab; Butt, Nadeem H.; Qazi, Zaheeruddin A.; Akram, Javed; Riazuddin, Sheikh; Ayyagari, Radha; Hejtmancik, J. Fielding

2015-01-01

Purpose This study was conducted to localize and identify causal mutations associated with autosomal recessive retinitis pigmentosa (RP) in consanguineous familial cases of Pakistani origin. Methods Ophthalmic examinations that included funduscopy and electroretinography (ERG) were performed to confirm the affectation status. Blood samples were collected from all participating individuals, and genomic DNA was extracted. A genome-wide scan was performed, and two-point logarithm of odds (LOD) scores were calculated. Sanger sequencing was performed to identify the causative variants. Subsequently, we performed whole exome sequencing to rule out the possibility of a second causal variant within the linkage interval. Sequence conservation was performed with alignment analyses of PDE6A orthologs, and in silico splicing analysis was completed with Human Splicing Finder version 2.4.1. Results A large multigenerational consanguineous family diagnosed with early-onset RP was ascertained. An ophthalmic clinical examination consisting of fundus photography and electroretinography confirmed the diagnosis of RP. A genome-wide scan was performed, and suggestive two-point LOD scores were observed with markers on chromosome 5q. Haplotype analyses identified the region; however, the region did not segregate with the disease phenotype in the family. Subsequently, we performed a second genome-wide scan that excluded the entire genome except the chromosome 5q region harboring PDE6A. Next-generation whole exome sequencing identified a splice acceptor site mutation in intron 16: c.2028–1G>A, which was completely conserved in PDE6A orthologs and was absent in ethnically matched 350 control chromosomes, the 1000 Genomes database, and the NHLBI Exome Sequencing Project. Subsequently, we investigated our entire cohort of RP familial cases and identified a second family who harbored a splice acceptor site mutation in intron 10: c.1408–2A>G. In silico analysis suggested that these mutations will result in the elimination of wild-type splice acceptor sites that would result in either skipping of the respective exon or the creation of a new cryptic splice acceptor site; both possibilities would result in retinal photoreceptor cells that lack PDE6A wild-type protein. Conclusions we report two splice acceptor site variations in PDE6A in consanguineous Pakistani families who manifested cardinal symptoms of RP. Taken together with our previously published work, our data suggest that mutations in PDE6A account for about 2% of the total genetic load of RP in our cohort and possibly in the Pakistani population as well. PMID:26321862

Cardio-vascular safety beyond hERG: in silico modelling of a guinea pig right atrium assay

NASA Astrophysics Data System (ADS)

Fenu, Luca A.; Teisman, Ard; De Buck, Stefan S.; Sinha, Vikash K.; Gilissen, Ron A. H. J.; Nijsen, Marjoleen J. M. A.; Mackie, Claire E.; Sanderson, Wendy E.

2009-12-01

As chemists can easily produce large numbers of new potential drug candidates, there is growing demand for high capacity models that can help in driving the chemistry towards efficacious and safe candidates before progressing towards more complex models. Traditionally, the cardiovascular (CV) safety domain plays an important role in this process, as many preclinical CV biomarkers seem to have high prognostic value for the clinical outcome. Throughout the industry, traditional ion channel binding data are generated to drive the early selection process. Although this assay can generate data at high capacity, it has the disadvantage of producing high numbers of false negatives. Therefore, our company applies the isolated guinea pig right atrium (GPRA) assay early-on in discovery. This functional multi-channel/multi-receptor model seems much more predictive in identifying potential CV liabilities. Unfortunately however, its capacity is limited, and there is no room for full automation. We assessed the correlation between ion channel binding and the GPRA's Rate of Contraction (RC), Contractile Force (CF), and effective refractory frequency (ERF) measures assay using over six thousand different data points. Furthermore, the existing experimental knowledge base was used to develop a set of in silico classification models attempting to mimic the GPRA inhibitory activity. The Naïve Bayesian classifier was used to built several models, using the ion channel binding data or in silico computed properties and structural fingerprints as descriptors. The models were validated on an independent and diverse test set of 200 reference compounds. Performances were assessed on the bases of their overall accuracy, sensitivity and specificity in detecting both active and inactive molecules. Our data show that all in silico models are highly predictive of actual GPRA data, at a level equivalent or superior to the ion channel binding assays. Furthermore, the models were interpreted in terms of the descriptors used to highlight the undesirable areas in the explored chemical space, specifically regions of low polarity, high lipophilicity and high molecular weight. In conclusion, we developed a predictive in silico model of a complex physiological assay based on a large and high quality set of experimental data. This model allows high throughput in silico safety screening based on chemical structure within a given chemical space.

AlgaGEM – a genome-scale metabolic reconstruction of algae based on the Chlamydomonas reinhardtii genome

PubMed Central

2011-01-01

Background Microalgae have the potential to deliver biofuels without the associated competition for land resources. In order to realise the rates and titres necessary for commercial production, however, system-level metabolic engineering will be required. Genome scale metabolic reconstructions have revolutionized microbial metabolic engineering and are used routinely for in silico analysis and design. While genome scale metabolic reconstructions have been developed for many prokaryotes and model eukaryotes, the application to less well characterized eukaryotes such as algae is challenging not at least due to a lack of compartmentalization data. Results We have developed a genome-scale metabolic network model (named AlgaGEM) covering the metabolism for a compartmentalized algae cell based on the Chlamydomonas reinhardtii genome. AlgaGEM is a comprehensive literature-based genome scale metabolic reconstruction that accounts for the functions of 866 unique ORFs, 1862 metabolites, 2249 gene-enzyme-reaction-association entries, and 1725 unique reactions. The reconstruction was compartmentalized into the cytoplasm, mitochondrion, plastid and microbody using available data for algae complemented with compartmentalisation data for Arabidopsis thaliana. AlgaGEM describes a functional primary metabolism of Chlamydomonas and significantly predicts distinct algal behaviours such as the catabolism or secretion rather than recycling of phosphoglycolate in photorespiration. AlgaGEM was validated through the simulation of growth and algae metabolic functions inferred from literature. Using efficient resource utilisation as the optimality criterion, AlgaGEM predicted observed metabolic effects under autotrophic, heterotrophic and mixotrophic conditions. AlgaGEM predicts increased hydrogen production when cyclic electron flow is disrupted as seen in a high producing mutant derived from mutational studies. The model also predicted the physiological pathway for H2 production and identified new targets to further improve H2 yield. Conclusions AlgaGEM is a viable and comprehensive framework for in silico functional analysis and can be used to derive new, non-trivial hypotheses for exploring this metabolically versatile organism. Flux balance analysis can be used to identify bottlenecks and new targets to metabolically engineer microalgae for production of biofuels. PMID:22369158

Comparative Analysis of Expressed Genes from Cacao Meristems Infected by Moniliophthora perniciosa

PubMed Central

Gesteira, Abelmon S.; Micheli, Fabienne; Carels, Nicolas; Da Silva, Aline C.; Gramacho, Karina P.; Schuster, Ivan; Macêdo, Joci N.; Pereira, Gonçalo A. G.; Cascardo, Júlio C. M.

2007-01-01

Background and Aims Witches' broom disease is caused by the hemibiotrophic basidiomycete Moniliophthora perniciosa, and is one of the most important diseases of cacao in the western hemisphere. Because very little is known about the global process of such disease development, expressed sequence tags (ESTs) were used to identify genes expressed during the Theobroma cacao–Moniliophthora perniciosa interaction. Methods Two cDNA libraries corresponding to the resistant (RT) and susceptible (SP) cacao–M. perniciosa interactions were constructed from total RNA, using the DB SMART Creator cDNA library kit (Clontech). Clones were randomly selected, sequenced from the 5′ end and analysed using bioinformatics tools including in silico analysis of the differential gene expression. Key Results A total of 6884 ESTs were generated from the RT and SP cDNA libraries. These ESTs were composed of 2585 singlets and 341 contigs for a total of 2926 non-redundant sequences. The redundancy of the libraries was low and their specificity high when compared with the few other cacao libraries already published. Sequence analysis allowed the assignment of a putative functional category for 54 % of sequences, whereas approx. 22 % of sequences corresponded to unknown function and approx. 24 % of sequences did not show any significant similarity with other proteins present in the database. Despite the similar overall distribution of the sequences in functional categories between the two libraries, qualitative differences were observed. Genes involved during the defence response to pathogen infection or in programmed cell death were identified, such as pathogenesis related-proteins, trypsin inhibitor or oxalate oxidase, and some of them showed an in silico differential expression between the resistant and the susceptible interactions. Conclusions As far as is known this is the first EST resource from the cacao–M. perniciosa interaction and it is believed that it will provide a significant contribution to the understanding of the molecular mechanisms of the resistance and susceptibility of cacao to M. perniciosa, to develop strategies to control witches broom, and as a source of polymorphism for molecular marker development and marker-assisted selection. PMID:17557832

Development of a Multiplex PCR Assay for Rapid Molecular Serotyping of Haemophilus parasuis

PubMed Central

Peters, Sarah E.; Wang, Jinhong; Hernandez-Garcia, Juan; Weinert, Lucy A.; Luan, Shi-Lu; Chaudhuri, Roy R.; Angen, Øystein; Aragon, Virginia; Williamson, Susanna M.; Langford, Paul R.; Rycroft, Andrew N.; Wren, Brendan W.; Maskell, Duncan J.; Tucker, Alexander W.

2015-01-01

Haemophilus parasuis causes Glässer's disease and pneumonia in pigs. Indirect hemagglutination (IHA) is typically used to serotype this bacterium, distinguishing 15 serovars with some nontypeable isolates. The capsule loci of the 15 reference strains have been annotated, and significant genetic variation was identified between serovars, with the exception of serovars 5 and 12. A capsule locus and in silico serovar were identified for all but two nontypeable isolates in our collection of >200 isolates. Here, we describe the development of a multiplex PCR, based on variation within the capsule loci of the 15 serovars of H. parasuis, for rapid molecular serotyping. The multiplex PCR (mPCR) distinguished between all previously described serovars except 5 and 12, which were detected by the same pair of primers. The detection limit of the mPCR was 4.29 × 105 ng/μl bacterial genomic DNA, and high specificity was indicated by the absence of reactivity against closely related commensal Pasteurellaceae and other bacterial pathogens of pigs. A subset of 150 isolates from a previously sequenced H. parasuis collection was used to validate the mPCR with 100% accuracy compared to the in silico results. In addition, the two in silico-nontypeable isolates were typeable using the mPCR. A further 84 isolates were analyzed by mPCR and compared to the IHA serotyping results with 90% concordance (excluding those that were nontypeable by IHA). The mPCR was faster, more sensitive, and more specific than IHA, enabling the differentiation of 14 of the 15 serovars of H. parasuis. PMID:26424843

An in silico algorithm for identifying stabilizing pockets in proteins: test case, the Y220C mutant of the p53 tumor suppressor protein

PubMed Central

Bromley, Dennis; Bauer, Matthias R.; Fersht, Alan R.; Daggett, Valerie

2016-01-01

The p53 tumor suppressor protein performs a critical role in stimulating apoptosis and cell cycle arrest in response to oncogenic stress. The function of p53 can be compromised by mutation, leading to increased risk of cancer; approximately 50% of cancers are associated with mutations in the p53 gene, the majority of which are in the core DNA-binding domain. The Y220C mutation of p53, for example, destabilizes the core domain by 4 kcal/mol, leading to rapid denaturation and aggregation. The associated loss of tumor suppressor functionality is associated with approximately 75 000 new cancer cases every year. Destabilized p53 mutants can be ‘rescued’ and their function restored; binding of a small molecule into a pocket on the surface of mutant p53 can stabilize its wild-type structure and restore its function. Here, we describe an in silico algorithm for identifying potential rescue pockets, including the algorithm's integration with the Dynameomics molecular dynamics data warehouse and the DIVE visual analytics engine. We discuss the results of the application of the method to the Y220C p53 mutant, entailing finding a putative rescue pocket through MD simulations followed by an in silico search for stabilizing ligands that dock into the putative rescue pocket. The top three compounds from this search were tested experimentally and one of them bound in the pocket, as shown by nuclear magnetic resonance, and weakly stabilized the mutant. PMID:27503952

Pharmacogenomic identification of small molecules for lineage specific manipulation of subventricular zone germinal activity.

PubMed

Azim, Kasum; Angonin, Diane; Marcy, Guillaume; Pieropan, Francesca; Rivera, Andrea; Donega, Vanessa; Cantù, Claudio; Williams, Gareth; Berninger, Benedikt; Butt, Arthur M; Raineteau, Olivier

2017-03-01

Strategies for promoting neural regeneration are hindered by the difficulty of manipulating desired neural fates in the brain without complex genetic methods. The subventricular zone (SVZ) is the largest germinal zone of the forebrain and is responsible for the lifelong generation of interneuron subtypes and oligodendrocytes. Here, we have performed a bioinformatics analysis of the transcriptome of dorsal and lateral SVZ in early postnatal mice, including neural stem cells (NSCs) and their immediate progenies, which generate distinct neural lineages. We identified multiple signaling pathways that trigger distinct downstream transcriptional networks to regulate the diversity of neural cells originating from the SVZ. Next, we used a novel in silico genomic analysis, searchable platform-independent expression database/connectivity map (SPIED/CMAP), to generate a catalogue of small molecules that can be used to manipulate SVZ microdomain-specific lineages. Finally, we demonstrate that compounds identified in this analysis promote the generation of specific cell lineages from NSCs in vivo, during postnatal life and adulthood, as well as in regenerative contexts. This study unravels new strategies for using small bioactive molecules to direct germinal activity in the SVZ, which has therapeutic potential in neurodegenerative diseases.

Specific Transcriptome Changes Associated with Blood Pressure Reduction in Hypertensive Patients After Relaxation Response Training.

PubMed

Bhasin, Manoj K; Denninger, John W; Huffman, Jeff C; Joseph, Marie G; Niles, Halsey; Chad-Friedman, Emma; Goldman, Roberta; Buczynski-Kelley, Beverly; Mahoney, Barbara A; Fricchione, Gregory L; Dusek, Jeffery A; Benson, Herbert; Zusman, Randall M; Libermann, Towia A

2018-05-01

Mind-body practices that elicit the relaxation response (RR) have been demonstrated to reduce blood pressure (BP) in essential hypertension (HTN) and may be an adjunct to antihypertensive drug therapy. However, the molecular mechanisms by which the RR reduces BP remain undefined. Genomic determinants associated with responsiveness to an 8-week RR-based mind-body intervention for lowering HTN in 13 stage 1 hypertensive patients classified as BP responders and 11 as nonresponders were identified. Transcriptome analysis in peripheral blood mononuclear cells identified 1771 genes regulated by the RR in responders. Biological process- and pathway-based analysis of transcriptome data demonstrated enrichment in the following gene categories: immune regulatory pathways and metabolism (among downregulated genes); glucose metabolism, cardiovascular system development, and circadian rhythm (among upregulated genes). Further in silico estimation of cell abundance from the microarray data showed enrichment of the anti-inflammatory M2 subtype of macrophages in BP responders. Nuclear factor-κB, vascular endothelial growth factor, and insulin were critical molecules emerging from interactive network analysis. These findings provide the first insights into the molecular mechanisms that are associated with the beneficial effects of the RR on HTN.

Specific Transcriptome Changes Associated with Blood Pressure Reduction in Hypertensive Patients After Relaxation Response Training

PubMed Central

Bhasin, Manoj K.; Denninger, John W.; Huffman, Jeff C.; Joseph, Marie G.; Niles, Halsey; Chad-Friedman, Emma; Goldman, Roberta; Buczynski-Kelley, Beverly; Mahoney, Barbara A.; Fricchione, Gregory L.; Dusek, Jeffery A.; Benson, Herbert; Zusman, Randall M.

2018-01-01

Abstract Objective: Mind–body practices that elicit the relaxation response (RR) have been demonstrated to reduce blood pressure (BP) in essential hypertension (HTN) and may be an adjunct to antihypertensive drug therapy. However, the molecular mechanisms by which the RR reduces BP remain undefined. Design: Genomic determinants associated with responsiveness to an 8-week RR-based mind–body intervention for lowering HTN in 13 stage 1 hypertensive patients classified as BP responders and 11 as nonresponders were identified. Results: Transcriptome analysis in peripheral blood mononuclear cells identified 1771 genes regulated by the RR in responders. Biological process- and pathway-based analysis of transcriptome data demonstrated enrichment in the following gene categories: immune regulatory pathways and metabolism (among downregulated genes); glucose metabolism, cardiovascular system development, and circadian rhythm (among upregulated genes). Further in silico estimation of cell abundance from the microarray data showed enrichment of the anti-inflammatory M2 subtype of macrophages in BP responders. Nuclear factor-κB, vascular endothelial growth factor, and insulin were critical molecules emerging from interactive network analysis. Conclusions: These findings provide the first insights into the molecular mechanisms that are associated with the beneficial effects of the RR on HTN. PMID:29616846

Detailed Analysis of the Binding Mode of Vanilloids to Transient Receptor Potential Vanilloid Type I (TRPV1) by a Mutational and Computational Study

PubMed Central

Mori, Yoshikazu; Ogawa, Kazuo; Warabi, Eiji; Yamamoto, Masahiro; Hirokawa, Takatsugu

2016-01-01

Transient receptor potential vanilloid type 1 (TRPV1) is a non-selective cation channel and a multimodal sensor protein. Since the precise structure of TRPV1 was obtained by electron cryo-microscopy, the binding mode of representative agonists such as capsaicin and resiniferatoxin (RTX) has been extensively characterized; however, detailed information on the binding mode of other vanilloids remains lacking. In this study, mutational analysis of human TRPV1 was performed, and four agonists (capsaicin, RTX, [6]-shogaol and [6]-gingerol) were used to identify amino acid residues involved in ligand binding and/or modulation of proton sensitivity. The detailed binding mode of each ligand was then simulated by computational analysis. As a result, three amino acids (L518, F591 and L670) were newly identified as being involved in ligand binding and/or modulation of proton sensitivity. In addition, in silico docking simulation and a subsequent mutational study suggested that [6]-gingerol might bind to and activate TRPV1 in a unique manner. These results provide novel insights into the binding mode of various vanilloids to the channel and will be helpful in developing a TRPV1 modulator. PMID:27606946

Oncogenic deregulation of NKL homeobox gene MSX1 in mantle cell lymphoma.

PubMed

Nagel, Stefan; Ehrentraut, Stefan; Meyer, Corinna; Kaufmann, Maren; Drexler, Hans G; MacLeod, Roderick A F

2014-08-01

NKL homeobox gene MSX1 is physiologically expressed during embryonic hematopoiesis. Here, we detected MSX1 overexpression in three examples of mantle cell lymphoma (MCL) and one of acute myeloid leukemia (AML) by screening 96 leukemia/lymphoma cell lines via microarray profiling. Moreover, in silico analysis identified significant overexpression of MSX1 in 3% each of patients with MCL and AML, confirming aberrant activity in subsets of both types of malignancies. Comparative expression profiling analysis and subsequent functional studies demonstrated overexpression of histone acetyltransferase PHF16 together with transcription factors FOXC1 and HLXB9 as activators of MSX1 transcription. Additionally, we identified regulation of cyclin D1/CCND1 by MSX1 and its repressive cofactor histone H1C. Fluorescence in situ hybridization in MCL cells showed that t(11;14)(q13;q32) results in detachment of CCND1 from its corresponding repressive MSX1 binding site. Taken together, we uncovered regulators and targets of homeobox gene MSX1 in leukemia/lymphoma cells, supporting the view of a recurrent genetic network that is reactivated in malignant transformation.

Comparative genomics study for the identification of drug and vaccine targets in Staphylococcus aureus: MurA ligase enzyme as a proposed candidate.

PubMed

Ghosh, Soma; Prava, Jyoti; Samal, Himanshu Bhusan; Suar, Mrutyunjay; Mahapatra, Rajani Kanta

2014-06-01

Now-a-days increasing emergence of antibiotic-resistant pathogenic microorganisms is one of the biggest challenges for management of disease. In the present study comparative genomics, metabolic pathways analysis and additional parameters were defined for the identification of 94 non-homologous essential proteins in Staphylococcus aureus genome. Further study prioritized 19 proteins as vaccine candidates where as druggability study reports 34 proteins suitable as drug targets. Enzymes from peptidoglycan biosynthesis, folate biosynthesis were identified as candidates for drug development. Furthermore, bacterial secretory proteins and few hypothetical proteins identified in our analysis fulfill the criteria of vaccine candidates. As a case study, we built a homology model of one of the potential drug target, MurA ligase, using MODELLER (9v12) software. The model has been further selected for in silico docking study with inhibitors from the DrugBank database. Results from this study could facilitate selection of proteins for entry into drug design and vaccine production pipelines. Copyright © 2014 Elsevier B.V. All rights reserved.

In silico identification and characterization of the WRKY gene superfamily in pepper (Capsicum annuum L.).

PubMed

Cheng, Y; Yao, Z P; Ruan, M Y; Ye, Q J; Wang, R Q; Zhou, G Z; Luo, J

2016-09-23

The WRKY family is one of the most important transcription factor families in plants, involved in the regulation of a broad range of biological roles. The recent releases of whole-genome sequences of pepper (Capsicum annuum L.) allow us to perform a genome-wide identification and characterization of the WRKY family. In this study, 61 CaWRKY proteins were identified in the pepper genome. Based on protein structural and phylogenetic analyses, these proteins were classified into four main groups (I, II, III, and NG), and Group II was further divided into five subgroups (IIa to IIe). Chromosome mapping analysis indicated that CaWRKY genes are distributed across all 12 chromosomes, although the location of four CaWRKYs (CaWRKY58-CaWRKY61) could not be identified. Two pairs of CaWRKYs located on chromosome 01 appear to be tandem duplications. Furthermore, the phylogenetic tree showed a close evolutionary relationship of WRKYs in three species from Solanaceae. In conclusion, this comprehensive analysis of CaWRKYs will provide rich resources for further functional studies in pepper.

Alu Elements as Novel Regulators of Gene Expression in Type 1 Diabetes Susceptibility Genes?

PubMed

Kaur, Simranjeet; Pociot, Flemming

2015-07-13

Despite numerous studies implicating Alu repeat elements in various diseases, there is sparse information available with respect to the potential functional and biological roles of the repeat elements in Type 1 diabetes (T1D). Therefore, we performed a genome-wide sequence analysis of T1D candidate genes to identify embedded Alu elements within these genes. We observed significant enrichment of Alu elements within the T1D genes (p-value < 10e-16), which highlights their importance in T1D. Functional annotation of T1D genes harboring Alus revealed significant enrichment for immune-mediated processes (p-value < 10e-6). We also identified eight T1D genes harboring inverted Alus (IRAlus) within their 3' untranslated regions (UTRs) that are known to regulate the expression of host mRNAs by generating double stranded RNA duplexes. Our in silico analysis predicted the formation of duplex structures by IRAlus within the 3'UTRs of T1D genes. We propose that IRAlus might be involved in regulating the expression levels of the host T1D genes.

Pregnancy-Induced Gingivitis and OMICS in Dentistry: In Silico Modeling and in Vivo Prospective Validation of Estradiol-Modulated Inflammatory Biomarkers

PubMed Central

Zeidán-Chuliá, Fares; Könönen, Eija; Moreira, José C. F.; Liukkonen, Joonas; Sorsa, Timo; Gürsoy, Ulvi K.

2014-01-01

Abstract Pregnancy-associated gingivitis is a bacterial-induced inflammatory disease with a remarkably high prevalence ranging from 35% to 100% across studies. Yet little is known about the attendant mechanisms or diagnostic biomarkers that can help predict individual susceptibility for rational personalized medicine. We aimed to define inflammatory proteins in saliva, induced or inhibited by estradiol, as early diagnostic biomarkers or target proteins in relation to pregnancy-associated gingivitis. An in silico gene/protein interaction network model was developed by using the STITCH 3.1 with “experiments” and “databases” as input options and a confidence score of 0.700 (high confidence). Salivary estradiol, interleukin (IL)-1β and -8, myeloperoxidase (MPO), matrix metalloproteinase (MMP)-2, -8, and -9, and tissue inhibitor of matrix metalloproteinase (TIMP)-1 levels from 30 women were measured prospectively three times during pregnancy and twice during postpartum. In silico analysis revealed that estradiol interacts with IL-1β and -8 by an activation link when the “actions view” was consulted. In saliva, estradiol concentrations associated positively with TIMP-1 and negatively with MPO and MMP-8 concentrations. When the gingival bleeding on probing percentage (BOP%) was included in the model as an effect modifier, the only association, a negative one, was found between estradiol and MMP-8. Throughout gestation, estradiol modulates the inflammatory response by inhibiting neutrophilic enzymes, such as MMP-8. The interactions between salivary degradative enzymes and proinflammatory cytokines during pregnancy suggest promising ways to identify candidate biomarkers for pregnancy-associated gingivitis, and for personalized medicine in the field of dentistry. Finally, we call for greater investments in, and action for biomarker research in periodontology and dentistry that have surprisingly lagged behind in personalized medicine compared to other fields, such as cancer research. PMID:24983467

A Novel Loss-of-Sclerostin Function Mutation in a First Egyptian Family with Sclerosteosis

PubMed Central

Fayez, Alaaeldin; Aglan, Mona; Esmaiel, Nora; El Zanaty, Taher; Abdel Kader, Mohamed; El Ruby, Mona

2015-01-01

Sclerosteosis is a rare autosomal recessive condition characterized by increased bone density. Mutations in SOST gene coding for sclerostin are linked to sclerosteosis. Two Egyptian brothers with sclerosteosis and their apparently normal consanguineous parents were included in this study. Clinical evaluation and genomic sequencing of the SOST gene were performed followed by in silico analysis of the resulting variation. A novel homozygous frameshift mutation in the SOST gene, characterized as one nucleotide cytosine insertion that led to premature stop codon and loss of functional sclerostin, was identified in the two affected brothers. Their parents were heterozygous for the same mutation. To our knowledge this is the first Egyptian study of sclerosteosis and SOST gene causing mutation. PMID:25984533

In silico toxicology protocols.

PubMed

Myatt, Glenn J; Ahlberg, Ernst; Akahori, Yumi; Allen, David; Amberg, Alexander; Anger, Lennart T; Aptula, Aynur; Auerbach, Scott; Beilke, Lisa; Bellion, Phillip; Benigni, Romualdo; Bercu, Joel; Booth, Ewan D; Bower, Dave; Brigo, Alessandro; Burden, Natalie; Cammerer, Zoryana; Cronin, Mark T D; Cross, Kevin P; Custer, Laura; Dettwiler, Magdalena; Dobo, Krista; Ford, Kevin A; Fortin, Marie C; Gad-McDonald, Samantha E; Gellatly, Nichola; Gervais, Véronique; Glover, Kyle P; Glowienke, Susanne; Van Gompel, Jacky; Gutsell, Steve; Hardy, Barry; Harvey, James S; Hillegass, Jedd; Honma, Masamitsu; Hsieh, Jui-Hua; Hsu, Chia-Wen; Hughes, Kathy; Johnson, Candice; Jolly, Robert; Jones, David; Kemper, Ray; Kenyon, Michelle O; Kim, Marlene T; Kruhlak, Naomi L; Kulkarni, Sunil A; Kümmerer, Klaus; Leavitt, Penny; Majer, Bernhard; Masten, Scott; Miller, Scott; Moser, Janet; Mumtaz, Moiz; Muster, Wolfgang; Neilson, Louise; Oprea, Tudor I; Patlewicz, Grace; Paulino, Alexandre; Lo Piparo, Elena; Powley, Mark; Quigley, Donald P; Reddy, M Vijayaraj; Richarz, Andrea-Nicole; Ruiz, Patricia; Schilter, Benoit; Serafimova, Rositsa; Simpson, Wendy; Stavitskaya, Lidiya; Stidl, Reinhard; Suarez-Rodriguez, Diana; Szabo, David T; Teasdale, Andrew; Trejo-Martin, Alejandra; Valentin, Jean-Pierre; Vuorinen, Anna; Wall, Brian A; Watts, Pete; White, Angela T; Wichard, Joerg; Witt, Kristine L; Woolley, Adam; Woolley, David; Zwickl, Craig; Hasselgren, Catrin

2018-07-01

The present publication surveys several applications of in silico (i.e., computational) toxicology approaches across different industries and institutions. It highlights the need to develop standardized protocols when conducting toxicity-related predictions. This contribution articulates the information needed for protocols to support in silico predictions for major toxicological endpoints of concern (e.g., genetic toxicity, carcinogenicity, acute toxicity, reproductive toxicity, developmental toxicity) across several industries and regulatory bodies. Such novel in silico toxicology (IST) protocols, when fully developed and implemented, will ensure in silico toxicological assessments are performed and evaluated in a consistent, reproducible, and well-documented manner across industries and regulatory bodies to support wider uptake and acceptance of the approaches. The development of IST protocols is an initiative developed through a collaboration among an international consortium to reflect the state-of-the-art in in silico toxicology for hazard identification and characterization. A general outline for describing the development of such protocols is included and it is based on in silico predictions and/or available experimental data for a defined series of relevant toxicological effects or mechanisms. The publication presents a novel approach for determining the reliability of in silico predictions alongside experimental data. In addition, we discuss how to determine the level of confidence in the assessment based on the relevance and reliability of the information. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Natural Compounds for the Treatment of Psoriatic Arthritis: A Proposal Based on Multi-Targeted Osteoclastic Regulation and on a Preclinical Study.

PubMed

Deng, Shiqiang; Cheng, Jianwen; Zhao, Jinmin; Yao, Felix; Xu, Jiake

2017-07-11

Psoriatic arthritis (PsA) is a chronic inflammatory arthritis affecting approximately 2% to 3% of the population globally, and is characterized by both peripheral articular manifestations and axial skeletal involvement. Conventional therapies for PsA have not been fully satisfactory, though natural products (NPs) have been shown to be highly effective and represent important treatment options for psoriasis. PsA is a multigenic autoimmune disease with both environmental and genetic factors contributing to its pathogenesis. Accordingly, it is likely that the use of natural compounds with a multi-targeted approach will enable us to develop better therapies for PsA and related disorders. PsA, either on joint damage or on bone erosion, has been shown to respond to anti-psoriatic pharmacotherapy (APP), APP-like NPs, and their natural compounds. This study aims to uncover specific natural compounds for improved PsA remedies. Specifically, by targeting bone erosion caused by increased osteoclastic bone resorption, we aim to predict the key signaling pathways affected by natural compounds. Further, the study will explore their anti-arthritis effects using an in silico, in vitro, and in vivo approach. Following the signaling pathway prediction, a preclinical efficacy study on animal models will be undertaken. Collectively, this work will discover lead compounds with improved therapeutic effects on PsA. We hypothesize that 9 potential APP-like NPs will have therapeutic effects on arthritis via the modulation of osteoclast bone resorption and signaling pathways. For in silico identification, the Latin name of each NP will be identified using the Encyclopedia of Traditional Chinese Medicine (Encyclopedia of TCM). The biological targets of NPs will be predicted or screened using the Herbal Ingredients' Targets (HIT) database. With the designed search terms, DrugBank will be used to further filter the above biological targets. Protein ANnotation THrough Evolutionary Relationship (PANTHER) will be used to predict the pathways of the natural compound sources. Subsequently, an in vitro sample preparation including extraction, fractionation, isolation, purification, and bioassays with high-speed counter-current chromatography-high-performance liquid chromatography-diode array detection (HSCCC-HPLC-DAD) will be carried out for each identified natural source. In vitro investigations into the effect of NPs on osteoclast signaling pathways will be performed. The experimental methods include cell viability assays, osteoclastogenesis and resorption pit assays, quantitative reverse transcription polymerase chain reaction (RT-PCR), western blot, and luciferase reporter gene assays. Finally, an in vivo preclinical efficacy on a collagen-induced arthritis rat model will be carried out using a treatment group (n=10), a control group (n=10), and a non-arthritis group (n=10). Main outcome measure assessments during intervention include daily macroscopic scores and a digital calipers measurement. Post-treatment tissue measurements will be analyzed by serological testing, radiographic imaging, and histopathological assessment. Studies are currently underway to evaluate the in silico data and the in vitro effects of compounds on osteoclastogenesis and bone resorption. The preclinical study is expected to start a year following completion of the in silico analysis. The in silico rapid approach is proposed as a more general method for adding value to the results of a systematic review of NPs. More importantly, the proposed study builds on a multi-targeted approach for the identification of natural compounds for future drug discovery. This innovative approach is likely to be more precise, efficient, and compatible to identify the novel natural compounds for effective treatment of PsA. ©Shiqiang Deng, Jianwen Cheng, Jinmin Zhao, Felix Yao, Jiake Xu. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 11.07.2017.

Sweetness prediction of natural compounds.

PubMed

Chéron, Jean-Baptiste; Casciuc, Iuri; Golebiowski, Jérôme; Antonczak, Serge; Fiorucci, Sébastien

2017-04-15

Based on the most exhaustive database of sweeteners with known sweetness values, a new quantitative structure-activity relationship model for sweetness prediction has been set up. Analysis of the physico-chemical properties of sweeteners in the database indicates that the structure of most potent sweeteners combines a hydrophobic scaffold functionalized by a limited number of hydrogen bond sites (less than 4 hydrogen bond donors and 10 acceptors), with a moderate molecular weight ranging from 350 to 450g·mol -1 . Prediction of sweetness, bitterness and toxicity properties of the largest database of natural compounds have been performed. In silico screening reveals that the majority of the predicted natural intense sweeteners comprise saponin or stevioside scaffolds. The model highlights that their sweetness potency is comparable to known natural sweeteners. The identified compounds provide a rational basis to initiate the design and chemosensory analysis of new low-calorie sweeteners. Copyright © 2016 Elsevier Ltd. All rights reserved.

Morning glory resin glycosides as α-glucosidase inhibitors: In vitro and in silico analysis.

PubMed

Rosas-Ramírez, Daniel; Escandón-Rivera, Sonia; Pereda-Miranda, Rogelio

2018-04-01

Twenty-seven individual resin glycosides from the morning glory family (Convolvulaceae) were evaluated for their α-glucosidase inhibitory potential. Four of these compounds displayed an inhibitory activity comparable to acarbose, which was used as a positive control. Molecular modeling studies performed by docking analysis were accomplished to predict that the active compounds and acarbose bind to the α-1,4-glucosidase enzyme catalytic site of MAL12 from the yeast Saccharomyces cerevisiae through stable hydrogen bonds primarily with the amino acid residues HIS279 and GLN322. Docking studies with the human maltase-glucoamylase (MGAM) also identified binding modes for resin glycosides inside the catalytic site in the proximity of TYR1251. These results postulate that resin glycosides may be a source of phytotherapeutic agents with antihyperglycemic properties for the prophylaxis and treatment of non-insulin-dependent type 2 diabetes mellitus. Copyright © 2018 Elsevier Ltd. All rights reserved.

Computational analysis and functional expression of ancestral copepod luciferase.

PubMed

Takenaka, Yasuhiro; Noda-Ogura, Akiko; Imanishi, Tadashi; Yamaguchi, Atsushi; Gojobori, Takashi; Shigeri, Yasushi

2013-10-10

We recently reported the cDNA sequences of 11 copepod luciferases from the superfamily Augaptiloidea in the order Calanoida. They were classified into two groups, Metridinidae and Heterorhabdidae/Lucicutiidae families, by phylogenetic analyses. To elucidate the evolutionary processes, we have now further isolated 12 copepod luciferases from Augaptiloidea species (Metridia asymmetrica, Metridia curticauda, Pleuromamma scutullata, Pleuromamma xiphias, Lucicutia ovaliformis and Heterorhabdus tanneri). Codon-based synonymous/nonsynonymous tests of positive selection for 25 identified copepod luciferases suggested that positive Darwinian selection operated in the evolution of Heterorhabdidae luciferases, whereas two types of Metridinidae luciferases had diversified via neutral mechanism. By in silico analysis of the decoded amino acid sequences of 25 copepod luciferases, we inferred two protein sequences as ancestral copepod luciferases. They were expressed in HEK293 cells where they exhibited notable luciferase activity both in intracellular lysates and cultured media, indicating that the luciferase activity was established before evolutionary diversification of these copepod species. © 2013.

Strength of bond with Comspan Opaque to three silicoated alloys and titanium.

PubMed

Hansson, O

1990-06-01

In Sweden high-gold alloys or cobalt-chromium alloys are used for resin-bonded prostheses. The bond strength between a resin cement and different sandblasted or silicoated metals were measured before and after thermocycling; in connection with this some rapid thermocycling methods were studied. The effect of different storage times and different protection coatings on bond strength were tested. Finally, the influence of rubbing and contamination with saliva on bond strength were investigated. Silicoating increased the bond strength significantly. The highest bond strengths were these of silicoated Wirobond and titanium, unsusceptible to thermal stress; the bond strengths of the sandblasted metals were the weakest, and sensitive to thermocycling as well. The influence on bond strength for silicoated gold alloys, protected with an unpolymerized composite resin coating, stored in sealed plastic bags up to 7 days, was negligible. Rubbing and contamination with saliva did not influence bond strength. Preferably, silicoated Wirobond and titanium should be used for resin-bonded prostheses, but gold alloys may still be adequate for clinical use. The experimental method described for storing, sealing, and cleaning the silicoated metal surfaces in this article can be recommended for laboratory and clinical use.

Integrated in silico analyses of regulatory and metabolic networks of Synechococcus sp. PCC 7002 reveal relationships between gene centrality and essentiality

DOE PAGES

Song, Hyun-Seob; McClure, Ryan S.; Bernstein, Hans C.; ...

2015-03-27

Cyanobacteria dynamically relay environmental inputs to intracellular adaptations through a coordinated adjustment of photosynthetic efficiency and carbon processing rates. The output of such adaptations is reflected through changes in transcriptional patterns and metabolic flux distributions that ultimately define growth strategy. To address interrelationships between metabolism and regulation, we performed integrative analyses of metabolic and gene co-expression networks in a model cyanobacterium, Synechococcus sp. PCC 7002. Centrality analyses using the gene co-expression network identified a set of key genes, which were defined here as ‘topologically important.’ Parallel in silico gene knock-out simulations, using the genome-scale metabolic network, classified what we termedmore » as ‘functionally important’ genes, deletion of which affected growth or metabolism. A strong positive correlation was observed between topologically and functionally important genes. Functionally important genes exhibited variable levels of topological centrality; however, the majority of topologically central genes were found to be functionally essential for growth. Subsequent functional enrichment analysis revealed that both functionally and topologically important genes in Synechococcus sp. PCC 7002 are predominantly associated with translation and energy metabolism, two cellular processes critical for growth. This research demonstrates how synergistic network-level analyses can be used for reconciliation of metabolic and gene expression data to uncover fundamental biological principles.« less

New insights into plant glycoside hydrolase family 32 in Agave species

PubMed Central

Avila de Dios, Emmanuel; Gomez Vargas, Alan D.; Damián Santos, Maura L.; Simpson, June

2015-01-01

In order to optimize the use of agaves for commercial applications, an understanding of fructan metabolism in these species at the molecular and genetic level is essential. Based on transcriptome data, this report describes the identification and molecular characterization of cDNAs and deduced amino acid sequences for genes encoding fructosyltransferases, invertases and fructan exohydrolases (FEH) (enzymes belonging to plant glycoside hydrolase family 32) from four different agave species (A. tequilana, A. deserti, A. victoriae-reginae, and A. striata). Conserved amino acid sequences and a hypervariable domain allowed classification of distinct isoforms for each enzyme type. Notably however neither 1-FFT nor 6-SFT encoding cDNAs were identified. In silico analysis revealed that distinct isoforms for certain enzymes found in a single species, showed different levels and tissue specific patterns of expression whereas in other cases expression patterns were conserved both within the species and between different species. Relatively high levels of in silico expression for specific isoforms of both invertases and fructosyltransferases were observed in floral tissues in comparison to vegetative tissues such as leaves and stems and this pattern was confirmed by Quantitative Real Time PCR using RNA obtained from floral and leaf tissue of A. tequilana. Thin layer chromatography confirmed the presence of fructans with degree of polymerization (DP) greater than DP three in both immature buds and fully opened flowers also obtained from A. tequilana. PMID:26300895

New insights into plant glycoside hydrolase family 32 in Agave species.

PubMed

Avila de Dios, Emmanuel; Gomez Vargas, Alan D; Damián Santos, Maura L; Simpson, June

2015-01-01

In order to optimize the use of agaves for commercial applications, an understanding of fructan metabolism in these species at the molecular and genetic level is essential. Based on transcriptome data, this report describes the identification and molecular characterization of cDNAs and deduced amino acid sequences for genes encoding fructosyltransferases, invertases and fructan exohydrolases (FEH) (enzymes belonging to plant glycoside hydrolase family 32) from four different agave species (A. tequilana, A. deserti, A. victoriae-reginae, and A. striata). Conserved amino acid sequences and a hypervariable domain allowed classification of distinct isoforms for each enzyme type. Notably however neither 1-FFT nor 6-SFT encoding cDNAs were identified. In silico analysis revealed that distinct isoforms for certain enzymes found in a single species, showed different levels and tissue specific patterns of expression whereas in other cases expression patterns were conserved both within the species and between different species. Relatively high levels of in silico expression for specific isoforms of both invertases and fructosyltransferases were observed in floral tissues in comparison to vegetative tissues such as leaves and stems and this pattern was confirmed by Quantitative Real Time PCR using RNA obtained from floral and leaf tissue of A. tequilana. Thin layer chromatography confirmed the presence of fructans with degree of polymerization (DP) greater than DP three in both immature buds and fully opened flowers also obtained from A. tequilana.

Structural model of the hUbA1-UbcH10 quaternary complex: in silico and experimental analysis of the protein-protein interactions between E1, E2 and ubiquitin.

PubMed

Correale, Stefania; de Paola, Ivan; Morgillo, Carmine Marco; Federico, Antonella; Zaccaro, Laura; Pallante, Pierlorenzo; Galeone, Aldo; Fusco, Alfredo; Pedone, Emilia; Luque, F Javier; Catalanotti, Bruno

2014-01-01

UbcH10 is a component of the Ubiquitin Conjugation Enzymes (Ubc; E2) involved in the ubiquitination cascade controlling the cell cycle progression, whereby ubiquitin, activated by E1, is transferred through E2 to the target protein with the involvement of E3 enzymes. In this work we propose the first three dimensional model of the tetrameric complex formed by the human UbA1 (E1), two ubiquitin molecules and UbcH10 (E2), leading to the transthiolation reaction. The 3D model was built up by using an experimentally guided incremental docking strategy that combined homology modeling, protein-protein docking and refinement by means of molecular dynamics simulations. The structural features of the in silico model allowed us to identify the regions that mediate the recognition between the interacting proteins, revealing the active role of the ubiquitin crosslinked to E1 in the complex formation. Finally, the role of these regions involved in the E1-E2 binding was validated by designing short peptides that specifically interfere with the binding of UbcH10, thus supporting the reliability of the proposed model and representing valuable scaffolds for the design of peptidomimetic compounds that can bind selectively to Ubcs and inhibit the ubiquitylation process in pathological disorders.

Degradation of Aflatoxins by Means of Laccases from Trametes versicolor: An In Silico Insight

PubMed Central

Dellafiora, Luca; Galaverna, Gianni; Reverberi, Massimo; Dall’Asta, Chiara

2017-01-01

Mycotoxins are secondary metabolites of fungi that contaminate food and feed, and are involved in a series of foodborne illnesses and disorders in humans and animals. The mitigation of mycotoxin content via enzymatic degradation is a strategy to ensure safer food and feed, and to address the forthcoming issues in view of the global trade and sustainability. Nevertheless, the search for active enzymes is still challenging and time-consuming. The in silico analysis may strongly support the research by providing the evidence-based hierarchization of enzymes for a rational design of more effective experimental trials. The present work dealt with the degradation of aflatoxin B1 and M1 by laccase enzymes from Trametes versicolor. The enzymes–substrate interaction for various enzyme isoforms was investigated through 3D molecular modeling techniques. Structural differences among the isoforms have been pinpointed, which may cause different patterns of interaction between aflatoxin B1 and M1. The possible formation of different products of degradation can be argued accordingly. Moreover, the laccase gamma isoform was identified as the most suitable for protein engineering aimed at ameliorating the substrate specificity. Overall, 3D modeling proved to be an effective analytical tool to assess the enzyme–substrate interaction and provided a solid foothold for supporting the search of degrading enzyme at the early stage. PMID:28045427

Integrated in silico analyses of regulatory and metabolic networks of Synechococcus sp. PCC 7002 reveal relationships between gene centrality and essentiality

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, Hyun-Seob; McClure, Ryan S.; Bernstein, Hans C.

Cyanobacteria dynamically relay environmental inputs to intracellular adaptations through a coordinated adjustment of photosynthetic efficiency and carbon processing rates. The output of such adaptations is reflected through changes in transcriptional patterns and metabolic flux distributions that ultimately define growth strategy. To address interrelationships between metabolism and regulation, we performed integrative analyses of metabolic and gene co-expression networks in a model cyanobacterium, Synechococcus sp. PCC 7002. Centrality analyses using the gene co-expression network identified a set of key genes, which were defined here as ‘topologically important.’ Parallel in silico gene knock-out simulations, using the genome-scale metabolic network, classified what we termedmore » as ‘functionally important’ genes, deletion of which affected growth or metabolism. A strong positive correlation was observed between topologically and functionally important genes. Functionally important genes exhibited variable levels of topological centrality; however, the majority of topologically central genes were found to be functionally essential for growth. Subsequent functional enrichment analysis revealed that both functionally and topologically important genes in Synechococcus sp. PCC 7002 are predominantly associated with translation and energy metabolism, two cellular processes critical for growth. This research demonstrates how synergistic network-level analyses can be used for reconciliation of metabolic and gene expression data to uncover fundamental biological principles.« less

An in silico pan-genomic probe for the molecular traits behind Lactobacillus ruminis gut autochthony

PubMed Central

Kant, Ravi; Palva, Airi

2017-01-01

As an ecological niche, the mammalian intestine provides the ideal habitat for a variety of bacterial microorganisms. Purportedly, some commensal genera and species offer a beneficial mix of metabolic, protective, and structural processes that help sustain the natural digestive health of the host. Among these sort of gut inhabitants is the Gram-positive lactic acid bacterium Lactobacillus ruminis, a strict anaerobe with both pili and flagella on its cell surface, but also known for being autochthonous (indigenous) to the intestinal environment. Given that the molecular basis of gut autochthony for this species is largely unexplored and unknown, we undertook a study at the genome level to pinpoint some of the adaptive traits behind its colonization behavior. In our pan-genomic probe of L. ruminis, the genomes of nine different strains isolated from human, bovine, porcine, and equine host guts were compiled and compared for in silico analysis. For this, we conducted a geno-phenotypic assessment of protein-coding genes, with an emphasis on those products involved with cell-surface morphology and anaerobic fermentation and respiration. We also categorized and examined the core and accessory genes that define the L. ruminis species and its strains. Here, we made an attempt to identify those genes having ecologically relevant phenotypes that might support or bring about intestinal indigenousness. PMID:28414739

An in silico high-throughput screen identifies potential selective inhibitors for the non-receptor tyrosine kinase Pyk2

PubMed Central

Meirson, Tomer; Samson, Abraham O; Gil-Henn, Hava

2017-01-01

The non-receptor tyrosine kinase proline-rich tyrosine kinase 2 (Pyk2) is a critical mediator of signaling from cell surface growth factor and adhesion receptors to cell migration, proliferation, and survival. Emerging evidence indicates that signaling by Pyk2 regulates hematopoietic cell response, bone density, neuronal degeneration, angiogenesis, and cancer. These physiological and pathological roles of Pyk2 warrant it as a valuable therapeutic target for invasive cancers, osteoporosis, Alzheimer’s disease, and inflammatory cellular response. Despite its potential as a therapeutic target, no potent and selective inhibitor of Pyk2 is available at present. As a first step toward discovering specific potential inhibitors of Pyk2, we used an in silico high-throughput screening approach. A virtual library of six million lead-like compounds was docked against four different high-resolution Pyk2 kinase domain crystal structures and further selected for predicted potency and ligand efficiency. Ligand selectivity for Pyk2 over focal adhesion kinase (FAK) was evaluated by comparative docking of ligands and measurement of binding free energy so as to obtain 40 potential candidates. Finally, the structural flexibility of a subset of the docking complexes was evaluated by molecular dynamics simulation, followed by intermolecular interaction analysis. These compounds may be considered as promising leads for further development of highly selective Pyk2 inhibitors. PMID:28572720

Lactobacillus acidophilus binds to MUC3 component of cultured intestinal epithelial cells with highest affinity.

PubMed

Das, Jugal Kishore; Mahapatra, Rajani Kanta; Patro, Shubhransu; Goswami, Chandan; Suar, Mrutyunjay

2016-04-01

Lactobacillus strains have been shown to adhere to the mucosal components of intestinal epithelial cells. However, established in vitro adhesion assays have several drawbacks in assessing the adhesion of new Lactobacillus strains. The present study aimed to compare the adhesion of four different Lactobacillus strains and select the most adherent microbe, based on in silico approach supported by in vitro results. The mucus-binding proteins in Lactobacillus acidophilus, L. plantarum, L. brevis and L. fermentum were identified and their capacities to interact with intestinal mucin were compared by molecular docking analysis. Lactobacillus acidophilus had the maximal affinity of binding to mucin with predicted free energy of -6.066 kcal mol(-1) Further, in vitro experimental assay of adhesion was performed to validate the in silico results. The adhesion of L. acidophilus to mucous secreting colon epithelial HT-29 MTX cells was highest at 12%, and it formed biofilm with maximum depth (Z = 84 μm). Lactobacillus acidophilus was determined to be the most adherent strain in the study. All the Lactobacillus strains tested in this study, displayed maximum affinity of binding to MUC3 component of mucus as compared to other gastrointestinal mucins. These findings may have importance in the design of probiotics and health care management. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Bridging the provenance gap: opportunities and challenges tracking in and ex silico provenance in sUAS workflows

NASA Astrophysics Data System (ADS)

Thomer, A.

2017-12-01

Data provenance - the record of the varied processes that went into the creation of a dataset, as well as the relationships between resulting data objects - is necessary to support the reusability, reproducibility and reliability of earth science data. In sUAS-based research, capturing provenance can be particularly challenging because of the breadth and distributed nature of the many platforms used to collect, process and analyze data. In any given project, multiple drones, controllers, computers, software systems, sensors, cameras, imaging processing algorithms and data processing workflows are used over sometimes long periods of time. These platforms and processing result in dozens - if not hundreds - of data products in varying stages of readiness-for-analysis and sharing. Provenance tracking mechanisms are needed to make the relationships between these many data products explicit, and therefore more reusable and shareable. In this talk, I discuss opportunities and challenges in tracking provenance in sUAS-based research, and identify gaps in current workflow-capture technologies. I draw on prior work conducted as part of the IMLS-funded Site-Based Data Curation project in which we developed methods of documenting in and ex silico (that is, computational and non-computation) workflows, and demonstrate this approaches applicability to research with sUASes. I conclude with a discussion of ontologies and other semantic technologies that have potential application in sUAS research.

High throughput virtual screening and in silico ADMET analysis for rapid and efficient identification of potential PAP248-286 aggregation inhibitors as anti-HIV agents

NASA Astrophysics Data System (ADS)

Malik, Ruchi; Bunkar, Devendra; Choudhary, Bhanwar Singh; Srivastava, Shubham; Mehta, Pakhuri; Sharma, Manish

2016-10-01

Human semen is principal vehicle for transmission of HIV-1 and other enveloped viruses. Several endogenous peptides present in semen, including a 39-amino acid fragments of prostatic acid phosphatase (PAP248-286) assemble into amyloid fibrils named as semen-derived enhancer of viral infection (SEVI) that promote virion attachment to target cells which dramatically enhance HIV virus infection by up to 105-fold. Epigallocatechin-3-gallate (EGCG), a polyphenolic compound, is the major catechin found in green tea which disaggregates existing SEVI fibers, and inhibits the formation of SEVI fibers. The aim of this study was to screen a number of relevant polyphenols to develop a rational approach for designing PAP248-286 aggregation inhibitors as potential anti-HIV agents. The molecular docking based virtual screening results showed that polyphenolic compounds 2-6 possessed good docking score and interacted well with the active site residues of PAP248-286. Amino acid residues of binding site namely; Lys255, Ser256, Leu258 and Asn265 are involved in binding of these compounds. In silico ADMET prediction studies on these hits were also found to be promising. Polyphenolic compounds 2-6 identified as hits may act as novel leads for inhibiting aggregation of PAP248-286 into SEVI.

Building scientific confidence in metabolic similarity in read-across through the use of in vitro, in silico and analytical data

EPA Science Inventory

The underlying principle of read-across is that the biological activity of a chemical is inherent in its molecular structure. Analogues are typically identified by structural similarity then evaluated on the basis of their bioavailability, reactivity and metabolic similarity. Whi...

20180312 - Building scientific confidence in metabolic similarity in read-across through the use of in vitro, in silico and analytical data (SOT)

EPA Science Inventory

The underlying principle of read-across is that the biological activity of a chemical is inherent in its molecular structure. Analogues are typically identified by structural similarity then evaluated on the basis of their bioavailability, reactivity and metabolic similarity. Whi...

The identification of protein domains that mediate functional interactions between Rab-GTPases and RabGAPs using 3D protein modeling.

PubMed

Davie, Jeremiah J; Faitar, Silviu L

2017-01-01

Currently, time-consuming serial in vitro experimentation involving immunocytochemistry or radiolabeled materials is required to identify which of the numerous Rab-GTPases (Rab) and Rab-GTPase activating proteins (RabGAP) are capable of functional interactions. These interactions are essential for numerous cellular functions, and in silico methods of reducing in vitro trial and error would accelerate the pace of research in cell biology. We have utilized a combination of three-dimensional protein modeling and protein bioinformatics to identify domains present in Rab proteins that are predictive of their functional interaction with a specific RabGAP. The RabF2 and RabSF1 domains appear to play functional roles in mediating the interaction between Rabs and RabGAPs. Moreover, the RabSF1 domain can be used to make in silico predictions of functional Rab/RabGAP pairs. This method is expected to be a broadly applicable tool for predicting protein-protein interactions where existing crystal structures for homologs of the proteins of interest are available.

IspE Inhibitors Identified by a Combination of In Silico and In Vitro High-Throughput Screening

PubMed Central

Tidten-Luksch, Naomi; Grimaldi, Raffaella; Torrie, Leah S.; Frearson, Julie A.; Hunter, William N.; Brenk, Ruth

2012-01-01

CDP-ME kinase (IspE) contributes to the non-mevalonate or deoxy-xylulose phosphate (DOXP) pathway for isoprenoid precursor biosynthesis found in many species of bacteria and apicomplexan parasites. IspE has been shown to be essential by genetic methods and since it is absent from humans it constitutes a promising target for antimicrobial drug development. Using in silico screening directed against the substrate binding site and in vitro high-throughput screening directed against both, the substrate and co-factor binding sites, non-substrate-like IspE inhibitors have been discovered and structure-activity relationships were derived. The best inhibitors in each series have high ligand efficiencies and favourable physico-chemical properties rendering them promising starting points for drug discovery. Putative binding modes of the ligands were suggested which are consistent with established structure-activity relationships. The applied screening methods were complementary in discovering hit compounds, and a comparison of both approaches highlights their strengths and weaknesses. It is noteworthy that compounds identified by virtual screening methods provided the controls for the biochemical screens. PMID:22563402

Isolation, identification and molecular docking as cyclooxygenase (COX) inhibitors of the main constituents of Matricaria chamomilla L. extract and its synergistic interaction with diclofenac on nociception and gastric damage in rats.

PubMed

Ortiz, Mario I; Fernández-Martínez, Eduardo; Soria-Jasso, Luis Enrique; Lucas-Gómez, Isaac; Villagómez-Ibarra, Roberto; González-García, Martha P; Castañeda-Hernández, Gilberto; Salinas-Caballero, Mireya

2016-03-01

Chamomile (Matricaria chamomilla L., Asteraceae) is a medicinal plant widely used as remedy for pain and gastric disorders. The association of non-steroidal anti-inflammatory drugs (NSAIDs) with medicinal plant extracts may increase its antinociceptive activity, permit the use of lower doses and limit side effects. The aim was to isolate and identify the main chemical constituents of Matricaria chamomilla ethanolic extract (MCE) as well as to explore their activity as cyclooxygenase (COX) inhibitors in silico; besides, to examine the interaction between MCE and diclofenac on nociception in the formalin test by isobolographic analysis, and to determine the level of gastric injury in rats. Three terpenoids, α-bisabolol, bisabolol oxide A, and guaiazulene, were isolated and identified by (1)H NMR. Docking simulation predicted COX inhibitory activity for those terpenoids. Diclofenac, MCE, or their combinations produced an antinociceptive effect. The sole administration of diclofenac and the highest combined dose diclofenac-MCE produced significant a gastric damage, but that effect was not seen with MCE alone. An isobologram was constructed and the derived theoretical ED35 for the antinociceptive effect was significantly different from the experimental ED35; hence, the interaction between diclofenac and MCE that mediates the antinociceptive effect is synergist. The MCE contains three major terpenoids with plausible COX inhibitory activity in silico, but α-bisabolol showed the highest affinity. Data suggest that the diclofenac-MCE combination can interact at the systemic level in a synergic manner and may have therapeutic advantages for the clinical treatment of inflammatory pain. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Novel Non-Peptide Inhibitors against SmCL1 of Schistosoma mansoni: In Silico Elucidation, Implications and Evaluation via Knowledge Based Drug Discovery

PubMed Central

Zafar, Atif; Ahmad, Sabahuddin; Rizvi, Asim; Ahmad, Masood

2015-01-01

Schistosomiasis is a major endemic disease known for excessive mortality and morbidity in developing countries. Because praziquantel is the only drug available for its treatment, the risk of drug resistance emphasizes the need to discover new drugs for this disease. Cathepsin SmCL1 is the critical target for drug design due to its essential role in the digestion of host proteins for growth and development of Schistosoma mansoni. Inhibiting the function of SmCL1 could control the wide spread of infections caused by S. mansoni in humans. With this objective, a homology modeling approach was used to obtain theoretical three-dimensional (3D) structure of SmCL1. In order to find the potential inhibitors of SmCL1, a plethora of in silico techniques were employed to screen non-peptide inhibitors against SmCL1 via structure-based drug discovery protocol. Receiver operating characteristic (ROC) curve analysis and molecular dynamics (MD) simulation were performed on the results of docked protein-ligand complexes to identify top ranking molecules against the modelled 3D structure of SmCL1. MD simulation results suggest the phytochemical Simalikalactone-D as a potential lead against SmCL1, whose pharmacophore model may be useful for future screening of potential drug molecules. To conclude, this is the first report to discuss the virtual screening of non-peptide inhibitors against SmCL1 of S. mansoni, with significant therapeutic potential. Results presented herein provide a valuable contribution to identify the significant leads and further derivatize them to suitable drug candidates for antischistosomal therapy. PMID:25933436

Secondary metabolites of Cynodon dactylon as an antagonist to angiotensin II type1 receptor: Novel in silico drug targeting approach for diabetic retinopathy

PubMed Central

Jananie, R. K.; Priya, V.; Vijayalakshmi, K.

2012-01-01

Objectives: To study the ability of the secondary metabolites of Cynodon dactylon to serve as an antagonist to angiotensin II type 1 receptor (AT1); activation of this receptor plays a vital role in diabetic retinopathy (DR). Materials and Methods: In silico methods are mainly harnessed to reduce time, cost and risk associated with drug discovery. Twenty-four compounds were identified as the secondary metabolites of hydroalcoholic extract of C. dactylon using the GCMS technique. These were considered as the ligands or inhibitors that would serve as an antagonist to the AT1. The ACD/Chemsketch tool was used to generate 3D structures of the ligands. A molecular file format converter tool was used to convert the generated data to the PDB format (Protein Data Bank) and was used for docking studies. The AT1 structure was retrieved from the Swissprot data base and PDB and visualized using the Rasmol tool. Domain analysis was carried from the Pfam data base; following this, the active site of the target protein was identified using a Q-site finder tool. The ability of the ligands to bind with the active site of AT1 was studied using the Autodocking tool. The docking results were analyzed using the WebLab viewer tool. Results: Sixteen ligands showed effective binding with the target protein; diazoprogesteron, didodecyl phthalate, and 9,12-octadecadienoyl chloride (z,z) may be considered as compounds that could be used to bind with the active site sequence of AT1. Conclusions: The present study shows that the metabolites of C. dactylon could serve as a natural antagonist to AT1 that could be used to treat diabetic retinopathy. PMID:22368412

Genome-wide identification and phylogenetic analysis of the AP2/ERF gene superfamily in sweet orange (Citrus sinensis).

PubMed

Ito, T M; Polido, P B; Rampim, M C; Kaschuk, G; Souza, S G H

2014-09-26

Sweet orange (Citrus sinensis) plays an important role in the economy of more than 140 countries, but it is grown in areas with intermittent stressful soil and climatic conditions. The stress tolerance could be addressed by manipulating the ethylene response factor (ERF) transcription factors because they orchestrate plant responses to environmental stress. We performed an in silico study on the ERFs in the expressed sequence tag database of C. sinensis to identify potential genes that regulate plant responses to stress. We identified 108 putative genes encoding protein sequences of the AP2/ERF superfamily distributed within 10 groups of amino acid sequences. Ninety-one genes were assembled from the ERF family containing only one AP2/ERF domain, 13 genes were assembled from the AP2 family containing two AP2/ERF domains, and four other genes were assembled from the RAV family containing one AP2/ERF domain and a B3 domain. Some conserved domains of the ERF family genes were disrupted into a few segments by introns. This irregular distribution of genes in the AP2/ERF superfamily in different plant species could be a result of genomic losses or duplication events in a common ancestor. The in silico gene expression revealed that 67% of AP2/ERF genes are expressed in tissues with usual plant development, and 14% were expressed in stressed tissues. Because the AP2/ERF superfamily is expressed in an orchestrated way, it is possible that the manipulation of only one gene may result in changes in the whole plant function, which could result in more tolerant crops.

Beyond an AFLP genome scan towards the identification of immune genes involved in plague resistance in Rattus rattus from Madagascar.

PubMed

Tollenaere, C; Jacquet, S; Ivanova, S; Loiseau, A; Duplantier, J-M; Streiff, R; Brouat, C

2013-01-01

Genome scans using amplified fragment length polymorphism (AFLP) markers became popular in nonmodel species within the last 10 years, but few studies have tried to characterize the anonymous outliers identified. This study follows on from an AFLP genome scan in the black rat (Rattus rattus), the reservoir of plague (Yersinia pestis infection) in Madagascar. We successfully sequenced 17 of the 22 markers previously shown to be potentially affected by plague-mediated selection and associated with a plague resistance phenotype. Searching these sequences in the genome of the closely related species Rattus norvegicus assigned them to 14 genomic regions, revealing a random distribution of outliers in the genome (no clustering). We compared these results with those of an in silico AFLP study of the R. norvegicus genome, which showed that outlier sequences could not have been inferred by this method in R. rattus (only four of the 15 sequences were predicted). However, in silico analysis allowed the prediction of AFLP markers distribution and the estimation of homoplasy rates, confirming its potential utility for designing AFLP studies in nonmodel species. The 14 genomic regions surrounding AFLP outliers (less than 300 kb from the marker) contained 75 genes encoding proteins of known function, including nine involved in immune function and pathogen defence. We identified the two interleukin 1 genes (Il1a and Il1b) that share homology with an antigen of Y. pestis, as the best candidates for genes subject to plague-mediated natural selection. At least six other genes known to be involved in proinflammatory pathways may also be affected by plague-mediated selection. © 2012 Blackwell Publishing Ltd.

Integrated In Silico-In Vitro Identification and Characterization of the SH3-Mediated Interaction between Human PTTG and its Cognate Partners in Medulloblastoma.

PubMed

Liu, Jiangang; Wang, Dapeng; Li, Yanyan; Yao, Hui; Zhang, Nan; Zhang, Xuewen; Zhong, Fangping; Huang, Yulun

2018-06-01

The human pituitary tumor-transforming gene is an oncogenic protein which serves as a central hub in the cellular signaling network of medulloblastoma. The protein contains two vicinal PxxP motifs at its C terminus that are potential binding sites of peptide-recognition SH3 domains. Here, a synthetic protocol that integrated in silico analysis and in vitro assay was described to identify the SH3-binding partners of pituitary tumor-transforming gene in the gene expression profile of medulloblastoma. In the procedure, a variety of structurally diverse, non-redundant SH3 domains with high gene expression in medulloblastoma were compiled, and their three-dimensional structures were either manually retrieved from the protein data bank database or computationally modeled through bioinformatics technique. The binding capability of these domains towards the two PxxP-containing peptides m1p: 161 LGPPSPVK 168 and m2p: 168 KMPSPPWE 175 of pituitary tumor-transforming gene were ranked by structure-based scoring and fluorescence-based assay. Consequently, a number of SH3 domains, including MAP3K and PI3K, were found to have moderate or high affinity for m1p and/or m2p. Interestingly, the two overlapping peptides exhibits a distinct binding profile to these identified domain partners, suggesting that the binding selectivity of m1p and m2p is optimized across the medulloblastoma expression spectrum by competing for domain candidates. In addition, two redesigned versions of m1p peptide ware obtained via a structure-based rational mutation approach, which exhibited an increased affinity for the domain as compared to native peptide.

High-Throughput and Rapid Screening of Novel ACE Inhibitory Peptides from Sericin Source and Inhibition Mechanism by Using in Silico and in Vitro Prescriptions.

PubMed

Sun, Huaju; Chang, Qing; Liu, Long; Chai, Kungang; Lin, Guangyan; Huo, Qingling; Zhao, Zhenxia; Zhao, Zhongxing

2017-11-22

Several novel peptides with high ACE-I inhibitory activity were successfully screened from sericin hydrolysate (SH) by coupling in silico and in vitro approaches for the first time. Most screening processes for ACE-I inhibitory peptides were achieved through high-throughput in silico simulation followed by in vitro verification. QSAR model based predicted results indicated that the ACE-I inhibitory activity of these SH peptides and six chosen peptides exhibited moderate high ACE-I inhibitory activities (log IC 50 values: 1.63-2.34). Moreover, two tripeptides among the chosen six peptides were selected for ACE-I inhibition mechanism analysis which based on Lineweaver-Burk plots indicated that they behave as competitive ACE-I inhibitors. The C-terminal residues of short-chain peptides that contain more H-bond acceptor groups could easily form hydrogen bonds with ACE-I and have higher ACE-I inhibitory activity. Overall, sericin protein as a strong ACE-I inhibition source could be deemed a promising agent for antihypertension applications.

Bond efficacy of recycled orthodontic brackets: A comparative in vitro evaluation of two methods.

PubMed

Shetty, Vikram; Shekatkar, Yash; Kumbhat, Neesu; Gautam, G; Karbelkar, Shalan; Vandekar, Meghna

2015-01-01

Recycling of orthodontic brackets in developing orthodontic economies is an extremely common procedure. Bonding protocols and reliability of these brackets is, however, questionable, and still the subject of research. The aim was to evaluate and compare the shear bond strength of brackets recycled with sandblasting and silicoating. Ninety extracted human premolars were bonded with 0.022" SS brackets (American Orthodontics, Sheboygan USA) and then debonded. The debonded brackets were divided into three groups of 30 each. Group I: Sandblasting with 50-μm aluminum oxide (control group) Group II: Sandblasting with 50-μm aluminum oxide followed by metal primer application Group III: Silicoating with 30-μm Cojet sand followed by silane application and rebonded with Transbond XT. The sandblasted brackets and silicoated brackets were viewed under the scanning electron microscope, immediately after surface conditioning before rebonding. The shear bond strength with each group was tested. One-way analysis of variance, post-hoc Scheffe multiple comparison tests. The results showed that sandblasting created more irregularities and deeper erosions while silica coating created superficial irregularities and shallow erosions.

Provisional in-silico biopharmaceutics classification (BCS) to guide oral drug product development

PubMed Central

Wolk, Omri; Agbaria, Riad; Dahan, Arik

2014-01-01

The main objective of this work was to investigate in-silico predictions of physicochemical properties, in order to guide oral drug development by provisional biopharmaceutics classification system (BCS). Four in-silico methods were used to estimate LogP: group contribution (CLogP) using two different software programs, atom contribution (ALogP), and element contribution (KLogP). The correlations (r2) of CLogP, ALogP and KLogP versus measured LogP data were 0.97, 0.82, and 0.71, respectively. The classification of drugs with reported intestinal permeability in humans was correct for 64.3%–72.4% of the 29 drugs on the dataset, and for 81.82%–90.91% of the 22 drugs that are passively absorbed using the different in-silico algorithms. Similar permeability classification was obtained with the various in-silico methods. The in-silico calculations, along with experimental melting points, were then incorporated into a thermodynamic equation for solubility estimations that largely matched the reference solubility values. It was revealed that the effect of melting point on the solubility is minor compared to the partition coefficient, and an average melting point (162.7°C) could replace the experimental values, with similar results. The in-silico methods classified 20.76% (±3.07%) as Class 1, 41.51% (±3.32%) as Class 2, 30.49% (±4.47%) as Class 3, and 6.27% (±4.39%) as Class 4. In conclusion, in-silico methods can be used for BCS classification of drugs in early development, from merely their molecular formula and without foreknowledge of their chemical structure, which will allow for the improved selection, engineering, and developability of candidates. These in-silico methods could enhance success rates, reduce costs, and accelerate oral drug products development. PMID:25284986

Clinical evaluation and mutational analysis of GALK and GALE genes in patients with galactosemia in Greece: one novel mutation and two rare cases.

PubMed

Schulpis, Kleopatra H; Thodi, Georgia; Iakovou, Konstantinos; Chatzidaki, Maria; Dotsikas, Yannis; Molou, Elina; Triantafylli, Olga; Loukas, Yannis L

2017-07-26

Deficiencies of galactokinase (GALK) and UDP-epimerase (GALE) are implicated with galactose metabolic disorders. The aim of the study was the identification of mutations in GALK and GALE genes and clinical evaluation of patients. Five patients with GALK and five with GALE deficiency were picked up via the Neonatal Screening Program. Additionally, two females, 4 years old, were referred with late diagnosed galactosemia, as rare cases. Mutational analysis was conducted via Sanger sequencing, while in silico analysis tools were utilized for the novel mutation. Psychomotor and speech development tests were performed, as well. The mutation p.Pro28Thr was identified in both alleles in GALK-deficient patients of Roma (gypsy) origin, whereas the novel p.Asn39Ser was detected in two non-Roma patients. In GALE-deficient patients benign and/or likely benign mutations were found. Psychomotor and speech delay were determined in the Roma GALK patients. In each of the late diagnosed females, four mutations were identified in all galactosemia-related genes. The mutational spectrums of GALE- and GALK-deficient patients in Greece are presented for the first time along with a clinical evaluation. Mutational analysis in all galactosemia-related genes of symptomatic patients is highly recommended for future cases.

Novel genome-wide association study-based candidate loci for differentiated thyroid cancer risk.

PubMed

Figlioli, Gisella; Köhler, Aleksandra; Chen, Bowang; Elisei, Rossella; Romei, Cristina; Cipollini, Monica; Cristaudo, Alfonso; Bambi, Franco; Paolicchi, Elisa; Hoffmann, Per; Herms, Stefan; Kalemba, Michał; Kula, Dorota; Pastor, Susana; Marcos, Ricard; Velázquez, Antonia; Jarząb, Barbara; Landi, Stefano; Hemminki, Kari; Försti, Asta; Gemignani, Federica

2014-10-01

Genome-wide association studies (GWASs) on differentiated thyroid cancer (DTC) have identified robust associations with single nucleotide polymorphisms (SNPs) at 9q22.33 (FOXE1), 14q13.3 (NKX2-1), and 2q35 (DIRC3). Our recently published GWAS suggested additional susceptibility loci specific for the high-incidence Italian population. The purpose of this study was to identify novel Italian-specific DTC risk variants based on our GWAS and to test them further in low-incidence populations. We investigated 45 SNPs selected from our GWAS first in an Italian population. SNPs that showed suggestive evidence of association were investigated in the Polish and Spanish cohorts. The combined analysis of the GWAS and the Italian replication study (2260 case patients and 2218 control subjects) provided strong evidence of association with rs10136427 near BATF (odds ratio [OR] =1.40, P = 4.35 × 10(-7)) and rs7267944 near DHX35 (OR = 1.39, P = 2.13 × 10(-8)). A possible role in DTC susceptibility in the Italian populations was also found for rs13184587 (ARSB) (P = 8.54 × 10(-6)) and rs1220597 (SPATA13) (P = 3.25 × 10(-6)). Only the associations between rs10136427 and rs7267944 and DTC risk were replicated in the Polish and the Spanish populations with little evidence of population heterogeneity (GWAS and all replications combined, OR = 1.30, P = 9.30 × 10(-7) and OR = 1.32, P = 1.34 × 10(-8), respectively). In silico analyses provided new insights into the possible functional consequences of the SNPs that showed the strongest association with DTC. Our findings provide evidence for novel DTC susceptibility variants. Further studies are warranted to identify the specific genetic variants responsible for the observed associations and to functionally validate our in silico predictions.

In-silico studies in Chinese herbal medicines' research: evaluation of in-silico methodologies and phytochemical data sources, and a review of research to date.

PubMed

Barlow, D J; Buriani, A; Ehrman, T; Bosisio, E; Eberini, I; Hylands, P J

2012-04-10

The available databases that catalogue information on traditional Chinese medicines are reviewed in terms of their content and utility for in-silico research on Chinese herbal medicines, as too are the various protein database resources, and the software available for use in such studies. The software available for bioinformatics and 'omics studies of Chinese herbal medicines are summarised, and a critical evaluation given of the various in-silico methods applied in screening Chinese herbal medicines, including classification trees, neural networks, support vector machines, docking and inverse docking algorithms. Recommendations are made regarding any future in-silico studies of Chinese herbal medicines. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Inverse expression of survivin and reprimo correlates with poor patient prognosis in gastric cancer

PubMed Central

Cerda-Opazo, Paulina; Valenzuela-Valderrama, Manuel; Wichmann, Ignacio; Rodríguez, Andrés; Contreras-Reyes, Daniel; Fernández, Elmer A.; Carrasco-Aviño, Gonzalo; Corvalán, Alejandro H.; Quest, Andrew F.G.

2018-01-01

BACKGROUND The objective of the study was to determine the relationship between Survivin and Reprimo transcript/protein expression levels, and gastric cancer outcome. METHODS In silico correlations between an agnostic set of twelve p53-dependent apoptosis and cell-cycle genes were explored in the gastric adenocarcinoma TCGA database, using cBioPortal. Findings were validated by regression analysis of RNAseq data. Separate regression analyses were performed to assess the impact of p53 status on Survivin and Reprimo. Quantitative reverse-transcription PCR (RT-qPCR) and immunohistochemistry confirmed in silico findings on fresh-frozen and paraffin-embedded gastric cancer tissues, respectively. Wild-type (AGS, SNU-1) and mutated p53 (NCI-N87) cell lines transfected with pEGFP-Survivin or pCMV6-Reprimo were evaluated by RT-qPCR and Western blotting. Kaplan-Meier method and Long-Rank test were used to assess differences in patient outcome. RESULTS cBioPortal analysis revealed an inverse correlation between Survivin and Reprimo expression (Pearson’s r= −0.3, Spearman’s ρ= −0.55). RNAseq analyses confirmed these findings (Spearman’s ρ= −0.37, p<4.2e-09) and revealed p53 dependence in linear regression models (p<0.05). mRNA and protein levels validated these observations in clinical samples (p<0.001). In vitro analysis in cell lines demonstrated that increasing Survivin reduced Reprimo, while increasing Reprimo reduced Survivin expression, but only did so in p53 wild-type gastric cells (p<0.05). Survivin-positive but Reprimo-negative patients displayed shorter overall survival rates (p=0.047, Long Rank Test) (HR=0.32; 95%IC: 0.11-0.97; p=0.044). CONCLUSIONS TCGA RNAseq data analysis, evaluation of clinical samples and studies in cell lines identified an inverse relationship between Survivin and Reprimo. Elevated Survivin and reduced Reprimo protein expression correlated with poor patient prognosis in gastric cancer. PMID:29560115

In Silico Prediction and Validation of Gfap as an miR-3099 Target in Mouse Brain.

PubMed

Abidin, Shahidee Zainal; Leong, Jia-Wen; Mahmoudi, Marzieh; Nordin, Norshariza; Abdullah, Syahril; Cheah, Pike-See; Ling, King-Hwa

2017-08-01

MicroRNAs are small non-coding RNAs that play crucial roles in the regulation of gene expression and protein synthesis during brain development. MiR-3099 is highly expressed throughout embryogenesis, especially in the developing central nervous system. Moreover, miR-3099 is also expressed at a higher level in differentiating neurons in vitro, suggesting that it is a potential regulator during neuronal cell development. This study aimed to predict the target genes of miR-3099 via in-silico analysis using four independent prediction algorithms (miRDB, miRanda, TargetScan, and DIANA-micro-T-CDS) with emphasis on target genes related to brain development and function. Based on the analysis, a total of 3,174 miR-3099 target genes were predicted. Those predicted by at least three algorithms (324 genes) were subjected to DAVID bioinformatics analysis to understand their overall functional themes and representation. The analysis revealed that nearly 70% of the target genes were expressed in the nervous system and a significant proportion were associated with transcriptional regulation and protein ubiquitination mechanisms. Comparison of in situ hybridization (ISH) expression patterns of miR-3099 in both published and in-house-generated ISH sections with the ISH sections of target genes from the Allen Brain Atlas identified 7 target genes (Dnmt3a, Gabpa, Gfap, Itga4, Lxn, Smad7, and Tbx18) having expression patterns complementary to miR-3099 in the developing and adult mouse brain samples. Of these, we validated Gfap as a direct downstream target of miR-3099 using the luciferase reporter gene system. In conclusion, we report the successful prediction and validation of Gfap as an miR-3099 target gene using a combination of bioinformatics resources with enrichment of annotations based on functional ontologies and a spatio-temporal expression dataset.

Should DNA sequence be incorporated with other taxonomical data for routine identifying of plant species?

PubMed

Suesatpanit, Tanakorn; Osathanunkul, Kitisak; Madesis, Panagiotis; Osathanunkul, Maslin

2017-08-31

A variety of plants in Acanthaceae have long been used in traditional Thai ailment and commercialised with significant economic value. Nowadays medicinal plants are sold in processed forms and thus morphological authentication is almost impossible. Full identification requires comparison of the specimen with some authoritative sources, such as a full and accurate description and verification of the species deposited in herbarium. Intake of wrong herbals can cause adverse effects. Identification of both raw materials and end products is therefore needed. Here, the potential of a DNA-based identification method, called Bar-HRM (DNA barcoding coupled with High Resolution Melting analysis), in raw material species identification is investigated. DNA barcode sequences from five regions (matK, rbcL, trnH-psbA spacer region, trnL and ITS2) of Acanthaceae species were retrieved for in silico analysis. Then the specific primer pairs were used in HRM assay to generate unique melting profiles for each plants species. The method allows identification of samples lacking necessary morphological parts. In silico analyses of all five selected regions suggested that ITS2 is the most suitable marker for Bar-HRM in this study. The HRM analysis on dried samples of 16 Acanthaceae medicinal species was then performed using primer pair derived from ITS2 region. 100% discrimination of the tested samples at both genus and species level was observed. However, two samples documented as Clinacanthus nutans and Clinacanthus siamensis were recognised as the same species from the HRM analysis. Further investigation reveals that C. siamensis is now accepted as C. nutans. The results here proved that Bar-HRM is a promising technique in species identification of the studied medicinal plants in Acanthaceae. In addition, molecular biological data is currently used in plant taxonomy and increasingly popular in recent years. Here, DNA barcode sequence data should be incorporated with morphological characters in the species identification.

De novo transcriptome analysis of rose-scented geranium provides insights into the metabolic specificity of terpene and tartaric acid biosynthesis.

PubMed

Narnoliya, Lokesh K; Kaushal, Girija; Singh, Sudhir P; Sangwan, Rajender S

2017-01-13

Rose-scented geranium (Pelargonium sp.) is a perennial herb that produces a high value essential oil of fragrant significance due to the characteristic compositional blend of rose-oxide and acyclic monoterpenoids in foliage. Recently, the plant has also been shown to produce tartaric acid in leaf tissues. Rose-scented geranium represents top-tier cash crop in terms of economic returns and significance of the plant and plant products. However, there has hardly been any study on its metabolism and functional genomics, nor any genomic expression dataset resource is available in public domain. Therefore, to begin the gains in molecular understanding of specialized metabolic pathways of the plant, de novo sequencing of rose-scented geranium leaf transcriptome, transcript assembly, annotation, expression profiling as well as their validation were carried out. De novo transcriptome analysis resulted a total of 78,943 unique contigs (average length: 623 bp, and N50 length: 752 bp) from 15.44 million high quality raw reads. In silico functional annotation led to the identification of several putative genes representing terpene, ascorbic acid and tartaric acid biosynthetic pathways, hormone metabolism, and transcription factors. Additionally, a total of 6,040 simple sequence repeat (SSR) motifs were identified in 6.8% of the expressed transcripts. The highest frequency of SSR was of tri-nucleotides (50%). Further, transcriptome assembly was validated for randomly selected putative genes by standard PCR-based approach. In silico expression profile of assembled contigs were validated by real-time PCR analysis of selected transcripts. Being the first report on transcriptome analysis of rose-scented geranium the data sets and the leads and directions reflected in this investigation will serve as a foundation for pursuing and understanding molecular aspects of its biology, and specialized metabolic pathways, metabolic engineering, genetic diversity as well as molecular breeding.

Inverse expression of survivin and reprimo correlates with poor patient prognosis in gastric cancer.

PubMed

Cerda-Opazo, Paulina; Valenzuela-Valderrama, Manuel; Wichmann, Ignacio; Rodríguez, Andrés; Contreras-Reyes, Daniel; Fernández, Elmer A; Carrasco-Aviño, Gonzalo; Corvalán, Alejandro H; Quest, Andrew F G

2018-02-27

The objective of the study was to determine the relationship between Survivin and Reprimo transcript/protein expression levels, and gastric cancer outcome. In silico correlations between an agnostic set of twelve p53-dependent apoptosis and cell-cycle genes were explored in the gastric adenocarcinoma TCGA database, using cBioPortal. Findings were validated by regression analysis of RNAseq data. Separate regression analyses were performed to assess the impact of p53 status on Survivin and Reprimo. Quantitative reverse-transcription PCR (RT-qPCR) and immunohistochemistry confirmed in silico findings on fresh-frozen and paraffin-embedded gastric cancer tissues, respectively. Wild-type (AGS, SNU-1) and mutated p53 (NCI-N87) cell lines transfected with pEGFP-Survivin or pCMV6-Reprimo were evaluated by RT-qPCR and Western blotting. Kaplan-Meier method and Long-Rank test were used to assess differences in patient outcome. cBioPortal analysis revealed an inverse correlation between Survivin and Reprimo expression (Pearson's r= -0.3, Spearman's ρ= -0.55). RNAseq analyses confirmed these findings (Spearman's ρ= -0.37, p<4.2e-09) and revealed p53 dependence in linear regression models (p<0.05). mRNA and protein levels validated these observations in clinical samples (p<0.001). In vitro analysis in cell lines demonstrated that increasing Survivin reduced Reprimo, while increasing Reprimo reduced Survivin expression, but only did so in p53 wild-type gastric cells (p<0.05). Survivin-positive but Reprimo-negative patients displayed shorter overall survival rates (p=0.047, Long Rank Test) (HR=0.32; 95%IC: 0.11-0.97; p=0.044). TCGA RNAseq data analysis, evaluation of clinical samples and studies in cell lines identified an inverse relationship between Survivin and Reprimo. Elevated Survivin and reduced Reprimo protein expression correlated with poor patient prognosis in gastric cancer.

Biological Evaluation in Vitro and in Silico of Azetidin-2-one Derivatives as Potential Anticancer Agents.

PubMed

Olazaran, Fabián E; Rivera, Gildardo; Pérez-Vázquez, Alondra M; Morales-Reyes, Cynthia M; Segura-Cabrera, Aldo; Balderas-Rentería, Isaías

2017-01-12

Potential anticancer activity of 16 azetidin-2-one derivatives was evaluated showing that compound 6 [ N -( p -methoxy-phenyl)-2-( p -methyl-phenyl)-3-phenoxy-azetidin-2-one] presented cytotoxic activity in SiHa cells and B16F10 cells. The caspase-3 assay in B16F10 cells displayed that azetidin-2-one derivatives induce apoptosis. Microarray and molecular analysis showed that compound 6 was involved on specific gene overexpression of cytoskeleton regulation and apoptosis due to the inhibition of some cell cycle genes. From the 16 derivatives, compound 6 showed the highest selectivity to neoplastic cells, it was an inducer of apoptosis, and according to an in silico analysis of chemical interactions with colchicine binding site of human α/β-tubulin, the mechanism of action could be a molecular interaction involving the amino acids outlining such binding site.

Biological Evaluation in Vitro and in Silico of Azetidin-2-one Derivatives as Potential Anticancer Agents

PubMed Central

2016-01-01

Potential anticancer activity of 16 azetidin-2-one derivatives was evaluated showing that compound 6 [N-(p-methoxy-phenyl)-2-(p-methyl-phenyl)-3-phenoxy-azetidin-2-one] presented cytotoxic activity in SiHa cells and B16F10 cells. The caspase-3 assay in B16F10 cells displayed that azetidin-2-one derivatives induce apoptosis. Microarray and molecular analysis showed that compound 6 was involved on specific gene overexpression of cytoskeleton regulation and apoptosis due to the inhibition of some cell cycle genes. From the 16 derivatives, compound 6 showed the highest selectivity to neoplastic cells, it was an inducer of apoptosis, and according to an in silico analysis of chemical interactions with colchicine binding site of human α/β-tubulin, the mechanism of action could be a molecular interaction involving the amino acids outlining such binding site. PMID:28105271

Management of Gene Variants of Unknown Significance: Analysis Method and Risk Assessment of the VHL Mutation p.P81S (c.241C>T).

PubMed

Alosi, Daniela; Bisgaard, Marie Luise; Hemmingsen, Sophie Nowak; Krogh, Lotte Nylandsted; Mikkelsen, Hanne Birte; Binderup, Marie Louise Mølgaard

2017-02-01

Evaluation of the pathogenicity of a gene variant of unknown significance (VUS) is crucial for molecular diagnosis and genetic counseling, but can be challenging. This is especially so in phenotypically variable diseases, such as von Hippel-Lindau disease (vHL). vHL is caused by germline mutations in the VHL gene, which predispose to the development of multiple tumors such as central nervous system hemangioblastomas and renal cell carcinoma (RCC). We propose a method for the evaluation of VUS pathogenicity through our experience with the VHL missense mutation c.241C>T (p.P81S). 1) Clinical evaluation of known variant carriers: We evaluated a family of five VHL p.P81S carriers, as well as the clinical characteristics of all the p.P81S carriers reported in the literature; 2) Evaluation of tumor tissue via genetic analysis, histology, and immunohistochemistry (IHC); 3) Assessment of the variant's impact on protein structure and function, using multiple databases, in silico algorithms, and reports of functional studies. Only one family member had clinical signs of vHL with early-onset RCC. IHC analysis showed no VHL protein expressed in the tumor, consistent with biallelic VHL inactivation. The majority of in silico algorithms reported p.P81S as possibly pathogenic in relation to vHL or RCC, but there were discrepancies. Functional studies suggest that p.P81S impairs the VHL protein's function. The VHL p.P81S mutation is most likely a low-penetrant pathogenic variant predisposing to RCC development. We suggest the above-mentioned method for VUS evaluation with use of different methods, especially a variety of in silico methods and tumor tissue analysis.

Challenges and recommendations for obtaining chemical structures of industry-provided repurposing candidates.

PubMed

Southan, Christopher; Williams, Antony J; Ekins, Sean

2013-01-01

There is an expanding amount of interest directed at the repurposing and repositioning of drugs, as well as how in silico methods can assist these endeavors. Recent repurposing project tendering calls by the National Center for Advancing Translational Sciences (USA) and the Medical Research Council (UK) have included compound information and pharmacological data. However, none of the internal company development code names were assigned to chemical structures in the official documentation. This not only abrogates in silico analysis to support repurposing but consequently necessitates data gathering and curation to assign structures. Here, we describe the approaches, results and major challenges associated with this. Copyright © 2012 Elsevier Ltd. All rights reserved.

Integrative, multimodal analysis of glioblastoma using TCGA molecular data, pathology images, and clinical outcomes.

PubMed

Kong, Jun; Cooper, Lee A D; Wang, Fusheng; Gutman, David A; Gao, Jingjing; Chisolm, Candace; Sharma, Ashish; Pan, Tony; Van Meir, Erwin G; Kurc, Tahsin M; Moreno, Carlos S; Saltz, Joel H; Brat, Daniel J

2011-12-01

Multimodal, multiscale data synthesis is becoming increasingly critical for successful translational biomedical research. In this letter, we present a large-scale investigative initiative on glioblastoma, a high-grade brain tumor, with complementary data types using in silico approaches. We integrate and analyze data from The Cancer Genome Atlas Project on glioblastoma that includes novel nuclear phenotypic data derived from microscopic slides, genotypic signatures described by transcriptional class and genetic alterations, and clinical outcomes defined by response to therapy and patient survival. Our preliminary results demonstrate numerous clinically and biologically significant correlations across multiple data types, revealing the power of in silico multimodal data integration for cancer research.

In silico and in vitro prediction of gastrointestinal absorption from potential drug eremantholide C.

PubMed

Caldeira, Tamires G; Saúde-Guimarães, Dênia A; Dezani, André B; Serra, Cristina Helena Dos Reis; de Souza, Jacqueline

2017-11-01

Analysis of the biopharmaceutical properties of eremantholide C, sesquiterpene lactone with proven pharmacological activity and low toxicity, is required to evaluate its potential to become a drug. Preliminary analysis of the physicochemical characteristics of eremantholide C was performed in silico. Equilibrium solubility was evaluated using the shake-flask method, at 37.0 °C, 100 rpm during 72 h in biorelevant media. The permeability was analysed using parallel artificial membrane permeability assay, at 37.0 °C, 50 rpm for 5 h. The donor compartment was composed of an eremantholide C solution in intestinal fluid simulated without enzymes, while the acceptor compartment consisted of phosphate buffer. Physicochemical characteristics predicted in silico indicated that eremantholide C has a low solubility and high permeability. In-vitro data of eremantholide C showed low solubility, with values for the dose/solubility ratio (ml): 9448.82, 10 389.61 e 15 000.00 for buffers acetate (pH 4.5), intestinal fluid simulated without enzymes (pH 6.8) and phosphate (pH 7.4), respectively. Also, it showed high permeability, with effective permeability of 30.4 × 10 -6 cm/s, a higher result compared with propranolol hydrochloride (9.23 × 10 -6 cm/s). The high permeability combined with its solubility, pharmacological activity and low toxicity demonstrate the importance of eremantholide C as a potential drug candidate. © 2017 Royal Pharmaceutical Society.

Genererating a core cluster of Fasciola hepatica virulence and immunomodulation-related genes using a comparative in silico approach.

PubMed

Haçarız, Orçun; Sayers, Gearóid P

2018-04-01

A total of 71 virulence and immunomodulation-related transcripts (VIRs) of Fasciola hepatica have been previously proposed (Haçarız et al., 2015). In an attempt to further refine this cohort, an in silico meta analysis approach was carried out using publicly available sequence data of related liver flukes, Clonorchis sinensis and Opisthorchis viverrini. Data of both liver flukes were investigated in terms of sequential homology with data of non-parasitic organisms, pathogens and VIRs of F. hepatica, directional selection (Ka/Ks), and cytokine signaling relation (protein motif based). Some VIRs of F. hepatica [showing homology with immune receptors (for toll/interleukin-1, TGF-β or TNF-α), TGF-β, TNF-α, CD147, or relation with suppressors of cytokine signaling/IKBKE 1 or stimulation of TGF-β (through thrombospondin similarity)] were found to be orthologous with those of both C. sinensis and O. viverrini. The in silico analysis indicates that on the basis of genetic commonality, a total of 30 VIRs of F. hepatica are highlighted as of foremost importance in the parasite evasion strategy, through controlling of host immune system. Findings in this study could be important to further enhance our understanding of the parasitic mechanisms and develop effective control strategies against F. hepatica and other related parasites. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0

PubMed Central

Schellenberger, Jan; Que, Richard; Fleming, Ronan M. T.; Thiele, Ines; Orth, Jeffrey D.; Feist, Adam M.; Zielinski, Daniel C.; Bordbar, Aarash; Lewis, Nathan E.; Rahmanian, Sorena; Kang, Joseph; Hyduke, Daniel R.; Palsson, Bernhard Ø.

2012-01-01

Over the past decade, a growing community of researchers has emerged around the use of COnstraint-Based Reconstruction and Analysis (COBRA) methods to simulate, analyze and predict a variety of metabolic phenotypes using genome-scale models. The COBRA Toolbox, a MATLAB package for implementing COBRA methods, was presented earlier. Here we present a significant update of this in silico ToolBox. Version 2.0 of the COBRA Toolbox expands the scope of computations by including in silico analysis methods developed since its original release. New functions include: (1) network gap filling, (2) 13C analysis, (3) metabolic engineering, (4) omics-guided analysis, and (5) visualization. As with the first version, the COBRA Toolbox reads and writes Systems Biology Markup Language formatted models. In version 2.0, we improved performance, usability, and the level of documentation. A suite of test scripts can now be used to learn the core functionality of the Toolbox and validate results. This Toolbox lowers the barrier of entry to use powerful COBRA methods. PMID:21886097

Proteomic analysis of sweet algerian apricot kernels (Prunus armeniaca L.) by combinatorial peptide ligand libraries and LC-MS/MS.

PubMed

Ghorab, Hamida; Lammi, Carmen; Arnoldi, Anna; Kabouche, Zahia; Aiello, Gilda

2018-01-15

An investigation on the proteome of the sweet kernel of apricot, based on equalisation with combinatorial peptide ligand libraries (CPLLs), SDS-PAGE, nLC-ESI-MS/MS, and database search, permitted identifying 175 proteins. Gene ontology analysis indicated that their main molecular functions are in nucleotide binding (20.9%), hydrolase activities (10.6%), kinase activities (7%), and catalytic activity (5.6%). A protein-protein association network analysis using STRING software permitted to build an interactomic map of all detected proteins, characterised by 34 interactions. In order to forecast the potential health benefits deriving from the consumption of these proteins, the two most abundant, i.e. Prunin 1 and 2, were enzymatically digested in silico predicting 10 and 14 peptides, respectively. Searching their sequences in the database BIOPEP, it was possible to suggest a variety of bioactivities, including dipeptidyl peptidase-IV (DPP-IV) and angiotensin converting enzyme I (ACE) inhibition, glucose uptake stimulation and antioxidant properties. Copyright © 2017 Elsevier Ltd. All rights reserved.

An RNAi in silico approach to find an optimal shRNA cocktail against HIV-1

PubMed Central

2010-01-01

Background HIV-1 can be inhibited by RNA interference in vitro through the expression of short hairpin RNAs (shRNAs) that target conserved genome sequences. In silico shRNA design for HIV has lacked a detailed study of virus variability constituting a possible breaking point in a clinical setting. We designed shRNAs against HIV-1 considering the variability observed in naïve and drug-resistant isolates available at public databases. Methods A Bioperl-based algorithm was developed to automatically scan multiple sequence alignments of HIV, while evaluating the possibility of identifying dominant and subdominant viral variants that could be used as efficient silencing molecules. Student t-test and Bonferroni Dunn correction test were used to assess statistical significance of our findings. Results Our in silico approach identified the most common viral variants within highly conserved genome regions, with a calculated free energy of ≥ -6.6 kcal/mol. This is crucial for strand loading to RISC complex and for a predicted silencing efficiency score, which could be used in combination for achieving over 90% silencing. Resistant and naïve isolate variability revealed that the most frequent shRNA per region targets a maximum of 85% of viral sequences. Adding more divergent sequences maintained this percentage. Specific sequence features that have been found to be related with higher silencing efficiency were hardly accomplished in conserved regions, even when lower entropy values correlated with better scores. We identified a conserved region among most HIV-1 genomes, which meets as many sequence features for efficient silencing. Conclusions HIV-1 variability is an obstacle to achieving absolute silencing using shRNAs designed against a consensus sequence, mainly because there are many functional viral variants. Our shRNA cocktail could be truly effective at silencing dominant and subdominant naïve viral variants. Additionally, resistant isolates might be targeted under specific antiretroviral selective pressure, but in both cases these should be tested exhaustively prior to clinical use. PMID:21172023

IMGMD: A platform for the integration and standardisation of In silico Microbial Genome-scale Metabolic Models.

PubMed

Ye, Chao; Xu, Nan; Dong, Chuan; Ye, Yuannong; Zou, Xuan; Chen, Xiulai; Guo, Fengbiao; Liu, Liming

2017-04-07

Genome-scale metabolic models (GSMMs) constitute a platform that combines genome sequences and detailed biochemical information to quantify microbial physiology at the system level. To improve the unity, integrity, correctness, and format of data in published GSMMs, a consensus IMGMD database was built in the LAMP (Linux + Apache + MySQL + PHP) system by integrating and standardizing 328 GSMMs constructed for 139 microorganisms. The IMGMD database can help microbial researchers download manually curated GSMMs, rapidly reconstruct standard GSMMs, design pathways, and identify metabolic targets for strategies on strain improvement. Moreover, the IMGMD database facilitates the integration of wet-lab and in silico data to gain an additional insight into microbial physiology. The IMGMD database is freely available, without any registration requirements, at http://imgmd.jiangnan.edu.cn/database.

An in vitro screening cascade to identify neuroprotective antioxidants in ALS

PubMed Central

Barber, Siân C.; Higginbottom, Adrian; Mead, Richard J.; Barber, Stuart; Shaw, Pamela J.

2009-01-01

Amyotrophic lateral sclerosis (ALS) is an adult-onset neurodegenerative disease, characterized by progressive dysfunction and death of motor neurons. Although evidence for oxidative stress in ALS pathogenesis is well described, antioxidants have generally shown poor efficacy in animal models and human clinical trials. We have developed an in vitro screening cascade to identify antioxidant molecules capable of rescuing NSC34 motor neuron cells expressing an ALS-associated mutation of superoxide dismutase 1. We have tested known antioxidants and screened a library of 2000 small molecules. The library screen identified 164 antioxidant molecules, which were refined to the 9 most promising molecules in subsequent experiments. Analysis of the in silico properties of hit compounds and a review of published literature on their in vivo effectiveness have enabled us to systematically identify molecules with antioxidant activity combined with chemical properties necessary to penetrate the central nervous system. The top-performing molecules identified include caffeic acid phenethyl ester, esculetin, and resveratrol. These compounds were tested for their ability to rescue primary motor neuron cultures after trophic factor withdrawal, and the mechanisms of action of their antioxidant effects were investigated. Subsequent in vivo studies can be targeted using molecules with the greatest probability of success. PMID:19439221

In vitro and in silico studies of 3-hydroxy-3-methyl-glutaryl coenzyme A reductase inhibitory activity of the cowpea Gln-Asp-Phe peptide.

PubMed

Silva, Mariana Barros de Cerqueira E; Souza, Caio Alexandre da Cruz; Philadelpho, Biane Oliveira; Cunha, Mariana Mota Novais da; Batista, Fabiana Pacheco Reis; Silva, Jaff Ribeiro da; Druzian, Janice Izabel; Castilho, Marcelo Santos; Cilli, Eduardo Maffud; Ferreira, Ederlan S

2018-09-01

Previous studies have shown that cowpea protein positively interferes with cholesterol metabolism. In this study, we evaluated the ability of the fraction containing peptides of <3 kDa, as well as that of the Gln-Asp-Phe (QDF) peptide, derived from cowpea β-vignin protein, to inhibit HMG-CoA reductase activity. We established isolation and chromatography procedures to effectively obtain the protein with a purity above 95%. In silico predictions were performed to identify peptide sequences capable of interacting with HMG-CoA reductase. In vitro experiments showed that the fraction containing peptides of <3 kDa displayed inhibition of HMG-CoA reductase activity. The tripeptide QDF inhibits HMG-CoA reductase (IC 50  = 12.8 μM) in a dose-dependent manner. Furthermore, in silico studies revealed the binding profile of the QDF peptide and hinted at the molecular interactions that are responsible for its activity. Therefore, this study shows, for the first time, a peptide from cowpea β-vignin protein that inhibits HMG-CoA reductase and the chemical modifications that should be investigated to evaluate its binding profile. Copyright © 2018 Elsevier Ltd. All rights reserved.

In Silico Investigation of a Surgical Interface for Remote Control of Modular Miniature Robots in Minimally Invasive Surgery

PubMed Central

Zygomalas, Apollon; Giokas, Konstantinos; Koutsouris, Dimitrios

2014-01-01

Aim. Modular mini-robots can be used in novel minimally invasive surgery techniques like natural orifice transluminal endoscopic surgery (NOTES) and laparoendoscopic single site (LESS) surgery. The control of these miniature assistants is complicated. The aim of this study is the in silico investigation of a remote controlling interface for modular miniature robots which can be used in minimally invasive surgery. Methods. The conceptual controlling system was developed, programmed, and simulated using professional robotics simulation software. Three different modes of control were programmed. The remote controlling surgical interface was virtually designed as a high scale representation of the respective modular mini-robot, therefore a modular controlling system itself. Results. With the proposed modular controlling system the user could easily identify the conformation of the modular mini-robot and adequately modify it as needed. The arrangement of each module was always known. The in silico investigation gave useful information regarding the controlling mode, the adequate speed of rearrangements, and the number of modules needed for efficient working tasks. Conclusions. The proposed conceptual model may promote the research and development of more sophisticated modular controlling systems. Modular surgical interfaces may improve the handling and the dexterity of modular miniature robots during minimally invasive procedures. PMID:25295187

In silico investigation of a surgical interface for remote control of modular miniature robots in minimally invasive surgery.

PubMed

Zygomalas, Apollon; Giokas, Konstantinos; Koutsouris, Dimitrios

2014-01-01

Aim. Modular mini-robots can be used in novel minimally invasive surgery techniques like natural orifice transluminal endoscopic surgery (NOTES) and laparoendoscopic single site (LESS) surgery. The control of these miniature assistants is complicated. The aim of this study is the in silico investigation of a remote controlling interface for modular miniature robots which can be used in minimally invasive surgery. Methods. The conceptual controlling system was developed, programmed, and simulated using professional robotics simulation software. Three different modes of control were programmed. The remote controlling surgical interface was virtually designed as a high scale representation of the respective modular mini-robot, therefore a modular controlling system itself. Results. With the proposed modular controlling system the user could easily identify the conformation of the modular mini-robot and adequately modify it as needed. The arrangement of each module was always known. The in silico investigation gave useful information regarding the controlling mode, the adequate speed of rearrangements, and the number of modules needed for efficient working tasks. Conclusions. The proposed conceptual model may promote the research and development of more sophisticated modular controlling systems. Modular surgical interfaces may improve the handling and the dexterity of modular miniature robots during minimally invasive procedures.

FutureTox II: in vitro data and in silico models for predictive toxicology.

PubMed

Knudsen, Thomas B; Keller, Douglas A; Sander, Miriam; Carney, Edward W; Doerrer, Nancy G; Eaton, David L; Fitzpatrick, Suzanne Compton; Hastings, Kenneth L; Mendrick, Donna L; Tice, Raymond R; Watkins, Paul B; Whelan, Maurice

2015-02-01

FutureTox II, a Society of Toxicology Contemporary Concepts in Toxicology workshop, was held in January, 2014. The meeting goals were to review and discuss the state of the science in toxicology in the context of implementing the NRC 21st century vision of predicting in vivo responses from in vitro and in silico data, and to define the goals for the future. Presentations and discussions were held on priority concerns such as predicting and modeling of metabolism, cell growth and differentiation, effects on sensitive subpopulations, and integrating data into risk assessment. Emerging trends in technologies such as stem cell-derived human cells, 3D organotypic culture models, mathematical modeling of cellular processes and morphogenesis, adverse outcome pathway development, and high-content imaging of in vivo systems were discussed. Although advances in moving towards an in vitro/in silico based risk assessment paradigm were apparent, knowledge gaps in these areas and limitations of technologies were identified. Specific recommendations were made for future directions and research needs in the areas of hepatotoxicity, cancer prediction, developmental toxicity, and regulatory toxicology. © The Author 2015. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Isoquinoline Alkaloids from Erythrinapoeppigiana (Leguminosae) and Cytotoxic Activity Against Breast Cancer Cells Line MCF-7 In Silico

NASA Astrophysics Data System (ADS)

Herlina, T.; Mardianingrum, R.; Gaffar, S.; Supratman, U.

2017-02-01

Erythrinapoeppigiana(Leguminosae) is a higher plant that has been used as a folk for the treatment of infection, fever, and inflammation. In the course of our continuing search for novel cytotoxic compounds from genus Erythrina, the methanol extract of E. poeppigiana showed a significant cytotoxic activity against breast cancer cells line MCF-7 in silico. The compounds in methanol extract of the E. poeppigiana was separated using a bioassay-guided fractionation. By using a cytotoxic activity to follow separation, the methylene chloride was separated by several column chromatography techniques on silica gel and ODS to yield three active compounds (1-3). The chemical structures of active compounds were determined on the basis of spectroscopic evidence and comparison with those identical compounds that previously reported and identified as a 10,11-dihydroxyerysodine (1) 6,7-dihydro-17-hydroxyerysotrine (2) 6,7-dihydro-11-methoxyerysotrine (3). Compounds (1-3) showed cytotoxic activity inhibits EGFR 2 against breast cancer cell line MCF-7 in silico molecular docking method with bond Gibbs free energy (ΔG) (kcal/mol) and inhibition constants (Ki) (nM) of value (-8.61121, 4.84×10-7) (-8.1145, 1.12×10-6) and (-7.3394, 4.14×10-6), respectively.

In silico dissection of miRNA targetome polymorphisms and their role in regulating miRNA-mediated gene expression in esophageal cancer.

PubMed

Nariman-Saleh-Fam, Ziba; Bastami, Milad; Somi, Mohammad Hossein; Samadi, Naser; Abbaszadegan, Mohammad Reza; Behjati, Farkhondeh; Ghaedi, Hamid; Tavakkoly-Bazzaz, Javad; Masotti, Andrea

2016-12-01

Esophageal cancer is the eighth most common cancer worldwide. Also middle-aged obese adults with higher body mass index during childhood have a greater risk to develop esophageal cancer. The contribution of microRNAs to esophageal cancer has been extensively studied and it became clear that these noncoding RNAs may play crucial roles in pathogenesis, diagnosis and prognosis of the disease. Increasing evidences have suggested that polymorphisms perturbing microRNA targetome (i.e., the compendium of all microRNA target sites) are associated with cancers including esophageal cancer. However, the extent to which such variants contribute to esophageal cancer is still unclear. In this study, we applied an in silico approach to systematically identify polymorphisms perturbing microRNA targetome in esophageal cancer and performed various analyses to predict the functional consequences of the occurrence of these variants. The computational results were integrated to provide a prioritized list of the most potentially disrupting esophageal cancer-implicated microRNA targetome polymorphisms along with the in silico insight into the mechanisms with which such variations may modulate microRNA-mediated regulation. The results of this study will be valuable for future functional experiments aimed at dissecting the roles of microRNA targetome polymorphisms in the onset and progression of esophageal cancer.

Advances in In Vitro and In Silico Tools for Toxicokinetic Dose ...

EPA Pesticide Factsheets

Recent advances in vitro assays, in silico tools, and systems biology approaches provide opportunities for refined mechanistic understanding for chemical safety assessment that will ultimately lead to reduced reliance on animal-based methods. With the U.S. commercial chemical landscape encompassing thousands of chemicals with limited data, safety assessment strategies that reliably predict in vivo systemic exposures and subsequent in vivo effects efficiently are a priority. Quantitative in vitro-in vivo extrapolation (QIVIVE) is a methodology that facilitates the explicit and quantitative application of in vitro experimental data and in silico modeling to predict in vivo system behaviors and can be applied to predict chemical toxicokinetics, toxicodynamics and also population variability. Tiered strategies that incorporate sufficient information to reliably inform the relevant decision context will facilitate acceptance of these alternative data streams for safety assessments. This abstract does not necessarily reflect U.S. EPA policy. This talk will provide an update to an international audience on the state of science being conducted within the EPA’s Office of Research and Development to develop and refine approaches that estimate internal chemical concentrations following a given exposure, known as toxicokinetics. Toxicokinetic approaches hold great potential in their ability to link in vitro activities or toxicities identified during high-throughput screen

In Silico and Wet Lab Studies Reveal the Cholesterol Lowering Efficacy of Lauric Acid, a Medium Chain Fat of Coconut Oil.

PubMed

Lekshmi Sheela, Devi; Nazeem, Puthiyaveetil Abdulla; Narayanankutty, Arunaksharan; Manalil, Jeksy Jos; Raghavamenon, Achuthan C

2016-12-01

The coconut oil (CO) contains 91 % of saturated fatty acids in which 72 % are medium chain fatty acids (MCFAs) like lauric, capric and caprylic acids. In contrast to animal fat, coconut oil has no cholesterol. Despite this fact, CO is sidelined among other vegetable oils due to the health hazards attributed to the saturated fatty acids. Though various medicinal effects of CO have been reported including the hypolipidemic activity, people are still confused in the consumption of this natural oil. In silico analyses and wet lab experiments have been carried out to identify the hypolipidemic properties of MCFAs and phenolic acids in CO by using different protein targets involved in cholesterol synthesis. The molecular docking studies were carried out using CDOCKER protocol in Accelery's Discovery Studio, by taking different proteins like HMG- CoA reductase and cholesterol esterase as targets and the different phytocompounds in coconut as ligands. Molecular docking highlighted the potential of lauric acid in inhibiting the protein targets involved in hyperlipidemics. Further, validation of in silico results was carried out through in vivo studies. The activity of key enzymes HMG- CoA reductase and lipoprotein lipase were found reduced in animals fed with lauric acid and CO.

In silico design of context-responsive mammalian promoters with user-defined functionality

PubMed Central

Gibson, Suzanne J.; Hatton, Diane

2017-01-01

Abstract Comprehensive de novo-design of complex mammalian promoters is restricted by unpredictable combinatorial interactions between constituent transcription factor regulatory elements (TFREs). In this study, we show that modular binding sites that do not function cooperatively can be identified by analyzing host cell transcription factor expression profiles, and subsequently testing cognate TFRE activities in varying homotypic and heterotypic promoter architectures. TFREs that displayed position-insensitive, additive function within a specific expression context could be rationally combined together in silico to create promoters with highly predictable activities. As TFRE order and spacing did not affect the performance of these TFRE-combinations, compositions could be specifically arranged to preclude the formation of undesirable sequence features. This facilitated simple in silico-design of promoters with context-required, user-defined functionalities. To demonstrate this, we de novo-created promoters for biopharmaceutical production in CHO cells that exhibited precisely designed activity dynamics and long-term expression-stability, without causing observable retroactive effects on cellular performance. The design process described can be utilized for applications requiring context-responsive, customizable promoter function, particularly where co-expression of synthetic TFs is not suitable. Although the synthetic promoter structure utilized does not closely resemble native mammalian architectures, our findings also provide additional support for a flexible billboard model of promoter regulation. PMID:28977454

Laboratory diagnosis of gestational diabetes: An in silico investigation into the effects of pre-analytical processing on the diagnostic sensitivity and specificity of the oral glucose tolerance test.

PubMed

Mansell, Erin; Lunt, Helen; Docherty, Paul

2017-06-01

Delayed separation of red cells from plasma causes pre analytical glucose loss, which in turn results in an under-diagnosis of GDM (gestational diabetes) based on the OGTT (oral glucose tolerance test). In silico investigations may help laboratory decision making, when exploring pragmatic improvements to sample processing. Late pregnancy 0, 1 and 2h 75g OGTT values were obtained from two distinct populations of pregnant women: 1. Values derived from the HAPO (Hyperglycemia and Adverse Pregnancy Outcome) Study and 2. New Zealand women identified as at higher risk of GDM by their caregivers, undergoing OGTT during routine antenatal care. In both populations studied, in silico modelling focussed on the effects of pre-analytical delays in plasma separation, when using fluoride collection tubes. Using a model that 'batched' samples from the three OGTT collection times, diagnostic sensitivity was estimated as follows: 66.1% for HAPO research population and 48.4% for the 1305 women receiving routine antenatal care. If samples were not batched, but processed shortly after each blood sample was collected, then sensitivity increased to 81%. Exploration of a range of clinical and laboratory scenarios using in silico modelling, showed that delaying the processing of pregnancy OGTT samples, using batched sample collection into fluoride tubes, causes unacceptable loss of GDM diagnostic sensitivity across two distinct population groups. This modelling approach will hopefully provide information that helps with final decision making around improved laboratory processing techniques. Copyright © 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Gastrointestinal Endogenous Proteins as a Source of Bioactive Peptides - An In Silico Study

PubMed Central

Dave, Lakshmi A.; Montoya, Carlos A.; Rutherfurd, Shane M.; Moughan, Paul J.

2014-01-01

Dietary proteins are known to contain bioactive peptides that are released during digestion. Endogenous proteins secreted into the gastrointestinal tract represent a quantitatively greater supply of protein to the gut lumen than those of dietary origin. Many of these endogenous proteins are digested in the gastrointestinal tract but the possibility that these are also a source of bioactive peptides has not been considered. An in silico prediction method was used to test if bioactive peptides could be derived from the gastrointestinal digestion of gut endogenous proteins. Twenty six gut endogenous proteins and seven dietary proteins were evaluated. The peptides present after gastric and intestinal digestion were predicted based on the amino acid sequence of the proteins and the known specificities of the major gastrointestinal proteases. The predicted resultant peptides possessing amino acid sequences identical to those of known bioactive peptides were identified. After gastrointestinal digestion (based on the in silico simulation), the total number of bioactive peptides predicted to be released ranged from 1 (gliadin) to 55 (myosin) for the selected dietary proteins and from 1 (secretin) to 39 (mucin-5AC) for the selected gut endogenous proteins. Within the intact proteins and after simulated gastrointestinal digestion, angiotensin converting enzyme (ACE)-inhibitory peptide sequences were the most frequently observed in both the dietary and endogenous proteins. Among the dietary proteins, after in silico simulated gastrointestinal digestion, myosin was found to have the highest number of ACE-inhibitory peptide sequences (49 peptides), while for the gut endogenous proteins, mucin-5AC had the greatest number of ACE-inhibitory peptide sequences (38 peptides). Gut endogenous proteins may be an important source of bioactive peptides in the gut particularly since gut endogenous proteins represent a quantitatively large and consistent source of protein. PMID:24901416

HLA-B*15:21 and carbamazepine-induced Stevens-Johnson syndrome: pooled-data and in silico analysis

NASA Astrophysics Data System (ADS)

Jaruthamsophon, Kanoot; Tipmanee, Varomyalin; Sangiemchoey, Antida; Sukasem, Chonlaphat; Limprasert, Pornprot

2017-03-01

HLA-B*15:02 screening before carbamazepine (CBZ) prescription in Asian populations is the recommended practice to prevent CBZ-induced Stevens-Johnson syndrome (CBZ-SJS). However, a number of patients have developed CBZ-SJS even having no HLA-B*15:02. Herein, we present the case of a Thai patient who had a negative HLA-B*15:02 screening result but later developed CBZ-SJS. Further HLA typing revealed HLA-B*15:21/B*13:01. HLA-B*15:21 is a member of the HLA-B75 serotype and is commonly found in Southeast Asian populations. Based on this case, we hypothesised that if all HLA-B*15:02 carriers were prevented from CBZ prescription, another common HLA-B75 serotype marker would show its association with CBZ-SJS. To test this hypothesis, we pooled data from previous association studies in Asian populations, excluded all cases with HLA-B*15:02, and analysed the association significance of HLA-B75 serotype markers. A significant association was found between CBZ-SJS and HLA-B*15:21 and HLA-B*15:11. We also applied an in silico analysis and found that all HLA-B75 serotype molecules shared similar capability in binding the CBZ molecule. In summary, this report provides the first evidence of a positive association between HLA-B*15:21 and CBZ-SJS and the first in silico analysis of CBZ binding sites and details of the molecular behaviour of HLA-B75 molecule to explain its molecular action.

An in silico argument for mitochondrial microRNA as a determinant of primary non function in liver transplantation.

PubMed

Khorsandi, Shirin Elizabeth; Salehi, Siamak; Cortes, Miriam; Vilca-Melendez, Hector; Menon, Krishna; Srinivasan, Parthi; Prachalias, Andreas; Jassem, Wayel; Heaton, Nigel

2018-02-15

Mitochondria have their own genomic, transcriptomic and proteomic machinery but are unable to be autonomous, needing both nuclear and mitochondrial genomes. The aim of this work was to use computational biology to explore the involvement of Mitochondrial microRNAs (MitomiRs) and their interactions with the mitochondrial proteome in a clinical model of primary non function (PNF) of the donor after cardiac death (DCD) liver. Archival array data on the differential expression of miRNA in DCD PNF was re-analyzed using a number of publically available computational algorithms. 10 MitomiRs were identified of importance in DCD PNF, 7 with predicted interaction of their seed sequence with the mitochondrial transcriptome that included both coding, and non coding areas of the hypervariability region 1 (HVR1) and control region. Considering miRNA regulation of the nuclear encoded mitochondrial proteome, 7 hypothetical small proteins were identified with homolog function that ranged from co-factor for formation of ATP Synthase, REDOX balance and an importin/exportin protein. In silico, unconventional seed interactions, both non canonical and alternative seed sites, appear to be of greater importance in MitomiR regulation of the mitochondrial genome. Additionally, a number of novel small proteins of relevance in transplantation have been identified which need further characterization.

Linking the salt transcriptome with physiological responses of a salt-resistant Populus species as a strategy to identify genes important for stress acclimation.

PubMed

Brinker, Monika; Brosché, Mikael; Vinocur, Basia; Abo-Ogiala, Atef; Fayyaz, Payam; Janz, Dennis; Ottow, Eric A; Cullmann, Andreas D; Saborowski, Joachim; Kangasjärvi, Jaakko; Altman, Arie; Polle, Andrea

2010-12-01

To investigate early salt acclimation mechanisms in a salt-tolerant poplar species (Populus euphratica), the kinetics of molecular, metabolic, and physiological changes during a 24-h salt exposure were measured. Three distinct phases of salt stress were identified by analyses of the osmotic pressure and the shoot water potential: dehydration, salt accumulation, and osmotic restoration associated with ionic stress. The duration and intensity of these phases differed between leaves and roots. Transcriptome analysis using P. euphratica-specific microarrays revealed clusters of coexpressed genes in these phases, with only 3% overlapping salt-responsive genes in leaves and roots. Acclimation of cellular metabolism to high salt concentrations involved remodeling of amino acid and protein biosynthesis and increased expression of molecular chaperones (dehydrins, osmotin). Leaves suffered initially from dehydration, which resulted in changes in transcript levels of mitochondrial and photosynthetic genes, indicating adjustment of energy metabolism. Initially, decreases in stress-related genes were found, whereas increases occurred only when leaves had restored the osmotic balance by salt accumulation. Comparative in silico analysis of the poplar stress regulon with Arabidopsis (Arabidopsis thaliana) orthologs was used as a strategy to reduce the number of candidate genes for functional analysis. Analysis of Arabidopsis knockout lines identified a lipocalin-like gene (AtTIL) and a gene encoding a protein with previously unknown functions (AtSIS) to play roles in salt tolerance. In conclusion, by dissecting the stress transcriptome of tolerant species, novel genes important for salt endurance can be identified.

Linking the Salt Transcriptome with Physiological Responses of a Salt-Resistant Populus Species as a Strategy to Identify Genes Important for Stress Acclimation1[W][OA

PubMed Central

Brinker, Monika; Brosché, Mikael; Vinocur, Basia; Abo-Ogiala, Atef; Fayyaz, Payam; Janz, Dennis; Ottow, Eric A.; Cullmann, Andreas D.; Saborowski, Joachim; Kangasjärvi, Jaakko; Altman, Arie; Polle, Andrea

2010-01-01

To investigate early salt acclimation mechanisms in a salt-tolerant poplar species (Populus euphratica), the kinetics of molecular, metabolic, and physiological changes during a 24-h salt exposure were measured. Three distinct phases of salt stress were identified by analyses of the osmotic pressure and the shoot water potential: dehydration, salt accumulation, and osmotic restoration associated with ionic stress. The duration and intensity of these phases differed between leaves and roots. Transcriptome analysis using P. euphratica-specific microarrays revealed clusters of coexpressed genes in these phases, with only 3% overlapping salt-responsive genes in leaves and roots. Acclimation of cellular metabolism to high salt concentrations involved remodeling of amino acid and protein biosynthesis and increased expression of molecular chaperones (dehydrins, osmotin). Leaves suffered initially from dehydration, which resulted in changes in transcript levels of mitochondrial and photosynthetic genes, indicating adjustment of energy metabolism. Initially, decreases in stress-related genes were found, whereas increases occurred only when leaves had restored the osmotic balance by salt accumulation. Comparative in silico analysis of the poplar stress regulon with Arabidopsis (Arabidopsis thaliana) orthologs was used as a strategy to reduce the number of candidate genes for functional analysis. Analysis of Arabidopsis knockout lines identified a lipocalin-like gene (AtTIL) and a gene encoding a protein with previously unknown functions (AtSIS) to play roles in salt tolerance. In conclusion, by dissecting the stress transcriptome of tolerant species, novel genes important for salt endurance can be identified. PMID:20959419

Genome-wide organization and expression profiling of the NAC transcription factor family in potato (Solanum tuberosum L.).

PubMed

Singh, Anil Kumar; Sharma, Vishal; Pal, Awadhesh Kumar; Acharya, Vishal; Ahuja, Paramvir Singh

2013-08-01

NAC [no apical meristem (NAM), Arabidopsis thaliana transcription activation factor [ATAF1/2] and cup-shaped cotyledon (CUC2)] proteins belong to one of the largest plant-specific transcription factor (TF) families and play important roles in plant development processes, response to biotic and abiotic cues and hormone signalling. Our genome-wide analysis identified 110 StNAC genes in potato encoding for 136 proteins, including 14 membrane-bound TFs. The physical map positions of StNAC genes on 12 potato chromosomes were non-random, and 40 genes were found to be distributed in 16 clusters. The StNAC proteins were phylogenetically clustered into 12 subgroups. Phylogenetic analysis of StNACs along with their Arabidopsis and rice counterparts divided these proteins into 18 subgroups. Our comparative analysis has also identified 36 putative TNAC proteins, which appear to be restricted to Solanaceae family. In silico expression analysis, using Illumina RNA-seq transcriptome data, revealed tissue-specific, biotic, abiotic stress and hormone-responsive expression profile of StNAC genes. Several StNAC genes, including StNAC072 and StNAC101that are orthologs of known stress-responsive Arabidopsis RESPONSIVE TO DEHYDRATION 26 (RD26) were identified as highly abiotic stress responsive. Quantitative real-time polymerase chain reaction analysis largely corroborated the expression profile of StNAC genes as revealed by the RNA-seq data. Taken together, this analysis indicates towards putative functions of several StNAC TFs, which will provide blue-print for their functional characterization and utilization in potato improvement.

Genome-scale model-driven strain design for dicarboxylic acid production in Yarrowia lipolytica.

PubMed

Mishra, Pranjul; Lee, Na-Rae; Lakshmanan, Meiyappan; Kim, Minsuk; Kim, Byung-Gee; Lee, Dong-Yup

2018-03-19

Recently, there have been several attempts to produce long-chain dicarboxylic acids (DCAs) in various microbial hosts. Of these, Yarrowia lipolytica has great potential due to its oleaginous characteristics and unique ability to utilize hydrophobic substrates. However, Y. lipolytica should be further engineered to make it more competitive: the current approaches are mostly intuitive and cumbersome, thus limiting its industrial application. In this study, we proposed model-guided metabolic engineering strategies for enhanced production of DCAs in Y. lipolytica. At the outset, we reconstructed genome-scale metabolic model (GSMM) of Y. lipolytica (iYLI647) by substantially expanding the previous models. Subsequently, the model was validated using three sets of published culture experiment data. It was finally exploited to identify genetic engineering targets for overexpression, knockout, and cofactor modification by applying several in silico strain design methods, which potentially give rise to high yield production of the industrially relevant long-chain DCAs, e.g., dodecanedioic acid (DDDA). The resultant targets include (1) malate dehydrogenase and malic enzyme genes and (2) glutamate dehydrogenase gene, in silico overexpression of which generated additional NADPH required for fatty acid synthesis, leading to the increased DDDA fluxes by 48% and 22% higher, respectively, compared to wild-type. We further investigated the effect of supplying branched-chain amino acids on the acetyl-CoA turn-over rate which is key metabolite for fatty acid synthesis, suggesting their significance for production of DDDA in Y. lipolytica. In silico model-based strain design strategies allowed us to identify several metabolic engineering targets for overproducing DCAs in lipid accumulating yeast, Y. lipolytica. Thus, the current study can provide a methodological framework that is applicable to other oleaginous yeasts for value-added biochemical production.

In Silico Identification and Pharmacological Evaluation of Novel Endocrine Disrupting Chemicals That Act via the Ligand-Binding Domain of the Estrogen Receptor α

PubMed Central

Kufareva, Irina; Abagyan, Ruben

2014-01-01

Endocrine disrupting chemicals (EDCs) pose a significant threat to human health, society, and the environment. Many EDCs elicit their toxic effects through nuclear hormone receptors, like the estrogen receptor α (ERα). In silico models can be used to prioritize chemicals for toxicological evaluation to reduce the amount of costly pharmacological testing and enable early alerts for newly designed compounds. However, many of the current computational models are overly dependent on the chemistry of known modulators and perform poorly for novel chemical scaffolds. Herein we describe the development of computational, three-dimensional multi-conformational pocket-field docking, and chemical-field docking models for the identification of novel EDCs that act via the ligand-binding domain of ERα. These models were highly accurate in the retrospective task of distinguishing known high-affinity ERα modulators from inactive or decoy molecules, with minimal training. To illustrate the utility of the models in prospective in silico compound screening, we screened a database of over 6000 environmental chemicals and evaluated the 24 top-ranked hits in an ERα transcriptional activation assay and a differential scanning fluorimetry-based ERα binding assay. Promisingly, six chemicals displayed ERα agonist activity (32nM–3.98μM) and two chemicals had moderately stabilizing effects on ERα. Two newly identified active compounds were chemically related β-adrenergic receptor (βAR) agonists, dobutamine, and ractopamine (a feed additive that promotes leanness in cattle and poultry), which are the first βAR agonists identified as activators of ERα-mediated gene transcription. This approach can be applied to other receptors implicated in endocrine disruption. PMID:24928891

In silico identification and pharmacological evaluation of novel endocrine disrupting chemicals that act via the ligand-binding domain of the estrogen receptor α.

PubMed

McRobb, Fiona M; Kufareva, Irina; Abagyan, Ruben

2014-09-01

Endocrine disrupting chemicals (EDCs) pose a significant threat to human health, society, and the environment. Many EDCs elicit their toxic effects through nuclear hormone receptors, like the estrogen receptor α (ERα). In silico models can be used to prioritize chemicals for toxicological evaluation to reduce the amount of costly pharmacological testing and enable early alerts for newly designed compounds. However, many of the current computational models are overly dependent on the chemistry of known modulators and perform poorly for novel chemical scaffolds. Herein we describe the development of computational, three-dimensional multi-conformational pocket-field docking, and chemical-field docking models for the identification of novel EDCs that act via the ligand-binding domain of ERα. These models were highly accurate in the retrospective task of distinguishing known high-affinity ERα modulators from inactive or decoy molecules, with minimal training. To illustrate the utility of the models in prospective in silico compound screening, we screened a database of over 6000 environmental chemicals and evaluated the 24 top-ranked hits in an ERα transcriptional activation assay and a differential scanning fluorimetry-based ERα binding assay. Promisingly, six chemicals displayed ERα agonist activity (32nM-3.98μM) and two chemicals had moderately stabilizing effects on ERα. Two newly identified active compounds were chemically related β-adrenergic receptor (βAR) agonists, dobutamine, and ractopamine (a feed additive that promotes leanness in cattle and poultry), which are the first βAR agonists identified as activators of ERα-mediated gene transcription. This approach can be applied to other receptors implicated in endocrine disruption. © The Author 2014. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Structural insights into pharmacophore-assisted in silico identification of protein-protein interaction inhibitors for inhibition of human toll-like receptor 4 - myeloid differentiation factor-2 (hTLR4-MD-2) complex.

PubMed

Mishra, Vinita; Pathak, Chandramani

2018-05-29

Toll-like receptor 4 (TLR4) is a member of Toll-Like Receptors (TLRs) family that serves as a receptor for bacterial lipopolysaccharide (LPS). TLR4 alone cannot recognize LPS without aid of co-receptor myeloid differentiation factor-2 (MD-2). Binding of LPS with TLR4 forms a LPS-TLR4-MD-2 complex and directs downstream signaling for activation of immune response, inflammation and NF-κB activation. Activation of TLR4 signaling is associated with various pathophysiological consequences. Therefore, targeting protein-protein interaction (PPI) in TLR4-MD-2 complex formation could be an attractive therapeutic approach for targeting inflammatory disorders. The aim of present study was directed to identify small molecule PPI inhibitors (SMPPIIs) using pharmacophore mapping-based approach of computational drug discovery. Here, we had retrieved the information about the hot spot residues and their pharmacophoric features at both primary (TLR4-MD-2) and dimerization (MD-2-TLR4*) protein-protein interaction interfaces in TLR4-MD-2 homo-dimer complex using in silico methods. Promising candidates were identified after virtual screening, which may restrict TLR4-MD-2 protein-protein interaction. In silico off-target profiling over the virtually screened compounds revealed other possible molecular targets. Two of the virtually screened compounds (C11 and C15) were predicted to have an inhibitory concentration in μM range after HYDE assessment. Molecular dynamics simulation study performed for these two compounds in complex with target protein confirms the stability of the complex. After virtual high throughput screening we found selective hTLR4-MD-2 inhibitors, which may have therapeutic potential to target chronic inflammatory diseases.

In-silico QTL mapping of postpubertal mammary ductal development in the mouse uncovers potential human breast cancer risk loci

USDA-ARS?s Scientific Manuscript database

Genetic background plays a dominant role in mammary gland development and breast cancer (BrCa). Despite this, the role of genetics is only partially understood. This study used strain-dependent variation in an inbred mouse mapping panel, to identify quantitative trait loci (QTL) underlying structura...

Investigating the metabolic capabilities of Mycobacterium tuberculosis H37Rv using the in silico strain iNJ661 and proposing alternative drug targets

PubMed Central

Jamshidi, Neema; Palsson, Bernhard Ø

2007-01-01

Background: Mycobacterium tuberculosis continues to be a major pathogen in the third world, killing almost 2 million people a year by the most recent estimates. Even in industrialized countries, the emergence of multi-drug resistant (MDR) strains of tuberculosis hails the need to develop additional medications for treatment. Many of the drugs used for treatment of tuberculosis target metabolic enzymes. Genome-scale models can be used for analysis, discovery, and as hypothesis generating tools, which will hopefully assist the rational drug development process. These models need to be able to assimilate data from large datasets and analyze them. Results: We completed a bottom up reconstruction of the metabolic network of Mycobacterium tuberculosis H37Rv. This functional in silico bacterium, iNJ661, contains 661 genes and 939 reactions and can produce many of the complex compounds characteristic to tuberculosis, such as mycolic acids and mycocerosates. We grew this bacterium in silico on various media, analyzed the model in the context of multiple high-throughput data sets, and finally we analyzed the network in an 'unbiased' manner by calculating the Hard Coupled Reaction (HCR) sets, groups of reactions that are forced to operate in unison due to mass conservation and connectivity constraints. Conclusion: Although we observed growth rates comparable to experimental observations (doubling times ranging from about 12 to 24 hours) in different media, comparisons of gene essentiality with experimental data were less encouraging (generally about 55%). The reasons for the often conflicting results were multi-fold, including gene expression variability under different conditions and lack of complete biological knowledge. Some of the inconsistencies between in vitro and in silico or in vivo and in silico results highlight specific loci that are worth further experimental investigations. Finally, by considering the HCR sets in the context of known drug targets for tuberculosis treatment we proposed new alternative, but equivalent drug targets. PMID:17555602

In silico analysis of the fucosylation-associated genome of the human blood fluke Schistosoma mansoni: cloning and characterization of the enzymes involved in GDP-L-fucose synthesis and Golgi import

PubMed Central

2013-01-01

Background Carbohydrate structures of surface-expressed and secreted/excreted glycoconjugates of the human blood fluke Schistosoma mansoni are key determinants that mediate host-parasite interactions in both snail and mammalian hosts. Fucose is a major constituent of these immunologically important glycans, and recent studies have sought to characterize fucosylation-associated enzymes, including the Golgi-localized fucosyltransferases that catalyze the transfer of L-fucose from a GDP-L-fucose donor to an oligosaccharide acceptor. Importantly, GDP-L-fucose is the only nucleotide-sugar donor used by fucosyltransferases and its availability represents a bottleneck in fucosyl-glycotope expression. Methods A homology-based genome-wide bioinformatics approach was used to identify and molecularly characterize the enzymes that contribute to GDP-L-fucose synthesis and Golgi import in S. mansoni. Putative functions were further investigated through molecular phylogenetic and immunocytochemical analyses. Results We identified homologs of GDP-D-mannose-4,6-dehydratase (GMD) and GDP-4-keto-6-deoxy-D-mannose-3,5-epimerase-4-reductase (GMER), which constitute a de novo pathway for GDP-L-fucose synthesis, in addition to a GDP-L-fucose transporter (GFT) that putatively imports cytosolic GDP-L-fucose into the Golgi. In silico primary sequence analyses identified characteristic Rossman loop and short-chain dehydrogenase/reductase motifs in GMD and GMER as well as 10 transmembrane domains in GFT. All genes are alternatively spliced, generating variants of unknown function. Observed quantitative differences in steady-state transcript levels between miracidia and primary sporocysts may contribute to differential glycotope expression in early larval development. Additionally, analyses of protein expression suggest the occurrence of cytosolic GMD and GMER in the ciliated epidermal plates and tegument of miracidia and primary sporocysts, respectively, which is consistent with previous localization of highly fucosylated glycotopes. Conclusions This study is the first to identify and characterize three key genes that are putatively involved in the synthesis and Golgi import of GDP-L-fucose in S. mansoni and provides fundamental information regarding their genomic organization, genetic variation, molecular phylogenetics, and developmental expression in intramolluscan larval stages. PMID:23835114

In silico analysis of the fucosylation-associated genome of the human blood fluke Schistosoma mansoni: cloning and characterization of the enzymes involved in GDP-L-fucose synthesis and Golgi import.

PubMed

Peterson, Nathan A; Anderson, Tavis K; Wu, Xiao-Jun; Yoshino, Timothy P

2013-07-09

Carbohydrate structures of surface-expressed and secreted/excreted glycoconjugates of the human blood fluke Schistosoma mansoni are key determinants that mediate host-parasite interactions in both snail and mammalian hosts. Fucose is a major constituent of these immunologically important glycans, and recent studies have sought to characterize fucosylation-associated enzymes, including the Golgi-localized fucosyltransferases that catalyze the transfer of L-fucose from a GDP-L-fucose donor to an oligosaccharide acceptor. Importantly, GDP-L-fucose is the only nucleotide-sugar donor used by fucosyltransferases and its availability represents a bottleneck in fucosyl-glycotope expression. A homology-based genome-wide bioinformatics approach was used to identify and molecularly characterize the enzymes that contribute to GDP-L-fucose synthesis and Golgi import in S. mansoni. Putative functions were further investigated through molecular phylogenetic and immunocytochemical analyses. We identified homologs of GDP-D-mannose-4,6-dehydratase (GMD) and GDP-4-keto-6-deoxy-D-mannose-3,5-epimerase-4-reductase (GMER), which constitute a de novo pathway for GDP-L-fucose synthesis, in addition to a GDP-L-fucose transporter (GFT) that putatively imports cytosolic GDP-L-fucose into the Golgi. In silico primary sequence analyses identified characteristic Rossman loop and short-chain dehydrogenase/reductase motifs in GMD and GMER as well as 10 transmembrane domains in GFT. All genes are alternatively spliced, generating variants of unknown function. Observed quantitative differences in steady-state transcript levels between miracidia and primary sporocysts may contribute to differential glycotope expression in early larval development. Additionally, analyses of protein expression suggest the occurrence of cytosolic GMD and GMER in the ciliated epidermal plates and tegument of miracidia and primary sporocysts, respectively, which is consistent with previous localization of highly fucosylated glycotopes. This study is the first to identify and characterize three key genes that are putatively involved in the synthesis and Golgi import of GDP-L-fucose in S. mansoni and provides fundamental information regarding their genomic organization, genetic variation, molecular phylogenetics, and developmental expression in intramolluscan larval stages.

Draft sequencing and comparative genomics of Xylella fastidiosa strains reveal novel biological insights.

PubMed

Bhattacharyya, Anamitra; Stilwagen, Stephanie; Reznik, Gary; Feil, Helene; Feil, William S; Anderson, Iain; Bernal, Axel; D'Souza, Mark; Ivanova, Natalia; Kapatral, Vinayak; Larsen, Niels; Los, Tamara; Lykidis, Athanasios; Selkov, Eugene; Walunas, Theresa L; Purcell, Alexander; Edwards, Rob A; Hawkins, Trevor; Haselkorn, Robert; Overbeek, Ross; Kyrpides, Nikos C; Predki, Paul F

2002-10-01

Draft sequencing is a rapid and efficient method for determining the near-complete sequence of microbial genomes. Here we report a comparative analysis of one complete and two draft genome sequences of the phytopathogenic bacterium, Xylella fastidiosa, which causes serious disease in plants, including citrus, almond, and oleander. We present highlights of an in silico analysis based on a comparison of reconstructions of core biological subsystems. Cellular pathway reconstructions have been used to identify a small number of genes, which are likely to reside within the draft genomes but are not captured in the draft assembly. These represented only a small fraction of all genes and were predominantly large and small ribosomal subunit protein components. By using this approach, some of the inherent limitations of draft sequence can be significantly reduced. Despite the incomplete nature of the draft genomes, it is possible to identify several phage-related genes, which appear to be absent from the draft genomes and not the result of insufficient sequence sampling. This region may therefore identify potential host-specific functions. Based on this first functional reconstruction of a phytopathogenic microbe, we spotlight an unusual respiration machinery as a potential target for biological control. We also predicted and developed a new defined growth medium for Xylella.

Comparative systems analysis of the secretome of the opportunistic pathogen Aspergillus fumigatus and other Aspergillus species.

PubMed

Vivek-Ananth, R P; Mohanraj, Karthikeyan; Vandanashree, Muralidharan; Jhingran, Anupam; Craig, James P; Samal, Areejit

2018-04-26

Aspergillus fumigatus and multiple other Aspergillus species cause a wide range of lung infections, collectively termed aspergillosis. Aspergilli are ubiquitous in environment with healthy immune systems routinely eliminating inhaled conidia, however, Aspergilli can become an opportunistic pathogen in immune-compromised patients. The aspergillosis mortality rate and emergence of drug-resistance reveals an urgent need to identify novel targets. Secreted and cell membrane proteins play a critical role in fungal-host interactions and pathogenesis. Using a computational pipeline integrating data from high-throughput experiments and bioinformatic predictions, we have identified secreted and cell membrane proteins in ten Aspergillus species known to cause aspergillosis. Small secreted and effector-like proteins similar to agents of fungal-plant pathogenesis were also identified within each secretome. A comparison with humans revealed that at least 70% of Aspergillus secretomes have no sequence similarity with the human proteome. An analysis of antigenic qualities of Aspergillus proteins revealed that the secretome is significantly more antigenic than cell membrane proteins or the complete proteome. Finally, overlaying an expression dataset, four A. fumigatus proteins upregulated during infection and with available structures, were found to be structurally similar to known drug target proteins in other organisms, and were able to dock in silico with the respective drug.

SNPs in NRXN1 and CHRNA5 are associated to smoking and regulation of GABAergic and glutamatergic pathways.

PubMed

Pérez-Rubio, Gloria; Pérez-Rodríguez, Martha E; Fernández-López, Juan Carlos; Ramírez-Venegas, Alejandra; García-Colunga, Jesús; Ávila-Moreno, Federico; Camarena, Angel; Sansores, Raúl H; Falfán-Valencia, Ramcés

2016-07-01

To identify genetic variants associated with greater tobacco consumption in a Mexican population. Daily smokers were classified as light smokers (LS; n = 742), heavy smokers (HS; n = 601) and nonsmokers (NS; n = 606). In the first stage, a genotyping microarray that included 347 SNPs in CHRNA2-CHRNA7/CHRNA10, CHRNB2-CHRNB4 and NRXN1 genes and 37 ancestry-informative markers was used to analyze 707 samples (187 HS, 328 LS and 192 NS). In the second stage, 14 SNPs from stage 1 were validated in the remaining samples (HS, LS and NS; n = 414 in each group) using real-time PCR. To predict the role of the associated SNPs, an in silico analysis was performed. Two SNPs in NRXN1 and two in CHRNA5 were associated with cigarette consumption, while rs10865246/C (NRXN1) was associated with high nicotine addiction. The in silico analysis revealed that rs1882296/T had a high level of homology with Hsa-miR-6740-5p, which encodes a putative miRNA that targets glutamate receptor subunits (GRIA2, GRID2) and GABA receptor subunits (GABRG1, GABRA4, GABRB2), while rs1882296/C had a high level of homology with Hsa-miR-6866-5p, which encodes a different miRNA that targets GRID2 and GABRB2. In a Mexican Mestizo population, greater consumption of cigarettes was influenced by polymorphisms in the NRXN1 and CHRNA5 genes. We proposed new hypotheses regarding the putative roles of miRNAs that influence the GABAergic and glutamatergic pathways in smoking addiction.

3D reconstruction optimization using imagery captured by unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Bassie, Abby L.; Meacham, Sean; Young, David; Turnage, Gray; Moorhead, Robert J.

2017-05-01

Because unmanned air vehicles (UAVs) are emerging as an indispensable image acquisition platform in precision agriculture, it is vitally important that researchers understand how to optimize UAV camera payloads for analysis of surveyed areas. In this study, imagery captured by a Nikon RGB camera attached to a Precision Hawk Lancaster was used to survey an agricultural field from six different altitudes ranging from 45.72 m (150 ft.) to 121.92 m (400 ft.). After collecting imagery, two different software packages (MeshLab and AgiSoft) were used to measure predetermined reference objects within six three-dimensional (3-D) point clouds (one per altitude scenario). In-silico measurements were then compared to actual reference object measurements, as recorded with a tape measure. Deviations of in-silico measurements from actual measurements were recorded as Δx, Δy, and Δz. The average measurement deviation in each coordinate direction was then calculated for each of the six flight scenarios. Results from MeshLab vs. AgiSoft offered insight into the effectiveness of GPS-defined point cloud scaling in comparison to user-defined point cloud scaling. In three of the six flight scenarios flown, MeshLab's 3D imaging software (user-defined scale) was able to measure object dimensions from 50.8 to 76.2 cm (20-30 inches) with greater than 93% accuracy. The largest average deviation in any flight scenario from actual measurements was 14.77 cm (5.82 in.). Analysis of the point clouds in AgiSoft (GPS-defined scale) yielded even smaller Δx, Δy, and Δz than the MeshLab measurements in over 75% of the flight scenarios. The precisions of these results are satisfactory in a wide variety of precision agriculture applications focused on differentiating and identifying objects using remote imagery.

In silico analysis of the polygalacturonase inhibiting protein 1 from apple, Malus domestica.

PubMed

Matsaunyane, Lerato Bt; Oelofse, Dean; Dubery, Ian A

2015-03-11

The Malus domestica polygalacturonase inhibiting protein 1 (MdPGIP1) gene, encoding the M. domestica polygalacturonase inhibiting protein 1 (MdPGIP1), was isolated from the Granny Smith apple cultivar (GenBank accession no. DQ185063). The gene was used to transform tobacco and potato for enhanced resistance against fungal diseases. Analysis of the MdPGIP1 nucleotide sequence revealed that the gene comprises 993 nucleotides that encode a 330 amino acid polypeptide. In silico characterization of the MdPGIP1 polypeptide revealed domains typical of PGIP proteins, which include a 24 amino acid putative signal peptide, a potential cleavage site [Alanine-Leucine-Serine (ALS)] for the signal peptide, a 238 amino acid leucine-rich repeat (LRR) domain, a 46 amino acid N-terminal domain and a 22 amino acid C-terminal domain. The hydropathic evaluation of MdPGIP1 indicated a repetitive hydrophobic motif in the LRR domain and a hydrophilic surface area consistent with a globular protein. The typical consensus glycosylation sequence of Asn-X-Ser/Thr was identified in MdPGIP1, indicating potential N-linked glycosylation of MdPGIP1. The molecular mass of non-glycosylated MdPGIP1 was calculated as 36.615 kDa and the theoretical isoelectric point as 6.98. Furthermore, the secondary and tertiary structure of MdPGIP1 was modelled, and revealed that MdPGIP1 is a curved and elongated molecule that contains sheet B1, sheet B2 and 310-helices on its LRR domain. The overall properties of the MdPGIP1 protein is similar to that of the prototypical Phaseolus vulgaris PGIP 2 (PvPGIP2), and the detected differences supported its use in biotechnological applications as an inhibitor of targeted fungal polygalacturonases (PGs).

Identification and In Silico Analysis of Major Redox Modulated Proteins from Brassica juncea Seedlings Using 2D Redox SDS PAGE (2-Dimensional Diagonal Redox Sodium Dodecyl Sulfate Polyacrylamide Gel Electrophoresis).

PubMed

Chaurasia, Satya Prakash; Deswal, Renu

2017-02-01

The thiol-disulphide exchange regulates the activity of proteins by redox modulation. Many studies to analyze reactive oxygen species (ROS), particularly, hydrogen peroxide (H 2 O 2 ) induced changes in the gene expression have been reported, but efforts to detect H 2 O 2 modified proteins are comparatively few. Two-dimensional diagonal redox sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS PAGE) was used to detect polypeptides which undergo thiol-disulphide exchange in Brassica juncea seedlings following H 2 O 2 (10 mM) treatment for 30 min. Eleven redox responsive polypeptides were identified which included cruciferin, NLI [Nuclear LIM (Lin11, Isl-1 & Mec-3 domains)] interacting protein phosphatase, RuBisCO (ribulose-1,5-bisphosphate carboxylase/oxygenase) large subunit, and myrosinase. Redox modulation of RuBisCO large subunit was further confirmed by western blotting. However, the small subunit of RuBisCO was not affected by these redox changes. All redox modulated targets except NLI interacting protein (although it contains two cysteines) showed oxidation sensitive cysteines by in silico analysis. Interestingly, interactome of cruciferin and myrosinase indicated that they may have additional function(s) beside their well-known roles in the seedling development and abiotic stress respectively. Cruciferin showed interactions with stress associated proteins like defensing-like protein 192 and 2-cys peroxiredoxin. Similarly, myrosinase showed interactions with nitrilase and cytochrome p450 which are involved in nitrogen metabolism and/or hormone biosynthesis. This simple procedure can be used to detect major stress mediated redox changes in other plants.

Novel in silico multivariate mapping of intrinsic and anticorrelated connectivity to neurocognitive functional maps supports the maturational hypothesis of ADHD.

PubMed

de Lacy, Nina; Kodish, Ian; Rachakonda, Srinivas; Calhoun, Vince D

2018-04-22

From childhood to adolescence, strengthened coupling in frontal, striatal and parieto-temporal regions associated with cognitive control, and increased anticorrelation between task-positive and task-negative circuits, subserve the reshaping of behavior. ADHD is a common condition peaking in adolescence and regressing in adulthood, with a wide variety of cognitive control deficits. Alternate hypotheses of ADHD emphasize lagging circuitry refinement versus categorical differences in network function. However, quantifying the individual circuit contributions to behavioral findings, and relative roles of maturational versus categorical effects, is challenging in vivo or in meta-analyses using task-based paradigms within the same pipeline, given the multiplicity of neurobehavioral functions implicated. To address this, we analyzed 46 positively-correlated and anticorrelated circuits in a multivariate model in resting-state data from 504 age- and gender-matched youth, and created a novel in silico method to map individual quantified effects to reverse inference maps of 8 neurocognitive functions consistently implicated in ADHD, as well as dopamine and hyperactivity. We identified only age- and gender-related effects in intrinsic connectivity, and found that maturational refinement of circuits in youth with ADHD occupied 3-10x more brain locations than in typical development, with the footprint, effect size and contribution of individual circuits varying substantially. Our analysis supports the maturational hypothesis of ADHD, suggesting lagging connectivity reorganization within specific subnetworks of fronto-parietal control, ventral attention, cingulo-opercular, temporo-limbic and cerebellar sub-networks contribute across neurocognitive findings present in this complex condition. We present the first analysis of anti-correlated connectivity in ADHD and suggest new directions for exploring residual and non-responsive symptoms. © 2018 Wiley Periodicals, Inc.

Elevated heart rate triggers action potential alternans and sudden death. translational study of a homozygous KCNH2 mutation.

PubMed

Schweigmann, Ulrich; Biliczki, Peter; Ramirez, Rafael J; Marschall, Christoph; Takac, Ina; Brandes, Ralf P; Kotzot, Dieter; Girmatsion, Zenawit; Hohnloser, Stefan H; Ehrlich, Joachim R

2014-01-01

Long QT syndrome (LQTS) leads to arrhythmic events and increased risk for sudden cardiac death (SCD). Homozygous KCNH2 mutations underlying LQTS-2 have previously been termed "human HERG knockout" and typically express severe phenotypes. We studied genotype-phenotype correlations of an LQTS type 2 mutation identified in the homozygous index patient from a consanguineous Turkish family after his brother died suddenly during febrile illness. Clinical work-up, DNA sequencing, mutagenesis, cell culture, patch-clamp, in silico mathematical modelling, protein biochemistry, confocal microscopy were performed. Genetic analysis revealed a homozygous C-terminal KCNH2 mutation (p.R835Q) in the index patient (QTc ∼506 ms with notched T waves). Parents were I° cousins - both heterozygous for the mutation and clinically unremarkable (QTc ∼447 ms, father and ∼396 ms, mother). Heterologous expression of KCNH2-R835Q showed mildly reduced current amplitudes. Biophysical properties of ionic currents were also only nominally changed with slight acceleration of deactivation and more negative V50 in R835Q-currents. Protein biochemistry and confocal microscopy revealed similar expression patterns and trafficking of WT and R835Q, even at elevated temperature. In silico analysis demonstrated mildly prolonged ventricular action potential duration (APD) compared to WT at a cycle length of 1000 ms. At a cycle length of 350 ms M-cell APD remained stable in WT, but displayed APD alternans in R835Q. Kv11.1 channels affected by the C-terminal R835Q mutation display mildly modified biophysical properties, but leads to M-cell APD alternans with elevated heart rate and could precipitate SCD under specific clinical circumstances associated with high heart rates.

Design, synthesis, pharmacological evaluation and in silico ADMET prediction of novel substituted benzimidazole derivatives as angiotensin II-AT1 receptor antagonists based on predictive 3D QSAR models.

PubMed

Vyas, V K; Gupta, N; Ghate, M; Patel, S

2014-01-01

In this study we designed novel substituted benzimidazole derivatives and predicted their absorption, distribution, metabolism, excretion and toxicity (ADMET) properties, based on a predictive 3D QSAR study on 132 substituted benzimidazoles as AngII-AT1 receptor antagonists. The two best predicted compounds were synthesized and evaluated for AngII-AT1 receptor antagonism. Three different alignment tools for comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used. The best 3D QSAR models were obtained using the rigid body (Distill) alignment method. CoMFA and CoMSIA models were found to be statistically significant with leave-one-out correlation coefficients (q(2)) of 0.630 and 0.623, respectively, cross-validated coefficients (r(2)cv) of 0.651 and 0.630, respectively, and conventional coefficients of determination (r(2)) of 0.848 and 0.843, respectively. 3D QSAR models were validated using a test set of 24 compounds, giving satisfactory predicted results (r(2)pred) of 0.727 and 0.689 for the CoMFA and CoMSIA models, respectively. We have identified some key features in substituted benzimidazole derivatives, such as lipophilicity and H-bonding at the 2- and 5-positions of the benzimidazole nucleus, respectively, for AT1 receptor antagonistic activity. We designed 20 novel substituted benzimidazole derivatives and predicted their activity. In silico ADMET properties were also predicted for these designed molecules. Finally, the compounds with best predicted activity were synthesized and evaluated for in vitro angiotensin II-AT1 receptor antagonism.

JRC GMO-Amplicons: a collection of nucleic acid sequences related to genetically modified organisms

PubMed Central

Petrillo, Mauro; Angers-Loustau, Alexandre; Henriksson, Peter; Bonfini, Laura; Patak, Alex; Kreysa, Joachim

2015-01-01

The DNA target sequence is the key element in designing detection methods for genetically modified organisms (GMOs). Unfortunately this information is frequently lacking, especially for unauthorized GMOs. In addition, patent sequences are generally poorly annotated, buried in complex and extensive documentation and hard to link to the corresponding GM event. Here, we present the JRC GMO-Amplicons, a database of amplicons collected by screening public nucleotide sequence databanks by in silico determination of PCR amplification with reference methods for GMO analysis. The European Union Reference Laboratory for Genetically Modified Food and Feed (EU-RL GMFF) provides these methods in the GMOMETHODS database to support enforcement of EU legislation and GM food/feed control. The JRC GMO-Amplicons database is composed of more than 240 000 amplicons, which can be easily accessed and screened through a web interface. To our knowledge, this is the first attempt at pooling and collecting publicly available sequences related to GMOs in food and feed. The JRC GMO-Amplicons supports control laboratories in the design and assessment of GMO methods, providing inter-alia in silico prediction of primers specificity and GM targets coverage. The new tool can assist the laboratories in the analysis of complex issues, such as the detection and identification of unauthorized GMOs. Notably, the JRC GMO-Amplicons database allows the retrieval and characterization of GMO-related sequences included in patents documentation. Finally, it can help annotating poorly described GM sequences and identifying new relevant GMO-related sequences in public databases. The JRC GMO-Amplicons is freely accessible through a web-based portal that is hosted on the EU-RL GMFF website. Database URL: http://gmo-crl.jrc.ec.europa.eu/jrcgmoamplicons/ PMID:26424080

JRC GMO-Amplicons: a collection of nucleic acid sequences related to genetically modified organisms.

PubMed

Petrillo, Mauro; Angers-Loustau, Alexandre; Henriksson, Peter; Bonfini, Laura; Patak, Alex; Kreysa, Joachim

2015-01-01

The DNA target sequence is the key element in designing detection methods for genetically modified organisms (GMOs). Unfortunately this information is frequently lacking, especially for unauthorized GMOs. In addition, patent sequences are generally poorly annotated, buried in complex and extensive documentation and hard to link to the corresponding GM event. Here, we present the JRC GMO-Amplicons, a database of amplicons collected by screening public nucleotide sequence databanks by in silico determination of PCR amplification with reference methods for GMO analysis. The European Union Reference Laboratory for Genetically Modified Food and Feed (EU-RL GMFF) provides these methods in the GMOMETHODS database to support enforcement of EU legislation and GM food/feed control. The JRC GMO-Amplicons database is composed of more than 240 000 amplicons, which can be easily accessed and screened through a web interface. To our knowledge, this is the first attempt at pooling and collecting publicly available sequences related to GMOs in food and feed. The JRC GMO-Amplicons supports control laboratories in the design and assessment of GMO methods, providing inter-alia in silico prediction of primers specificity and GM targets coverage. The new tool can assist the laboratories in the analysis of complex issues, such as the detection and identification of unauthorized GMOs. Notably, the JRC GMO-Amplicons database allows the retrieval and characterization of GMO-related sequences included in patents documentation. Finally, it can help annotating poorly described GM sequences and identifying new relevant GMO-related sequences in public databases. The JRC GMO-Amplicons is freely accessible through a web-based portal that is hosted on the EU-RL GMFF website. Database URL: http://gmo-crl.jrc.ec.europa.eu/jrcgmoamplicons/. © The Author(s) 2015. Published by Oxford University Press.

Decoding Crucial LncRNAs Implicated in Neurogenesis and Neurological Disorders.

PubMed

Ayana, R; Singh, Shailja; Pati, Soumya

2017-04-15

Unraveling transcriptional heterogeneity and the labyrinthine nature of neurodevelopment can probe insights into neuropsychiatric disorders. It is noteworthy that adult neurogenesis is restricted to the subventricular and subgranular zones of the brain. Recent studies suggest long non-coding RNAs (lncRNAs) as an avant-garde class of regulators implicated in neurodevelopment. But, paucity exists in the knowledge regarding lncRNAs in neurogenesis and their associations with neurodevelopmental defects. To address this, we extensively reviewed the existing literature databases as well as performed relevant in-silico analysis. We utilized Allen Brain Atlas (ABA) differential search module and generated a catalogue of ∼30,000 transcripts specific to the neurogenic zones, including coding and non-coding transcripts. To explore the existing lncRNAs reported in neurogenesis, we performed extensive literature mining and identified 392 lncRNAs. These degenerate lncRNAs were mapped onto the ABA transcript list leading to detection of 20 lncRNAs specific to neurogenic zones (Dentate gyrus/Lateral ventricle), among which 10 showed associations to several neurodevelopmental disorders following in-silico mapping onto brain disease databases like Simons Foundation Autism Research Initiative, AutDB, and lncRNADisease. Notably, using ABA correlation module, we could establish lncRNA-to-mRNA coexpression networks for the above 10 candidate lncRNAs. Finally, pathway prediction revealed physical, biochemical, or regulatory interactions for nine lncRNAs. In addition, ABA differential search also revealed 54 novel significant lncRNAs from the null set (∼30,000). Conclusively, this review represents an updated catalogue of lncRNAs in neurogenesis and neurological diseases, and overviews the field of OMICs-based data analysis for understanding lncRNome-based regulation in neurodevelopment.

Analysis and Evaluation of the Inhibitory Mechanism of a Novel Angiotensin-I-Converting Enzyme Inhibitory Peptide Derived from Casein Hydrolysate.

PubMed

Tu, Maolin; Liu, Hanxiong; Zhang, Ruyi; Chen, Hui; Mao, Fengjiao; Cheng, Shuzhen; Lu, Weihong; Du, Ming

2018-04-25

Casein hydrolysates exert various biological activities, and the responsible functional peptides are being identified from them continuously. In this study, the tryptic casein hydrolysate was fractionated by an ultrafiltration membrane (3 kDa), and the peptides were identified by capillary electrophoresis-quadrupole-time-of-flight-tandem mass spectrometry. Meanwhile, in silico methods were used to analyze the toxicity, solubility, stability, and affinity between the peptides and angiotensin-I-converting enzyme (ACE). Finally, a new angiotensin-I-converting enzyme inhibitory (ACEI) peptide, EKVNELSK, derived from α s1 -casein (fragment 35-42) was screened. The half maximal inhibitory concentration value of the peptide is 5.998 mM, which was determined by a high-performance liquid chromatography method. The Lineweaver-Burk plot indicated that this peptide is a mixed-type inhibitor against ACE. Moreover, Discovery Studio 2017 R2 software was adopted to perform molecular docking to propose the potential mechanisms underlying the ACEI activity of the peptide. These results indicated that EKVNELSK is a new ACEI peptide identified from casein hydrolysate.

A proteomic analysis of the chromoplasts isolated from sweet orange fruits [Citrus sinensis (L.) Osbeck

PubMed Central

Zeng, Yunliu; Pan, Zhiyong; Ding, Yuduan; Zhu, Andan; Cao, Hongbo; Xu, Qiang; Deng, Xiuxin

2011-01-01

Here, a comprehensive proteomic analysis of the chromoplasts purified from sweet orange using Nycodenz density gradient centrifugation is reported. A GeLC-MS/MS shotgun approach was used to identify the proteins of pooled chromoplast samples. A total of 493 proteins were identified from purified chromoplasts, of which 418 are putative plastid proteins based on in silico sequence homology and functional analyses. Based on the predicted functions of these identified plastid proteins, a large proportion (∼60%) of the chromoplast proteome of sweet orange is constituted by proteins involved in carbohydrate metabolism, amino acid/protein synthesis, and secondary metabolism. Of note, HDS (hydroxymethylbutenyl 4-diphosphate synthase), PAP (plastid-lipid-associated protein), and psHSPs (plastid small heat shock proteins) involved in the synthesis or storage of carotenoid and stress response are among the most abundant proteins identified. A comparison of chromoplast proteomes between sweet orange and tomato suggested a high level of conservation in a broad range of metabolic pathways. However, the citrus chromoplast was characterized by more extensive carotenoid synthesis, extensive amino acid synthesis without nitrogen assimilation, and evidence for lipid metabolism concerning jasmonic acid synthesis. In conclusion, this study provides an insight into the major metabolic pathways as well as some unique characteristics of the sweet orange chromoplasts at the whole proteome level. PMID:21841170

IVS-II-648/649 (-T) (HBB: c.316-202del) Triggers a Novel β-Thalassemia Phenotype.

PubMed

Azimi, Azam; Alibakhshi, Reza; Hayati, Hasibeh; Tahmasebi, Soosan; Alimoradi, Sasan

2017-01-01

Thalassemia is the most common inherited disorder in Iran. There are approximately 800 different genomic alterations of the β-globin gene described in the HbVar database. In this study, we identified a novel mutation in a 21-year-old woman [IVS-II-648/649 (-T); HBB: c.316-202del)] and describe its clinical implications. Two other members of this family, all with hematological and clinical features associated with β-thalassemia (β-thal), also carried this mutation. The molecular diagnosis of the β-globin gene mutation was performed by direct sequencing. Based on the observed β-thal phenotype and in silico analysis results, we concluded that this novel β-globin gene mutation was associated with the mild phenotype of β-thal.

Significance of functional disease-causal/susceptible variants identified by whole-genome analyses for the understanding of human diseases.

PubMed

Hitomi, Yuki; Tokunaga, Katsushi

2017-01-01

Human genome variation may cause differences in traits and disease risks. Disease-causal/susceptible genes and variants for both common and rare diseases can be detected by comprehensive whole-genome analyses, such as whole-genome sequencing (WGS), using next-generation sequencing (NGS) technology and genome-wide association studies (GWAS). Here, in addition to the application of an NGS as a whole-genome analysis method, we summarize approaches for the identification of functional disease-causal/susceptible variants from abundant genetic variants in the human genome and methods for evaluating their functional effects in human diseases, using an NGS and in silico and in vitro functional analyses. We also discuss the clinical applications of the functional disease causal/susceptible variants to personalized medicine.

In silico platform for xenobiotics ADME-T pharmacological properties modeling and prediction. Part II: The body in a Hilbertian space.

PubMed

Jacob, Alexandre; Pratuangdejkul, Jaturong; Buffet, Sébastien; Launay, Jean-Marie; Manivet, Philippe

2009-04-01

We have broken old surviving dogmas and concepts used in computational chemistry and created an efficient in silico ADME-T pharmacological properties modeling and prediction toolbox for any xenobiotic. With the help of an innovative and pragmatic approach combining various in silico techniques, like molecular modeling, quantum chemistry and in-house developed algorithms, the interactions between drugs and those enzymes, transporters and receptors involved in their biotransformation can be studied. ADME-T pharmacological parameters can then be predicted after in vitro and in vivo validations of in silico models.

Sequence analysis of PROTEOLYSIS 6 from Solanum lycopersicum

NASA Astrophysics Data System (ADS)

Roslan, Nur Farhana; Chew, Bee Lyn; Goh, Hoe-Han; Isa, Nurulhikma Md

2018-04-01

The N-end rule pathway is a protein degradation pathway that relates the protein half-life with the identity of its N-terminal residues. A destabilizing N-terminal residues is created by enzymatic reaction or chemical modifications. This destabilized substrate will be recognized by PROTEOLYSIS 6 (PRT6) protein, which encodes an E3 ligase enzyme and resulted in substrate degradation by proteasome. PRT6 has been studied in Arabidopsis thaliana and barley but not yet been studied in fleshy fruit plants. Hence, this study was carried out in tomato that is known as the model for fleshy fruit plants. BLASTX analysis identified that Solyc09g010830 which encodes for a PRT6 gene in tomato based on its sequence similarity with PRT6 in A. thaliana. In silico gene expression analysis shows that PRT6 gene was highly expressed in tomato fruits breaker +5. Co-expression analysis shows that PRT6 may not only involved in abiotic stresses but also in biotic stresses. The objective is to analyze the sequence and characterize PRT6 gene in tomato.

Metagenomic Analysis of the Sponge Discodermia Reveals the Production of the Cyanobacterial Natural Product Kasumigamide by 'Entotheonella'.

PubMed

Nakashima, Yu; Egami, Yoko; Kimura, Miki; Wakimoto, Toshiyuki; Abe, Ikuro

2016-01-01

Sponge metagenomes are a useful platform to mine cryptic biosynthetic gene clusters responsible for production of natural products involved in the sponge-microbe association. Since numerous sponge-derived bioactive metabolites are biosynthesized by the symbiotic bacteria, this strategy may concurrently reveal sponge-symbiont produced compounds. Accordingly, a metagenomic analysis of the Japanese marine sponge Discodermia calyx has resulted in the identification of a hybrid type I polyketide synthase-nonribosomal peptide synthetase gene (kas). Bioinformatic analysis of the gene product suggested its involvement in the biosynthesis of kasumigamide, a tetrapeptide originally isolated from freshwater free-living cyanobacterium Microcystis aeruginosa NIES-87. Subsequent investigation of the sponge metabolic profile revealed the presence of kasumigamide in the sponge extract. The kasumigamide producing bacterium was identified as an 'Entotheonella' sp. Moreover, an in silico analysis of kas gene homologs uncovered the presence of kas family genes in two additional bacteria from different phyla. The production of kasumigamide by distantly related multiple bacterial strains implicates horizontal gene transfer and raises the potential for a wider distribution across other bacterial groups.

Issues on machine learning for prediction of classes among molecular sequences of plants and animals

NASA Astrophysics Data System (ADS)

Stehlik, Milan; Pant, Bhasker; Pant, Kumud; Pardasani, K. R.

2012-09-01

Nowadays major laboratories of the world are turning towards in-silico experimentation due to their ease, reproducibility and accuracy. The ethical issues concerning wet lab experimentations are also minimal in in-silico experimentations. But before we turn fully towards dry lab simulations it is necessary to understand the discrepancies and bottle necks involved with dry lab experimentations. It is necessary before reporting any result using dry lab simulations to perform in-depth statistical analysis of the data. Keeping same in mind here we are presenting a collaborative effort to correlate findings and results of various machine learning algorithms and checking underlying regressions and mutual dependencies so as to develop an optimal classifier and predictors.

Discovering Novel Alternaria solani Succinate Dehydrogenase Inhibitors by In Silico Modeling and Virtual Screening Strategies to Combat Early Blight

NASA Astrophysics Data System (ADS)

Iftikhar, Sehrish; Shahid, Ahmad A.; Halim, Sobia A.; Wolters, Pieter J.; Vleeshouwers, Vivianne G. A. A.; Khan, Ajmal; Al-Harrasi, Ahmed; Ahmad, Shahbaz

2017-11-01

Alternaria blight is an important foliage disease caused by Alternaria solani. The enzyme Succinate dehydrogenase (SDH) is a potential drug target because of its role in tricarboxylic acid cycle. Hence targeting Alternaria solani SDH enzyme could be efficient tool to design novel fungicides against A. solani. We employed computational methodologies to design new SDH inhibitors using homology modeling; pharmacophore modeling and structure based virtual screening protocol. The three dimensional SDH model showed good stereo-chemical and structural properties. Based on virtual screening results twelve commercially available compounds were purchased and tested in vitro and in vivo. The compounds were found to inhibit mycelial growth of A. solani. Moreover in vitro trials showed that inhibitory effects were enhanced with increase in concentrations. Similarly increased disease control was observed in pre-treated potato tubers. Hence the applied in silico strategy led us to identify new and novel fungicides.

Discovering Novel Alternaria solani Succinate Dehydrogenase Inhibitors by in Silico Modeling and Virtual Screening Strategies to Combat Early Blight

PubMed Central

Iftikhar, Sehrish; Shahid, Ahmad A.; Halim, Sobia A.; Wolters, Pieter J.; Vleeshouwers, Vivianne G. A. A.; Khan, Ajmal; Al-Harrasi, Ahmed; Ahmad, Shahbaz

2017-01-01

Alternaria blight is an important foliage disease caused by Alternaria solani. The enzyme Succinate dehydrogenase (SDH) is a potential drug target because of its role in tricarboxylic acid cycle. Hence targeting Alternaria solani SDH enzyme could be efficient tool to design novel fungicides against A. solani. We employed computational methodologies to design new SDH inhibitors using homology modeling; pharmacophore modeling and structure based virtual screening. The three dimensional SDH model showed good stereo-chemical and structural properties. Based on virtual screening results twelve commercially available compounds were purchased and tested in vitro and in vivo. The compounds were found to inhibit mycelial growth of A. solani. Moreover in vitro trials showed that inhibitory effects were enhanced with increase in concentrations. Similarly increased disease control was observed in pre-treated potato tubers. Hence the applied in silico strategy led us to identify novel fungicides. PMID:29204422

A community computational challenge to predict the activity of pairs of compounds.

PubMed

Bansal, Mukesh; Yang, Jichen; Karan, Charles; Menden, Michael P; Costello, James C; Tang, Hao; Xiao, Guanghua; Li, Yajuan; Allen, Jeffrey; Zhong, Rui; Chen, Beibei; Kim, Minsoo; Wang, Tao; Heiser, Laura M; Realubit, Ronald; Mattioli, Michela; Alvarez, Mariano J; Shen, Yao; Gallahan, Daniel; Singer, Dinah; Saez-Rodriguez, Julio; Xie, Yang; Stolovitzky, Gustavo; Califano, Andrea

2014-12-01

Recent therapeutic successes have renewed interest in drug combinations, but experimental screening approaches are costly and often identify only small numbers of synergistic combinations. The DREAM consortium launched an open challenge to foster the development of in silico methods to computationally rank 91 compound pairs, from the most synergistic to the most antagonistic, based on gene-expression profiles of human B cells treated with individual compounds at multiple time points and concentrations. Using scoring metrics based on experimental dose-response curves, we assessed 32 methods (31 community-generated approaches and SynGen), four of which performed significantly better than random guessing. We highlight similarities between the methods. Although the accuracy of predictions was not optimal, we find that computational prediction of compound-pair activity is possible, and that community challenges can be useful to advance the field of in silico compound-synergy prediction.

Identification and in silico prediction of metabolites of the model compound, tebufenozide by human CYP3A4 and CYP2C19.

PubMed

Shirotani, Naoki; Togawa, Moe; Ikushiro, Shinichi; Sakaki, Toshiyuki; Harada, Toshiyuki; Miyagawa, Hisashi; Matsui, Masayoshi; Nagahori, Hirohisa; Mikata, Kazuki; Nishioka, Kazuhiko; Hirai, Nobuhiro; Akamatsu, Miki

2015-10-15

The metabolites of tebufenozide, a model compound, formed by the yeast-expressed human CYP3A4 and CYP2C19 were identified to clarify the substrate recognition mechanism of the human cytochrome P450 (CYP) isozymes. We then determined whether tebufenozide metabolites may be predicted in silico. Hydrogen abstraction energies were calculated with the density functional theory method B3LYP/6-31G(∗). A docking simulation was performed using FRED software. Several alkyl sites of tebufenozide were hydroxylated by CYP3A4 whereas only one site was modified by CYP2C19. The accessibility of each site of tebufenozide to the reaction center of CYP enzymes and the susceptibility of each hydrogen atom for metabolism by CYP enzymes were evaluated by a docking simulation and hydrogen abstraction energy estimation, respectively. Copyright © 2015 Elsevier Ltd. All rights reserved.

Visualization and Analysis of MiRNA-Targets Interactions Networks.

PubMed

León, Luis E; Calligaris, Sebastián D

2017-01-01

MicroRNAs are a class of small, noncoding RNA molecules of 21-25 nucleotides in length that regulate the gene expression by base-pairing with the target mRNAs, mainly leading to down-regulation or repression of the target genes. MicroRNAs are involved in diverse regulatory pathways in normal and pathological conditions. In this context, it is highly important to identify the targets of specific microRNA in order to understand the mechanism of its regulation and consequently its involvement in disease. However, the microRNA target identification is experimentally laborious and time-consuming. The in silico prediction of microRNA targets is an extremely useful approach because you can identify potential mRNA targets, reduce the number of possibilities and then, validate a few microRNA-mRNA interactions in an in vitro experimental model. In this chapter, we describe, in a simple way, bioinformatics guidelines to use miRWalk database and Cytoscape software for analyzing microRNA-mRNA interactions through their visualization as a network.

Engineering of carboligase activity reaction in Candida glabrata for acetoin production.

PubMed

Li, Shubo; Xu, Nan; Liu, Liming; Chen, Jian

2014-03-01

Utilization of Candida glabrata overproducing pyruvate is a promising strategy for high-level acetoin production. Based on the known regulatory and metabolic information, acetaldehyde and thiamine were fed to identify the key nodes of carboligase activity reaction (CAR) pathway and provide a direction for engineering C. glabrata. Accordingly, alcohol dehydrogenase, acetaldehyde dehydrogenase, pyruvate decarboxylase, and butanediol dehydrogenase were selected to be manipulated for strengthening the CAR pathway. Following the rational metabolic engineering, the engineered strain exhibited increased acetoin biosynthesis (2.24 g/L). In addition, through in silico simulation and redox balance analysis, NADH was identified as the key factor restricting higher acetoin production. Correspondingly, after introduction of NADH oxidase, the final acetoin production was further increased to 7.33 g/L. By combining the rational metabolic engineering and cofactor engineering, the acetoin-producing C. glabrata was improved stepwise, opening a novel pathway for rational development of microorganisms for bioproduction. Copyright © 2013. Published by Elsevier Inc.

DNA microarray-based detection and identification of Burkholderia mallei, Burkholderia pseudomallei and Burkholderia spp.

PubMed

Schmoock, Gernot; Ehricht, Ralf; Melzer, Falk; Rassbach, Astrid; Scholz, Holger C; Neubauer, Heinrich; Sachse, Konrad; Mota, Rinaldo Aparecido; Saqib, Muhammad; Elschner, Mandy

2009-01-01

We developed a rapid oligonucleotide microarray assay based on genetic markers for the accurate identification and differentiation of Burkholderia (B.) mallei and Burkholderia pseudomallei, the agents of glanders and melioidosis, respectively. These two agents were clearly identified using at least 4 independent genetic markers including 16S rRNA gene, fliC, motB and also by novel species-specific target genes, identified by in silico sequence analysis. Specific hybridization signal profiles allowed the detection and differentiation of up to 10 further Burkholderia spp., including the closely related species Burkholderia thailandensis and Burkholderia-like agents, such as Burkholderia cepacia, Burkholderia cenocepacia, Burkholderia vietnamiensis, Burkholderia ambifaria, and Burkholderia gladioli, which are often associated with cystic fibrosis (CF) lung disease. The assay was developed using the easy-to-handle and economical ArrayTube (AT) platform. A representative strain panel comprising 44 B. mallei, 32 B. pseudomallei isolates, and various Burkholderia type strains were examined to validate the test. Assay specificity was determined by examination of 40 non-Burkholderia strains.

The essential and downstream common proteins of amyotrophic lateral sclerosis: A protein-protein interaction network analysis.

PubMed

Mao, Yimin; Kuo, Su-Wei; Chen, Le; Heckman, C J; Jiang, M C

2017-01-01

Amyotrophic Lateral Sclerosis (ALS) is a devastative neurodegenerative disease characterized by selective loss of motoneurons. While several breakthroughs have been made in identifying ALS genetic defects, the detailed molecular mechanisms are still unclear. These genetic defects involve in numerous biological processes, which converge to a common destiny: motoneuron degeneration. In addition, the common comorbid Frontotemporal Dementia (FTD) further complicates the investigation of ALS etiology. In this study, we aimed to explore the protein-protein interaction network built on known ALS-causative genes to identify essential proteins and common downstream proteins between classical ALS and ALS+FTD (classical ALS + ALS/FTD) groups. The results suggest that classical ALS and ALS+FTD share similar essential protein set (VCP, FUS, TDP-43 and hnRNPA1) but have distinctive functional enrichment profiles. Thus, disruptions to these essential proteins might cause motoneuron susceptible to cellular stresses and eventually vulnerable to proteinopathies. Moreover, we identified a common downstream protein, ubiquitin-C, extensively interconnected with ALS-causative proteins (22 out of 24) which was not linked to ALS previously. Our in silico approach provides the computational background for identifying ALS therapeutic targets, and points out the potential downstream common ground of ALS-causative mutations.

Systematic identification and analysis of frequent gene fusion events in metabolic pathways

DOE Office of Scientific and Technical Information (OSTI.GOV)

Henry, Christopher S.; Lerma-Ortiz, Claudia; Gerdes, Svetlana Y.

Here, gene fusions are the most powerful type of in silico-derived functional associations. However, many fusion compilations were made when <100 genomes were available, and algorithms for identifying fusions need updating to handle the current avalanche of sequenced genomes. The availability of a large fusion dataset would help probe functional associations and enable systematic analysis of where and why fusion events occur. As a result, here we present a systematic analysis of fusions in prokaryotes. We manually generated two training sets: (i) 121 fusions in the model organism Escherichia coli; (ii) 131 fusions found in B vitamin metabolism. These setsmore » were used to develop a fusion prediction algorithm that captured the training set fusions with only 7 % false negatives and 50 % false positives, a substantial improvement over existing approaches. This algorithm was then applied to identify 3.8 million potential fusions across 11,473 genomes. The results of the analysis are available in a searchable database. A functional analysis identified 3,000 reactions associated with frequent fusion events and revealed areas of metabolism where fusions are particularly prevalent. In conclusion, customary definitions of fusions were shown to be ambiguous, and a stricter one was proposed. Exploring the genes participating in fusion events showed that they most commonly encode transporters, regulators, and metabolic enzymes. The major rationales for fusions between metabolic genes appear to be overcoming pathway bottlenecks, avoiding toxicity, controlling competing pathways, and facilitating expression and assembly of protein complexes. Finally, our fusion dataset provides powerful clues to decipher the biological activities of domains of unknown function.« less

Systematic identification and analysis of frequent gene fusion events in metabolic pathways

DOE PAGES

Henry, Christopher S.; Lerma-Ortiz, Claudia; Gerdes, Svetlana Y.; ...

2016-06-24

Here, gene fusions are the most powerful type of in silico-derived functional associations. However, many fusion compilations were made when <100 genomes were available, and algorithms for identifying fusions need updating to handle the current avalanche of sequenced genomes. The availability of a large fusion dataset would help probe functional associations and enable systematic analysis of where and why fusion events occur. As a result, here we present a systematic analysis of fusions in prokaryotes. We manually generated two training sets: (i) 121 fusions in the model organism Escherichia coli; (ii) 131 fusions found in B vitamin metabolism. These setsmore » were used to develop a fusion prediction algorithm that captured the training set fusions with only 7 % false negatives and 50 % false positives, a substantial improvement over existing approaches. This algorithm was then applied to identify 3.8 million potential fusions across 11,473 genomes. The results of the analysis are available in a searchable database. A functional analysis identified 3,000 reactions associated with frequent fusion events and revealed areas of metabolism where fusions are particularly prevalent. In conclusion, customary definitions of fusions were shown to be ambiguous, and a stricter one was proposed. Exploring the genes participating in fusion events showed that they most commonly encode transporters, regulators, and metabolic enzymes. The major rationales for fusions between metabolic genes appear to be overcoming pathway bottlenecks, avoiding toxicity, controlling competing pathways, and facilitating expression and assembly of protein complexes. Finally, our fusion dataset provides powerful clues to decipher the biological activities of domains of unknown function.« less

Next-generation sequencing for identification of candidate genes for Fusarium wilt and sterility mosaic disease in pigeonpea (Cajanus cajan).

PubMed

Singh, Vikas K; Khan, Aamir W; Saxena, Rachit K; Kumar, Vinay; Kale, Sandip M; Sinha, Pallavi; Chitikineni, Annapurna; Pazhamala, Lekha T; Garg, Vanika; Sharma, Mamta; Sameer Kumar, Chanda Venkata; Parupalli, Swathi; Vechalapu, Suryanarayana; Patil, Suyash; Muniswamy, Sonnappa; Ghanta, Anuradha; Yamini, Kalinati Narasimhan; Dharmaraj, Pallavi Subbanna; Varshney, Rajeev K

2016-05-01

To map resistance genes for Fusarium wilt (FW) and sterility mosaic disease (SMD) in pigeonpea, sequencing-based bulked segregant analysis (Seq-BSA) was used. Resistant (R) and susceptible (S) bulks from the extreme recombinant inbred lines of ICPL 20096 × ICPL 332 were sequenced. Subsequently, SNP index was calculated between R- and S-bulks with the help of draft genome sequence and reference-guided assembly of ICPL 20096 (resistant parent). Seq-BSA has provided seven candidate SNPs for FW and SMD resistance in pigeonpea. In parallel, four additional genotypes were re-sequenced and their combined analysis with R- and S-bulks has provided a total of 8362 nonsynonymous (ns) SNPs. Of 8362 nsSNPs, 60 were found within the 2-Mb flanking regions of seven candidate SNPs identified through Seq-BSA. Haplotype analysis narrowed down to eight nsSNPs in seven genes. These eight nsSNPs were further validated by re-sequencing 11 genotypes that are resistant and susceptible to FW and SMD. This analysis revealed association of four candidate nsSNPs in four genes with FW resistance and four candidate nsSNPs in three genes with SMD resistance. Further, In silico protein analysis and expression profiling identified two most promising candidate genes namely C.cajan_01839 for SMD resistance and C.cajan_03203 for FW resistance. Identified candidate genomic regions/SNPs will be useful for genomics-assisted breeding in pigeonpea. © 2015 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Using argument notation to engineer biological simulations with increased confidence

PubMed Central

Alden, Kieran; Andrews, Paul S.; Polack, Fiona A. C.; Veiga-Fernandes, Henrique; Coles, Mark C.; Timmis, Jon

2015-01-01

The application of computational and mathematical modelling to explore the mechanics of biological systems is becoming prevalent. To significantly impact biological research, notably in developing novel therapeutics, it is critical that the model adequately represents the captured system. Confidence in adopting in silico approaches can be improved by applying a structured argumentation approach, alongside model development and results analysis. We propose an approach based on argumentation from safety-critical systems engineering, where a system is subjected to a stringent analysis of compliance against identified criteria. We show its use in examining the biological information upon which a model is based, identifying model strengths, highlighting areas requiring additional biological experimentation and providing documentation to support model publication. We demonstrate our use of structured argumentation in the development of a model of lymphoid tissue formation, specifically Peyer's Patches. The argumentation structure is captured using Artoo (www.york.ac.uk/ycil/software/artoo), our Web-based tool for constructing fitness-for-purpose arguments, using a notation based on the safety-critical goal structuring notation. We show how argumentation helps in making the design and structured analysis of a model transparent, capturing the reasoning behind the inclusion or exclusion of each biological feature and recording assumptions, as well as pointing to evidence supporting model-derived conclusions. PMID:25589574

Using argument notation to engineer biological simulations with increased confidence.

PubMed

Alden, Kieran; Andrews, Paul S; Polack, Fiona A C; Veiga-Fernandes, Henrique; Coles, Mark C; Timmis, Jon

2015-03-06

The application of computational and mathematical modelling to explore the mechanics of biological systems is becoming prevalent. To significantly impact biological research, notably in developing novel therapeutics, it is critical that the model adequately represents the captured system. Confidence in adopting in silico approaches can be improved by applying a structured argumentation approach, alongside model development and results analysis. We propose an approach based on argumentation from safety-critical systems engineering, where a system is subjected to a stringent analysis of compliance against identified criteria. We show its use in examining the biological information upon which a model is based, identifying model strengths, highlighting areas requiring additional biological experimentation and providing documentation to support model publication. We demonstrate our use of structured argumentation in the development of a model of lymphoid tissue formation, specifically Peyer's Patches. The argumentation structure is captured using Artoo (www.york.ac.uk/ycil/software/artoo), our Web-based tool for constructing fitness-for-purpose arguments, using a notation based on the safety-critical goal structuring notation. We show how argumentation helps in making the design and structured analysis of a model transparent, capturing the reasoning behind the inclusion or exclusion of each biological feature and recording assumptions, as well as pointing to evidence supporting model-derived conclusions.

No novel, high penetrant gene might remain to be found in Japanese patients with unknown MODY.

PubMed

Horikawa, Yukio; Hosomichi, Kazuyoshi; Enya, Mayumi; Ishiura, Hiroyuki; Suzuki, Yutaka; Tsuji, Shoji; Sugano, Sumio; Inoue, Ituro; Takeda, Jun

2018-07-01

MODY 5 and 6 have been shown to be low-penetrant MODYs. As the genetic background of unknown MODY is assumed to be similar, a new analytical strategy is applied here to elucidate genetic predispositions to unknown MODY. We examined to find whether there are major MODY gene loci remaining to be identified using SNP linkage analysis in Japanese. Whole-exome sequencing was performed with seven families with typical MODY. Candidates for novel MODY genes were examined combined with in silico network analysis. Some peaks were found only in either parametric or non-parametric analysis; however, none of these peaks showed a LOD score greater than 3.7, which is approved to be the significance threshold of evidence for linkage. Exome sequencing revealed that three mutated genes were common among 3 families and 42 mutated genes were common in two families. Only one of these genes, MYO5A, having rare amino acid mutations p.R849Q and p.V1601G, was involved in the biological network of known MODY genes through the intermediary of the INS. Although only one promising candidate gene, MYO5A, was identified, no novel, high penetrant MODY genes might remain to be found in Japanese MODY.

Mathematical methods to analysis of topology, functional variability and evolution of metabolic systems based on different decomposition concepts.

PubMed

Mrabet, Yassine; Semmar, Nabil

2010-05-01

Complexity of metabolic systems can be undertaken at different scales (metabolites, metabolic pathways, metabolic network map, biological population) and under different aspects (structural, functional, evolutive). To analyse such a complexity, metabolic systems need to be decomposed into different components according to different concepts. Four concepts are presented here consisting in considering metabolic systems as sets of metabolites, chemical reactions, metabolic pathways or successive processes. From a metabolomic dataset, such decompositions are performed using different mathematical methods including correlation, stiochiometric, ordination, classification, combinatorial and kinetic analyses. Correlation analysis detects and quantifies affinities/oppositions between metabolites. Stoichiometric analysis aims to identify the organisation of a metabolic network into different metabolic pathways on the hand, and to quantify/optimize the metabolic flux distribution through the different chemical reactions of the system. Ordination and classification analyses help to identify different metabolic trends and their associated metabolites in order to highlight chemical polymorphism representing different variability poles of the metabolic system. Then, metabolic processes/correlations responsible for such a polymorphism can be extracted in silico by combining metabolic profiles representative of different metabolic trends according to a weighting bootstrap approach. Finally evolution of metabolic processes in time can be analysed by different kinetic/dynamic modelling approaches.

Notch ligand Delta-like 1 as a novel molecular target in childhood neuroblastoma.

PubMed

Bettinsoli, P; Ferrari-Toninelli, G; Bonini, S A; Prandelli, C; Memo, M

2017-05-19

Neuroblastoma is the most common extracranial solid malignancy in childhood, responsible for 15% of all pediatric cancer deaths. It is an heterogeneous disease that does not always respond to classical therapy; so the identification of new and specific molecular targets to improve existing therapy is needed. We have previously demonstrated the involvement of the Notch pathway in the onset and progression of neuroblastoma. In this study we further investigated the role of Notch signaling and identified Delta-like 1 (DLL1) as a novel molecular target in neuroblastoma cells with a high degree of MYCN amplification, which is a major oncogenic driver in neuroblastoma. The possibility to act on DLL1 expression levels by using microRNAs (miRNAs) was assessed. DLL1 mRNA and protein expression levels were measured in three different neuroblastoma cell lines using quantitative real-time PCR and Western Blot analysis, respectively. Activation of the Notch pathway as a result of increased levels of DLL1 was analyzed by Immunofluorescence and Western Blot methods. In silico tools revealed the possibility to act on DLL1 expression levels with miRNAs, in particular with the miRNA-34 family. Neuroblastoma cells were transfected with miRNA-34 family members, and the effect of miRNAs transfection on DLL1 mRNA expression levels, on cell differentiation, proliferation and apoptosis was measured. In this study, the DLL1 ligand was identified as the Notch pathway component highly expressed in neuroblastoma cells with MYCN amplification. In silico analysis demonstrated that DLL1 is one of the targets of miRNA-34 family members that maps on chromosome regions that are frequently deregulated or deleted in neuroblastoma. We studied the possibility to use miRNAs to target DLL1. Among all miRNA-34 family members, miRNA-34b is able to significantly downregulate DLL1 mRNA expression levels, to arrest cell proliferation and to induce neuronal differentiation in malignant neuroblastoma cells. Targeted therapies have emerged as new strategies for cancer treatment. This study identified the Notch ligand DLL1 as a novel and attractive molecular target in childhood neuroblastoma and its results could help to devise a targeted therapy using miRNAs.

In silico aided thoughts on mitochondrial vitamin C transport.

PubMed

Szarka, András; Balogh, Tibor

2015-01-21

The huge demand of mitochondria as the quantitatively most important sources of ROS in the majority of heterotrophic cells for vitamin C is indisputable. The reduced form of the vitamin, l-ascorbic acid, is imported by an active mechanism requiring two sodium-dependent vitamin C transporters (SVCT1 and SVCT2). The oxidized form, dehydroascorbate is taken up by different members of the GLUT family. Because of the controversial experimental results the picture on mitochondrial vitamin C transport became quite obscure by the spring of 2014. Thus in silico prediction tools were applied in aid of the support of in vitro and in vivo results. The role of GLUT1 as a mitochondrial dehydroascorbate transporter could be reinforced by in silico predictions however the mitochondrial presence of GLUT10 is not likely since this transport protein got far the lowest mitochondrial localization scores. Furthermore the possible roles of GLUT9 and 11 in mitochondrial vitamin C transport can be proposed leastwise on the base of their computational localization analysis. In good concordance with the newest experimental observations on SVCT2 the mitochondrial presence of this transporter could also be supported by the computational prediction tools. Copyright © 2014 Elsevier Ltd. All rights reserved.

In silico peptide prediction for antibody generation to recognize 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) in genetically modified organisms.

PubMed

Marani, Mariela M; Costa, Joana; Mafra, Isabel; Oliveira, Maria Beatriz P P; Camperi, Silvia A; Leite, José Roberto de Souza Almeida

2015-03-01

For the prospective immunorecognition of 5-enolpyruvylshikimate-3-phosphate synthase (CP4-EPSPS) as a biomarker protein expressed by transgenic soybean, an extensive in silico evaluation of the referred protein was performed. The main objective of this study was the selection of a set of peptides that could function as potential immunogens for the production of novel antibodies against CP4-EPSPS protein. For this purpose, the protein was in silico cleaved with trypsin/chymotrypsin and the resultant peptides were extensively analyzed for further selection of the best candidates for antibody production. The analysis enabled the successful proposal of four peptides with potential immunogenicity for their future use as screening biomarkers of genetically modified organisms. To our knowledge, this is the first attempt to select and define potential linear epitopes for the immunization of animals and, subsequently, to generate adequate antibodies for CP4-EPSPS recognition. The present work will be followed by the synthesis of the candidate peptides to be incubated in animals for antibody generation and potential applicability for the development of an immunosensor for CP4-EPSPS detection. © 2015 Wiley Periodicals, Inc.

Computational analysis of multimorbidity between asthma, eczema and rhinitis

PubMed Central

Aguilar, Daniel; Pinart, Mariona; Koppelman, Gerard H.; Saeys, Yvan; Nawijn, Martijn C.; Postma, Dirkje S.; Akdis, Mübeccel; Auffray, Charles; Ballereau, Stéphane; Benet, Marta; García-Aymerich, Judith; González, Juan Ramón; Guerra, Stefano; Keil, Thomas; Kogevinas, Manolis; Lambrecht, Bart; Lemonnier, Nathanael; Melen, Erik; Sunyer, Jordi; Valenta, Rudolf; Valverde, Sergi; Wickman, Magnus; Bousquet, Jean; Oliva, Baldo; Antó, Josep M.

2017-01-01

Background The mechanisms explaining the co-existence of asthma, eczema and rhinitis (allergic multimorbidity) are largely unknown. We investigated the mechanisms underlying multimorbidity between three main allergic diseases at a molecular level by identifying the proteins and cellular processes that are common to them. Methods An in silico study based on computational analysis of the topology of the protein interaction network was performed in order to characterize the molecular mechanisms of multimorbidity of asthma, eczema and rhinitis. As a first step, proteins associated to either disease were identified using data mining approaches, and their overlap was calculated. Secondly, a functional interaction network was built, allowing to identify cellular pathways involved in allergic multimorbidity. Finally, a network-based algorithm generated a ranked list of newly predicted multimorbidity-associated proteins. Results Asthma, eczema and rhinitis shared a larger number of associated proteins than expected by chance, and their associated proteins exhibited a significant degree of interconnectedness in the interaction network. There were 15 pathways involved in the multimorbidity of asthma, eczema and rhinitis, including IL4 signaling and GATA3-related pathways. A number of proteins potentially associated to these multimorbidity processes were also obtained. Conclusions These results strongly support the existence of an allergic multimorbidity cluster between asthma, eczema and rhinitis, and suggest that type 2 signaling pathways represent a relevant multimorbidity mechanism of allergic diseases. Furthermore, we identified new candidates contributing to multimorbidity that may assist in identifying new targets for multimorbid allergic diseases. PMID:28598986

Computational analysis of multimorbidity between asthma, eczema and rhinitis.

PubMed

Aguilar, Daniel; Pinart, Mariona; Koppelman, Gerard H; Saeys, Yvan; Nawijn, Martijn C; Postma, Dirkje S; Akdis, Mübeccel; Auffray, Charles; Ballereau, Stéphane; Benet, Marta; García-Aymerich, Judith; González, Juan Ramón; Guerra, Stefano; Keil, Thomas; Kogevinas, Manolis; Lambrecht, Bart; Lemonnier, Nathanael; Melen, Erik; Sunyer, Jordi; Valenta, Rudolf; Valverde, Sergi; Wickman, Magnus; Bousquet, Jean; Oliva, Baldo; Antó, Josep M

2017-01-01

The mechanisms explaining the co-existence of asthma, eczema and rhinitis (allergic multimorbidity) are largely unknown. We investigated the mechanisms underlying multimorbidity between three main allergic diseases at a molecular level by identifying the proteins and cellular processes that are common to them. An in silico study based on computational analysis of the topology of the protein interaction network was performed in order to characterize the molecular mechanisms of multimorbidity of asthma, eczema and rhinitis. As a first step, proteins associated to either disease were identified using data mining approaches, and their overlap was calculated. Secondly, a functional interaction network was built, allowing to identify cellular pathways involved in allergic multimorbidity. Finally, a network-based algorithm generated a ranked list of newly predicted multimorbidity-associated proteins. Asthma, eczema and rhinitis shared a larger number of associated proteins than expected by chance, and their associated proteins exhibited a significant degree of interconnectedness in the interaction network. There were 15 pathways involved in the multimorbidity of asthma, eczema and rhinitis, including IL4 signaling and GATA3-related pathways. A number of proteins potentially associated to these multimorbidity processes were also obtained. These results strongly support the existence of an allergic multimorbidity cluster between asthma, eczema and rhinitis, and suggest that type 2 signaling pathways represent a relevant multimorbidity mechanism of allergic diseases. Furthermore, we identified new candidates contributing to multimorbidity that may assist in identifying new targets for multimorbid allergic diseases.

Predicted MHC peptide binding promiscuity explains MHC class I 'hotspots' of antigen presentation defined by mass spectrometry eluted ligand data.

PubMed

Jappe, Emma Christine; Kringelum, Jens; Trolle, Thomas; Nielsen, Morten

2018-02-15

Peptides that bind to and are presented by MHC class I and class II molecules collectively make up the immunopeptidome. In the context of vaccine development, an understanding of the immunopeptidome is essential, and much effort has been dedicated to its accurate and cost-effective identification. Current state-of-the-art methods mainly comprise in silico tools for predicting MHC binding, which is strongly correlated with peptide immunogenicity. However, only a small proportion of the peptides that bind to MHC molecules are, in fact, immunogenic, and substantial work has been dedicated to uncovering additional determinants of peptide immunogenicity. In this context, and in light of recent advancements in mass spectrometry (MS), the existence of immunological hotspots has been given new life, inciting the hypothesis that hotspots are associated with MHC class I peptide immunogenicity. We here introduce a precise terminology for defining these hotspots and carry out a systematic analysis of MS and in silico predicted hotspots. We find that hotspots defined from MS data are largely captured by peptide binding predictions, enabling their replication in silico. This leads us to conclude that hotspots, to a great degree, are simply a result of promiscuous HLA binding, which disproves the hypothesis that the identification of hotspots provides novel information in the context of immunogenic peptide prediction. Furthermore, our analyses demonstrate that the signal of ligand processing, although present in the MS data, has very low predictive power to discriminate between MS and in silico defined hotspots. © 2018 John Wiley & Sons Ltd.

High-resolution chromatography/time-of-flight MSE with in silico data mining is an information-rich approach to reactive metabolite screening.

PubMed

Barbara, Joanna E; Castro-Perez, Jose M

2011-10-30

Electrophilic reactive metabolite screening by liquid chromatography/mass spectrometry (LC/MS) is commonly performed during drug discovery and early-stage drug development. Accurate mass spectrometry has excellent utility in this application, but sophisticated data processing strategies are essential to extract useful information. Herein, a unified approach to glutathione (GSH) trapped reactive metabolite screening with high-resolution LC/TOF MS(E) analysis and drug-conjugate-specific in silico data processing was applied to rapid analysis of test compounds without the need for stable- or radio-isotope-labeled trapping agents. Accurate mass defect filtering (MDF) with a C-heteroatom dealkylation algorithm dynamic with mass range was compared to linear MDF and shown to minimize false positive results. MS(E) data-filtering, time-alignment and data mining post-acquisition enabled detection of 53 GSH conjugates overall formed from 5 drugs. Automated comparison of sample and control data in conjunction with the mass defect filter enabled detection of several conjugates that were not evident with mass defect filtering alone. High- and low-energy MS(E) data were time-aligned to generate in silico product ion spectra which were successfully applied to structural elucidation of detected GSH conjugates. Pseudo neutral loss and precursor ion chromatograms derived post-acquisition demonstrated 50.9% potential coverage, at best, of the detected conjugates by any individual precursor or neutral loss scan type. In contrast with commonly applied neutral loss and precursor-based techniques, the unified method has the advantage of applicability across different classes of GSH conjugates. The unified method was also successfully applied to cyanide trapping analysis and has potential for application to alternate trapping agents. Copyright © 2011 John Wiley & Sons, Ltd.

Isolation and in silico analysis of Fe-superoxide dismutase in the cyanobacterium Nostoc commune.

PubMed

Kesheri, Minu; Kanchan, Swarna; Richa; Sinha, Rajeshwar P

2014-12-15

Cyanobacteria are known to endure various stress conditions due to the inbuilt potential for oxidative stress alleviation owing to the presence of an array of antioxidants. The present study shows that Antarctic cyanobacterium Nostoc commune possesses two antioxidative enzymes viz., superoxide dismutase (SOD) and catalase that jointly cope with environmental stresses prevailing at its natural habitat. Native-PAGE analysis illustrates the presence of a single prominent isoform recognized as Fe-SOD and three distinct isoforms of catalase. The protein sequence of Fe-SOD in N. commune retrieved from NCBI protein sequence database was used for in silico analysis. 3D structure of N. commune was predicted by comparative modeling using MODELLER 9v11. Further, this model was validated for its quality by Ramachandran plot, ERRAT, Verify 3D and ProSA-web which revealed good structure quality of the model. Multiple sequence alignment showed high conservation in N and C-terminal domain regions along with all metal binding positions in Fe-SOD which were also found to be highly conserved in all 28 cyanobacterial species under study, including N. commune. In silico prediction of isoelectric point and molecular weight of Fe-SOD was found to be 5.48 and 22,342.98Da respectively. The phylogenetic tree revealed that among 28 cyanobacterial species, Fe-SOD in N. commune was the closest evolutionary homolog of Fe-SOD in Nostoc punctiforme as evident by strong bootstrap value. Thus, N. commune may serve as a good biological model for studies related to survival of life under extreme conditions prevailing at the Antarctic region. Moreover cyanobacteria may be exploited for biochemical and biotechnological applications of enzymatic antioxidants. Copyright © 2014 Elsevier B.V. All rights reserved.

In silico analysis of high affinity potassium transporter (HKT) isoforms in different plants

PubMed Central

2014-01-01

Background High affinity potassium transporters (HKTs) are located in the plasma membrane of the vessels and have significant influence on salt tolerance in some plants. They exclude Na+ from the parenchyma cells to reduce Na+ concentration. Despite many studies, the underlying regulatory mechanisms and the exact functions of HKTs within different genomic backgrounds are relatively unknown. In this study, various bioinformatics techniques, including promoter analysis, identification of HKT-surrounding genes, and construction of gene networks, were applied to investigate the HKT regulatory mechanism. Results Promoter analysis showed that rice HKTs carry ABA response elements. Additionally, jasmonic acid response elements were detected on promoter region of TmHKT1;5. In silico synteny highlighted several unknown and new loci near rice, Arabidopsis thaliana and Physcomitrella patent HKTs, which may play a significant role in salt stress tolerance in concert with HKTs. Gene network prediction unravelled that crosstalk between jasmonate and ethylene reduces AtHKT1;1 expression. Furthermore, antiporter and transferase proteins were found in AtHKT1;1 gene network. Interestingly, regulatory elements on the promoter region of HKT in wild genotype (TmHKT1;5) were more frequent and variable than the ones in cultivated wheat (TaHKT1;5) which provides the possibility of rapid response and better understanding of environmental conditions for wild genotype. Conclusion Detecting ABA and jasmonic acid response elements on promoter regions of HKTs provide valuable clues on underlying regulatory mechanisms of HKTs. In silico synteny and pathway discovery indicated several candidates which act in concert with HKTs in stress condition. We highlighted different arrangement of regulatory elements on promoter region of wild wheat (TmHKT1;5) compared to bread wheat (TaHKT1;5) in this study. PMID:25279141

Using RNA-sequencing and in silico subtraction to identify resistance gene analog markers for Lr16 in wheat

USDA-ARS?s Scientific Manuscript database

Leaf rust, caused by Puccinia triticina Eriks., is one of the most widespread diseases of wheat worldwide and breeding for resistance is one of the most effective methods of control. Lr16 is a wheat leaf rust resistance gene that provides resistance at both the seedling and adult stages. Simple s...

Using diverse U.S. beef cattle genomes to identify missense mutations in EPAS1, a gene associated with high-altitude pulmonary hypertension

USDA-ARS?s Scientific Manuscript database

The availability of whole genome sequence (WGS) data has made it possible to discover protein variants in silico. However, bovine WGS databases comprised of related influential sires from relatively few breeds tend to under represent the breadth of genetic diversity in U.S. beef cattle. Thus, our ...

Cholinesterase inhibitory, anti-amyloidogenic and neuroprotective effect of the medicinal plant Grewia tiliaefolia - An in vitro and in silico study.

PubMed

Sheeja Malar, Dicson; Beema Shafreen, Rajamohamed; Karutha Pandian, Shunmugiah; Pandima Devi, Kasi

2017-12-01

Grewia tiliaefolia Vahl. (Tiliaceae) is a sub-tropical plant used as an indigenous medicine in India. However, its efficacy has not been evaluated against Alzheimer's disease. The objective of this study is to evaluate cholinesterase inhibitory, anti-aggregation and neuroprotective activity of G. tiliaefolia. Grewia tiliaefolia leaves were collected from Eastern Ghats region, India, and subjected to successive extraction (petroleum ether, chloroform, ethyl acetate, methanol and water). The extracts were subjected to in vitro antioxidant, anticholinesterase and anti-aggregation assays. The active methanol extract (MEGT) was separated using column chromatography. LC-MS analysis was done and the obtained compounds were docked against acetylcholinesterase (AChE) enzyme to identify the active component. Antioxidant assays demonstrated that the MEGT showed significant free radical scavenging activity at the IC 50 value of 71.5 ± 1.12 μg/mL. MEGT also exhibited significant dual cholinesterase inhibition with IC 50 value of 64.26 ± 2.56 and 54 ± 0.7 μg/mL for acetyl and butyrylcholinesterase (BChE), respectively. Also, MEGT showed significant anti-aggregation activity by preventing the oligomerization of Aβ 25-35 . Further, MEGT increased the viability of Neuro2a cells up to 95% against Aβ 25-35 neurotoxicity. LC-MS analysis revealed the presence of 16 compounds including vitexin, ellagic acid, isovitexin, etc. In silico analysis revealed that vitexin binds effectively with AChE through strong hydrogen bonding. These results were further confirmed by evaluating the activity of vitexin in vitro, which showed dual cholinesterase inhibition with IC 50 value of 15.21 ± 0.41 and 19.75 ± 0.16 μM for acetyl and butyrlcholinesterase, respectively. Grewia tiliaefolia can be considered as a promising therapeutic agent for the treatment of AD.

In silico strategies for the selection of chelating compounds with potential application in metal-promoted neurodegenerative diseases

NASA Astrophysics Data System (ADS)

Rodríguez-Rodríguez, Cristina; Rimola, Albert; Alí-Torres, Jorge; Sodupe, Mariona; González-Duarte, Pilar

2011-01-01

The development of new strategies to find commercial molecules with promising biochemical features is a main target in the field of biomedicine chemistry. In this work we present an in silico-based protocol that allows identifying commercial compounds with suitable metal coordinating and pharmacokinetic properties to act as metal-ion chelators in metal-promoted neurodegenerative diseases (MpND). Selection of the chelating ligands is done by combining quantum chemical calculations with the search of commercial compounds on different databases via virtual screening. Starting from different designed molecular frameworks, which mainly constitute the binding site, the virtual screening on databases facilitates the identification of different commercial molecules that enclose such scaffolds and, by imposing a set of chemical and pharmacokinetic filters, obey some drug-like requirements mandatory to deal with MpND. The quantum mechanical calculations are useful to gauge the chelating properties of the selected candidate molecules by determining the structure of metal complexes and evaluating their stability constants. With the proposed strategy, commercial compounds containing N and S donor atoms in the binding sites and capable to cross the BBB have been identified and their chelating properties analyzed.

In Silico Ionomics Segregates Parasitic from Free-Living Eukaryotes

PubMed Central

Greganova, Eva; Steinmann, Michael; Mäser, Pascal; Fankhauser, Niklaus

2013-01-01

Ion transporters are fundamental to life. Due to their ancient origin and conservation in sequence, ion transporters are also particularly well suited for comparative genomics of distantly related species. Here, we perform genome-wide ion transporter profiling as a basis for comparative genomics of eukaryotes. From a given predicted proteome, we identify all bona fide ion channels, ion porters, and ion pumps. Concentrating on unicellular eukaryotes (n = 37), we demonstrate that clustering of species according to their repertoire of ion transporters segregates obligate endoparasites (n = 23) on the one hand, from free-living species and facultative parasites (n = 14) on the other hand. This surprising finding indicates strong convergent evolution of the parasites regarding the acquisition and homeostasis of inorganic ions. Random forest classification identifies transporters of ammonia, plus transporters of iron and other transition metals, as the most informative for distinguishing the obligate parasites. Thus, in silico ionomics further underscores the importance of iron in infection biology and suggests access to host sources of nitrogen and transition metals to be selective forces in the evolution of parasitism. This finding is in agreement with the phenomenon of iron withholding as a primordial antimicrobial strategy of infected mammals. PMID:24048281

In silico maturation of binding-specificity of DNA aptamers against Proteus mirabilis.

PubMed

Savory, Nasa; Lednor, Danielle; Tsukakoshi, Kaori; Abe, Koichi; Yoshida, Wataru; Ferri, Stefano; Jones, Brian V; Ikebukuro, Kazunori

2013-10-01

Proteus mirabilis is a prominent cause of catheter-associated urinary tract infections (CAUTIs) among patients undergoing long-term bladder catheterization. There are currently no effective means of preventing P. mirabilis infections, and strategies for prophylaxis and rapid early diagnosis are urgently required. Aptamers offer significant potential for development of countermeasures against P. mirabilis CAUTI and are an ideal class of molecules for the development of diagnostics and therapeutics. Here we demonstrate the application of Cell-SELEX to identify DNA aptamers that show high affinity for P. mirabilis. While the aptamers identified displayed high affinity for P. mirabilis cells in dot blotting assays, they also bound to other uropathogenic bacteria. To improve aptamer specificity for P. mirabilis, an in silico maturation (ISM) approach was employed. Two cycles of ISM allowed the identification of an aptamer showing 36% higher specificity, evaluated as a ratio of binding signal for P. mirabilis to that for Escherichia coli (also a cause of CAUTI and the most common urinary tract pathogen). Aptamers that specifically recognize P. mirabilis would have diagnostic and therapeutic values and constitute useful tools for studying membrane-associated proteins in this organism. Copyright © 2013 Wiley Periodicals, Inc.

Putative histidine kinase inhibitors with antibacterial effect against multi-drug resistant clinical isolates identified by in vitro and in silico screens

NASA Astrophysics Data System (ADS)

Velikova, Nadya; Fulle, Simone; Manso, Ana Sousa; Mechkarska, Milena; Finn, Paul; Conlon, J. Michael; Oggioni, Marco Rinaldo; Wells, Jerry M.; Marina, Alberto

2016-05-01

Novel antibacterials are urgently needed to address the growing problem of bacterial resistance to conventional antibiotics. Two-component systems (TCS) are widely used by bacteria to regulate gene expression in response to various environmental stimuli and physiological stress and have been previously proposed as promising antibacterial targets. TCS consist of a sensor histidine kinase (HK) and an effector response regulator. The HK component contains a highly conserved ATP-binding site that is considered to be a promising target for broad-spectrum antibacterial drugs. Here, we describe the identification of putative HK autophosphorylation inhibitors following two independent experimental approaches: in vitro fragment-based screen via differential scanning fluorimetry and in silico structure-based screening, each followed up by the exploration of analogue compounds as identified by ligand-based similarity searches. Nine of the tested compounds showed antibacterial effect against multi-drug resistant clinical isolates of bacterial pathogens and include three novel scaffolds, which have not been explored so far in other antibacterial compounds. Overall, putative HK autophosphorylation inhibitors were found that together provide a promising starting point for further optimization as antibacterials.

A Model of Differential Growth-Guided Apical Hook Formation in Plants

PubMed Central

Žádníková, Petra; Wabnik, Krzysztof; Abuzeineh, Anas; Prusinkiewicz, Przemysław

2016-01-01

Differential cell growth enables flexible organ bending in the presence of environmental signals such as light or gravity. A prominent example of the developmental processes based on differential cell growth is the formation of the apical hook that protects the fragile shoot apical meristem when it breaks through the soil during germination. Here, we combined in silico and in vivo approaches to identify a minimal mechanism producing auxin gradient-guided differential growth during the establishment of the apical hook in the model plant Arabidopsis thaliana. Computer simulation models based on experimental data demonstrate that asymmetric expression of the PIN-FORMED auxin efflux carrier at the concave (inner) versus convex (outer) side of the hook suffices to establish an auxin maximum in the epidermis at the concave side of the apical hook. Furthermore, we propose a mechanism that translates this maximum into differential growth, and thus curvature, of the apical hook. Through a combination of experimental and in silico computational approaches, we have identified the individual contributions of differential cell elongation and proliferation to defining the apical hook and reveal the role of auxin-ethylene crosstalk in balancing these two processes. PMID:27754878

In silico ionomics segregates parasitic from free-living eukaryotes.

PubMed

Greganova, Eva; Steinmann, Michael; Mäser, Pascal; Fankhauser, Niklaus

2013-01-01

Ion transporters are fundamental to life. Due to their ancient origin and conservation in sequence, ion transporters are also particularly well suited for comparative genomics of distantly related species. Here, we perform genome-wide ion transporter profiling as a basis for comparative genomics of eukaryotes. From a given predicted proteome, we identify all bona fide ion channels, ion porters, and ion pumps. Concentrating on unicellular eukaryotes (n = 37), we demonstrate that clustering of species according to their repertoire of ion transporters segregates obligate endoparasites (n = 23) on the one hand, from free-living species and facultative parasites (n = 14) on the other hand. This surprising finding indicates strong convergent evolution of the parasites regarding the acquisition and homeostasis of inorganic ions. Random forest classification identifies transporters of ammonia, plus transporters of iron and other transition metals, as the most informative for distinguishing the obligate parasites. Thus, in silico ionomics further underscores the importance of iron in infection biology and suggests access to host sources of nitrogen and transition metals to be selective forces in the evolution of parasitism. This finding is in agreement with the phenomenon of iron withholding as a primordial antimicrobial strategy of infected mammals.

SOX2, OTX2 and PAX6 analysis in subjects with anophthalmia and microphthalmia.

PubMed

Mauri, Lucia; Franzoni, Alessandra; Scarcello, Manuela; Sala, Stefano; Garavelli, Livia; Modugno, Alessandra; Grammatico, Paola; Patrosso, Maria Cristina; Piozzi, Elena; Del Longo, Alessandra; Gesu, Giovanni P; Manfredini, Emanuela; Primignani, Paola; Damante, Giuseppe; Penco, Silvana

2015-02-01

Anophthalmia (A) and microphthalmia (M) are rare developmental anomalies that have significant effects on visual activity. In fraction of A/M subjects, single genetic defects have been identified as causative. In this study we analysed 65 Italian A/M patients, 21 of whom are syndromic, for mutations in SOX2, OTX2 and PAX6 genes. In syndromic patients the presence of genome imbalances through array CGH was also investigated. No mutations were found for OTX2 and PAX6 genes. Three causative SOX2 mutations were found in subjects with syndromic A. In a subject with syndromic signs and monolateral M, two de novo 6.26 Mb and 1.37 Mb deletions in 4q13.2q13.3 have been identified. A SOX2 missense (p.Ala161Ser) mutation was found in 1 out of 39 a subject with non-syndromic monolateral M. Alanine at position 161 is conserved along phylogeny and the p.Ala161Ser mutation is estimated pathogenic by in silico analysis. However, this mutation was also present in the unaffected patient's daughter. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Mutagenicity in a Molecule: Identification of Core Structural Features of Mutagenicity Using a Scaffold Analysis

PubMed Central

Hsu, Kuo-Hsiang; Su, Bo-Han; Tu, Yi-Shu; Lin, Olivia A.; Tseng, Yufeng J.

2016-01-01

With advances in the development and application of Ames mutagenicity in silico prediction tools, the International Conference on Harmonisation (ICH) has amended its M7 guideline to reflect the use of such prediction models for the detection of mutagenic activity in early drug safety evaluation processes. Since current Ames mutagenicity prediction tools only focus on functional group alerts or side chain modifications of an analog series, these tools are unable to identify mutagenicity derived from core structures or specific scaffolds of a compound. In this study, a large collection of 6512 compounds are used to perform scaffold tree analysis. By relating different scaffolds on constructed scaffold trees with Ames mutagenicity, four major and one minor novel mutagenic groups of scaffold are identified. The recognized mutagenic groups of scaffold can serve as a guide for medicinal chemists to prevent the development of potentially mutagenic therapeutic agents in early drug design or development phases, by modifying the core structures of mutagenic compounds to form non-mutagenic compounds. In addition, five series of substructures are provided as recommendations, for direct modification of potentially mutagenic scaffolds to decrease associated mutagenic activities. PMID:26863515

Isolation and characterization of the promoter sequence of a cassava gene coding for Pt2L4, a glutamic acid-rich protein differentially expressed in storage roots.

PubMed

de Souza, C R; Aragão, F J; Moreira, E C O; Costa, C N M; Nascimento, S B; Carvalho, L J

2009-03-24

Cassava is one of the most important tropical food crops for more than 600 million people worldwide. Transgenic technologies can be useful for increasing its nutritional value and its resistance to viral diseases and insect pests. However, tissue-specific promoters that guarantee correct expression of transgenes would be necessary. We used inverse polymerase chain reaction to isolate a promoter sequence of the Mec1 gene coding for Pt2L4, a glutamic acid-rich protein differentially expressed in cassava storage roots. In silico analysis revealed putative cis-acting regulatory elements within this promoter sequence, including root-specific elements that may be required for its expression in vascular tissues. Transient expression experiments showed that the Mec1 promoter is functional, since this sequence was able to drive GUS expression in bean embryonic axes. Results from our computational analysis can serve as a guide for functional experiments to identify regions with tissue-specific Mec1 promoter activity. The DNA sequence that we identified is a new promoter that could be a candidate for genetic engineering of cassava roots.

Microsatellite analysis in the genome of Acanthaceae: An in silico approach.

PubMed

Kaliswamy, Priyadharsini; Vellingiri, Srividhya; Nathan, Bharathi; Selvaraj, Saravanakumar

2015-01-01

Acanthaceae is one of the advanced and specialized families with conventionally used medicinal plants. Simple sequence repeats (SSRs) play a major role as molecular markers for genome analysis and plant breeding. The microsatellites existing in the complete genome sequences would help to attain a direct role in the genome organization, recombination, gene regulation, quantitative genetic variation, and evolution of genes. The current study reports the frequency of microsatellites and appropriate markers for the Acanthaceae family genome sequences. The whole nucleotide sequences of Acanthaceae species were obtained from National Center for Biotechnology Information database and screened for the presence of SSRs. SSR Locator tool was used to predict the microsatellites and inbuilt Primer3 module was used for primer designing. Totally 110 repeats from 108 sequences of Acanthaceae family plant genomes were identified, and the occurrence of dinucleotide repeats was found to be abundant in the genome sequences. The essential amino acid isoleucine was found rich in all the sequences. We also designed the SSR-based primers/markers for 59 sequences of this family that contains microsatellite repeats in their genome. The identified microsatellites and primers might be useful for breeding and genetic studies of plants that belong to Acanthaceae family in the future.

In silico genomic insights into aspects of food safety and defense mechanisms of a potentially probiotic Lactobacillus pentosus MP-10 isolated from brines of naturally fermented Aloreña green table olives.

PubMed

Abriouel, Hikmate; Pérez Montoro, Beatriz; Casado Muñoz, María Del Carmen; Knapp, Charles W; Gálvez, Antonio; Benomar, Nabil

2017-01-01

Lactobacillus pentosus MP-10, isolated from brines of naturally fermented Aloreña green table olives, exhibited high probiotic potential. The genome sequence of L. pentosus MP-10 is currently considered the largest genome among lactobacilli, highlighting the microorganism's ecological flexibility and adaptability. Here, we analyzed the complete genome sequence for the presence of acquired antibiotic resistance and virulence determinants to understand their defense mechanisms and explore its putative safety in food. The annotated genome sequence revealed evidence of diverse mobile genetic elements, such as prophages, transposases and transposons involved in their adaptation to brine-associated niches. In-silico analysis of L. pentosus MP-10 genome sequence identified a CRISPR (clustered regularly interspaced short palindromic repeats)/cas (CRISPR-associated protein genes) as an immune system against foreign genetic elements, which consisted of six arrays (4-12 repeats) and eleven predicted cas genes [CRISPR1 and CRISPR2 consisted of 3 (Type II-C) and 8 (Type I) genes] with high similarity to L. pentosus KCA1. Bioinformatic analyses revealed L. pentosus MP-10 to be absent of acquired antibiotic resistance genes, and most resistance genes were related to efflux mechanisms; no virulence determinants were found in the genome. This suggests that L. pentosus MP-10 could be considered safe and with high-adaptation potential, which could facilitate its application as a starter culture and probiotic in food preparations.

First Pass Annotation of Promoters on Human Chromosome 22

PubMed Central

Scherf, Matthias; Klingenhoff, Andreas; Frech, Kornelie; Quandt, Kerstin; Schneider, Ralf; Grote, Korbinian; Frisch, Matthias; Gailus-Durner, Valérie; Seidel, Alexander; Brack-Werner, Ruth; Werner, Thomas

2001-01-01

The publication of the first almost complete sequence of a human chromosome (chromosome 22) is a major milestone in human genomics. Together with the sequence, an excellent annotation of genes was published which certainly will serve as an information resource for numerous future projects. We noted that the annotation did not cover regulatory regions; in particular, no promoter annotation has been provided. Here we present an analysis of the complete published chromosome 22 sequence for promoters. A recent breakthrough in specific in silico prediction of promoter regions enabled us to attempt large-scale prediction of promoter regions on chromosome 22. Scanning of sequence databases revealed only 20 experimentally verified promoters, of which 10 were correctly predicted by our approach. Nearly 40% of our 465 predicted promoter regions are supported by the currently available gene annotation. Promoter finding also provides a biologically meaningful method for “chromosomal scaffolding”, by which long genomic sequences can be divided into segments starting with a gene. As one example, the combination of promoter region prediction with exon/intron structure predictions greatly enhances the specificity of de novo gene finding. The present study demonstrates that it is possible to identify promoters in silico on the chromosomal level with sufficient reliability for experimental planning and indicates that a wealth of information about regulatory regions can be extracted from current large-scale (megabase) sequencing projects. Results are available on-line at http://genomatix.gsf.de/chr22/. PMID:11230158

Integration of parallel 13 C-labeling experiments and in silico pathway analysis for enhanced production of ascomycin.

PubMed

Qi, Haishan; Lv, Mengmeng; Song, Kejing; Wen, Jianping

2017-05-01

Herein, the hyper-producing strain for ascomycin was engineered based on 13 C-labeling experiments and elementary flux modes analysis (EFMA). First, the metabolism of non-model organism Streptomyces hygroscopicus var. ascomyceticus SA68 was investigated and an updated network model was reconstructed using 13 C- metabolic flux analysis. Based on the precise model, EFMA was further employed to predict genetic targets for higher ascomycin production. Chorismatase (FkbO) and pyruvate carboxylase (Pyc) were predicted as the promising overexpression and deletion targets, respectively. The corresponding mutant TD-FkbO and TD-ΔPyc exhibited the consistency effects between model prediction and experimental results. Finally, the combined genetic manipulations were performed, achieving a high-yield ascomycin engineering strain TD-ΔPyc-FkbO with production up to 610 mg/L, 84.8% improvement compared with the parent strain SA68. These results manifested that the integration of 13 C-labeling experiments and in silico pathway analysis could serve as a promising concept to enhance ascomycin production, as well as other valuable products. Biotechnol. Bioeng. 2017;114: 1036-1044. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Purification, developmental expression, and in silico characterization of α-amylase inhibitor from Echinochloa frumentacea.

PubMed

Panwar, Priyankar; Verma, A K; Dubey, Ashutosh

2018-05-01

Barnyard ( Echinochloa frumentacea ) and finger ( Eleusine coracana ) millet growing at northwestern Himalaya were explored for the α-amylase inhibitor (α-AI). The mature seeds of barnyard millet variety PRJ1 had maximum α-AI activity which increases in different developmental stage. α-AI was purified up to 22.25-fold from barnyard millet variety PRJ1. Semi-quantitative PCR of different developmental stages of barnyard millet seeds showed increased levels of the transcript from 7 to 28 days. Sequence analysis revealed that it contained 315 bp nucleotide which encodes 104 amino acid sequence with molecular weight 10.72 kDa. The predicted 3D structure of α-AI was 86.73% similar to a bifunctional inhibitor of ragi. In silico analysis of 71 α-AI protein sequences were carried out for biochemical features, homology search, multiple sequence alignment, phylogenetic tree construction, motif, and superfamily distribution of protein sequences. Analysis of multiple sequence alignment revealed the existence of conserved regions NPLP[S/G]CRWYVV[S/Q][Q/R]TCG[V/I] throughout sequences. Superfam analysis revealed that α-AI protein sequences were distributed among seven different superfamilies.

Investigation of metabolic objectives in cultured hepatocytes.

PubMed

Uygun, Korkut; Matthew, Howard W T; Huang, Yinlun

2007-06-15

Using optimization based methods to predict fluxes in metabolic flux balance models has been a successful approach for some microorganisms, enabling construction of in silico models and even inference of some regulatory motifs. However, this success has not been translated to mammalian cells. The lack of knowledge about metabolic objectives in mammalian cells is a major obstacle that prevents utilization of various metabolic engineering tools and methods for tissue engineering and biomedical purposes. In this work, we investigate and identify possible metabolic objectives for hepatocytes cultured in vitro. To achieve this goal, we present a special data-mining procedure for identifying metabolic objective functions in mammalian cells. This multi-level optimization based algorithm enables identifying the major fluxes in the metabolic objective from MFA data in the absence of information about critical active constraints of the system. Further, once the objective is determined, active flux constraints can also be identified and analyzed. This information can be potentially used in a predictive manner to improve cell culture results or clinical metabolic outcomes. As a result of the application of this method, it was found that in vitro cultured hepatocytes maximize oxygen uptake, coupling of urea and TCA cycles, and synthesis of serine and urea. Selection of these fluxes as the metabolic objective enables accurate prediction of the flux distribution in the system given a limited amount of flux data; thus presenting a workable in silico model for cultured hepatocytes. It is observed that an overall homeostasis picture is also emergent in the findings.

Genome-Wide Distribution, Organisation and Functional Characterization of Disease Resistance and Defence Response Genes across Rice Species

PubMed Central

Singh, Sangeeta; Chand, Suresh; Singh, N. K.; Sharma, Tilak Raj

2015-01-01

The resistance (R) genes and defense response (DR) genes have become very important resources for the development of disease resistant cultivars. In the present investigation, genome-wide identification, expression, phylogenetic and synteny analysis was done for R and DR-genes across three species of rice viz: Oryza sativa ssp indica cv 93-11, Oryza sativa ssp japonica and wild rice species, Oryza brachyantha. We used the in silico approach to identify and map 786 R -genes and 167 DR-genes, 672 R-genes and 142 DR-genes, 251 R-genes and 86 DR-genes in the japonica, indica and O. brachyanth a genomes, respectively. Our analysis showed that 60.5% and 55.6% of the R-genes are tandemly repeated within clusters and distributed over all the rice chromosomes in indica and japonica genomes, respectively. The phylogenetic analysis along with motif distribution shows high degree of conservation of R- and DR-genes in clusters. In silico expression analysis of R-genes and DR-genes showed more than 85% were expressed genes showing corresponding EST matches in the databases. This study gave special emphasis on mechanisms of gene evolution and duplication for R and DR genes across species. Analysis of paralogs across rice species indicated 17% and 4.38% R-genes, 29% and 11.63% DR-genes duplication in indica and Oryza brachyantha, as compared to 20% and 26% duplication of R-genes and DR-genes in japonica respectively. We found that during the course of duplication only 9.5% of R- and DR-genes changed their function and rest of the genes have maintained their identity. Syntenic relationship across three genomes inferred that more orthology is shared between indica and japonica genomes as compared to brachyantha genome. Genome wide identification of R-genes and DR-genes in the rice genome will help in allele mining and functional validation of these genes, and to understand molecular mechanism of disease resistance and their evolution in rice and related species. PMID:25902056

In silico database screening of potential targets and pathways of compounds contained in plants used for psoriasis vulgaris.

PubMed

May, Brian H; Deng, Shiqiang; Zhang, Anthony L; Lu, Chuanjian; Xue, Charlie C L

2015-09-01

Reviews and meta-analyses of clinical trials identified plants used as traditional medicines (TMs) that show promise for psoriasis. These include Rehmannia glutinosa, Camptotheca acuminata, Indigo naturalis and Salvia miltiorrhiza. Compounds contained in these TMs have shown activities of relevance to psoriasis in experimental models. To further investigate the likely mechanisms of action of the multiple compounds in these TMs, we undertook a computer-based in silico investigation of the proteins known to be regulated by these compounds and their associated biological pathways. The proteins reportedly regulated by compounds in these four TMs were identified using the HIT (Herbal Ingredients' Targets) database. The resultant data were entered into the PANTHER (Protein ANnotation THrough Evolutionary Relationship) database to identify the pathways in which the proteins could be involved. The study identified 237 compounds in the TMs and these retrieved 287 proteins from HIT. These proteins identified 59 pathways in PANTHER with most proteins being located in the Apoptosis, Angiogenesis, Inflammation mediated by chemokine and cytokine, Gonadotropin releasing hormone receptor, and/or Interleukin signaling pathways. All four TMs contained compounds that had regulating effects on Apoptosis regulator BAX, Apoptosis regulator Bcl-2, Caspase-3, Tumor necrosis factor (TNF) or Prostaglandin G/H synthase 2 (COX2). The main proteins and pathways are primarily related to inflammation, proliferation and angiogenesis which are all processes involved in psoriasis. Experimental studies have reported that certain compounds from these TMs can regulate the expression of proteins involved in each of these pathways.

Structure based drug discovery for designing leads for the non-toxic metabolic targets in multi drug resistant Mycobacterium tuberculosis.

PubMed

Kaur, Divneet; Mathew, Shalu; Nair, Chinchu G S; Begum, Azitha; Jainanarayan, Ashwin K; Sharma, Mukta; Brahmachari, Samir K

2017-12-21

The problem of drug resistance and bacterial persistence in tuberculosis is a cause of global alarm. Although, the UN's Sustainable Development Goals for 2030 has targeted a Tb free world, the treatment gap exists and only a few new drug candidates are in the pipeline. In spite of large information from medicinal chemistry to 'omics' data, there has been a little effort from pharmaceutical companies to generate pipelines for the development of novel drug candidates against the multi drug resistant Mycobacterium tuberculosis. In the present study, we describe an integrated methodology; utilizing systems level information to optimize ligand selection to lower the failure rates at the pre-clinical and clinical levels. In the present study, metabolic targets (Rv2763c, Rv3247c, Rv1094, Rv3607c, Rv3048c, Rv2965c, Rv2361c, Rv0865, Rv0321, Rv0098, Rv0390, Rv3588c, Rv2244, Rv2465c and Rv2607) in M. tuberculosis, identified using our previous Systems Biology and data-intensive genome level analysis, have been used to design potential lead molecules, which are likely to be non-toxic. Various in silico drug discovery tools have been utilized to generate small molecular leads for each of the 15 targets with available crystal structures. The present study resulted in identification of 20 novel lead molecules including 4 FDA approved drugs (droxidropa, tetroxoprim, domperidone and nemonapride) which can be further taken for drug repurposing. This comprehensive integrated methodology, with both experimental and in silico approaches, has the potential to not only tackle the MDR form of Mtb but also the most important persister population of the bacterium, with a potential to reduce the failures in the Tb drug discovery. We propose an integrated approach of systems and structural biology for identifying targets that address the high attrition rate issue in lead identification and drug development We expect that this system level analysis will be applicable for identification of drug candidates to other pathogenic organisms as well.

Drug-Like Protein–Protein Interaction Modulators: Challenges and Opportunities for Drug Discovery and Chemical Biology

PubMed Central

Villoutreix, Bruno O; Kuenemann, Melaine A; Poyet, Jean-Luc; Bruzzoni-Giovanelli, Heriberto; Labbé, Céline; Lagorce, David; Sperandio, Olivier; Miteva, Maria A

2014-01-01

Fundamental processes in living cells are largely controlled by macromolecular interactions and among them, protein–protein interactions (PPIs) have a critical role while their dysregulations can contribute to the pathogenesis of numerous diseases. Although PPIs were considered as attractive pharmaceutical targets already some years ago, they have been thus far largely unexploited for therapeutic interventions with low molecular weight compounds. Several limiting factors, from technological hurdles to conceptual barriers, are known, which, taken together, explain why research in this area has been relatively slow. However, this last decade, the scientific community has challenged the dogma and became more enthusiastic about the modulation of PPIs with small drug-like molecules. In fact, several success stories were reported both, at the preclinical and clinical stages. In this review article, written for the 2014 International Summer School in Chemoinformatics (Strasbourg, France), we discuss in silico tools (essentially post 2012) and databases that can assist the design of low molecular weight PPI modulators (these tools can be found at www.vls3d.com). We first introduce the field of protein–protein interaction research, discuss key challenges and comment recently reported in silico packages, protocols and databases dedicated to PPIs. Then, we illustrate how in silico methods can be used and combined with experimental work to identify PPI modulators. PMID:25254076

The N-terminal amphipathic helix of Pex11p self-interacts to induce membrane remodelling during peroxisome fission.

PubMed

Su, Juanjuan; Thomas, Ann S; Grabietz, Tanja; Landgraf, Christiane; Volkmer, Rudolf; Marrink, Siewert J; Williams, Chris; Melo, Manuel N

2018-06-01

Pex11p plays a crucial role in peroxisome fission. Previously, it was shown that a conserved N-terminal amphipathic helix in Pex11p, termed Pex11-Amph, was necessary for peroxisomal fission in vivo while in vitro studies revealed that this region alone was sufficient to bring about tubulation of liposomes with a lipid consistency resembling the peroxisomal membrane. However, molecular details of how Pex11-Amph remodels the peroxisomal membrane remain unknown. Here we have combined in silico, in vitro and in vivo approaches to gain insights into the molecular mechanisms underlying Pex11-Amph activity. Using molecular dynamics simulations, we observe that Pex11-Amph peptides form linear aggregates on a model membrane. Furthermore, we identify mutations that disrupted this aggregation in silico, which also abolished the peptide's ability to remodel liposomes in vitro, establishing that Pex11p oligomerisation plays a direct role in membrane remodelling. In vivo studies revealed that these mutations resulted in a strong reduction in Pex11 protein levels, indicating that these residues are important for Pex11p function. Taken together, our data demonstrate the power of combining in silico techniques with experimental approaches to investigate the molecular mechanisms underlying Pex11p-dependent membrane remodelling. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

FORUM - FutureTox II: In vitro Data and In Silico Models for ...

EPA Pesticide Factsheets

FutureTox II, a Society of Toxicology Contemporary Concepts in Toxicology workshop, was held in January, 2014. The meeting goals were to review and discuss the state of the science in toxicology in the context of implementing the NRC 21st century vision of predicting in vivo responses from in vitro and in silico data, and to define the goals for the future. Presentations and discussions were held on priority concerns such as predicting and modeling of metabolism, cell growth and differentiation, effects on sensitive subpopulations, and integrating data into risk assessment. Emerging trends in technologies such as stem cell-derived human cells, 3D organotypic culture models, mathematical modeling of cellular processes and morphogenesis, adverse outcome pathway development, and high-content imaging of in vivo systems were discussed. Although advances in moving towards an in vitro/in silico based risk assessment paradigm were apparent, knowledge gaps in these areas and limitations of technologies were identified. Specific recommendations were made for future directions and research needs in the areas of hepatotoxicity, cancer prediction, developmental toxicity, and regulatory toxicology. This article reports on the outcome of FutureTox II1,2, the second in a series of Society of Toxicology (SOT) Contemporary Concepts in Toxicology (CCT) Workshops, which was attended by invitees and participants from governmental and regulatory agencies, research institutes, academ

Crops In Silico: Generating Virtual Crops Using an Integrative and Multi-scale Modeling Platform.

PubMed

Marshall-Colon, Amy; Long, Stephen P; Allen, Douglas K; Allen, Gabrielle; Beard, Daniel A; Benes, Bedrich; von Caemmerer, Susanne; Christensen, A J; Cox, Donna J; Hart, John C; Hirst, Peter M; Kannan, Kavya; Katz, Daniel S; Lynch, Jonathan P; Millar, Andrew J; Panneerselvam, Balaji; Price, Nathan D; Prusinkiewicz, Przemyslaw; Raila, David; Shekar, Rachel G; Shrivastava, Stuti; Shukla, Diwakar; Srinivasan, Venkatraman; Stitt, Mark; Turk, Matthew J; Voit, Eberhard O; Wang, Yu; Yin, Xinyou; Zhu, Xin-Guang

2017-01-01

Multi-scale models can facilitate whole plant simulations by linking gene networks, protein synthesis, metabolic pathways, physiology, and growth. Whole plant models can be further integrated with ecosystem, weather, and climate models to predict how various interactions respond to environmental perturbations. These models have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts. Outcomes will potentially accelerate improvement of crop yield, sustainability, and increase future food security. It is time for a paradigm shift in plant modeling, from largely isolated efforts to a connected community that takes advantage of advances in high performance computing and mechanistic understanding of plant processes. Tools for guiding future crop breeding and engineering, understanding the implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment are urgently needed. The purpose of this perspective is to introduce Crops in silico (cropsinsilico.org), an integrative and multi-scale modeling platform, as one solution that combines isolated modeling efforts toward the generation of virtual crops, which is open and accessible to the entire plant biology community. The major challenges involved both in the development and deployment of a shared, multi-scale modeling platform, which are summarized in this prospectus, were recently identified during the first Crops in silico Symposium and Workshop.

Crops In Silico: Generating Virtual Crops Using an Integrative and Multi-scale Modeling Platform

PubMed Central

Marshall-Colon, Amy; Long, Stephen P.; Allen, Douglas K.; Allen, Gabrielle; Beard, Daniel A.; Benes, Bedrich; von Caemmerer, Susanne; Christensen, A. J.; Cox, Donna J.; Hart, John C.; Hirst, Peter M.; Kannan, Kavya; Katz, Daniel S.; Lynch, Jonathan P.; Millar, Andrew J.; Panneerselvam, Balaji; Price, Nathan D.; Prusinkiewicz, Przemyslaw; Raila, David; Shekar, Rachel G.; Shrivastava, Stuti; Shukla, Diwakar; Srinivasan, Venkatraman; Stitt, Mark; Turk, Matthew J.; Voit, Eberhard O.; Wang, Yu; Yin, Xinyou; Zhu, Xin-Guang

2017-01-01

Multi-scale models can facilitate whole plant simulations by linking gene networks, protein synthesis, metabolic pathways, physiology, and growth. Whole plant models can be further integrated with ecosystem, weather, and climate models to predict how various interactions respond to environmental perturbations. These models have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts. Outcomes will potentially accelerate improvement of crop yield, sustainability, and increase future food security. It is time for a paradigm shift in plant modeling, from largely isolated efforts to a connected community that takes advantage of advances in high performance computing and mechanistic understanding of plant processes. Tools for guiding future crop breeding and engineering, understanding the implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment are urgently needed. The purpose of this perspective is to introduce Crops in silico (cropsinsilico.org), an integrative and multi-scale modeling platform, as one solution that combines isolated modeling efforts toward the generation of virtual crops, which is open and accessible to the entire plant biology community. The major challenges involved both in the development and deployment of a shared, multi-scale modeling platform, which are summarized in this prospectus, were recently identified during the first Crops in silico Symposium and Workshop. PMID:28555150

In silico studies on marine actinomycetes as potential inhibitors for Glioblastoma multiforme

PubMed Central

Kirubakaran, Palani; Kothapalli, Roopa; Singh, Kh Dhanachandra; Nagamani, Selvaraman; Arjunan, Subramanian; Muthusamy, Karthikeyan

2011-01-01

Glioblastoma multiforme (GBM) is considered to be the most common and often deadly disorder which affects the brain. It is caused by the over expression of proteins such as ephrin type-A receptor 2 (EphA2), epidermal growth factor receptor (EGFR) and EGFRvIII. These 3 proteins are considered to be the potential therapeutic targets for GBM. Among these, EphA2 is reported to be over-expressed in ˜90% of GBM. Herein we selected 35 compounds from marine actinomycetes, 5 in vitro and in vivo studied drug candidates and 4 commercially available drugs for GBM which were identified from literature and analysed by using comparative docking studies. Based on the glide scores and other in silico parameters available in Schrödinger, two selected marine actinomycetes compounds which include Tetracenomycin D and Chartreusin exhibited better binding energy among all the compounds studied in comparative docking. In this study we have demonstrated the inhibition of the 3 selected targets by the two bioactive compounds from marine actinomycetes through in-silico docking studies. Furthermore molecular dynamics simulation were also been performed to check the stability and the amino acids interacted with the 3 molecular targets (EphA2 receptor, EGFR, EGFRvIII) for GBM. Our results suggest that Tetracinomycin D and Chartreusin are the novel and potential inhibitor for the treatment of GBM. PMID:21584184

Better, Cheaper Biofuels through Computational Analysis - Continuum

Science.gov Websites

than 30 years, NREL researchers have made significant experimental advances in understanding the polymers to fermentable sugars. But while experimental studies are critical, this research approach can increasingly use computational (or "in silico") studies to complement their experimental work

Identification of the PLA2G6 c.1579G>A Missense Mutation in Papillon Dog Neuroaxonal Dystrophy Using Whole Exome Sequencing Analysis

PubMed Central

Tsuboi, Masaya; Watanabe, Manabu; Nibe, Kazumi; Yoshimi, Natsuko; Kato, Akihisa; Sakaguchi, Masahiro; Yamato, Osamu; Tanaka, Miyuu; Kuwamura, Mitsuru; Kushida, Kazuya; Harada, Tomoyuki; Chambers, James Kenn; Sugano, Sumio; Uchida, Kazuyuki; Nakayama, Hiroyuki

2017-01-01

Whole exome sequencing (WES) has become a common tool for identifying genetic causes of human inherited disorders, and it has also recently been applied to canine genome research. We conducted WES analysis of neuroaxonal dystrophy (NAD), a neurodegenerative disease that sporadically occurs worldwide in Papillon dogs. The disease is considered an autosomal recessive monogenic disease, which is histopathologically characterized by severe axonal swelling, known as “spheroids,” throughout the nervous system. By sequencing all eleven DNA samples from one NAD-affected Papillon dog and her parents, two unrelated NAD-affected Papillon dogs, and six unaffected control Papillon dogs, we identified 10 candidate mutations. Among them, three candidates were determined to be “deleterious” by in silico pathogenesis evaluation. By subsequent massive screening by TaqMan genotyping analysis, only the PLA2G6 c.1579G>A mutation had an association with the presence or absence of the disease, suggesting that it may be a causal mutation of canine NAD. As a human homologue of this gene is a causative gene for infantile neuroaxonal dystrophy, this canine phenotype may serve as a good animal model for human disease. The results of this study also indicate that WES analysis is a powerful tool for exploring canine hereditary diseases, especially in rare monogenic hereditary diseases. PMID:28107443

Comparison of secretory signal peptides for heterologous protein expression in microalgae: Expanding the secretion portfolio for Chlamydomonas reinhardtii

PubMed Central

de Carvalho, João Carlos Monteiro; Mayfield, Stephen Patrick

2018-01-01

Efficient protein secretion is a desirable trait for any recombinant protein expression system, together with simple, low-cost, and defined media, such as the typical media used for photosynthetic cultures of microalgae. However, low titers of secreted heterologous proteins are usually obtained, even with the most extensively studied microalga Chlamydomonas reinhardtii, preventing their industrial application. In this study, we aimed to expand and evaluate secretory signal peptides (SP) for heterologous protein secretion in C. reinhardtii by comparing previously described SP with untested sequences. We compared the SPs from arylsulfatase 1 and carbonic anhydrase 1, with those of untried SPs from binding protein 1, an ice-binding protein, and six sequences identified in silico. We identified over 2000 unique SPs using the SignalP 4.0 software. mCherry fluorescence was used to compare the protein secretion of up to 96 colonies for each construct, non-secretion construct, and parental wild-type cc1690 cells. Supernatant fluorescence varied according to the SP used, with a 10-fold difference observed between the highest and lowest secretors. Moreover, two SPs identified in silico secreted the highest amount of mCherry. Our results demonstrate that the SP should be carefully selected and that efficient sequences can be coded in the C. reinhardtii genome. The SPs described here expand the portfolio available for research on heterologous protein secretion and for biomanufacturing applications. PMID:29408937

Recombinant expression of in silico identified Bcell epitope of epsilon toxin of Clostridium perfringens in translational fusion with a carrier protein.

PubMed

Kaushik, Himani; Deshmukh, Sachin; Mathur, Deepika Dayal; Tiwari, Archana; Garg, Lalit C

2013-01-01

Epsilon toxin secreted by Clostridium perfringens types B and D has been directly implicated as the causative agent of fatal enterotoxemia in domestic animals. The aim of the present study is to use in silico approach for identification of B-cell epitope(s) of epsilon toxin, and its expression in fusion with a carrier protein to analyze its potential as vaccine candidate(s). Using different computational analyses and bioinformatics tools, a number of antigenic determinant regions of epsilon toxin were identified. One of the B cell epitopes of epsilon toxin comprising the region (amino acids 40-62) was identified as a promising antigenic determinant. This Etx epitope (Etx40-62) was cloned and expressed as a translational fusion with B-subunit of heat labile enterotoxin (LTB) of E. coli in a secretory expression system. Similar to the native LTB, the recombinant fusion protein retained the ability to pentamerize and bind to GM1 ganglioside receptor of LTB. The rLTB.Etx40-62 could be detected both with anti-Etx and anti-LTB antisera. The rLTB.Etx40-62 fusion protein thus can be evaluated as a potential vaccine candidate against C. perfringens. aa - amino acid(s), Etx - epsilon toxin of Clostridium perfringens, LTB - B-subunit of heat labile enterotoxin of E. coli.

Identification of phototransformation products of thalidomide and mixture toxicity assessment: an experimental and quantitative structural activity relationships (QSAR) approach.

PubMed

Mahmoud, Waleed M M; Toolaram, Anju P; Menz, Jakob; Leder, Christoph; Schneider, Mandy; Kümmerer, Klaus

2014-02-01

The fate of thalidomide (TD) was investigated after irradiation with a medium-pressure Hg-lamp. The primary elimination of TD was monitored and structures of phototransformation products (PTPs) were assessed by LC-UV-FL-MS/MS. Environmentally relevant properties of TD and its PTPs as well as hydrolysis products (HTPs) were predicted using in silico QSAR models. Mutagenicity of TD and its PTPs was investigated in the Ames microplate format (MPF) aqua assay (Xenometrix, AG). Furthermore, a modified luminescent bacteria test (kinetic luminescent bacteria test (kinetic LBT)), using the luminescent bacteria species Vibrio fischeri, was applied for the initial screening of environmental toxicity. Additionally, toxicity of phthalimide, one of the identified PTPs, was investigated separately in the kinetic LBT. The UV irradiation eliminated TD itself without complete mineralization and led to the formation of several PTPs. TD and its PTPs did not exhibit mutagenic response in the Salmonella typhimurium strains TA 98, and TA 100 with and without metabolic activation. In contrast, QSAR analysis of PTPs and HTPs provided evidence for mutagenicity, genotoxicity and carcinogenicity using additional endpoints in silico software. QSAR analysis of different ecotoxicological endpoints, such as acute toxicity towards V. fischeri, provided positive alerts for several identified PTPs and HTPs. This was partially confirmed by the results of the kinetic LBT, in which a steady increase of acute and chronic toxicity during the UV-treatment procedure was observed for the photolytic mixtures at the highest tested concentration. Moreover, the number of PTPs within the reaction mixture that might be responsible for the toxification of TD during UV-treatment was successfully narrowed down by correlating the formation kinetics of PTPs with QSAR predictions and experimental toxicity data. Beyond that, further analysis of the commercially available PTP phthalimide indicated that transformation of TD into phthalimide was not the cause for the toxification of TD during UV-treatment. These results provide a path for toxicological assessment of complex chemical mixtures and in detail show the toxic potential of TD and its PTPs as well as its HTPs. This deserves further attention as UV irradiation might not always be a green technology, because it might pose a toxicological risk for the environment in general and specifically for water compartments. Copyright © 2013 Elsevier Ltd. All rights reserved.

Molecular analysis of the PAX6 gene in Mexican patients with congenital aniridia: report of four novel mutations

PubMed Central

Villarroel, Camilo E.; Villanueva-Mendoza, Cristina; Orozco, Lorena; Alcántara-Ortigoza, Miguel Angel; Jiménez, Diana F.; Ordaz, Juan C.

2008-01-01

Purpose Paired box gene 6 (PAX6) heterozygous mutations are well known to cause congenital non-syndromic aniridia. These mutations produce primarily protein truncations and have been identified in approximately 40%–80% of all aniridia cases worldwide. In Mexico, there is only one previous report describing three intragenic deletions in five cases. In this study, we further analyze PAX6 variants in a group of Mexican aniridia patients and describe associated ocular findings. Methods We evaluated 30 nonrelated probands from two referral hospitals. Mutations were detected by single-strand conformation polymorphism (SSCP) and direct sequencing, and novel missense mutations and intronic changes were analyzed by in silico analysis. One intronic variation (IVS2+9G>A), which in silico analysis suggested had no pathological effects, was searched in 103 unaffected controls. Results Almost all cases exhibited phenotypes that were at the severe end of the aniridia spectrum with associated ocular alterations such as nystagmus, macular hypoplasia, and congenital cataracts. The mutation detection rate was 30%. Eight different mutations were identified: four (c.184_188dupGAGAC, c.361T>C, c.879dupC, and c.277G>A) were novel, and four (c.969C>T, IVS6+1G>C, c.853delC, and IVS7–2A>G) have been previously reported. The substitution at position 969 was observed in two patients. None of the intragenic deletions previously reported in Mexican patients were found. Most of the mutations detected predict either truncation of the PAX6 protein or conservative amino acid changes in the paired domain. We also detected two intronic non-pathogenic variations, IVS9–12C>T and IVS2+9G>A, that had been previously reported. Because the latter variation was considered potentially pathogenic, it was analyzed in 103 healthy Mexican newborns where we found an allelic frequency of 0.1116 for the A allele. Conclusions This study adds four novel mutations to the worldwide PAX6 mutational spectrum, and reaffirms the finding that c.969C>T is one of the three more frequent causal mutations in aniridia cases. It also provides evidence that IVS2+9G>A is an intronic change without pathogenic effect. PMID:18776953

Mutational analysis of GALT gene in Greek patients with galactosaemia: identification of two novel mutations and clinical evaluation.

PubMed

Schulpis, Kleopatra H; Thodi, Georgia; Iakovou, Konstantinos; Chatzidaki, Maria; Dotsikas, Yannis; Molou, Elina; Triantafylli, Olga; Loukas, Yannis L

2017-10-01

Classical galactosaemia is an inborn error of metabolism due to the deficiency of the enzyme galactose-1-phosphate uridylyltransferase (GALT). The aim of the study was to identify the underlying mutations in Greek patients with GALT deficiency and evaluate their psychomotor and speech development. Patients with GALT deficiency (n = 17) were picked up through neonatal screening. Mutational analysis was conducted via Sanger sequencing, while in silico analysis was used in the cases of novel missense mutations. Psychomotor speech development tests were utilized for the clinical evaluation of the patients. Eleven different mutations in the GALT gene were detected in the patient cohort, including two novel ones. The most frequent mutation was p.Q188R (c.563 A > G). As for the novel mutations, p.M298I (c.894 G > A) was identified in four out of 32 independent alleles, while p.P115S (c.343 C > T) was identified once. Psychomotor evaluation revealed that most of the patients were found in the borderline area (Peabody test), while only two had speech delay problems. The WISK test revealed three patients at borderline limits and two were at lower than normal limits. The mutational spectrum of the GALT gene in Greek patients is presented for the first time. The mutation p.Q188R is the most frequent among Greek patients. Two novel mutations were identified and their potential pathogenicity was estimated. Regarding the phenotypic characteristics, psychomotor disturbances and speech delay were mainly observed among GALT-deficient patients.