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.

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.

Environmental metabarcodes for insects: in silico PCR reveals potential for taxonomic bias.

PubMed

Clarke, Laurence J; Soubrier, Julien; Weyrich, Laura S; Cooper, Alan

2014-11-01

Studies of insect assemblages are suited to the simultaneous DNA-based identification of multiple taxa known as metabarcoding. To obtain accurate estimates of diversity, metabarcoding markers ideally possess appropriate taxonomic coverage to avoid PCR-amplification bias, as well as sufficient sequence divergence to resolve species. We used in silico PCR to compare the taxonomic coverage and resolution of newly designed insect metabarcodes (targeting 16S) with that of existing markers [16S and cytochrome oxidase c subunit I (COI)] and then compared their efficiency in vitro. Existing metabarcoding primers amplified in silico <75% of insect species with complete mitochondrial genomes available, whereas new primers targeting 16S provided >90% coverage. Furthermore, metabarcodes targeting COI appeared to introduce taxonomic PCR-amplification bias, typically amplifying a greater percentage of Lepidoptera and Diptera species, while failing to amplify certain orders in silico. To test whether bias predicted in silico was observed in vitro, we created an artificial DNA blend containing equal amounts of DNA from 14 species, representing 11 insect orders and one arachnid. We PCR-amplified the blend using five primer sets, targeting either COI or 16S, with high-throughput amplicon sequencing yielding more than 6 million reads. In vitro results typically corresponded to in silico PCR predictions, with newly designed 16S primers detecting 11 insect taxa present, thus providing equivalent or better taxonomic coverage than COI metabarcodes. Our results demonstrate that in silico PCR is a useful tool for predicting taxonomic bias in mixed template PCR and that researchers should be wary of potential bias when selecting metabarcoding markers. © 2014 John Wiley & Sons Ltd.

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 .

Assessment of the predictive accuracy of five in silico prediction tools, alone or in combination, and two metaservers to classify long QT syndrome gene mutations.

PubMed

Leong, Ivone U S; Stuckey, Alexander; Lai, Daniel; Skinner, Jonathan R; Love, Donald R

2015-05-13

Long QT syndrome (LQTS) is an autosomal dominant condition predisposing to sudden death from malignant arrhythmia. Genetic testing identifies many missense single nucleotide variants of uncertain pathogenicity. Establishing genetic pathogenicity is an essential prerequisite to family cascade screening. Many laboratories use in silico prediction tools, either alone or in combination, or metaservers, in order to predict pathogenicity; however, their accuracy in the context of LQTS is unknown. We evaluated the accuracy of five in silico programs and two metaservers in the analysis of LQTS 1-3 gene variants. The in silico tools SIFT, PolyPhen-2, PROVEAN, SNPs&GO and SNAP, either alone or in all possible combinations, and the metaservers Meta-SNP and PredictSNP, were tested on 312 KCNQ1, KCNH2 and SCN5A gene variants that have previously been characterised by either in vitro or co-segregation studies as either "pathogenic" (283) or "benign" (29). The accuracy, sensitivity, specificity and Matthews Correlation Coefficient (MCC) were calculated to determine the best combination of in silico tools for each LQTS gene, and when all genes are combined. The best combination of in silico tools for KCNQ1 is PROVEAN, SNPs&GO and SIFT (accuracy 92.7%, sensitivity 93.1%, specificity 100% and MCC 0.70). The best combination of in silico tools for KCNH2 is SIFT and PROVEAN or PROVEAN, SNPs&GO and SIFT. Both combinations have the same scores for accuracy (91.1%), sensitivity (91.5%), specificity (87.5%) and MCC (0.62). In the case of SCN5A, SNAP and PROVEAN provided the best combination (accuracy 81.4%, sensitivity 86.9%, specificity 50.0%, and MCC 0.32). When all three LQT genes are combined, SIFT, PROVEAN and SNAP is the combination with the best performance (accuracy 82.7%, sensitivity 83.0%, specificity 80.0%, and MCC 0.44). Both metaservers performed better than the single in silico tools; however, they did not perform better than the best performing combination of in silico tools. The combination of in silico tools with the best performance is gene-dependent. The in silico tools reported here may have some value in assessing variants in the KCNQ1 and KCNH2 genes, but caution should be taken when the analysis is applied to SCN5A gene variants.

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.

[Prediction of ETA oligopeptides antagonists from Glycine max based on in silico proteolysis].

PubMed

Qiao, Lian-Sheng; Jiang, Lu-di; Luo, Gang-Gang; Lu, Fang; Chen, Yan-Kun; Wang, Ling-Zhi; Li, Gong-Yu; Zhang, Yan-Ling

2017-02-01

Oligopeptides are one of the the key pharmaceutical effective constituents of traditional Chinese medicine(TCM). Systematic study on composition and efficacy of TCM oligopeptides is essential for the analysis of material basis and mechanism of TCM. In this study, the potential anti-hypertensive oligopeptides from Glycine max and their endothelin receptor A (ETA) antagonistic activity were discovered and predicted based on in silico technologies.Main protein sequences of G. max were collected and oligopeptides were obtained using in silico gastrointestinal tract proteolysis. Then, the pharmacophore of ETA antagonistic peptides was constructed and included one hydrophobic feature, one ionizable negative feature, one ring aromatic feature and five excluded volumes. Meanwhile, three-dimensional structure of ETA was developed by homology modeling methods for further docking studies. According to docking analysis and consensus score, the key amino acid of GLN165 was identified for ETA antagonistic activity. And 27 oligopeptides from G. max were predicted as the potential ETA antagonists by pharmacophore and docking studies.In silico proteolysis could be used to analyze the protein sequences from TCM. According to combination of in silico proteolysis and molecular simulation, the biological activities of oligopeptides could be predicted rapidly based on the known TCM protein sequence. It might provide the methodology basis for rapidly and efficiently implementing the mechanism analysis of TCM oligopeptides. Copyright© by the Chinese Pharmaceutical Association.

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.

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.

Synthesis of aryl pyrazole via Suzuki coupling reaction, in vitro mushroom tyrosinase enzyme inhibition assay and in silico comparative molecular docking analysis with Kojic acid.

PubMed

Channar, Pervaiz Ali; Saeed, Aamer; Larik, Fayaz Ali; Batool, Bakhtawar; Kalsoom, Saima; Hasan, M M; Erben, Mauricio F; El-Seedi, Hesham R; Ali, Musrat; Ashraf, Zaman

2018-04-30

Aryl pyrazoles are well recognized class of heterocyclic compounds found in several commercially available drugs. Owing to their significance in medicinal chemistry, in this current account we have synthesized a series of suitably substituted aryl pyrazole by employing Suzuki cross-coupling reaction. All compounds were evaluated for inhibition of mushroom tyrosinase enzyme both in vitro and in silico. Compound 3f (IC 50  = 1.568 ± 0.01 µM) showed relatively better potential compared to reference kojic acid (IC 50  = 16.051 ± 1.27 µM). A comparative docking studies showed that compound 3f have maximum binding affinity against mushroom tyrosinase (PDBID: 2Y9X) with binding energy value (-6.90 kcal/mol) as compared to Kojic acid. The 4-methoxy group in compound 3f shows 100% interaction with Cu. Compound 3f displayed hydrogen binding interaction with His61 and His94 at distance of 1.71 and 1.74 Å which might be responsible for higher activity compared to Kojic acid. Copyright © 2018 Elsevier Inc. All rights reserved.

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 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.

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.

Differential Expression of In Vivo and In Vitro Protein Profile of Outer Membrane of Acidovorax avenae Subsp. avenae

PubMed Central

Qiu, Hui; Li, Bin; Jabeen, Amara; Li, Liping; Liu, He; Kube, Michael; Xie, Guanlin; Wang, Yanli; Sun, Guochang

2012-01-01

Outer membrane (OM) proteins play a significant role in bacterial pathogenesis. In this work, we examined and compared the expression of the OM proteins of the rice pathogen Acidovorax avenae subsp. avenae strain RS-1, a Gram-negative bacterium, both in an in vitro culture medium and in vivo rice plants. Global proteomic profiling of A. avenae subsp. avenae strain RS-1 comparing in vivo and in vitro conditions revealed the differential expression of proteins affecting the survival and pathogenicity of the rice pathogen in host plants. The shotgun proteomics analysis of OM proteins resulted in the identification of 97 proteins in vitro and 62 proteins in vivo by mass spectrometry. Among these OM proteins, there is a high number of porins, TonB-dependent receptors, lipoproteins of the NodT family, ABC transporters, flagellins, and proteins of unknown function expressed under both conditions. However, the major proteins such as phospholipase and OmpA domain containing proteins were expressed in vitro, while the proteins such as the surface anchored protein F, ATP-dependent Clp protease, OmpA and MotB domain containing proteins were expressed in vivo. This may indicate that these in vivo OM proteins have roles in the pathogenicity of A. avenae subsp. avenae strain RS-1. In addition, the LC-MS/MS identification of OmpA and MotB validated the in silico prediction of the existance of Type VI secretion system core components. To the best of our knowledge, this is the first study to reveal the in vitro and in vivo protein profiles, in combination with LC-MS/MS mass spectra, in silico OM proteome and in silico genome wide analysis, of pathogenicity or plant host required proteins of a plant pathogenic bacterium. PMID:23166741

An integrated in silico approach for functional and structural impact of non- synonymous SNPs in the MYH1 gene in Jeju Native Pigs.

PubMed

Ghosh, Mrinmoy; Sodhi, Simrinder Singh; Sharma, Neelesh; Mongre, Raj Kumar; Kim, Nameun; Singh, Amit Kumar; Lee, Sung Jin; Kim, Dae Cheol; Kim, Sung Woo; Lee, Hak Kyo; Song, Ki-Duk; Jeong, Dong Kee

2016-02-04

This study was performed to identify the non- synonymous polymorphisms in the myosin heavy chain 1 gene (MYH1) association with skeletal muscle development in economically important Jeju Native Pig (JNP) and Berkshire breeds. Herein, we present an in silico analysis, with a focus on (a) in silico approaches to predict the functional effect of non-synonymous SNP (nsSNP) in MYH1 on growth, and (b) molecular docking and dynamic simulation of MYH1 to predict the effects of those nsSNP on protein-protein association. The NextGENe (V 2.3.4.) tool was used to identify the variants in MYH1 from JNP and Berkshire using RNA seq. Gene ontology analysis of MYH1 revealed significant association with muscle contraction and muscle organ development. The 95 % confidence intervals clearly indicate that the mRNA expression of MYH1 is significantly higher in the Berkshire longissimus dorsi muscle samples than JNP breed. Concordant in silico analysis of MYH1, the open-source software tools identified 4 potential nsSNP (L884T, K972C, N981G, and Q1285C) in JNP and 1 nsSNP (H973G) in Berkshire pigs. Moreover, protein-protein interactions were studied to investigate the effect of MYH1 mutations on association with hub proteins, and MYH1 was found to be closely associated with the protein myosin light chain, phosphorylatable, fast skeletal muscle MYLPF. The results of molecular docking studies on MYH1 (native and 4 mutants) and MYLFP demonstrated that the native complex showed higher electrostatic energy (-466.5 Kcal mol(-1)), van der Walls energy (-87.3 Kcal mol(-1)), and interaction energy (-835.7 Kcal mol(-1)) than the mutant complexes. Furthermore, the molecular dynamic simulation revealed that the native complex yielded a higher root-mean-square deviation (0.2-0.55 nm) and lower root-mean-square fluctuation (approximately 0.08-0.3 nm) as compared to the mutant complexes. The results suggest that the variants at L884T, K972C, N981G, and Q1285C in MYH1 in JNP might represent a cause for the poor growth performance for this breed. This study is a pioneering in-depth in silico analysis of polymorphic MYH1 and will serve as a valuable resource for further targeted molecular diagnosis and population-based studies conducted for improving the growth performance of JNP.

Purely in silico BCS classification: science based quality standards for the world's drugs.

PubMed

Dahan, Arik; Wolk, Omri; Kim, Young Hoon; Ramachandran, Chandrasekharan; Crippen, Gordon M; Takagi, Toshihide; Bermejo, Marival; Amidon, Gordon L

2013-11-04

BCS classification is a vital tool in the development of both generic and innovative drug products. The purpose of this work was to provisionally classify the world's top selling oral drugs according to the BCS, using in silico methods. Three different in silico methods were examined: the well-established group contribution (CLogP) and atom contribution (ALogP) methods, and a new method based solely on the molecular formula and element contribution (KLogP). Metoprolol was used as the benchmark for the low/high permeability class boundary. Solubility was estimated in silico using a thermodynamic equation that relies on the partition coefficient and melting point. The validity of each method was affirmed by comparison to reference data and literature. We then used each method to provisionally classify the orally administered, IR drug products found in the WHO Model list of Essential Medicines, and the top-selling oral drug products in the United States (US), Great Britain (GB), Spain (ES), Israel (IL), Japan (JP), and South Korea (KR). A combined list of 363 drugs was compiled from the various lists, and 257 drugs were classified using the different in silico permeability methods and literature solubility data, as well as BDDCS classification. Lastly, we calculated the solubility values for 185 drugs from the combined set using in silico approach. Permeability classification with the different in silico methods was correct for 69-72.4% of the 29 reference drugs with known human jejunal permeability, and for 84.6-92.9% of the 14 FDA reference drugs in the set. The correlations (r(2)) between experimental log P values of 154 drugs and their CLogP, ALogP and KLogP were 0.97, 0.82 and 0.71, respectively. The different in silico permeability methods produced comparable results: 30-34% of the US, GB, ES and IL top selling drugs were class 1, 27-36.4% were class 2, 22-25.5% were class 3, and 5.46-14% were class 4 drugs, while ∼8% could not be classified. The WHO list included significantly less class 1 and more class 3 drugs in comparison to the countries' lists, probably due to differences in commonly used drugs in developing vs industrial countries. BDDCS classified more drugs as class 1 compared to in silico BCS, likely due to the more lax benchmark for metabolism (70%), in comparison to the strict permeability benchmark (metoprolol). For 185 out of the 363 drugs, in silico solubility values were calculated, and successfully matched the literature solubility data. In conclusion, relatively simple in silico methods can be used to estimate both permeability and solubility. While CLogP produced the best correlation to experimental values, even KLogP, the most simplified in silico method that is based on molecular formula with no knowledge of molecular structure, produced comparable BCS classification to the sophisticated methods. This KLogP, when combined with a mean melting point and estimated dose, can be used to provisionally classify potential drugs from just molecular formula, even before synthesis. 49-59% of the world's top-selling drugs are highly soluble (class 1 and class 3), and are therefore candidates for waivers of in vivo bioequivalence studies. For these drugs, the replacement of expensive human studies with affordable in vitro dissolution tests would ensure their bioequivalence, and encourage the development and availability of generic drug products in both industrial and developing countries.

Effect of Different Sampling Schedules on Results of Bioavailability and Bioequivalence Studies: Evaluation by Means of Monte Carlo Simulations.

PubMed

Kano, Eunice Kazue; Chiann, Chang; Fukuda, Kazuo; Porta, Valentina

2017-08-01

Bioavailability and bioequivalence study is one of the most frequently performed investigations in clinical trials. Bioequivalence testing is based on the assumption that 2 drug products will be therapeutically equivalent when they are equivalent in the rate and extent to which the active drug ingredient or therapeutic moiety is absorbed and becomes available at the site of drug action. In recent years there has been a significant growth in published papers that use in silico studies based on mathematical simulations to analyze pharmacokinetic and pharmacodynamic properties of drugs, including bioavailability and bioequivalence aspects. The goal of this study is to evaluate the usefulness of in silico studies as a tool in the planning of bioequivalence, bioavailability and other pharmacokinetic assays, e.g., to determine an appropriate sampling schedule. Monte Carlo simulations were used to define adequate blood sampling schedules for a bioequivalence assay comparing 2 different formulations of cefadroxil oral suspensions. In silico bioequivalence studies comparing different formulation of cefadroxil oral suspensions using various sampling schedules were performed using models. An in vivo study was conducted to confirm in silico results. The results of in silico and in vivo bioequivalence studies demonstrated that schedules with fewer sampling times are as efficient as schedules with larger numbers of sampling times in the assessment of bioequivalence, but only if T max is included as a sampling time. It was also concluded that in silico studies are useful tools in the planning of bioequivalence, bioavailability and other pharmacokinetic in vivo assays. © Georg Thieme Verlag KG Stuttgart · New York.

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

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.

Comparative analysis of genome-wide Mlo gene family in Cajanus cajan and Phaseolus vulgaris.

PubMed

Deshmukh, Reena; Singh, V K; Singh, B D

2016-04-01

The Mlo gene was discovered in barley because the mutant 'mlo' allele conferred broad-spectrum, non-race-specific resistance to powdery mildew caused by Blumeria graminis f. sp. hordei. The Mlo genes also play important roles in growth and development of plants, and in responses to biotic and abiotic stresses. The Mlo gene family has been characterized in several crop species, but only a single legume species, soybean (Glycine max L.), has been investigated so far. The present report describes in silico identification of 18 CcMlo and 20 PvMlo genes in the important legume crops Cajanus cajan (L.) Millsp. and Phaseolus vulgaris L., respectively. In silico analysis of gene organization, protein properties and conserved domains revealed that the C. cajan and P. vulgaris Mlo gene paralogs are more divergent from each other than from their orthologous pairs. The comparative phylogenetic analysis classified CcMlo and PvMlo genes into three major clades. A comparative analysis of CcMlo and PvMlo proteins with the G. max Mlo proteins indicated close association of one CcMlo, one PvMlo with two GmMlo genes, indicating that there was no further expansion of the Mlo gene family after the separation of these species. Thus, most of the diploid species of eudicots might be expected to contain 15-20 Mlo genes. The genes CcMlo12 and 14, and PvMlo11 and 12 are predicted to participate in powdery mildew resistance. If this prediction were verified, these genes could be targeted by TILLING or CRISPR to isolate powdery mildew resistant mutants.

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/.

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.

MTHFR-Ala222Val and male infertility: a study in Iranian men, an updated meta-analysis and an in silico-analysis.

PubMed

Nikzad, Hossein; Karimian, Mohammad; Sareban, Kobra; Khoshsokhan, Maryam; Hosseinzadeh Colagar, Abasalt

2015-11-01

Methylenetetrahydrofolate reductase (MTHFR) functions as a main regulatory enzyme in folate metabolism. The association of MTHFR gene Ala222Val polymorphism with male infertility in an Iranian population was investigated by undertaking a meta-analysis and in-silico approach. A genetic association study included 497 men; 242 had unexplained infertility and 255 were healthy controls. Polymerase chain reaction restriction fragment length polymorphism was used for genotyping MTHFR-Ala222Val. OpenMeta[Analyst] software was used to conduct the analysis; 22 studies were identified by searching PubMed and the currently reported genetic association study. A novel in-silico approach was used to analyse the effects of Ala222Val substitution on the structure of mRNA and protein. Genetic association study revealed a significant association of MTHFR-222Val/Val genotype with oligozoospermia (OR 2.32; 95% CI, 1.12 to 4.78; P = 0.0451) and azoospermia (OR 2.59; 95% CI 1.09 to 6.17; P = 0.0314). Meta-analysis for allelic, dominant and codominant models showed a significant association between Ala222Val polymorphism and the risk of male infertility (P < 0.001). In silico-analysis showed MTHFR-Ala222Val affects enzyme structure and could also change the mRNA properties (P = 0.1641; P < 0.2 is significant). The meta-analysis suggested significant association of MTHFR-Ala222Val with risk of male infertility, especially in Asian populations. Copyright © 2015 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

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

Antibody quantum dot conjugates developed via copper-free click chemistry for rapid analysis of biological samples using a microfluidic microsphere array system.

PubMed

Kotagiri, Nalinikanth; Li, Zhenyu; Xu, Xiaoxiao; Mondal, Suman; Nehorai, Arye; Achilefu, Samuel

2014-07-16

Antibody-based proteomics is an enabling technology that has significant implications for cancer biomarker discovery, diagnostic screening, prognostic and pharmacodynamic evaluation of disease state, and targeted therapeutics. Quantum dot based fluoro-immunoconjugates possess promising features toward realization of this goal such as high photostability, brightness, and multispectral tunability. However, current strategies to generate such conjugates are riddled with complications such as improper orientation of antigen binding sites of the antibody, aggregation, and stability issues. We report a facile yet effective strategy to conjugate anti-epidermal growth factor receptor (EGFR) antibody to quantum dots using copper-free click reaction, and compared them to similar constructs prepared using traditional strategies such as succinimidyl-4-(N-maleimidomethyl) cyclohexane-1-carboxylate (SMCC) and biotin-streptavidin schemes. The Fc and Fab regions of the conjugates retain their binding potential, compared to those generated through the traditional schemes. We further applied the conjugates in testing a novel microsphere array device designed to carry out sensitive detection of cancer biomarkers through fluoroimmunoassays. Using purified EGFR, we determined the limit of detection of the microscopy centric system to be 12.5 ng/mL. The biological assay, in silico, was successfully tested and validated by using tumor cell lysates, as well as human serum from breast cancer patients, and the results were compared to normal serum. A pattern consistent with established clinical data was observed, which further validates the effectiveness of the developed conjugates and its successful implementation both in vitro as well as in silico fluoroimmunoassays. The results suggest the potential development of a high throughput in silico paradigm for predicting the class of patient cancer based on EGFR expression levels relative to normal reference levels in blood.

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

Whole-exome sequencing analysis of Waardenburg syndrome in a Chinese family.

PubMed

Chen, Dezhong; Zhao, Na; Wang, Jing; Li, Zhuoyu; Wu, Changxin; Fu, Jie; Xiao, Han

2017-01-01

Waardenburg syndrome (WS) is a dominantly inherited, genetically heterogeneous auditory-pigmentary syndrome characterized by non-progressive sensorineural hearing loss and iris discoloration. By whole-exome sequencing (WES), we identified a nonsense mutation (c.598C>T) in PAX3 gene, predicted to be disease causing by in silico analysis. This is the first report of genetically diagnosed case of WS PAX3 c.598C>T nonsense mutation in Chinese ethnic origin by WES and in silico functional prediction methods.

Whole-exome sequencing analysis of Waardenburg syndrome in a Chinese family

PubMed Central

Chen, Dezhong; Zhao, Na; Wang, Jing; Li, Zhuoyu; Wu, Changxin; Fu, Jie; Xiao, Han

2017-01-01

Waardenburg syndrome (WS) is a dominantly inherited, genetically heterogeneous auditory-pigmentary syndrome characterized by non-progressive sensorineural hearing loss and iris discoloration. By whole-exome sequencing (WES), we identified a nonsense mutation (c.598C>T) in PAX3 gene, predicted to be disease causing by in silico analysis. This is the first report of genetically diagnosed case of WS PAX3 c.598C>T nonsense mutation in Chinese ethnic origin by WES and in silico functional prediction methods. PMID:28690861

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.

Advanced continuous cultivation methods for systems microbiology.

PubMed

Adamberg, Kaarel; Valgepea, Kaspar; Vilu, Raivo

2015-09-01

Increasing the throughput of systems biology-based experimental characterization of in silico-designed strains has great potential for accelerating the development of cell factories. For this, analysis of metabolism in the steady state is essential as only this enables the unequivocal definition of the physiological state of cells, which is needed for the complete description and in silico reconstruction of their phenotypes. In this review, we show that for a systems microbiology approach, high-resolution characterization of metabolism in the steady state--growth space analysis (GSA)--can be achieved by using advanced continuous cultivation methods termed changestats. In changestats, an environmental parameter is continuously changed at a constant rate within one experiment whilst maintaining cells in the physiological steady state similar to chemostats. This increases the resolution and throughput of GSA compared with chemostats, and, moreover, enables following of the dynamics of metabolism and detection of metabolic switch-points and optimal growth conditions. We also describe the concept, challenge and necessary criteria of the systematic analysis of steady-state metabolism. Finally, we propose that such systematic characterization of the steady-state growth space of cells using changestats has value not only for fundamental studies of metabolism, but also for systems biology-based metabolic engineering of cell factories.

Metabolic analyses elucidate non-trivial gene targets for amplifying dihydroartemisinic acid production in yeast

PubMed Central

Misra, Ashish; Conway, Matthew F.; Johnnie, Joseph; Qureshi, Tabish M.; Lige, Bao; Derrick, Anne M.; Agbo, Eddy C.; Sriram, Ganesh

2013-01-01

Synthetic biology enables metabolic engineering of industrial microbes to synthesize value-added molecules. In this, a major challenge is the efficient redirection of carbon to the desired metabolic pathways. Pinpointing strategies toward this goal requires an in-depth investigation of the metabolic landscape of the organism, particularly primary metabolism, to identify precursor and cofactor availability for the target compound. The potent antimalarial therapeutic artemisinin and its precursors are promising candidate molecules for production in microbial hosts. Recent advances have demonstrated the production of artemisinin precursors in engineered yeast strains as an alternative to extraction from plants. We report the application of in silico and in vivo metabolic pathway analyses to identify metabolic engineering targets to improve the yield of the direct artemisinin precursor dihydroartemisinic acid (DHA) in yeast. First, in silico extreme pathway (ExPa) analysis identified NADPH-malic enzyme and the oxidative pentose phosphate pathway (PPP) as mechanisms to meet NADPH demand for DHA synthesis. Next, we compared key DHA-synthesizing ExPas to the metabolic flux distributions obtained from in vivo 13C metabolic flux analysis of a DHA-synthesizing strain. This comparison revealed that knocking out ethanol synthesis and overexpressing glucose-6-phosphate dehydrogenase in the oxidative PPP (gene YNL241C) or the NADPH-malic enzyme ME2 (YKL029C) are vital steps toward overproducing DHA. Finally, we employed in silico flux balance analysis and minimization of metabolic adjustment on a yeast genome-scale model to identify gene knockouts for improving DHA yields. The best strategy involved knockout of an oxaloacetate transporter (YKL120W) and an aspartate aminotransferase (YKL106W), and was predicted to improve DHA yields by 70-fold. Collectively, our work elucidates multiple non-trivial metabolic engineering strategies for improving DHA yield in yeast. PMID:23898325

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

Exploration of structural stability in deleterious nsSNPs of the XPA gene: A molecular dynamics approach.

PubMed

Nagasundaram, N; Priya Doss, C George

2011-01-01

Distinguishing the deleterious from the massive number of non-functional nsSNPs that occur within a single genome is a considerable challenge in mutation research. In this approach, we have used the existing in silico methods to explore the mutation-structure-function relationship in the XPAgene. We used the Sorting Intolerant From Tolerant (SIFT), Polymorphism Phenotyping (PolyPhen), I-Mutant 2.0, and the Protein Analysis THrough Evolutionary Relationships methods to predict the effects of deleterious nsSNPs on protein function and evaluated the impact of mutation on protein stability by Molecular Dynamics simulations. By comparing the scores of all the four in silico methods, nsSNP with an ID rs104894131 at position C108F was predicted to be highly deleterious. We extended our Molecular dynamics approach to gain insight into the impact of this non-synonymous polymorphism on structural changes that may affect the activity of the XPAgene. Based on the in silico methods score, potential energy, root-mean-square deviation, and root-mean-square fluctuation, we predict that deleterious nsSNP at position C108F would play a significant role in causing disease by the XPA gene. Our approach would present the application of in silicotools in understanding the functional variation from the perspective of structure, evolution, and phenotype.

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

Bioinformatics Identification of Modules of Transcription Factor Binding Sites in Alzheimer's Disease-Related Genes by In Silico Promoter Analysis and Microarrays

PubMed Central

Augustin, Regina; Lichtenthaler, Stefan F.; Greeff, Michael; Hansen, Jens; Wurst, Wolfgang; Trümbach, Dietrich

2011-01-01

The molecular mechanisms and genetic risk factors underlying Alzheimer's disease (AD) pathogenesis are only partly understood. To identify new factors, which may contribute to AD, different approaches are taken including proteomics, genetics, and functional genomics. Here, we used a bioinformatics approach and found that distinct AD-related genes share modules of transcription factor binding sites, suggesting a transcriptional coregulation. To detect additional coregulated genes, which may potentially contribute to AD, we established a new bioinformatics workflow with known multivariate methods like support vector machines, biclustering, and predicted transcription factor binding site modules by using in silico analysis and over 400 expression arrays from human and mouse. Two significant modules are composed of three transcription factor families: CTCF, SP1F, and EGRF/ZBPF, which are conserved between human and mouse APP promoter sequences. The specific combination of in silico promoter and multivariate analysis can identify regulation mechanisms of genes involved in multifactorial diseases. PMID:21559189

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.

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

Integrated stoichiometric, thermodynamic and kinetic modelling of steady state metabolism

PubMed Central

Fleming, R.M.T.; Thiele, I.; Provan, G.; Nasheuer, H.P.

2010-01-01

The quantitative analysis of biochemical reactions and metabolites is at frontier of biological sciences. The recent availability of high-throughput technology data sets in biology has paved the way for new modelling approaches at various levels of complexity including the metabolome of a cell or an organism. Understanding the metabolism of a single cell and multi-cell organism will provide the knowledge for the rational design of growth conditions to produce commercially valuable reagents in biotechnology. Here, we demonstrate how equations representing steady state mass conservation, energy conservation, the second law of thermodynamics, and reversible enzyme kinetics can be formulated as a single system of linear equalities and inequalities, in addition to linear equalities on exponential variables. Even though the feasible set is non-convex, the reformulation is exact and amenable to large-scale numerical analysis, a prerequisite for computationally feasible genome scale modelling. Integrating flux, concentration and kinetic variables in a unified constraint-based formulation is aimed at increasing the quantitative predictive capacity of flux balance analysis. Incorporation of experimental and theoretical bounds on thermodynamic and kinetic variables ensures that the predicted steady state fluxes are both thermodynamically and biochemically feasible. The resulting in silico predictions are tested against fluxomic data for central metabolism in E. coli and compare favourably with in silico prediction by flux balance analysis. PMID:20230840

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.

Efficacy of Silicosec, a diatomaceous earth formulation against Tribolium castaneum (Herbst) (Coleoptera: Tenebrionidae).

PubMed

Ziaee, Masumeh; Safaralizadeh, Mohammad H; Shayesteh, Nouraddin

2007-11-01

Laboratory bioassays were carried out to evaluate the insecticidal efficacy of SilicoSec against 7- 14-days-old adults of Tribolium castaneum; old and young larvae with the mean weight of 3.4 +/- 0.1 and 0.6 +/- 0.1 mg, respectively at 27 degrees C and 55 +/- 5% r.h in the dark. Wheat treated with four dose rates of SilicoSec with three replications. Adult's mortality was measured after 2, 7 and 14 days of exposure. After 14 days mortality count, all adults were removed and samples retained under the same conditions for a further 60 days to assess progeny production. In the case of larvae, mortality was counted after 1, 2 and 7 days. After 2 days of exposure no concentration achieved 11% mortality for adults, however; adult's mortality exceeds 89.65% when exposed for 7 days to SilicoSec. Mortality of old and young larvae at 0.6 g kg(-1) after 2 days were 28.88 and 22.22%, respectively and exceed to 60.71 and 69.04% at longer exposure of 7 days. Results indicated that mortality of T. castaneum was influenced by interval exposed to wheat treated with SilicoSec and over this exposure; the increases in application rate of SilicoSec had significant effect on the mortality. Young larvae of red flour beetle were more sensitive to SilicoSec than old larvae and adults were more tolerant. Reproductive potential of adults in the treated wheat was suppressed when compared with untreated wheat. The high retention level of SilicoSec (78.62%) was noted in wheat kernels.

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.

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.

Mobile Genetic Elements: In Silico, In Vitro, In Vivo

PubMed Central

Arkhipova, Irina R.; Rice, Phoebe A.

2016-01-01

Mobile genetic elements (MGEs), also called transposable elements (TEs), represent universal components of most genomes and are intimately involved in nearly all aspects of genome organization, function, and evolution. However, there is currently a gap between fast-paced TE discovery in silico, stimulated by exponential growth of comparative genomic studies, and a limited number of experimental models amenable to more traditional in vitro and in vivo studies of structural, mechanistic, and regulatory properties of diverse MGEs. Experimental and computational scientists came together to bridge this gap at a recent conference, “Mobile Genetic Elements: in silico, in vitro, in vivo,” held at the Marine Biological Laboratory (MBL) in Woods Hole, MA, USA. PMID:26822117

Characterisation and In Silico Analysis of Interleukin-4 cDNA of Nilgai (Boselaphus tragocamelus) and Indian Buffalo (Bubalus bubalis)

PubMed Central

Saini, M.; Palai, T. K.; Das, D. K.; Hatle, K. M.; Gupta, P. K.

2013-01-01

Interleukin-4 (IL-4) produced from Th2 cells modulates both innate and adaptive immune responses. It is a common belief that wild animals possess better immunity against diseases than domestic and laboratory animals; however, the immune system of wild animals is not fully explored yet. Therefore, a comparative study was designed to explore the wildlife immunity through characterisation of IL-4 cDNA of nilgai, a wild ruminant, and Indian buffalo, a domestic ruminant. Total RNA was extracted from peripheral blood mononuclear cells of nilgai and Indian buffalo and reverse transcribed into cDNA. Respective cDNA was further cloned and sequenced. Sequences were analysed in silico and compared with their homologues available at GenBank. The deduced 135 amino acid protein of nilgai IL-4 is 95.6% similar to that of Indian buffalo. N-linked glycosylation sequence, leader sequence, Cysteine residues in the signal peptide region, and 3′ UTR of IL-4 were found to be conserved across species. Six nonsynonymous nucleotide substitutions were found in Indian buffalo compared to nilgai amino acid sequence. Tertiary structure of this protein in both species was modeled, and it was found that this protein falls under 4-helical cytokines superfamily and short chain cytokine family. Phylogenetic analysis revealed a single cluster of ruminants including both nilgai and Indian buffalo that was placed distinct from other nonruminant mammals. PMID:24348167

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 Assigned Resistance Genes Confer Bifidobacterium with Partial Resistance to Aminoglycosides but Not to Β-Lactams

PubMed Central

Fouhy, Fiona; O’Connell Motherway, Mary; Fitzgerald, Gerald F.; Ross, R. Paul; Stanton, Catherine; van Sinderen, Douwe; Cotter, Paul D.

2013-01-01

Bifidobacteria have received significant attention due to their contribution to human gut health and the use of specific strains as probiotics. It is thus not surprising that there has also been significant interest with respect to their antibiotic resistance profile. Numerous culture-based studies have demonstrated that bifidobacteria are resistant to the majority of aminoglycosides, but are sensitive to β-lactams. However, limited research exists with respect to the genetic basis for the resistance of bifidobacteria to aminoglycosides. Here we performed an in-depth in silico analysis of putative Bifidobacterium-encoded aminoglycoside resistance proteins and β-lactamases and assess the contribution of these proteins to antibiotic resistance. The in silico-based screen detected putative aminoglycoside and β-lactam resistance proteins across the Bifidobacterium genus. Laboratory-based investigations of a number of representative bifidobacteria strains confirmed that despite containing putative β-lactamases, these strains were sensitive to β-lactams. In contrast, all strains were resistant to the aminoglycosides tested. To assess the contribution of genes encoding putative aminoglycoside resistance proteins in Bifidobacterium sp. two genes, namely Bbr_0651 and Bbr_1586, were targeted for insertional inactivation in B. breve UCC2003. As compared to the wild-type, the UCC2003 insertion mutant strains exhibited decreased resistance to gentamycin, kanamycin and streptomycin. This study highlights the associated risks of relying on the in silico assignment of gene function. Although several putative β-lactam resistance proteins are located in bifidobacteria, their presence does not coincide with resistance to these antibiotics. In contrast however, this approach has resulted in the identification of two loci that contribute to the aminoglycoside resistance of B. breve UCC2003 and, potentially, many other bifidobacteria. PMID:24324818

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

The Virtual Anemia Trial: An Assessment of Model‐Based In Silico Clinical Trials of Anemia Treatment Algorithms in Patients With Hemodialysis

PubMed Central

Topping, Alice; Kappel, Franz; Thijssen, Stephan; Kotanko, Peter

2018-01-01

In silico approaches have been proposed as a novel strategy to increase the repertoire of clinical trial designs. Realistic simulations of clinical trials can provide valuable information regarding safety and limitations of treatment protocols and have been shown to assist in the cost‐effective planning of clinical studies. In this report, we present a blueprint for the stepwise integration of internal, external, and ecological validity considerations in virtual clinical trials (VCTs). We exemplify this approach in the context of a model‐based in silico clinical trial aimed at anemia treatment in patients undergoing hemodialysis (HD). Hemoglobin levels and subsequent anemia treatment were simulated on a per patient level over the course of a year and compared to real‐life clinical data of 79,426 patients undergoing HD. The novel strategies presented here, aimed to improve external and ecological validity of a VCT, significantly increased the predictive power of the discussed in silico trial. PMID:29368434

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

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

Exploration of structural stability in deleterious nsSNPs of the XPA gene: A molecular dynamics approach

PubMed Central

NagaSundaram, N; Priya Doss, C George

2011-01-01

Background: Distinguishing the deleterious from the massive number of non-functional nsSNPs that occur within a single genome is a considerable challenge in mutation research. In this approach, we have used the existing in silico methods to explore the mutation-structure-function relationship in the XPAgene. Materials and Methods: We used the Sorting Intolerant From Tolerant (SIFT), Polymorphism Phenotyping (PolyPhen), I-Mutant 2.0, and the Protein Analysis THrough Evolutionary Relationships methods to predict the effects of deleterious nsSNPs on protein function and evaluated the impact of mutation on protein stability by Molecular Dynamics simulations. Results: By comparing the scores of all the four in silico methods, nsSNP with an ID rs104894131 at position C108F was predicted to be highly deleterious. We extended our Molecular dynamics approach to gain insight into the impact of this non-synonymous polymorphism on structural changes that may affect the activity of the XPAgene. Conclusion: Based on the in silico methods score, potential energy, root-mean-square deviation, and root-mean-square fluctuation, we predict that deleterious nsSNP at position C108F would play a significant role in causing disease by the XPA gene. Our approach would present the application of in silicotools in understanding the functional variation from the perspective of structure, evolution, and phenotype. PMID:22190868

Molecular rationale delineating the role of lycopene as a potent HMG-CoA reductase inhibitor: in vitro and in silico study.

PubMed

Alvi, Sahir Sultan; Iqbal, Danish; Ahmad, Saheem; Khan, M Salman

2016-09-01

This study initially aimed to depict the molecular rationale evolving the role of lycopene in inhibiting the enzymatic activity of β-hydroxy-β-methylglutaryl-CoA (HMG-CoA) reductase via in vitro and in silico analysis. Our results illustrated that lycopene exhibited strong HMG-CoA reductase inhibitory activity (IC50 value of 36 ng/ml) quite better than pravastatin (IC50 = 42 ng/ml) and strong DPPH free radical scavenging activity (IC50 value = 4.57 ± 0.23 μg/ml) as compared to ascorbic acid (IC50 value = 9.82 ± 0.42 μg/ml). Moreover, the Ki value of lycopene (36 ng/ml) depicted via Dixon plot was well concurred with an IC50 value of 36 ± 1.8 ng/ml. Moreover, molecular informatics study showed that lycopene exhibited binding energy of -5.62 kcal/mol indicating high affinity for HMG-CoA reductase than HMG-CoA (ΔG: -5.34 kcal/mol). Thus, in silico data clearly demonstrate and support the in vitro results that lycopene competitively inhibit HMG-CoA reductase activity by binding at the hydrophobic portion of HMG-CoA reductase.

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

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.

Enhanced Isotopic Ratio Outlier Analysis (IROA) Peak Detection and Identification with Ultra-High Resolution GC-Orbitrap/MS: Potential Application for Investigation of Model Organism Metabolomes.

PubMed

Qiu, Yunping; Moir, Robyn D; Willis, Ian M; Seethapathy, Suresh; Biniakewitz, Robert C; Kurland, Irwin J

2018-01-18

Identifying non-annotated peaks may have a significant impact on the understanding of biological systems. In silico methodologies have focused on ESI LC/MS/MS for identifying non-annotated MS peaks. In this study, we employed in silico methodology to develop an Isotopic Ratio Outlier Analysis (IROA) workflow using enhanced mass spectrometric data acquired with the ultra-high resolution GC-Orbitrap/MS to determine the identity of non-annotated metabolites. The higher resolution of the GC-Orbitrap/MS, together with its wide dynamic range, resulted in more IROA peak pairs detected, and increased reliability of chemical formulae generation (CFG). IROA uses two different 13 C-enriched carbon sources (randomized 95% 12 C and 95% 13 C) to produce mirror image isotopologue pairs, whose mass difference reveals the carbon chain length (n), which aids in the identification of endogenous metabolites. Accurate m/z, n, and derivatization information are obtained from our GC/MS workflow for unknown metabolite identification, and aids in silico methodologies for identifying isomeric and non-annotated metabolites. We were able to mine more mass spectral information using the same Saccharomyces cerevisiae growth protocol (Qiu et al. Anal. Chem 2016) with the ultra-high resolution GC-Orbitrap/MS, using 10% ammonia in methane as the CI reagent gas. We identified 244 IROA peaks pairs, which significantly increased IROA detection capability compared with our previous report (126 IROA peak pairs using a GC-TOF/MS machine). For 55 selected metabolites identified from matched IROA CI and EI spectra, using the GC-Orbitrap/MS vs. GC-TOF/MS, the average mass deviation for GC-Orbitrap/MS was 1.48 ppm, however, the average mass deviation was 32.2 ppm for the GC-TOF/MS machine. In summary, the higher resolution and wider dynamic range of the GC-Orbitrap/MS enabled more accurate CFG, and the coupling of accurate mass GC/MS IROA methodology with in silico fragmentation has great potential in unknown metabolite identification, with applications for characterizing model organism networks.

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.

Similarities among receptor pockets and among compounds: analysis and application to in silico ligand screening.

PubMed

Fukunishi, Yoshifumi; Mikami, Yoshiaki; Nakamura, Haruki

2005-09-01

We developed a new method to evaluate the distances and similarities between receptor pockets or chemical compounds based on a multi-receptor versus multi-ligand docking affinity matrix. The receptors were classified by a cluster analysis based on calculations of the distance between receptor pockets. A set of low homologous receptors that bind a similar compound could be classified into one cluster. Based on this line of reasoning, we proposed a new in silico screening method. According to this method, compounds in a database were docked to multiple targets. The new docking score was a slightly modified version of the multiple active site correction (MASC) score. Receptors that were at a set distance from the target receptor were not included in the analysis, and the modified MASC scores were calculated for the selected receptors. The choice of the receptors is important to achieve a good screening result, and our clustering of receptors is useful to this purpose. This method was applied to the analysis of a set of 132 receptors and 132 compounds, and the results demonstrated that this method achieves a high hit ratio, as compared to that of a uniform sampling, using a receptor-ligand docking program, Sievgene, which was newly developed with a good docking performance yielding 50.8% of the reconstructed complexes at a distance of less than 2 A RMSD.

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.

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.

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.

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

Pharmacological validation of in-silico guided novel nootropic potential of Achyranthes aspera L.

PubMed

Gawande, Dinesh Yugraj; Goel, Rajesh Kumar

2015-12-04

Achyranthes aspera (A. aspera) has been used as a brain tonic in folk medicine. Although, ethnic use of medicinal plant has been basis for drug discovery from medicinal plants, but the available in-silico tools can be useful to find novel pharmacological uses of medicinal plants beyond their ethnic use. To validate in-silico prediction for novel nootropic effect of A. aspera by employing battery of tests in mice. Phytoconstituents of A. aspera reported in Dictionary of Natural Product were subjected to in-silico prediction using PASS and Pharmaexpert. The nootropic activity predicted for A. aspera was assessed using radial arm maze, passive shock avoidance and novel object recognition tests in mice. After behavioral evaluation animals were decapitated and their brains were collected and stored for estimation of glutamate levels and acetylcholinesterase activity. In-silico activity spectrum for majority of A. aspera phytoconstituents exhibited excellent prediction score for nootropic activity of this plant. A. aspera extract treatment significantly improved the learning and memory as evident by decreased working memory errors, reference memory errors and latency time in radial arm maze, step through latency in passive shock avoidance and increased recognition index in novel object recognition were observed, moreover significantly enhanced glutamate levels and reduced acetylcholinesterase activity in hippocampus and cortex were observed as compared to the saline treated group. In-silico and in-vivo results suggest that A. aspera plant may improve the learning and memory by modulating the brain glutamatergic and cholinergic neurotransmission. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Benefit of particle therapy in re-irradiation of head and neck patients. Results of a multicentric in silico ROCOCO trial.

PubMed

Eekers, Daniëlle B P; Roelofs, Erik; Jelen, Urszula; Kirk, Maura; Granzier, Marlies; Ammazzalorso, Filippo; Ahn, Peter H; Janssens, Geert O R J; Hoebers, Frank J P; Friedmann, Tobias; Solberg, Timothy; Walsh, Sean; Troost, Esther G C; Kaanders, Johannes H A M; Lambin, Philippe

2016-12-01

In this multicentric in silico trial we compared photon, proton, and carbon-ion radiotherapy plans for re-irradiation of patients with squamous cell carcinoma of the head and neck (HNSCC) regarding dose to tumour and doses to surrounding organs at risk (OARs). Twenty-five HNSCC patients with a second new or recurrent cancer after previous irradiation (70Gy) were included. Intensity-modulated proton therapy (IMPT) and ion therapy (IMIT) re-irradiation plans to a second subsequent dose of 70Gy were compared to photon therapy delivered with volumetric modulated arc therapy (VMAT). When comparing IMIT and IMPT to VMAT, the mean dose to all investigated 22 OARs was significantly reduced for IMIT and to 15 out of 22 OARs (68%) using IMPT. The maximum dose to 2% volume (D 2 ) of the brainstem and spinal cord were significantly reduced using IMPT and IMIT compared to VMAT. The data are available on www.cancerdata.org. In this ROCOCO in silico trial, a reduction in mean dose to OARs was achieved using particle therapy compared to photons in the re-irradiation of HNSCC. There was a dosimetric benefit favouring carbon-ions above proton therapy. These dose reductions may potentially translate into lower severe complication rates related to the re-irradiation. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

The Virtual Anemia Trial: An Assessment of Model-Based In Silico Clinical Trials of Anemia Treatment Algorithms in Patients With Hemodialysis.

PubMed

Fuertinger, Doris H; Topping, Alice; Kappel, Franz; Thijssen, Stephan; Kotanko, Peter

2018-04-01

In silico approaches have been proposed as a novel strategy to increase the repertoire of clinical trial designs. Realistic simulations of clinical trials can provide valuable information regarding safety and limitations of treatment protocols and have been shown to assist in the cost-effective planning of clinical studies. In this report, we present a blueprint for the stepwise integration of internal, external, and ecological validity considerations in virtual clinical trials (VCTs). We exemplify this approach in the context of a model-based in silico clinical trial aimed at anemia treatment in patients undergoing hemodialysis (HD). Hemoglobin levels and subsequent anemia treatment were simulated on a per patient level over the course of a year and compared to real-life clinical data of 79,426 patients undergoing HD. The novel strategies presented here, aimed to improve external and ecological validity of a VCT, significantly increased the predictive power of the discussed in silico trial. © 2018 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

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 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.

Interplay between CedA, rpoB and double stranded DNA: A step towards understanding CedA mediated cell division in E. coli.

PubMed

Sharma, Pankaj; Tomar, Anil Kumar; Kundu, Bishwajit

2018-02-01

Cell division is compromised in DnaAcos mutant E. coli cells due to chromosome over-replication. In these cells, CedA acts as a regulatory protein and initiates cell division by a hitherto unknown mechanism. CedA, a double stranded DNA binding protein, interacts with various subunits of RNA polymerase complex, including rpoB. To reveal how this concert between CedA, rpoB and DNA brings about cell division in E. coli, we performed biophysical and in silico analysis and obtained mechanistic insights. Interaction between CedA and rpoB was shown by circular dichroism spectrometry and in silico docking experiments. Further, CedA and rpoB were allowed to interact individually to a selected DNA and their binding was monitored by fluorescence spectroscopy. The binding constants of these interactions as determined by BioLayer Interferometry clearly show that rpoB binds to DNA with higher affinity (K D2 =<1.0E-12M) as compared to CedA (K D2 =9.58E-09M). These findings were supported by docking analysis where 12 intermolecular H-bonds were formed in rpoB-DNA complex as compared to 4 in CedA-DNA complex. Based on our data we propose that in E. coli cells chromosome over-replication signals CedA to recruit rpoB to specific DNA site(s), which initiates transcription of cell division regulatory elements. Copyright © 2017 Elsevier B.V. All rights reserved.

MobilomeFINDER: web-based tools for in silico and experimental discovery of bacterial genomic islands

PubMed Central

Ou, Hong-Yu; He, Xinyi; Harrison, Ewan M.; Kulasekara, Bridget R.; Thani, Ali Bin; Kadioglu, Aras; Lory, Stephen; Hinton, Jay C. D.; Barer, Michael R.; Rajakumar, Kumar

2007-01-01

MobilomeFINDER (http://mml.sjtu.edu.cn/MobilomeFINDER) is an interactive online tool that facilitates bacterial genomic island or ‘mobile genome’ (mobilome) discovery; it integrates the ArrayOme and tRNAcc software packages. ArrayOme utilizes a microarray-derived comparative genomic hybridization input data set to generate ‘inferred contigs’ produced by merging adjacent genes classified as ‘present’. Collectively these ‘fragments’ represent a hypothetical ‘microarray-visualized genome (MVG)’. ArrayOme permits recognition of discordances between physical genome and MVG sizes, thereby enabling identification of strains rich in microarray-elusive novel genes. Individual tRNAcc tools facilitate automated identification of genomic islands by comparative analysis of the contents and contexts of tRNA sites and other integration hotspots in closely related sequenced genomes. Accessory tools facilitate design of hotspot-flanking primers for in silico and/or wet-science-based interrogation of cognate loci in unsequenced strains and analysis of islands for features suggestive of foreign origins; island-specific and genome-contextual features are tabulated and represented in schematic and graphical forms. To date we have used MobilomeFINDER to analyse several Enterobacteriaceae, Pseudomonas aeruginosa and Streptococcus suis genomes. MobilomeFINDER enables high-throughput island identification and characterization through increased exploitation of emerging sequence data and PCR-based profiling of unsequenced test strains; subsequent targeted yeast recombination-based capture permits full-length sequencing and detailed functional studies of novel genomic islands. PMID:17537813

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.

LipidFrag: Improving reliability of in silico fragmentation of lipids and application to the Caenorhabditis elegans lipidome

PubMed Central

Neumann, Steffen; Schmitt-Kopplin, Philippe

2017-01-01

Lipid identification is a major bottleneck in high-throughput lipidomics studies. However, tools for the analysis of lipid tandem MS spectra are rather limited. While the comparison against spectra in reference libraries is one of the preferred methods, these libraries are far from being complete. In order to improve identification rates, the in silico fragmentation tool MetFrag was combined with Lipid Maps and lipid-class specific classifiers which calculate probabilities for lipid class assignments. The resulting LipidFrag workflow was trained and evaluated on different commercially available lipid standard materials, measured with data dependent UPLC-Q-ToF-MS/MS acquisition. The automatic analysis was compared against manual MS/MS spectra interpretation. With the lipid class specific models, identification of the true positives was improved especially for cases where candidate lipids from different lipid classes had similar MetFrag scores by removing up to 56% of false positive results. This LipidFrag approach was then applied to MS/MS spectra of lipid extracts of the nematode Caenorhabditis elegans. Fragments explained by LipidFrag match known fragmentation pathways, e.g., neutral losses of lipid headgroups and fatty acid side chain fragments. Based on prediction models trained on standard lipid materials, high probabilities for correct annotations were achieved, which makes LipidFrag a good choice for automated lipid data analysis and reliability testing of lipid identifications. PMID:28278196

In silico genomic analyses reveal three distinct lineages of Escherichia coli O157:H7, one of which is associated with hyper-virulence.

PubMed

Laing, Chad R; Buchanan, Cody; Taboada, Eduardo N; Zhang, Yongxiang; Karmali, Mohamed A; Thomas, James E; Gannon, Victor Pj

2009-06-29

Many approaches have been used to study the evolution, population structure and genetic diversity of Escherichia coli O157:H7; however, observations made with different genotyping systems are not easily relatable to each other. Three genetic lineages of E. coli O157:H7 designated I, II and I/II have been identified using octamer-based genome scanning and microarray comparative genomic hybridization (mCGH). Each lineage contains significant phenotypic differences, with lineage I strains being the most commonly associated with human infections. Similarly, a clade of hyper-virulent O157:H7 strains implicated in the 2006 spinach and lettuce outbreaks has been defined using single-nucleotide polymorphism (SNP) typing. In this study an in silico comparison of six different genotyping approaches was performed on 19 E. coli genome sequences from 17 O157:H7 strains and single O145:NM and K12 MG1655 strains to provide an overall picture of diversity of the E. coli O157:H7 population, and to compare genotyping methods for O157:H7 strains. In silico determination of lineage, Shiga-toxin bacteriophage integration site, comparative genomic fingerprint, mCGH profile, novel region distribution profile, SNP type and multi-locus variable number tandem repeat analysis type was performed and a supernetwork based on the combination of these methods was produced. This supernetwork showed three distinct clusters of strains that were O157:H7 lineage-specific, with the SNP-based hyper-virulent clade 8 synonymous with O157:H7 lineage I/II. Lineage I/II/clade 8 strains clustered closest on the supernetwork to E. coli K12 and E. coli O55:H7, O145:NM and sorbitol-fermenting O157 strains. The results of this study highlight the similarities in relationships derived from multi-locus genome sampling methods and suggest a "common genotyping language" may be devised for population genetics and epidemiological studies. Future genotyping methods should provide data that can be stored centrally and accessed locally in an easily transferable, informative and extensible format based on comparative genomic analyses.

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.

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.

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.

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.

Comparative studies of three cholesteryl ester transfer proteins and their interactions with known inhibitors

PubMed Central

Wang, Ziyun; Niimi, Manabu; Ding, Qianzhi; Liu, Zhenming; Wang, Ling; Zhang, Jifeng; Xu, Jun

2017-01-01

Cholesteryl ester transfer protein (CETP) is a plasma protein that mediates bidirectional transfers of cholesteryl esters and triglycerides between low-density lipoproteins and high-density lipoproteins (HDL). Because low levels of plasma CETP are associated with increased plasma HDL-cholesterol, therapeutic inhibition of CETP activity is considered an attractive strategy for elevating plasma HDL-cholesterol, thereby hoping to reduce the risk of cardiovascular disease. Interestingly, only a few laboratory animals, such as rabbits, guinea pigs, and hamsters, have plasma CETP activity, whereas mice and rats do not. It is not known whether all CETPs in these laboratory animals are functionally similar to human CETP. In the current study, we compared plasma CETP activity and characterized the plasma lipoprotein profiles of these animals. Furthermore, we studied the three CETP molecular structures, physicochemical characteristics, and binding properties with known CETP inhibitors in silico. Our results showed that rabbits exhibited higher CETP activity than guinea pigs and hamsters, while these animals had different lipoprotein profiles. CETP inhibitors can inhibit rabbit and hamster CETP activity in a similar manner to human CETP. Analysis of CETP molecules in silico revealed that rabbit and hamster CETP showed many features that are similar to human CETP. These results provide novel insights into understanding CETP functions and molecular properties. PMID:28767652

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

The P/N (Positive-to-Negative Links) Ratio in Complex Networks-A Promising In Silico Biomarker for Detecting Changes Occurring in the Human Microbiome.

PubMed

Ma, Zhanshan Sam

2018-05-01

Relatively little progress in the methodology for differentiating between the healthy and diseased microbiomes, beyond comparing microbial community diversities with traditional species richness or Shannon index, has been made. Network analysis has increasingly been called for the task, but most currently available microbiome datasets only allows for the construction of simple species correlation networks (SCNs). The main results from SCN analysis are a series of network properties such as network degree and modularity, but the metrics for these network properties often produce inconsistent evidence. We propose a simple new network property, the P/N ratio, defined as the ratio of positive links to the number of negative links in the microbial SCN. We postulate that the P/N ratio should reflect the balance between facilitative and inhibitive interactions among microbial species, possibly one of the most important changes occurring in diseased microbiome. We tested our hypothesis with five datasets representing five major human microbiome sites and discovered that the P/N ratio exhibits contrasting differences between healthy and diseased microbiomes and may be harnessed as an in silico biomarker for detecting disease-associated changes in the human microbiome, and may play an important role in personalized diagnosis of the human microbiome-associated diseases.

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

Cyclin D1 G870A polymorphism: Association with uterine leiomyoma risk and in silico analysis

PubMed Central

Salimi, Saeedeh; Shahrakipour, Mahnaz; Hajizadeh, Azam; Mokhtari, Mojgan; Mousavi, Mahdieh; Teimoori, Batool; Yaghmaei, Minoo

2017-01-01

Uterine leiomyoma (UL) is the most common benign tumor causing considerable morbidity during the reproductive years in women. Cyclin D1 (CCND1) is a cell cycle regulatory protein that is required for the G1 phase, and increased expression levels of this protein may affect tumorigenesis. The present study aimed to assess the possible effect of the CCND1 G870A polymorphism on UL susceptibility. A total of 154 women with UL and 197 healthy women who were age-, body mass index (BMI)- and ethnicity-matched were genotyped for the CCND1 G870A (rs9344) polymorphism using the polymerase chain reaction-restriction fragment length polymorphism method. The effects of G870A transition on the structure of mRNA and proteins of CCND1 was evaluated using bioinformatics tools. The frequency of the CCND1 870AA genotype was significantly higher in women with UL compared with the control subjects, and the risk of UL was 1.4-fold higher in women with the AA genotype when compared with the GG genotype before and after adjusting for age, BMI, and ethnicity [odds ratio (OR), 1.4; 95% confidence interval (CI), 1.1–2 (P=0.02)]. The frequency of CCND1 870GA genotype was not significantly different between the two groups. The frequency of the CCND1 870A allele was significantly higher in the women with UL when compared with the control subjects (57 vs. 48%; P=0.02). The in silico analysis revealed that the G870A transition may fundamentally alter the structure of the CCND1-mRNA. Thus, the CCND1 870AA genotype was associated with UL susceptibility in a sample of women from the southeast of Iran. PMID:28357079

In silico and experimental evaluation of DNA-based detection methods for the ability to discriminate almond from other Prunus spp.

PubMed

Brežná, Barbara; Šmíd, Jiří; Costa, Joana; Radvanszky, Jan; Mafra, Isabel; Kuchta, Tomáš

2015-04-01

Ten published DNA-based analytical methods aiming at detecting material of almond (Prunus dulcis) were in silico evaluated for potential cross-reactivity with other stone fruits (Prunus spp.), including peach, apricot, plum, cherry, sour cherry and Sargent cherry. For most assays, the analysis of nucleotide databases suggested none or insufficient discrimination of at least some stone fruits. On the other hand, the assay targeting non-specific lipid transfer protein (Röder et al., 2011, Anal Chim Acta 685:74-83) was sufficiently discriminative, judging from nucleotide alignments. Empirical evaluation was performed for three of the published methods, one modification of a commercial kit (SureFood allergen almond) and one attempted novel method targeting thaumatin-like protein gene. Samples of leaves and kernels were used in the experiments. The empirical results were favourable for the method from Röder et al. (2011) and a modification of SureFood allergen almond kit, both showing cross-reactivity <10(-3) compared to the model almond. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

In silico approach to explore the disruption in the molecular mechanism of human hyaluronidase 1 by mutant E268K that directs Natowicz syndrome.

PubMed

Meshach Paul, D; Rajasekaran, R

2017-03-01

Natowicz syndrome (mucopolysaccharidoses type 9) is a lysosomal storage disorder caused by deficient or defective human hyaluronidase 1. The disorder is not well studied at the molecular level. Therefore, a new in silico approach was proposed to study the molecular basis on which one clinically observed mutation, Glu268Lys, results in a defective enzyme. The native and mutant structures were subjected to comparative analyses using a conformational sampling approach for geometrical variables viz, RMSF, RMSD, and Ramachandran plot. In addition, the strength of a Cys207-Cys221 disulfide bond and electrostatic interaction between Arg265 and Asp206 were studied, as they are known to be involved in the catalytic activity of the enzyme. Native and mutant E268K showed statistically significant variations with p < 0.05 in RMSD, Ramachandran plot, strengths of disulfide bond, and electrostatic interactions. Further, single model analysis showed variations between native and mutant structures in terms of intra-protein interactions, hydrogen bond dilution, secondary structure, and dihedral angles. Docking analysis predicted the mutant to have a less favorable substrate binding energy compared to the native protein. Additionally, steered MD analysis indicated that the substrate should have more affinity to the native than mutant enzymes. The observed changes theoretically explain the less favorable binding energy of substrate towards mutant E268K, thereby providing a structural basis for its reduced catalytic activity. Hence, our study provides a basis for understanding the disruption in the molecular mechanism of human hyaluronidase 1 by mutation E268K, which may prove useful for the development of synthetic chaperones as a treatment option for Natowicz syndrome.

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.

A new in silico classification model for ready biodegradability, based on molecular fragments.

PubMed

Lombardo, Anna; Pizzo, Fabiola; Benfenati, Emilio; Manganaro, Alberto; Ferrari, Thomas; Gini, Giuseppina

2014-08-01

Regulations such as the European REACH (Registration, Evaluation, Authorization and restriction of Chemicals) often require chemicals to be evaluated for ready biodegradability, to assess the potential risk for environmental and human health. Because not all chemicals can be tested, there is an increasing demand for tools for quick and inexpensive biodegradability screening, such as computer-based (in silico) theoretical models. We developed an in silico model starting from a dataset of 728 chemicals with ready biodegradability data (MITI-test Ministry of International Trade and Industry). We used the novel software SARpy to automatically extract, through a structural fragmentation process, a set of substructures statistically related to ready biodegradability. Then, we analysed these substructures in order to build some general rules. The model consists of a rule-set made up of the combination of the statistically relevant fragments and of the expert-based rules. The model gives good statistical performance with 92%, 82% and 76% accuracy on the training, test and external set respectively. These results are comparable with other in silico models like BIOWIN developed by the United States Environmental Protection Agency (EPA); moreover this new model includes an easily understandable explanation. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

In silico method for modelling metabolism and gene product expression at genome scale

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

Lerman, Joshua A.; Hyduke, Daniel R.; Latif, Haythem

2012-07-03

Transcription and translation use raw materials and energy generated metabolically to create the macromolecular machinery responsible for all cellular functions, including metabolism. A biochemically accurate model of molecular biology and metabolism will facilitate comprehensive and quantitative computations of an organism's molecular constitution as a function of genetic and environmental parameters. Here we formulate a model of metabolism and macromolecular expression. Prototyping it using the simple microorganism Thermotoga maritima, we show our model accurately simulates variations in cellular composition and gene expression. Moreover, through in silico comparative transcriptomics, the model allows the discovery of new regulons and improving the genome andmore » transcription unit annotations. Our method presents a framework for investigating molecular biology and cellular physiology in silico and may allow quantitative interpretation of multi-omics data sets in the context of an integrated biochemical description of an organism.« less

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

Novel Polyurethane Matrix Systems Reveal a Particular Sustained Release Behavior Studied by Imaging and Computational Modeling.

PubMed

Campiñez, María Dolores; Caraballo, Isidoro; Puchkov, Maxim; Kuentz, Martin

2017-07-01

The aim of the present work was to better understand the drug-release mechanism from sustained release matrices prepared with two new polyurethanes, using a novel in silico formulation tool based on 3-dimensional cellular automata. For this purpose, two polymers and theophylline as model drug were used to prepare binary matrix tablets. Each formulation was simulated in silico, and its release behavior was compared to the experimental drug release profiles. Furthermore, the polymer distributions in the tablets were imaged by scanning electron microscopy (SEM) and the changes produced by the tortuosity were quantified and verified using experimental data. The obtained results showed that the polymers exhibited a surprisingly high ability for controlling drug release at low excipient concentrations (only 10% w/w of excipient controlled the release of drug during almost 8 h). The mesoscopic in silico model helped to reveal how the novel biopolymers were controlling drug release. The mechanism was found to be a special geometrical arrangement of the excipient particles, creating an almost continuous barrier surrounding the drug in a very effective way, comparable to lipid or waxy excipients but with the advantages of a much higher compactability, stability, and absence of excipient polymorphism.

In-silico wear prediction for knee replacements--methodology and corroboration.

PubMed

Strickland, M A; Taylor, M

2009-07-22

The capability to predict in-vivo wear of knee replacements is a valuable pre-clinical analysis tool for implant designers. Traditionally, time-consuming experimental tests provided the principal means of investigating wear. Today, computational models offer an alternative. However, the validity of these models has not been demonstrated across a range of designs and test conditions, and several different formulas are in contention for estimating wear rates, limiting confidence in the predictive power of these in-silico models. This study collates and retrospectively simulates a wide range of experimental wear tests using fast rigid-body computational models with extant wear prediction algorithms, to assess the performance of current in-silico wear prediction tools. The number of tests corroborated gives a broader, more general assessment of the performance of these wear-prediction tools, and provides better estimates of the wear 'constants' used in computational models. High-speed rigid-body modelling allows a range of alternative algorithms to be evaluated. Whilst most cross-shear (CS)-based models perform comparably, the 'A/A+B' wear model appears to offer the best predictive power amongst existing wear algorithms. However, the range and variability of experimental data leaves considerable uncertainty in the results. More experimental data with reduced variability and more detailed reporting of studies will be necessary to corroborate these models with greater confidence. With simulation times reduced to only a few minutes, these models are ideally suited to large-volume 'design of experiment' or probabilistic studies (which are essential if pre-clinical assessment tools are to begin addressing the degree of variation observed clinically and in explanted components).

A validated method for modeling anthropoid hip abduction in silico.

PubMed

Hammond, Ashley S; Plavcan, J Michael; Ward, Carol V

2016-07-01

The ability to reconstruct hip joint mobility from femora and pelves could provide insight into the locomotion and paleobiology of fossil primates. This study presents a method for modeling hip abduction in anthropoids validated with in vivo data. Hip abduction simulations were performed on a large sample of anthropoids. The modeling approach integrates three-dimensional (3D) polygonal models created from laser surface scans of bones, 3D landmark data, and shape analysis software to digitally articulate and manipulate the hip joint. Range of femoral abduction (degrees) and the abducted knee position (distance spanned at the knee during abduction) were compared with published live animal data. The models accurately estimate knee position and (to a lesser extent) angular abduction across broad locomotor groups. They tend to underestimate abduction for acrobatic or suspensory taxa, but overestimate it in more stereotyped taxa. Correspondence between in vivo and in silico data varies at the specific and generic level. Our models broadly correspond to in vivo data on hip abduction, although the relationship between the models and live animal data is less straightforward than hypothesized. The models can predict acrobatic or stereotyped locomotor adaptation for taxa with values near the extremes of the range of abduction ability. Our findings underscore the difficulties associated with modeling complex systems and the importance of validating in silico models. They suggest that models of joint mobility can offer additional insight into the functional abilities of extinct primates when done in consideration of how joints move and function in vivo. Am J Phys Anthropol 160:529-548, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

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.

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

PubMed

Nasir, Muhammad; Ahmad, Nafees; Sieber, Christian M K; Latif, Amir; Malik, Salman Akbar; Hameed, Abdul

2013-09-24

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. 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. 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.

Meal Disturbance Effect on Control of Blood Glucose Level for Critically-ill Patients using In-silico Works

NASA Astrophysics Data System (ADS)

Yusof, N. F. M.; Som, A. M.; Ali, S. A.; Azman, N. H.

2018-05-01

This study was conducted to determine the effect of meal disturbance on blood glucose level of the critically ill patients and to simulate the control algorithm previously developed using in-silico works. The study is significant so as to reduce the mortality rate of critically ill patients who usually encounter hyperglycaemia or/and hypoglycaemia while in treatment. The meal intake is believed to affect the blood glucose regulation and causes the hyperglycaemia to occur. Critically ill patients receive their meal through parenteral and enteral nutrition. Furthermore, by using in-silico works, time consumed and resources needed for clinical evaluation of the patients can be reduced. Hovorka model was employed in which the simulation study was carried out using MATLAB on the virtual patient and it was being compared with actual patient in which the data were provided by Institut Jantung Negara (IJN). Based on the simulation, the disturbance on enteral glucose supplied had affected the blood glucose level of the patient; however, it remained unchanged for the parental glucose. To reduce the occurrence of hypoglycaemia and hyperglycaemia, the patient was injected with 30 g/hr and 10 g/hr of enteral glucose, respectively. In conclusion, the disturbance of meal received can be controlled through in-silico works.

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

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 study of carvone derivatives as potential neuraminidase inhibitors.

PubMed

Jusoh, Noorakmar; Zainal, Hasanuddin; Abdul Hamid, Azzmer Azzar; Bunnori, Noraslinda M; Abd Halim, Khairul Bariyyah; Abd Hamid, Shafida

2018-03-15

Recent outbreaks of highly pathogenic influenza strains have highlighted the need to develop new anti-influenza drugs. Here, we report an in silico study of carvone derivatives to analyze their binding modes with neuraminidase (NA) active sites. Two proposed carvone analogues, CV(A) and CV(B), with 36 designed ligands were predicted to inhibit NA (PDB ID: 3TI6) using molecular docking. The design is based on structural resemblance with the commercial inhibitor, oseltamivir (OTV), ligand polarity, and amino acid residues in the NA active sites. Docking simulations revealed that ligand A18 has the lowest energy binding (∆G bind ) value of -8.30 kcal mol -1 , comparable to OTV with ∆G bind of -8.72 kcal mol -1 . A18 formed seven hydrogen bonds (H-bonds) at residues Arg292, Arg371, Asp151, Trp178, Glu227, and Tyr406, while eight H-bonds were formed by OTV with amino acids Arg118, Arg292, Arg371, Glu119, Asp151, and Arg152. Molecular dynamics (MD) simulation was conducted to compare the stability between ligand A18 and OTV with NA. Our simulation study showed that the A18-NA complex is as stable as the OTV-NA complex during the MD simulation of 50 ns through the analysis of RMSD, RMSF, total energy, hydrogen bonding, and MM/PBSA free energy calculations.

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.

In silico studies on tryparedoxin peroxidase of Leishmania infantum: structural aspects.

PubMed

Singh, Bishal Kumar; Dubey, Vikash Kumar

2009-09-01

Tryparedoxin peroxidase (TryP) is a key enzyme of the trypanothione-dependent metabolism for removal of oxidative stress in leishmania. These enzymes function as antioxidants through their peroxidase and peroxynitrite reductase activities. Inhibitors of this enzyme are presumed to be antilesihmania drugs and structural studies are prerequisite of rational drug design. We have constructed three dimensional structure of TryP of Leishmania infantum using comparative modeling. Structural analysis reveals several interesting features. Moreover, it shows remarkable structural difference with human host glutathione peroxidase, an enzyme involved in similar function and TryP from Leishmania major.

Inhibition of MAO-A and stimulation of behavioural activities in mice by the inactive prodrug form of the anti-influenza agent oseltamivir.

PubMed

Hiasa, Miki; Isoda, Yumiko; Kishimoto, Yasushi; Saitoh, Kenta; Kimura, Yasuaki; Kanai, Motomu; Shibasaki, Masakatsu; Hatakeyama, Dai; Kirino, Yutaka; Kuzuhara, Takashi

2013-05-01

Oseltamivir is the most widely prescribed anti-influenza medication. However, in rare instances, it has been reported to stimulate behavioural activities in adolescents. The goal of this study was to determine the molecular mechanism responsible for these behavioural activities. We performed an in vitro assay of MAO-A, the enzyme responsible for neurotransmitter degradation, using either the active form - oseltamivir carboxylate (OC) or the inactive prodrug - oseltamivir ethyl ester (OEE). We also analysed the docking of MAO-A with OEE or OC in silico. Mouse behaviours after OEE or OC administration were monitored using automated video and computer analysis. OEE, but not OC, competitively and selectively inhibited human MAO-A. The estimated Ki value was comparable with the Km values of native substrates of MAO-A. Docking simulations in silico based on the tertiary structure of MAO-A suggested that OEE could fit into the inner pocket of the enzyme. Behavioural monitoring using automated video analysis further revealed that OEE, not OC, significantly enhanced spontaneous behavioural activities in mice, such as jumping, rearing, sniffing, turning and walking. Our multilevel analyses suggested OEE to be the cause of the side effects associated with oseltamivir and revealed the molecular mechanism underlying the stimulated behaviours induced by oseltamivir in some circumstances. © 2013 The Authors. British Journal of Pharmacology © 2013 The British Pharmacological Society.

Inhibition of MAO-A and stimulation of behavioural activities in mice by the inactive prodrug form of the anti-influenza agent oseltamivir

PubMed Central

Hiasa, Miki; Isoda, Yumiko; Kishimoto, Yasushi; Saitoh, Kenta; Kimura, Yasuaki; Kanai, Motomu; Shibasaki, Masakatsu; Hatakeyama, Dai; Kirino, Yutaka; Kuzuhara, Takashi

2013-01-01

Background and Purpose Oseltamivir is the most widely prescribed anti-influenza medication. However, in rare instances, it has been reported to stimulate behavioural activities in adolescents. The goal of this study was to determine the molecular mechanism responsible for these behavioural activities. Experimental Approach We performed an in vitro assay of MAO-A, the enzyme responsible for neurotransmitter degradation, using either the active form – oseltamivir carboxylate (OC) or the inactive prodrug – oseltamivir ethyl ester (OEE). We also analysed the docking of MAO-A with OEE or OC in silico. Mouse behaviours after OEE or OC administration were monitored using automated video and computer analysis. Key Results OEE, but not OC, competitively and selectively inhibited human MAO-A. The estimated Ki value was comparable with the Km values of native substrates of MAO-A. Docking simulations in silico based on the tertiary structure of MAO-A suggested that OEE could fit into the inner pocket of the enzyme. Behavioural monitoring using automated video analysis further revealed that OEE, not OC, significantly enhanced spontaneous behavioural activities in mice, such as jumping, rearing, sniffing, turning and walking. Conclusions and Implications Our multilevel analyses suggested OEE to be the cause of the side effects associated with oseltamivir and revealed the molecular mechanism underlying the stimulated behaviours induced by oseltamivir in some circumstances. PMID:23320399

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 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

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.

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.

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

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.

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

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.

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.

In Vitro and In Silico Antidiabetic and Antimicrobial Evaluation of Constituents from Kickxia ramosissima (Nanorrhinum ramosissimum)

PubMed Central

Amin, Adnan; Tuenter, Emmy; Foubert, Kenn; Iqbal, Jamhsed; Cos, Paul; Maes, Louis; Exarchou, Vassiliki; Apers, Sandra; Pieters, Luc

2017-01-01

Background and Aims: Kickxia ramosissima (Wall.) Janch (or Nanorrhinum ramosissimum (Wall.) Betsche is a well-known medicinal plant in Pakistan that is traditionally used in diabetic and inflammatory conditions. Because little information is available on its phytochemical composition, a range of constituents were isolated and evaluated in vitro in assays related to the traditional use. Methods: Dried whole plant material was extracted and chromatographically fractionated. Isolated constituents were evaluated in silico and in vitro in assays related to the traditional use against diabetes (inhibition of α-glucosidase activity; inhibition of advanced glycation endproducts) and in inflammatory conditions (inhibition of AAPH induced linoleic acid peroxidation, inhibition of 15-LOX, antimicrobial activity). Results: Phytochemical analysis of the extracts and fractions led to isolation of 7 compounds, including the iridoids kickxiasine (being a new compound), mussaenosidic acid, mussaenoside and linarioside; the flavonoids pectolinarigenin and pectolinarin; and 4-hydroxy-benzoic acid methyl ester. The iridoids showed weak antiglycation activity. The flavonoids, however, showed interesting results as pectolinarigenin was highly active compared to pectolinarin. In the α-glucosidase inhibition assay, only weak activity was observed for the iridoids. However, the flavonoid pectolinarigenin showed good activity, followed by pectolinarin. In the 15-LOX experiment, moderate inhibition was recorded for most compounds, the iridoids mussaenosidic acid and mussaenoside being the most active. In the AAPH assay, weak or no inhibition was recorded for all compounds. The in silico assays for the α-glucosidase and 15-LOX assays confirmed the results of respective in vitro assays. Pectolinarigenin showed moderate antimicrobial activity against Staphylococcus aureus, Plasmodium falciparum K1, and Trypanosoma cruzi, but it was not cytotoxic on a human MRC-5 cell line. Conclusion: Our findings may in part contribute to explain the traditional use of K. ramosissima. PMID:28507520

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.

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

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.

Modeling Dynamic Contrast-Enhanced MRI Data with a Constrained Local AIF.

PubMed

Duan, Chong; Kallehauge, Jesper F; Pérez-Torres, Carlos J; Bretthorst, G Larry; Beeman, Scott C; Tanderup, Kari; Ackerman, Joseph J H; Garbow, Joel R

2018-02-01

This study aims to develop a constrained local arterial input function (cL-AIF) to improve quantitative analysis of dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) data by accounting for the contrast-agent bolus amplitude error in the voxel-specific AIF. Bayesian probability theory-based parameter estimation and model selection were used to compare tracer kinetic modeling employing either the measured remote-AIF (R-AIF, i.e., the traditional approach) or an inferred cL-AIF against both in silico DCE-MRI data and clinical, cervical cancer DCE-MRI data. When the data model included the cL-AIF, tracer kinetic parameters were correctly estimated from in silico data under contrast-to-noise conditions typical of clinical DCE-MRI experiments. Considering the clinical cervical cancer data, Bayesian model selection was performed for all tumor voxels of the 16 patients (35,602 voxels in total). Among those voxels, a tracer kinetic model that employed the voxel-specific cL-AIF was preferred (i.e., had a higher posterior probability) in 80 % of the voxels compared to the direct use of a single R-AIF. Maps of spatial variation in voxel-specific AIF bolus amplitude and arrival time for heterogeneous tissues, such as cervical cancer, are accessible with the cL-AIF approach. The cL-AIF method, which estimates unique local-AIF amplitude and arrival time for each voxel within the tissue of interest, provides better modeling of DCE-MRI data than the use of a single, measured R-AIF. The Bayesian-based data analysis described herein affords estimates of uncertainties for each model parameter, via posterior probability density functions, and voxel-wise comparison across methods/models, via model selection in data modeling.

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.

Anopheles salivary gland proteomes from major malaria vectors

PubMed Central

2012-01-01

Background Antibody responses against Anopheles salivary proteins can indicate individual exposure to bites of malaria vectors. The extent to which these salivary proteins are species-specific is not entirely resolved. Thus, a better knowledge of the diversity among salivary protein repertoires from various malaria vector species is necessary to select relevant genus-, subgenus- and/or species-specific salivary antigens. Such antigens could be used for quantitative (mosquito density) and qualitative (mosquito species) immunological evaluation of malaria vectors/host contact. In this study, salivary gland protein repertoires (sialomes) from several Anopheles species were compared using in silico analysis and proteomics. The antigenic diversity of salivary gland proteins among different Anopheles species was also examined. Results In silico analysis of secreted salivary gland protein sequences retrieved from an NCBInr database of six Anopheles species belonging to the Cellia subgenus (An. gambiae, An. arabiensis, An. stephensi and An. funestus) and Nyssorhynchus subgenus (An. albimanus and An. darlingi) displayed a higher degree of similarity compared to salivary proteins from closely related Anopheles species. Additionally, computational hierarchical clustering allowed identification of genus-, subgenus- and species-specific salivary proteins. Proteomic and immunoblot analyses performed on salivary gland extracts from four Anopheles species (An. gambiae, An. arabiensis, An. stephensi and An. albimanus) indicated that heterogeneity of the salivary proteome and antigenic proteins was lower among closely related anopheline species and increased with phylogenetic distance. Conclusion This is the first report on the diversity of the salivary protein repertoire among species from the Anopheles genus at the protein level. This work demonstrates that a molecular diversity is exhibited among salivary proteins from closely related species despite their common pharmacological activities. The involvement of these proteins as antigenic candidates for genus-, subgenus- or species-specific immunological evaluation of individual exposure to Anopheles bites is discussed. PMID:23148599

Exploiting Genomic Knowledge in Optimising Molecular Breeding Programmes: Algorithms from Evolutionary Computing

PubMed Central

O'Hagan, Steve; Knowles, Joshua; Kell, Douglas B.

2012-01-01

Comparatively few studies have addressed directly the question of quantifying the benefits to be had from using molecular genetic markers in experimental breeding programmes (e.g. for improved crops and livestock), nor the question of which organisms should be mated with each other to best effect. We argue that this requires in silico modelling, an approach for which there is a large literature in the field of evolutionary computation (EC), but which has not really been applied in this way to experimental breeding programmes. EC seeks to optimise measurable outcomes (phenotypic fitnesses) by optimising in silico the mutation, recombination and selection regimes that are used. We review some of the approaches from EC, and compare experimentally, using a biologically relevant in silico landscape, some algorithms that have knowledge of where they are in the (genotypic) search space (G-algorithms) with some (albeit well-tuned ones) that do not (F-algorithms). For the present kinds of landscapes, F- and G-algorithms were broadly comparable in quality and effectiveness, although we recognise that the G-algorithms were not equipped with any ‘prior knowledge’ of epistatic pathway interactions. This use of algorithms based on machine learning has important implications for the optimisation of experimental breeding programmes in the post-genomic era when we shall potentially have access to the full genome sequence of every organism in a breeding population. The non-proprietary code that we have used is made freely available (via Supplementary information). PMID:23185279

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 characterization and expression analysis of the multigene family encoding the Bowman-Birk protease inhibitor in soybean.

PubMed

de Almeida Barros, Beatriz; da Silva, Wiliane Garcia; Moreira, Maurilio Alves; de Barros, Everaldo Gonçalves

2012-01-01

The Bowman-Birk (BBI) protease inhibitors can be used as source of sulfur amino acids, can regulate endogenous protease activity during seed germination and during the defense response of plants to pathogens. In soybean this family has not been fully described. The goal of this work was to characterize in silico and analyze the expression of the members of this family in soybean. We identified 11 potential BBI genes in the soybean genome. In each one of them at least a characteristic BBI conserved domain was detected in addition to a potential signal peptide. The sequences have been positioned in the soybean physical map and the promoter regions were analyzed with respect to known regulatory elements. Elements related to seed-specific expression and also to response to biotic and abiotic stresses have been identified. Based on the in silico analysis and also on quantitative RT-PCR data it was concluded that BBI-A, BBI-CII and BBI-DII are expressed specifically in the seed. The expression profiles of these three genes are similar along seed development. Their expressions reach a maximum in the intermediate stages and decrease as the seed matures. The BBI-DII transcripts are the most abundant ones followed by those of BBI-A and BBI-CII.

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.

AutoClickChem: click chemistry in silico.

PubMed

Durrant, Jacob D; McCammon, J Andrew

2012-01-01

Academic researchers and many in industry often lack the financial resources available to scientists working in "big pharma." High costs include those associated with high-throughput screening and chemical synthesis. In order to address these challenges, many researchers have in part turned to alternate methodologies. Virtual screening, for example, often substitutes for high-throughput screening, and click chemistry ensures that chemical synthesis is fast, cheap, and comparatively easy. Though both in silico screening and click chemistry seek to make drug discovery more feasible, it is not yet routine to couple these two methodologies. We here present a novel computer algorithm, called AutoClickChem, capable of performing many click-chemistry reactions in silico. AutoClickChem can be used to produce large combinatorial libraries of compound models for use in virtual screens. As the compounds of these libraries are constructed according to the reactions of click chemistry, they can be easily synthesized for subsequent testing in biochemical assays. Additionally, in silico modeling of click-chemistry products may prove useful in rational drug design and drug optimization. AutoClickChem is based on the pymolecule toolbox, a framework that may facilitate the development of future python-based programs that require the manipulation of molecular models. Both the pymolecule toolbox and AutoClickChem are released under the GNU General Public License version 3 and are available for download from http://autoclickchem.ucsd.edu.

AutoClickChem: Click Chemistry in Silico

PubMed Central

Durrant, Jacob D.; McCammon, J. Andrew

2012-01-01

Academic researchers and many in industry often lack the financial resources available to scientists working in “big pharma.” High costs include those associated with high-throughput screening and chemical synthesis. In order to address these challenges, many researchers have in part turned to alternate methodologies. Virtual screening, for example, often substitutes for high-throughput screening, and click chemistry ensures that chemical synthesis is fast, cheap, and comparatively easy. Though both in silico screening and click chemistry seek to make drug discovery more feasible, it is not yet routine to couple these two methodologies. We here present a novel computer algorithm, called AutoClickChem, capable of performing many click-chemistry reactions in silico. AutoClickChem can be used to produce large combinatorial libraries of compound models for use in virtual screens. As the compounds of these libraries are constructed according to the reactions of click chemistry, they can be easily synthesized for subsequent testing in biochemical assays. Additionally, in silico modeling of click-chemistry products may prove useful in rational drug design and drug optimization. AutoClickChem is based on the pymolecule toolbox, a framework that may facilitate the development of future python-based programs that require the manipulation of molecular models. Both the pymolecule toolbox and AutoClickChem are released under the GNU General Public License version 3 and are available for download from http://autoclickchem.ucsd.edu. PMID:22438795

In silico clinical trials: concepts and early adoptions.

PubMed

Pappalardo, Francesco; Russo, Giulia; Tshinanu, Flora Musuamba; Viceconti, Marco

2018-06-02

Innovations in information and communication technology infuse all branches of science, including life sciences. Nevertheless, healthcare is historically slow in adopting technological innovation, compared with other industrial sectors. In recent years, new approaches in modelling and simulation have started to provide important insights in biomedicine, opening the way for their potential use in the reduction, refinement and partial substitution of both animal and human experimentation. In light of this evidence, the European Parliament and the United States Congress made similar recommendations to their respective regulators to allow wider use of modelling and simulation within the regulatory process. In the context of in silico medicine, the term 'in silico clinical trials' refers to the development of patient-specific models to form virtual cohorts for testing the safety and/or efficacy of new drugs and of new medical devices. Moreover, it could be envisaged that a virtual set of patients could complement a clinical trial (reducing the number of enrolled patients and improving statistical significance), and/or advise clinical decisions. This article will review the current state of in silico clinical trials and outline directions for a full-scale adoption of patient-specific modelling and simulation in the regulatory evaluation of biomedical products. In particular, we will focus on the development of vaccine therapies, which represents, in our opinion, an ideal target for this innovative approach.

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...

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.

Computational insights of K1444N substitution in GAP-related domain of NF1 gene associated with neurofibromatosis type 1 disease: a molecular modeling and dynamics approach.

PubMed

Agrahari, Ashish Kumar; Muskan, Meghana; George Priya Doss, C; Siva, R; Zayed, Hatem

2018-05-27

The NF1 gene encodes for neurofibromin protein, which is ubiquitously expressed, but most highly in the central nervous system. Non-synonymous SNPs (nsSNPs) in the NF1 gene were found to be associated with Neurofibromatosis Type 1 disease, which is characterized by the growth of tumors along nerves in the skin, brain, and other parts of the body. In this study, we used several in silico predictions tools to analyze 16 nsSNPs in the RAS-GAP domain of neurofibromin, the K1444N (K1423N) mutation was predicted as the most pathogenic. The comparative molecular dynamic simulation (MDS; 50 ns) between the wild type and the K1444N (K1423N) mutant suggested a significant change in the electrostatic potential. In addition, the RMSD, RMSF, Rg, hydrogen bonds, and PCA analysis confirmed the loss of flexibility and increase in compactness of the mutant protein. Further, SASA analysis revealed exchange between hydrophobic and hydrophilic residues from the core of the RAS-GAP domain to the surface of the mutant domain, consistent with the secondary structure analysis that showed significant alteration in the mutant protein conformation. Our data concludes that the K1444N (K1423N) mutant lead to increasing the rigidity and compactness of the protein. This study provides evidence of the benefits of the computational tools in predicting the pathogenicity of genetic mutations and suggests the application of MDS and different in silico prediction tools for variant assessment and classification in genetic clinics.

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.

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/ .

Functional proteomic analyses of Bothrops atrox venom reveals phenotypes associated with habitat variation in the Amazon.

PubMed

Sousa, Leijiane F; Portes-Junior, José A; Nicolau, Carolina A; Bernardoni, Juliana L; Nishiyama, Milton Y; Amazonas, Diana R; Freitas-de-Sousa, Luciana A; Mourão, Rosa Hv; Chalkidis, Hipócrates M; Valente, Richard H; Moura-da-Silva, Ana M

2017-04-21

Venom variability is commonly reported for venomous snakes including Bothrops atrox. Here, we compared the composition of venoms from B. atrox snakes collected at Amazonian conserved habitats (terra-firme upland forest and várzea) and human modified areas (pasture and degraded areas). Venom samples were submitted to shotgun proteomic analysis as a whole or compared after fractionation by reversed-phase chromatography. Whole venom proteomes revealed a similar composition among the venoms with predominance of SVMPs, CTLs, and SVSPs and intermediate amounts of PLA 2 s and LAAOs. However, when distribution of particular isoforms was analyzed by either method, the venom from várzea snakes showed a decrease in hemorrhagic SVMPs and an increase in SVSPs, and procoagulant SVMPs and PLA 2 s. These differences were validated by experimental approaches including both enzymatic and in vivo assays, and indicated restrictions in respect to antivenom efficacy to variable components. Thus, proteomic analysis at the isoform level combined to in silico prediction of functional properties may indicate venom biological activity. These results also suggest that the prevalence of functionally distinct isoforms contributes to the variability of the venoms and could reflect the adaptation of B. atrox to distinct prey communities in different Amazon habitats. In this report, we compared isoforms present in venoms from snakes collected at different Amazonian habitats. By means of a species venom gland transcriptome and the in silico functional prediction of each isoform, we were able to predict the principal venom activities in vitro and in animal models. We also showed remarkable differences in the venom pools from snakes collected at the floodplain (várzea habitat) compared to other habitats. Not only was this venom less hemorrhagic and more procoagulant, when compared to the venom pools from the other three habitats studied, but also this enhanced procoagulant activity was not efficiently neutralized by Bothrops antivenom. Thus, using a functional proteomic approach, we highlighted intraspecific differences in B. atrox venom that could impact both in the ecology of snakes but also in the treatment of snake bite patients in the region. Copyright © 2017 Elsevier B.V. All rights reserved.

[Bone cement adhesion on ceramic surfaces - surface activation of retention surfaces of knee prostheses by atmospheric plasma versus thermal surface treatment].

PubMed

Marx, B; Marx, R; Reisgen, U; Wirtz, D

2015-04-01

CoCrMo alloys are contraindicated for allergy sufferers. For these patients, uncemented and cemented prostheses made of titanium alloy are indicated. Knee prostheses machined from that alloy, however, may have poor tribological behaviour, especially in relation to UHMWPE inlays. Therefore, for knee replacement cemented high-strength oxide ceramic prostheses are suitable for allergy sufferers and in cases of particle-induced aseptic loosening. For adhesion of bone cement, the ceramic surface, however, only exposes inefficient mechanical retention spots as compared with a textured metal surface. Undercuts generated by corundum blasting which in the short-term are highly efficient on a CoCrMo surface are not possible on a ceramic surface due to the brittleness of ceramics. Textures due to blasting may initiate cracks which will weaken the strength of a ceramic prosthesis. Due to the lack of textures mechanical retention is poor or even not existent. Micromotions are promoted and early aseptic loosening is predictable. Instead silicoating of the ceramic surface will allow specific adhesion and result in better hydrolytic stability of bonding thereby preventing early aseptic loosening. Silicoating, however, presupposes a clean and chemically active surface which can be achieved by atmospheric plasma or thermal surface treatment. In order to evaluate the effectiveness of silicoating the bond strengths of atmospheric plasma versus thermal surface treated and silicate layered ZPTA surfaces were compared with "as-fired" surfaces by utilising TiAlV probes (diameter 6 mm) for traction-adhesive strength tests. After preparing samples for traction-adhesive strength tests (sequence: ceramic substrate, silicate and silane, protective lacquer [PolyMA], bone cement, TiAlV probe) they were aged for up to 150 days at 37 °C in Ringer's solution. The bond strengths observed for all ageing intervals were well above 20 MPa and much higher and more hydrolytically stable for silicate layered compared with "as-fired" ZPTA samples. Silicoating may be effective for achieving high initial bond strength of bone cement on surfaces of oxide ceramics and also suitable to stabilise bond strength under hydrolytic conditions as present in the human body in the long-term. Activation by atmospheric plasma or thermal surface treatment seems to be effective for activation prior to silicoating. Due the proposed silicate layer migration, micromotions and debonding should be widely reduced or even eliminated. Georg Thieme Verlag KG Stuttgart · New York.

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

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.

Robust estimation of microbial diversity in theory and in practice

PubMed Central

Haegeman, Bart; Hamelin, Jérôme; Moriarty, John; Neal, Peter; Dushoff, Jonathan; Weitz, Joshua S

2013-01-01

Quantifying diversity is of central importance for the study of structure, function and evolution of microbial communities. The estimation of microbial diversity has received renewed attention with the advent of large-scale metagenomic studies. Here, we consider what the diversity observed in a sample tells us about the diversity of the community being sampled. First, we argue that one cannot reliably estimate the absolute and relative number of microbial species present in a community without making unsupported assumptions about species abundance distributions. The reason for this is that sample data do not contain information about the number of rare species in the tail of species abundance distributions. We illustrate the difficulty in comparing species richness estimates by applying Chao's estimator of species richness to a set of in silico communities: they are ranked incorrectly in the presence of large numbers of rare species. Next, we extend our analysis to a general family of diversity metrics (‘Hill diversities'), and construct lower and upper estimates of diversity values consistent with the sample data. The theory generalizes Chao's estimator, which we retrieve as the lower estimate of species richness. We show that Shannon and Simpson diversity can be robustly estimated for the in silico communities. We analyze nine metagenomic data sets from a wide range of environments, and show that our findings are relevant for empirically-sampled communities. Hence, we recommend the use of Shannon and Simpson diversity rather than species richness in efforts to quantify and compare microbial diversity. PMID:23407313

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.

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 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.

Multi-scale analysis of the effect of nano-filler particle diameter on the physical properties of CAD/CAM composite resin blocks.

PubMed

Yamaguchi, Satoshi; Inoue, Sayuri; Sakai, Takahiko; Abe, Tomohiro; Kitagawa, Haruaki; Imazato, Satoshi

2017-05-01

The objective of this study was to assess the effect of silica nano-filler particle diameters in a computer-aided design/manufacturing (CAD/CAM) composite resin (CR) block on physical properties at the multi-scale in silico. CAD/CAM CR blocks were modeled, consisting of silica nano-filler particles (20, 40, 60, 80, and 100 nm) and matrix (Bis-GMA/TEGDMA), with filler volume contents of 55.161%. Calculation of Young's moduli and Poisson's ratios for the block at macro-scale were analyzed by homogenization. Macro-scale CAD/CAM CR blocks (3 × 3 × 3 mm) were modeled and compressive strengths were defined when the fracture loads exceeded 6075 N. MPS values of the nano-scale models were compared by localization analysis. As the filler size decreased, Young's moduli and compressive strength increased, while Poisson's ratios and MPS decreased. All parameters were significantly correlated with the diameters of the filler particles (Pearson's correlation test, r = -0.949, 0.943, -0.951, 0.976, p < 0.05). The in silico multi-scale model established in this study demonstrates that the Young's moduli, Poisson's ratios, and compressive strengths of CAD/CAM CR blocks can be enhanced by loading silica nanofiller particles of smaller diameter. CAD/CAM CR blocks by using smaller silica nano-filler particles have a potential to increase fracture resistance.

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.

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

Improving draft genome contiguity with reference-derived in silico mate-pair libraries.

PubMed

Grau, José Horacio; Hackl, Thomas; Koepfli, Klaus-Peter; Hofreiter, Michael

2018-05-01

Contiguous genome assemblies are a highly valued biological resource because of the higher number of completely annotated genes and genomic elements that are usable compared to fragmented draft genomes. Nonetheless, contiguity is difficult to obtain if only low coverage data and/or only distantly related reference genome assemblies are available. In order to improve genome contiguity, we have developed Cross-Species Scaffolding-a new pipeline that imports long-range distance information directly into the de novo assembly process by constructing mate-pair libraries in silico. We show how genome assembly metrics and gene prediction dramatically improve with our pipeline by assembling two primate genomes solely based on ∼30x coverage of shotgun sequencing data.

MetaFluxNet: the management of metabolic reaction information and quantitative metabolic flux analysis.

PubMed

Lee, Dong-Yup; Yun, Hongsoek; Park, Sunwon; Lee, Sang Yup

2003-11-01

MetaFluxNet is a program package for managing information on the metabolic reaction network and for quantitatively analyzing metabolic fluxes in an interactive and customized way. It allows users to interpret and examine metabolic behavior in response to genetic and/or environmental modifications. As a result, quantitative in silico simulations of metabolic pathways can be carried out to understand the metabolic status and to design the metabolic engineering strategies. The main features of the program include a well-developed model construction environment, user-friendly interface for metabolic flux analysis (MFA), comparative MFA of strains having different genotypes under various environmental conditions, and automated pathway layout creation. http://mbel.kaist.ac.kr/ A manual for MetaFluxNet is available as PDF file.

Non-animal models of wound healing in cutaneous repair: In silico, in vitro, ex vivo, and in vivo models of wounds and scars in human skin.

PubMed

Ud-Din, Sara; Bayat, Ardeshir

2017-04-01

Tissue repair models are essential to explore the pathogenesis of wound healing and scar formation, identify new drug targets/biomarkers and to test new therapeutics. However, no animal model is an exact replicate of the clinical situation in man as in addition to differences in the healing of animal skin; the response to novel therapeutics can be variable when compared to human skin. The aim of this review is to evaluate currently available non-animal wound repair models in human skin, including: in silico, in vitro, ex vivo, and in vivo. The appropriate use of these models is extremely relevant to wound-healing research as it enables improved understanding of the basic mechanisms present in the wound healing cascade and aid in discovering better means to regulate them for enhanced healing or prevention of abnormal scarring. The advantage of in silico models is that they can be used as a first in virtue screening tool to predict the effect of a drug/stimulus on cells/tissues and help plan experimental research/clinical trial studies but remain theoretical until validated. In vitro models allow direct quantitative examination of an effect on specific cell types alone without incorporating other tissue-matrix components, which limits their utility. Ex vivo models enable immediate and short-term evaluation of a particular effect on cells and its surrounding tissue components compared with in vivo models that provide direct analysis of a stimulus in the living human subject before/during/after exposure to a stimulus. Despite clear advantages, there remains a lack of standardisation in design, evaluation and follow-up, for acute/chronic wounds and scars in all models. In conclusion, ideal models of wound healing research are desirable and should mimic not only the structure but also the cellular and molecular interactions, of wound types in human skin. Future models may also include organ/skin-on-a-chip with potential application in wound healing research. © 2017 by the Wound Healing Society.

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

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.

Airflow and particle deposition simulations in health and emphysema: from in vivo to in silico animal experiments.

PubMed

Oakes, Jessica M; Marsden, Alison L; Grandmont, Celine; Shadden, Shawn C; Darquenne, Chantal; Vignon-Clementel, Irene E

2014-04-01

Image-based in silico modeling tools provide detailed velocity and particle deposition data. However, care must be taken when prescribing boundary conditions to model lung physiology in health or disease, such as in emphysema. In this study, the respiratory resistance and compliance were obtained by solving an inverse problem; a 0D global model based on healthy and emphysematous rat experimental data. Multi-scale CFD simulations were performed by solving the 3D Navier-Stokes equations in an MRI-derived rat geometry coupled to a 0D model. Particles with 0.95 μm diameter were tracked and their distribution in the lung was assessed. Seven 3D-0D simulations were performed: healthy, homogeneous, and five heterogeneous emphysema cases. Compliance (C) was significantly higher (p = 0.04) in the emphysematous rats (C = 0.37 ± 0.14 cm(3)/cmH2O) compared to the healthy rats (C = 0.25 ± 0.04 cm(3)/cmH2O), while the resistance remained unchanged (p = 0.83). There were increases in airflow, particle deposition in the 3D model, and particle delivery to the diseased regions for the heterogeneous cases compared to the homogeneous cases. The results highlight the importance of multi-scale numerical simulations to study airflow and particle distribution in healthy and diseased lungs. The effect of particle size and gravity were studied. Once available, these in silico predictions may be compared to experimental deposition data.

Synthesis and biological activity of pyrazolo[3,4-d]thiazolo[3,2-a]pyrimidin-4-one derivatives: in silico approach.

PubMed

Khobragade, Chandrahas N; Bodade, Ragini G; Dawane, Bhaskar S; Konda, Shankaraiah G; Khandare, Namdev T

2010-10-01

Xanthine oxidase (XO) is responsible for the pathological condition called gout. Inhibition of XO activity by various pyrazolo[3,4-d]thiazolo[3,2-a]pyrimidine-4-one derivatives was assessed and compared with the standard inhibitor allopurinol. Out of 10 synthesized compounds, two compounds, viz. 3-amino-6-(2-hydroxyphenyl)-1H-pyrazolo[3,4-d]thiazolo[3,2-a]pyrimidin-4-one (3b) and 3-amino-6-(4-chloro-2-hydroxy-5-methylphenyl)-1H-pyrazolo[3,4-d]thiazolo[3,2-a]pyrimidin-4-one (3g) were found to have promising XO inhibitory activity of the same order as allopurinol. Both compounds and allopurinol inhibited competitively with comparable Ki (3b: 3.56 microg, 3g: 2.337 microg, allopurinol: 1.816 microg) and IC(50) (3b: 4.228 microg, 3g: 3.1 microg, allopurinol: 2.9 microg) values. The enzyme-ligand interaction was studied by molecular docking using Autodock in BioMed Cache V. 6.1 software. The results revealed a significant dock score for 3b (-84.976 kcal/mol) and 3g (-90.921 kcal/mol) compared with allopurinol (-55.01 kcal/mol). The physiochemical properties and toxicity of the compounds were determined in silico using online computational tools. Overall, in vitro and in silico study revealed 3-amino-6-(4-chloro-2-hydroxy-5-methylphenyl)-1H-pyrazolo[3,4-d]thiazolo[3,2-a]pyrimidin-4-one (3g) as a potential lead compound for the design and development of XO inhibitors.

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.

Incorporation of in silico biodegradability screening in early drug development--a feasible approach?

PubMed

Steger-Hartmann, Thomas; Länge, Reinhard; Heuck, Klaus

2011-05-01

The concentration of a pharmaceutical found in the environment is determined by the amount used by the patient, the excretion and metabolism pattern, and eventually by its persistence. Biological degradation or persistence of a pharmaceutical is experimentally tested rather late in the development of a pharmaceutical, often shortly before submission of the dossier to regulatory authorities. To investigate whether the aspect of persistence of a compound could be assessed early during drug development, we investigated whether biodegradation of pharmaceuticals could be predicted with the help of in silico tools. To assess the value of in silico prediction, we collected results for the OECD 301 degradation test ("ready biodegradability") of 42 drugs or drug synthesis intermediates and compared them to the prediction of the in silico tool BIOWIN. Of these compounds, 38 were predictable with BIOWIN, which is a module of the Estimation Programs Interface (EPI) Suite™ provided by the US EPA. The program failed to predict the two drugs which proved to be readily biodegradable in the degradation tests. On the other hand, BIOWIN predicted two compounds to be readily biodegradable which, however, proved to be persistent in the test setting. The comparison of experimental data with the predicted one resulted in a specificity of 94% and a sensitivity of 0%. The results of this study do not indicate that application of the biodegradation prediction tool BIOWIN is a feasible approach to assess the ready biodegradability during early drug development.

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.

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.

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.

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

Structural Diversity in the Dandelion (Taraxacum officinale) Polyphenol Oxidase Family Results in Different Responses to Model Substrates

PubMed Central

Dirks-Hofmeister, Mareike E.; Singh, Ratna; Leufken, Christine M.; Inlow, Jennifer K.; Moerschbacher, Bruno M.

2014-01-01

Polyphenol oxidases (PPOs) are ubiquitous type-3 copper enzymes that catalyze the oxygen-dependent conversion of o-diphenols to the corresponding quinones. In most plants, PPOs are present as multiple isoenzymes that probably serve distinct functions, although the precise relationship between sequence, structure and function has not been addressed in detail. We therefore compared the characteristics and activities of recombinant dandelion PPOs to gain insight into the structure–function relationships within the plant PPO family. Phylogenetic analysis resolved the 11 isoenzymes of dandelion into two evolutionary groups. More detailed in silico and in vitro analyses of four representative PPOs covering both phylogenetic groups were performed. Molecular modeling and docking predicted differences in enzyme-substrate interactions, providing a structure-based explanation for grouping. One amino acid side chain positioned at the entrance to the active site (position HB2+1) potentially acts as a “selector” for substrate binding. In vitro activity measurements with the recombinant, purified enzymes also revealed group-specific differences in kinetic parameters when the selected PPOs were presented with five model substrates. The combination of our enzyme kinetic measurements and the in silico docking studies therefore indicate that the physiological functions of individual PPOs might be defined by their specific interactions with different natural substrates. PMID:24918587

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.

Synthesis of Thymoquinone derivatives and its activity analysis: In-silico approach

NASA Astrophysics Data System (ADS)

Ulfa, Siti Mariyah; Sholikhah, Shoimatus; Utomo, Edi Priyo

2017-03-01

Thymoquinone derivatives which synthesized in this research is bromoalkylquinones with alkyl chain consist of seven carbons (C7) and ten carbons (C10). The synthesis was carried out by oxidation of 2,3-dimethylhydroquinone followed by alkylation using reflux for 1.5 hours. The alkylation products were successfully characterized as 5-(7-bromoheptyl)-2,3-dimethyl-1,4-benzoquinone (C7) and 5-(10-bromodecyl)-2,3-dimethyl-1,4-benzoquinone (C10) in 31.93 and 16.89%, respectively. These compounds were fully characterized using FT-IR, 1H-NMR and 13C-NMR. Thus, the activity of C7 and C10 was analyzed by in silico approach with molecular docking using macromolecule model extracted from Protein Data Bank (PDB). Macromolecules used in this research is mitochondrial translocator protein (TSPO) as an antioxidant receptor, glycogen phosphorylase (GPA) as antidiabetic receptor and phosphatase tensin homolog (PTEN) as an anticancer agent. The result showed that C7 and C10 has a very good activity as antioxidant and antidiabetic agents with IC50 2.03 and 1.02 ppm (TSPO) and 16.98 and 14.88 ppm (GPA) compared with Thymoquinone. While the activity of C7 and C10 against PTEN gave the IC50 23.13 and 18.31 ppm showed a good candidate for an anticancer agent.

Structural diversity in the dandelion (Taraxacum officinale) polyphenol oxidase family results in different responses to model substrates.

PubMed

Dirks-Hofmeister, Mareike E; Singh, Ratna; Leufken, Christine M; Inlow, Jennifer K; Moerschbacher, Bruno M

2014-01-01

Polyphenol oxidases (PPOs) are ubiquitous type-3 copper enzymes that catalyze the oxygen-dependent conversion of o-diphenols to the corresponding quinones. In most plants, PPOs are present as multiple isoenzymes that probably serve distinct functions, although the precise relationship between sequence, structure and function has not been addressed in detail. We therefore compared the characteristics and activities of recombinant dandelion PPOs to gain insight into the structure-function relationships within the plant PPO family. Phylogenetic analysis resolved the 11 isoenzymes of dandelion into two evolutionary groups. More detailed in silico and in vitro analyses of four representative PPOs covering both phylogenetic groups were performed. Molecular modeling and docking predicted differences in enzyme-substrate interactions, providing a structure-based explanation for grouping. One amino acid side chain positioned at the entrance to the active site (position HB2+1) potentially acts as a "selector" for substrate binding. In vitro activity measurements with the recombinant, purified enzymes also revealed group-specific differences in kinetic parameters when the selected PPOs were presented with five model substrates. The combination of our enzyme kinetic measurements and the in silico docking studies therefore indicate that the physiological functions of individual PPOs might be defined by their specific interactions with different natural substrates.

Using genome-scale metabolic models to compare serovars of the foodborne pathogen Listeria monocytogenes.

PubMed

Metz, Zachary P; Ding, Tong; Baumler, David J

2018-01-01

Listeria monocytogenes is a microorganism of great concern for the food industry and the cause of human foodborne disease. Therefore, novel methods of control are needed, and systems biology is one such approach to identify them. Using a combination of computational techniques and laboratory methods, genome-scale metabolic models (GEMs) can be created, validated, and used to simulate growth environments and discern metabolic capabilities of microbes of interest, including L. monocytogenes. The objective of the work presented here was to generate GEMs for six different strains of L. monocytogenes, and to both qualitatively and quantitatively validate these GEMs with experimental data to examine the diversity of metabolic capabilities of numerous strains from the three different serovar groups most associated with foodborne outbreaks and human disease. Following qualitative validation, 57 of the 95 carbon sources tested experimentally were present in the GEMs, and; therefore, these were the compounds from which comparisons could be drawn. Of these 57 compounds, agreement between in silico predictions and in vitro results for carbon source utilization ranged from 80.7% to 91.2% between strains. Nutrient utilization agreement between in silico predictions and in vitro results were also conducted for numerous nitrogen, phosphorous, and sulfur sources. Additionally, quantitative validation showed that the L. monocytogenes GEMs were able to generate in silico predictions for growth rate and growth yield that were strongly and significantly (p < 0.0013 and p < 0.0015, respectively) correlated with experimental results. These findings are significant because they show that these GEMs for L. monocytogenes are comparable to published GEMs of other organisms for agreement between in silico predictions and in vitro results. Therefore, as with the other GEMs, namely those for Escherichia coli, Staphylococcus aureus, Vibrio vulnificus, and Salmonella spp., they can be used to determine new methods of growth control and disease treatment.

SU-G-JeP1-12: Head-To-Head Performance Characterization of Two Multileaf Collimator Tracking Algorithms for Radiotherapy

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

Caillet, V; Colvill, E; Royal North Shore Hospital, St Leonards, Sydney

2016-06-15

Purpose: Multi-leaf collimator (MLC) tracking is being clinically pioneered to continuously compensate for thoracic and abdominal motion during radiotherapy. The purpose of this work is to characterize the performance of two MLC tracking algorithms for cancer radiotherapy, based on a direct optimization and a piecewise leaf fitting approach respectively. Methods: To test the algorithms, both physical and in silico experiments were performed. Previously published high and low modulation VMAT plans for lung and prostate cancer cases were used along with eight patient-measured organ-specific trajectories. For both MLC tracking algorithm, the plans were run with their corresponding patient trajectories. The physicalmore » experiments were performed on a Trilogy Varian linac and a programmable phantom (HexaMotion platform). For each MLC tracking algorithm, plan and patient trajectory, the tracking accuracy was quantified as the difference in aperture area between ideal and fitted MLC. To compare algorithms, the average cumulative tracking error area for each experiment was calculated. The two-sample Kolmogorov-Smirnov (KS) test was used to evaluate the cumulative tracking errors between algorithms. Results: Comparison of tracking errors for the physical and in silico experiments showed minor differences between the two algorithms. The KS D-statistics for the physical experiments were below 0.05 denoting no significant differences between the two distributions pattern and the average error area (direct optimization/piecewise leaf-fitting) were comparable (66.64 cm2/65.65 cm2). For the in silico experiments, the KS D-statistics were below 0.05 and the average errors area were also equivalent (49.38 cm2/48.98 cm2). Conclusion: The comparison between the two leaf fittings algorithms demonstrated no significant differences in tracking errors, neither in a clinically realistic environment nor in silico. The similarities in the two independent algorithms give confidence in the use of either algorithm for clinical implementation.« less

Cinnamaldehyde, Cinnamic Acid, and Cinnamyl Alcohol, the Bioactives of Cinnamomum cassia Exhibit HDAC8 Inhibitory Activity: An In vitro and In silico Study

PubMed Central

Patil, Mangesh; Choudhari, Amit S.; Pandita, Savita; Islam, Md Ataul; Raina, Prerna; Kaul-Ghanekar, Ruchika

2017-01-01

Background: The altered expression of histone deacetylase family member 8 (HDAC8) has been found to be linked with various cancers, thereby making its selective inhibition a potential strategy in cancer therapy. Recently, plant secondary metabolites, particularly phenolic compounds, have been shown to possess HDAC inhibitory activity. Objective: In the present work, we have evaluated the potential of cinnamaldehyde (CAL), cinnamic acid (CA), and cinnamyl alcohol (CALC) (bioactives of Cinnamomum) as well as aqueous cinnamon extract (ACE), to inhibit HDAC8 activity in vitro and in silico. Materials and Methods: HDAC8 inhibitory activity of ACE and cinnamon bioactives was determined in vitro using HDAC8 inhibitor screening kit. Trichostatin A (TSA), a well-known anti-cancer agent and HDAC inhibitor, was used as a positive control. In silico studies included molecular descriptor Analysis molecular docking absorption, distribution, metabolism, excretion, and toxicity prediction, density function theory calculation and synthetic accessibility program. Results: Pharmacoinformatics studies implicated that ACE and its Bioactives (CAL, CA, and CALC) exhibited comparable activity with that of TSA. The highest occupied molecular orbitals and lowest unoccupied molecular orbitals along with binding energy of cinnamon bioactives were comparable with that of TSA. Molecular docking results suggested that all the ligands maintained two hydrogen bond interactions within the active site of HDAC8. Finally, the synthetic accessibility values showed that cinnamon bioactives were easy to synthesize compared to TSA. Conclusion: It was evident from both the experimental and computational data that cinnamon bioactives exhibited significant HDAC8 inhibitory activity, thereby suggesting their potential therapeutic implications against cancer. SUMMARY Pharmacoinformatics studies revealed that cinnamon bioactives bound to the active site of HDAC8 enzyme in a way similar to that of TSAThe molecular descriptors of cinnamon compounds successfully correlated with TSA values. The binding interactions and energies were also found to be close to TSASynthetic accessibility values showed that cinnamon bioactives were easy to synthesize compared to TSA. Abbreviations used: ACE: Aqueous Cinnamon Extract; DFT: Density Function Theory; CAL: Cinnamaldehyde; CA: Cinnamic Acid; CALC: Cinnamyl Alcohol; MW: Molecular Weight; ROTBs: Rotatable Bonds; ROF: Lipinski's Rule of Five; TSA: Trichostatin A; PDB: Protein Data Bank; RMSD: Root Mean Square Deviation; HBA: Hydrogen Bond Acceptor; HBD: Hydrogen Bond Donor; ADMET: Absorption, Distribution, Metabolism, Excretion and Toxicity; FO: Frontier Orbital; HOMOs: Highest Occupied Molecular Orbitals; LUMOs: Lowest Unoccupied Molecular Orbitals; BE: Binding Energy. PMID:29142427

In silico peptide-binding predictions of passerine MHC class I reveal similarities across distantly related species, suggesting convergence on the level of protein function.

PubMed

Follin, Elna; Karlsson, Maria; Lundegaard, Claus; Nielsen, Morten; Wallin, Stefan; Paulsson, Kajsa; Westerdahl, Helena

2013-04-01

The major histocompatibility complex (MHC) genes are the most polymorphic genes found in the vertebrate genome, and they encode proteins that play an essential role in the adaptive immune response. Many songbirds (passerines) have been shown to have a large number of transcribed MHC class I genes compared to most mammals. To elucidate the reason for this large number of genes, we compared 14 MHC class I alleles (α1-α3 domains), from great reed warbler, house sparrow and tree sparrow, via phylogenetic analysis, homology modelling and in silico peptide-binding predictions to investigate their functional and genetic relationships. We found more pronounced clustering of the MHC class I allomorphs (allele specific proteins) in regards to their function (peptide-binding specificities) compared to their genetic relationships (amino acid sequences), indicating that the high number of alleles is of functional significance. The MHC class I allomorphs from house sparrow and tree sparrow, species that diverged 10 million years ago (MYA), had overlapping peptide-binding specificities, and these similarities across species were also confirmed in phylogenetic analyses based on amino acid sequences. Notably, there were also overlapping peptide-binding specificities in the allomorphs from house sparrow and great reed warbler, although these species diverged 30 MYA. This overlap was not found in a tree based on amino acid sequences. Our interpretation is that convergent evolution on the level of the protein function, possibly driven by selection from shared pathogens, has resulted in allomorphs with similar peptide-binding repertoires, although trans-species evolution in combination with gene conversion cannot be ruled out.

Whole-genome comparative analysis of three phytopathogenic Xylella fastidiosa strains.

PubMed

Bhattacharyya, Anamitra; Stilwagen, Stephanie; Ivanova, Natalia; D'Souza, Mark; Bernal, Axel; Lykidis, Athanasios; Kapatral, Vinayak; Anderson, Iain; Larsen, Niels; Los, Tamara; Reznik, Gary; Selkov, Eugene; Walunas, Theresa L; Feil, Helene; Feil, William S; Purcell, Alexander; Lassez, Jean-Louis; Hawkins, Trevor L; Haselkorn, Robert; Overbeek, Ross; Predki, Paul F; Kyrpides, Nikos C

2002-09-17

Xylella fastidiosa (Xf) causes wilt disease in plants and is responsible for major economic and crop losses globally. Owing to the public importance of this phytopathogen we embarked on a comparative analysis of the complete genome of Xf pv citrus and the partial genomes of two recently sequenced strains of this species: Xf pv almond and Xf pv oleander, which cause leaf scorch in almond and oleander plants, respectively. We report a reanalysis of the previously sequenced Xf 9a5c (CVC, citrus) strain and the two "gapped" Xf genomes revealing ORFs encoding critical functions in pathogenicity and conjugative transfer. Second, a detailed whole-genome functional comparison was based on the three sequenced Xf strains, identifying the unique genes present in each strain, in addition to those shared between strains. Third, an "in silico" cellular reconstruction of these organisms was made, based on a comparison of their core functional subsystems that led to a characterization of their conjugative transfer machinery, identification of potential differences in their adhesion mechanisms, and highlighting of the absence of a classical quorum-sensing mechanism. This study demonstrates the effectiveness of comparative analysis strategies in the interpretation of genomes that are closely related.

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

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.

Transcriptome mining and in silico structural and functional analysis of ascorbic acid and tartaric acid biosynthesis pathway enzymes in rose-scanted geranium.

PubMed

Narnoliya, Lokesh K; Sangwan, Rajender S; Singh, Sudhir P

2018-06-01

Rose-scented geranium (Pelargonium sp.) is widely known as aromatic and medicinal herb, accumulating specialized metabolites of high economic importance, such as essential oils, ascorbic acid, and tartaric acid. Ascorbic acid and tartaric acid are multifunctional metabolites of human value to be used as vital antioxidants and flavor enhancing agents in food products. No information is available related to the structural and functional properties of the enzymes involved in ascorbic acid and tartaric acid biosynthesis in rose-scented geranium. In the present study, transcriptome mining was done to identify full-length genes, followed by their bioinformatic and molecular modeling investigations and understanding of in silico structural and functional properties of these enzymes. Evolutionary conserved domains were identified in the pathway enzymes. In silico physicochemical characterization of the catalytic enzymes revealed isoelectric point (pI), instability index, aliphatic index, and grand average hydropathy (GRAVY) values of the enzymes. Secondary structural prediction revealed abundant proportion of alpha helix and random coil confirmations in the pathway enzymes. Three-dimensional homology models were developed for these enzymes. The predicted structures showed significant structural similarity with their respective templates in root mean square deviation analysis. Ramachandran plot analysis of the modeled enzymes revealed that more than 84% of the amino acid residues were within the favored regions. Further, functionally important residues were identified corresponding to catalytic sites located in the enzymes. To, our best knowledge, this is the first report which provides a foundation on functional annotation and structural determination of ascorbic acid and tartaric acid pathway enzymes in rose-scanted geranium.

Pharmacokinetics, brain distribution and plasma protein binding of carbamazepine and nine derivatives: new set of data for predictive in silico ADME models.

PubMed

Fortuna, Ana; Alves, Gilberto; Soares-da-Silva, Patrício; Falcão, Amílcar

2013-11-01

In silico approaches to predict absorption, distribution, metabolism and excretion (ADME) of new drug candidates are gaining a relevant importance in drug discovery programmes. When considering particularly the pharmacokinetics during the development of oral antiepileptic drugs (AEDs), one of the most prominent goals is designing compounds with good bioavailability and brain penetration. Thus, it is expected that in silico models able to predict these features may be applied during the early stages of AEDs discovery. The present investigation was mainly carried out in order to generate in vivo pharmacokinetic data that can be utilized for development and validation of in silico models. For this purpose, a single dose of each compound (1.4mmol/kg) was orally administered to male CD-1 mice. After quantifying the parent compound and main metabolites in plasma and brain up to 12h post-dosing, a non-compartmental pharmacokinetic analysis was performed and the corresponding brain/plasma ratios were calculated. Moreover the plasma protein binding was estimated in vitro applying the ultrafiltration procedure. The present in vivo pharmacokinetic characterization of the test compounds and corresponding metabolites demonstrated that the metabolism extensively compromised the in vivo activity of CBZ derivatives and their toxicity. Furthermore, it was clearly evidenced that the time to reach maximum peak concentration, bioavailability (given by the area under the curve) and metabolic stability (given by the AUC0-12h ratio of the parent compound and total systemic drug) influenced the in vivo pharmacological activities and must be considered as primary parameters to be investigated. All the test compounds presented brain/plasma ratios lower than 1.0, suggesting that the blood-brain barrier restricts drug entry into the brain. In agreement with in vitro studies already performed within our research group, CBZ, CBZ-10,11-epoxide and oxcarbazepine exhibited the highest brain/plasma ratios (>0.50), followed by eslicarbazepine, R-licarbazepine, trans-diol and BIA 2-024 (ratios within 0.05-0.50). BIA 2-265 was not found in the biophase, probably due to its high plasma-protein bound fraction (>90%) herein revealed for the first time. The comparative in vivo pharmacokinetic data obtained in the present work might be usefully applied in the context of discovery of new antiepileptic drugs that are derivatives of CBZ. Copyright © 2013 Elsevier B.V. All rights reserved.

Time dependent analysis of assay comparability: a novel approach to understand intra- and inter-site variability over time

NASA Astrophysics Data System (ADS)

Winiwarter, Susanne; Middleton, Brian; Jones, Barry; Courtney, Paul; Lindmark, Bo; Page, Ken M.; Clark, Alan; Landqvist, Claire

2015-09-01

We demonstrate here a novel use of statistical tools to study intra- and inter-site assay variability of five early drug metabolism and pharmacokinetics in vitro assays over time. Firstly, a tool for process control is presented. It shows the overall assay variability but allows also the following of changes due to assay adjustments and can additionally highlight other, potentially unexpected variations. Secondly, we define the minimum discriminatory difference/ratio to support projects to understand how experimental values measured at different sites at a given time can be compared. Such discriminatory values are calculated for 3 month periods and followed over time for each assay. Again assay modifications, especially assay harmonization efforts, can be noted. Both the process control tool and the variability estimates are based on the results of control compounds tested every time an assay is run. Variability estimates for a limited set of project compounds were computed as well and found to be comparable. This analysis reinforces the need to consider assay variability in decision making, compound ranking and in silico modeling.

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

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.

SACCHARIS: an automated pipeline to streamline discovery of carbohydrate active enzyme activities within polyspecific families and de novo sequence datasets.

PubMed

Jones, Darryl R; Thomas, Dallas; Alger, Nicholas; Ghavidel, Ata; Inglis, G Douglas; Abbott, D Wade

2018-01-01

Deposition of new genetic sequences in online databases is expanding at an unprecedented rate. As a result, sequence identification continues to outpace functional characterization of carbohydrate active enzymes (CAZymes). In this paradigm, the discovery of enzymes with novel functions is often hindered by high volumes of uncharacterized sequences particularly when the enzyme sequence belongs to a family that exhibits diverse functional specificities (i.e., polyspecificity). Therefore, to direct sequence-based discovery and characterization of new enzyme activities we have developed an automated in silico pipeline entitled: Sequence Analysis and Clustering of CarboHydrate Active enzymes for Rapid Informed prediction of Specificity (SACCHARIS). This pipeline streamlines the selection of uncharacterized sequences for discovery of new CAZyme or CBM specificity from families currently maintained on the CAZy website or within user-defined datasets. SACCHARIS was used to generate a phylogenetic tree of a GH43, a CAZyme family with defined subfamily designations. This analysis confirmed that large datasets can be organized into sequence clusters of manageable sizes that possess related functions. Seeding this tree with a GH43 sequence from Bacteroides dorei DSM 17855 (BdGH43b, revealed it partitioned as a single sequence within the tree. This pattern was consistent with it possessing a unique enzyme activity for GH43 as BdGH43b is the first described α-glucanase described for this family. The capacity of SACCHARIS to extract and cluster characterized carbohydrate binding module sequences was demonstrated using family 6 CBMs (i.e., CBM6s). This CBM family displays a polyspecific ligand binding profile and contains many structurally determined members. Using SACCHARIS to identify a cluster of divergent sequences, a CBM6 sequence from a unique clade was demonstrated to bind yeast mannan, which represents the first description of an α-mannan binding CBM. Additionally, we have performed a CAZome analysis of an in-house sequenced bacterial genome and a comparative analysis of B. thetaiotaomicron VPI-5482 and B. thetaiotaomicron 7330, to demonstrate that SACCHARIS can generate "CAZome fingerprints", which differentiate between the saccharolytic potential of two related strains in silico. Establishing sequence-function and sequence-structure relationships in polyspecific CAZyme families are promising approaches for streamlining enzyme discovery. SACCHARIS facilitates this process by embedding CAZyme and CBM family trees generated from biochemically to structurally characterized sequences, with protein sequences that have unknown functions. In addition, these trees can be integrated with user-defined datasets (e.g., genomics, metagenomics, and transcriptomics) to inform experimental characterization of new CAZymes or CBMs not currently curated, and for researchers to compare differential sequence patterns between entire CAZomes. In this light, SACCHARIS provides an in silico tool that can be tailored for enzyme bioprospecting in datasets of increasing complexity and for diverse applications in glycobiotechnology.

The revival of the Baldwin effect

NASA Astrophysics Data System (ADS)

Fontanari, José F.; Santos, Mauro

2017-10-01

The idea that a genetically fixed behavior evolved from the once differential learning ability of individuals that performed the behavior is known as the Baldwin effect. A highly influential paper [G.E. Hinton, S.J. Nowlan, Complex Syst. 1, 495 (1987)] claimed that this effect can be observed in silico, but here we argue that what was actually shown is that the learning ability is easily selected for. Then we demonstrate the Baldwin effect to happen in the in silico scenario by estimating the probability and waiting times for the learned behavior to become innate. Depending on parameter values, we find that learning can increase the chance of fixation of the learned behavior by several orders of magnitude compared with the non-learning situation.

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.

CEQer: a graphical tool for copy number and allelic imbalance detection from whole-exome sequencing data.

PubMed

Piazza, Rocco; Magistroni, Vera; Pirola, Alessandra; Redaelli, Sara; Spinelli, Roberta; Redaelli, Serena; Galbiati, Marta; Valletta, Simona; Giudici, Giovanni; Cazzaniga, Giovanni; Gambacorti-Passerini, Carlo

2013-01-01

Copy number alterations (CNA) are common events occurring in leukaemias and solid tumors. Comparative Genome Hybridization (CGH) is actually the gold standard technique to analyze CNAs; however, CGH analysis requires dedicated instruments and is able to perform only low resolution Loss of Heterozygosity (LOH) analyses. Here we present CEQer (Comparative Exome Quantification analyzer), a new graphical, event-driven tool for CNA/allelic-imbalance (AI) coupled analysis of exome sequencing data. By using case-control matched exome data, CEQer performs a comparative digital exonic quantification to generate CNA data and couples this information with exome-wide LOH and allelic imbalance detection. This data is used to build mixed statistical/heuristic models allowing the identification of CNA/AI events. To test our tool, we initially used in silico generated data, then we performed whole-exome sequencing from 20 leukemic specimens and corresponding matched controls and we analyzed the results using CEQer. Taken globally, these analyses showed that the combined use of comparative digital exon quantification and LOH/AI allows generating very accurate CNA data. Therefore, we propose CEQer as an efficient, robust and user-friendly graphical tool for the identification of CNA/AI in the context of whole-exome sequencing data.

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.

In Silico Assessment of Literature Insulin Bolus Calculation Methods Accounting for Glucose Rate of Change.

PubMed

Cappon, Giacomo; Marturano, Francesca; Vettoretti, Martina; Facchinetti, Andrea; Sparacino, Giovanni

2018-05-01

The standard formula (SF) used in bolus calculators (BCs) determines meal insulin bolus using "static" measurement of blood glucose concentration (BG) obtained by self-monitoring of blood glucose (SMBG) fingerprick device. Some methods have been proposed to improve efficacy of SF using "dynamic" information provided by continuous glucose monitoring (CGM), and, in particular, glucose rate of change (ROC). This article compares, in silico and in an ideal framework limiting the exposition to possibly confounding factors (such as CGM noise), the performance of three popular techniques devised for such a scope, that is, the methods of Buckingham et al (BU), Scheiner (SC), and Pettus and Edelman (PE). Using the UVa/Padova Type 1 diabetes simulator we generated data of 100 virtual subjects in noise-free, single-meal scenarios having different preprandial BG and ROC values. Meal insulin bolus was computed using SF, BU, SC, and PE. Performance was assessed with the blood glucose risk index (BGRI) on the 9 hours after meal. On average, BU, SC, and PE improve BGRI compared to SF. When BG is rapidly decreasing, PE obtains the best performance. In the other ROC scenarios, none of the considered methods prevails in all the preprandial BG conditions tested. Our study showed that, at least in the considered ideal framework, none of the methods to correct SF according to ROC is globally better than the others. Critical analysis of the results also suggests that further investigations are needed to develop more effective formulas to account for ROC information in BCs.

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.

Pediatric in vitro and in silico models of deposition via oral and nasal inhalation.

PubMed

Carrigy, Nicholas B; Ruzycki, Conor A; Golshahi, Laleh; Finlay, Warren H

2014-06-01

Respiratory tract deposition models provide a useful method for optimizing the design and administration of inhaled pharmaceutical aerosols, and can be useful for estimating exposure risks to inhaled particulate matter. As aerosol must first pass through the extrathoracic region prior to reaching the lungs, deposition in this region plays an important role in both cases. Compared to adults, much less extrathoracic deposition data are available with pediatric subjects. Recently, progress in magnetic resonance imaging and computed tomography scans to develop pediatric extrathoracic airway replicas has facilitated addressing this issue. Indeed, the use of realistic replicas for benchtop inhaler testing is now relatively common during the development and in vitro evaluation of pediatric respiratory drug delivery devices. Recently, in vitro empirical modeling studies using a moderate number of these realistic replicas have related airway geometry, particle size, fluid properties, and flow rate to extrathoracic deposition. Idealized geometries provide a standardized platform for inhaler testing and exposure risk assessment and have been designed to mimic average in vitro deposition in infants and children by replicating representative average geometrical dimensions. In silico mathematical models have used morphometric data and aerosol physics to illustrate the relative importance of different deposition mechanisms on respiratory tract deposition. Computational fluid dynamics simulations allow for the quantification of local deposition patterns and an in-depth examination of aerosol behavior in the respiratory tract. Recent studies have used both in vitro and in silico deposition measurements in realistic pediatric airway geometries to some success. This article reviews the current understanding of pediatric in vitro and in silico deposition modeling via oral and nasal inhalation.

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.

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.

MCCE analysis of the pKas of introduced buried acids and bases in staphylococcal nuclease.

PubMed

Gunner, M R; Zhu, Xuyu; Klein, Max C

2011-12-01

The pK(a)s of 96 acids and bases introduced into buried sites in the staphylococcal nuclease protein (SNase) were calculated using the multiconformation continuum electrostatics (MCCE) program and the results compared with experimental values. The pK(a)s are obtained by Monte Carlo sampling of coupled side chain protonation and position as a function of pH. The dependence of the results on the protein dielectric constant (ε(prot)) in the continuum electrostatics analysis and on the Lennard-Jones non-electrostatics parameters was evaluated. The pK(a)s of the introduced residues have a clear dependence on ε(prot,) whereas native ionizable residues do not. The native residues have electrostatic interactions with other residues in the protein favoring ionization, which are larger than the desolvation penalty favoring the neutral state. Increasing ε(prot) scales both terms, which for these residues leads to small changes in pK(a). The introduced residues have a larger desolvation penalty and negligible interactions with residues in the protein. For these residues, changing ε(prot) has a large influence on the calculated pK(a). An ε(prot) of 8-10 and a Lennard-Jones scaling of 0.25 is best here. The X-ray crystal structures of the mutated proteins are found to provide somewhat better results than calculations carried out on mutations made in silico. Initial relaxation of the in silico mutations by Gromacs and extensive side chain rotamer sampling within MCCE can significantly improve the match with experiment. Copyright © 2011 Wiley-Liss, Inc.

In Silico Modeling Approach for the Evaluation of Gastrointestinal Dissolution, Supersaturation, and Precipitation of Posaconazole.

PubMed

Hens, Bart; Pathak, Shriram M; Mitra, Amitava; Patel, Nikunjkumar; Liu, Bo; Patel, Sanjaykumar; Jamei, Masoud; Brouwers, Joachim; Augustijns, Patrick; Turner, David B

2017-12-04

The aim of this study was to evaluate gastrointestinal (GI) dissolution, supersaturation, and precipitation of posaconazole, formulated as an acidified (pH 1.6) and neutral (pH 7.1) suspension. A physiologically based pharmacokinetic (PBPK) modeling and simulation tool was applied to simulate GI and systemic concentration-time profiles of posaconazole, which were directly compared with intraluminal and systemic data measured in humans. The Advanced Dissolution Absorption and Metabolism (ADAM) model of the Simcyp Simulator correctly simulated incomplete gastric dissolution and saturated duodenal concentrations of posaconazole in the duodenal fluids following administration of the neutral suspension. In contrast, gastric dissolution was approximately 2-fold higher after administration of the acidified suspension, which resulted in supersaturated concentrations of posaconazole upon transfer to the upper small intestine. The precipitation kinetics of posaconazole were described by two precipitation rate constants, extracted by semimechanistic modeling of a two-stage medium change in vitro dissolution test. The 2-fold difference in exposure in the duodenal compartment for the two formulations corresponded with a 2-fold difference in systemic exposure. This study demonstrated for the first time predictive in silico simulations of GI dissolution, supersaturation, and precipitation for a weakly basic compound in part informed by modeling of in vitro dissolution experiments and validated via clinical measurements in both GI fluids and plasma. Sensitivity analysis with the PBPK model indicated that the critical supersaturation ratio (CSR) and second precipitation rate constant (sPRC) are important parameters of the model. Due to the limitations of the two-stage medium change experiment the CSR was extracted directly from the clinical data. However, in vitro experiments with the BioGIT transfer system performed after completion of the in silico modeling provided an almost identical CSR to the clinical study value; this had no significant impact on the PBPK model predictions.

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

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.

The Druggable Pocketome of Corynebacterium diphtheriae: A New Approach for in silico Putative Druggable Targets

PubMed Central

Hassan, Syed S.; Jamal, Syed B.; Radusky, Leandro G.; Tiwari, Sandeep; Ullah, Asad; Ali, Javed; Behramand; de Carvalho, Paulo V. S. D.; Shams, Rida; Khan, Sabir; Figueiredo, Henrique C. P.; Barh, Debmalya; Ghosh, Preetam; Silva, Artur; Baumbach, Jan; Röttger, Richard; Turjanski, Adrián G.; Azevedo, Vasco A. C.

2018-01-01

Diphtheria is an acute and highly infectious disease, previously regarded as endemic in nature but vaccine-preventable, is caused by Corynebacterium diphtheriae (Cd). In this work, we used an in silico approach along the 13 complete genome sequences of C. diphtheriae followed by a computational assessment of structural information of the binding sites to characterize the “pocketome druggability.” To this end, we first computed the “modelome” (3D structures of a complete genome) of a randomly selected reference strain Cd NCTC13129; that had 13,763 open reading frames (ORFs) and resulted in 1,253 (∼9%) structure models. The amino acid sequences of these modeled structures were compared with the remaining 12 genomes and consequently, 438 conserved protein sequences were obtained. The RCSB-PDB database was consulted to check the template structures for these conserved proteins and as a result, 401 adequate 3D models were obtained. We subsequently predicted the protein pockets for the obtained set of models and kept only the conserved pockets that had highly druggable (HD) values (137 across all strains). Later, an off-target host homology analyses was performed considering the human proteome using NCBI database. Furthermore, the gene essentiality analysis was carried out that gave a final set of 10-conserved targets possessing highly druggable protein pockets. To check the target identification robustness of the pipeline used in this work, we crosschecked the final target list with another in-house target identification approach for C. diphtheriae thereby obtaining three common targets, these were; hisE-phosphoribosyl-ATP pyrophosphatase, glpX-fructose 1,6-bisphosphatase II, and rpsH-30S ribosomal protein S8. Our predicted results suggest that the in silico approach used could potentially aid in experimental polypharmacological target determination in C. diphtheriae and other pathogens, thereby, might complement the existing and new drug-discovery pipelines. PMID:29487617

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

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.

In-silico identification of miRNAs and their regulating target functions in Ocimum basilicum.

PubMed

Singh, Noopur; Sharma, Ashok

2014-12-01

microRNA is known to play an important role in growth and development of the plants and also in environmental stress. Ocimum basilicum (Basil) is a well known herb for its medicinal properties. In this study, we used in-silico approaches to identify miRNAs and their targets regulating different functions in O. basilicum using EST approach. Additionally, functional annotation, gene ontology and pathway analysis of identified target transcripts were also done. Seven miRNA families were identified. Meaningful regulations of target transcript by identified miRNAs were computationally evaluated. Four miRNA families have been reported by us for the first time from the Lamiaceae. Our results further confirmed that uracil was the predominant base in the first positions of identified mature miRNA sequence, while adenine and uracil were predominant in pre-miRNA sequences. Phylogenetic analysis was carried out to determine the relation between O. basilicum and other plant pre-miRNAs. Thirteen potential targets were evaluated for 4 miRNA families. Majority of the identified target transcripts regulated by miRNAs showed response to stress. miRNA 5021 was also indicated for playing an important role in the amino acid metabolism and co-factor metabolism in this plant. To the best of our knowledge this is the first in silico study describing miRNAs and their regulation in different metabolic pathways of O. basilicum. Copyright © 2014 Elsevier B.V. All rights reserved.

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

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.

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.

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.

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.

In silico characterization and analysis of RTBP1 and NgTRF1 protein through MD simulation and molecular docking - A comparative study.

PubMed

Mukherjee, Koel; Pandey, Dev Mani; Vidyarthi, Ambarish Saran

2015-02-06

Gaining access to sequence and structure information of telomere binding proteins helps in understanding the essential biological processes involve in conserved sequence specific interaction between DNA and the proteins. Rice telomere binding protein (RTBP1) and Nicotiana glutinosa telomere repeat binding factor (NgTRF1) are helix turn helix motif type of proteins that plays role in telomeric DNA protection and length regulation. Both the proteins share same type of domain but till now there is very less communication on the in silico studies of these complete proteins.Here we intend to do a comparative study between two proteins through modeling of the complete proteins, physiochemical characterization, MD simulation and DNA-protein docking. I-TASSER and CLC protein work bench was performed to find out the protein 3D structure as well as the different parameters to characterize the proteins. MD simulation was completed by GROMOS forcefield of GROMACS for 10 ns of time stretch. The simulated 3D structures were docked with template DNA (3D DNA modeled through 3D-DART) of TTTAGGG conserved sequence motif using HADDOCK web server.Digging up all the facts about the proteins it was reveled that around 120 amino acids in the tail part was showing a good sequence similarity between the proteins. Molecular modeling, sequence characterization and secondary structure prediction also indicates the similarity between the protein's structure and sequence. The result of MD simulation highlights on the RMSD, RMSF, Rg, PCA and Energy plots which also conveys the similar type of motional behavior between them. The best complex formation for both the proteins in docking result also indicates for the first interaction site which is mainly the helix3 region of the DNA binding domain. The overall computational analysis reveals that RTBP1 and NgTRF1 proteins display good amount of similarity in their physicochemical properties, structure, dynamics and binding mode.

In Silico Characterization and Analysis of RTBP1 and NgTRF1 Protein Through MD Simulation and Molecular Docking: A Comparative Study.

PubMed

Mukherjee, Koel; Pandey, Dev Mani; Vidyarthi, Ambarish Saran

2015-09-01

Gaining access to sequence and structure information of telomere-binding proteins helps in understanding the essential biological processes involve in conserved sequence-specific interaction between DNA and the proteins. Rice telomere-binding protein (RTBP1) and Nicotiana glutinosa telomere repeat binding factor (NgTRF1) are helix-turn-helix motif type of proteins that plays role in telomeric DNA protection and length regulation. Both the proteins share same type of domain, but till now there is very less communication on the in silico studies of these complete proteins. Here we intend to do a comparative study between two proteins through modeling of the complete proteins, physiochemical characterization, MD simulation and DNA-protein docking. I-TASSER and CLC protein work bench was performed to find out the protein 3D structure as well as the different parameters to characterize the proteins. MD simulation was completed by GROMOS forcefield of GROMACS for 10 ns of time stretch. The simulated 3D structures were docked with template DNA (3D DNA modeled through 3D-DART) of TTTAGGG conserved sequence motif using HADDOCK Web server. By digging up all the facts about the proteins, it was revealed that around 120 amino acids in the tail part were showing a good sequence similarity between the proteins. Molecular modeling, sequence characterization and secondary structure prediction also indicate the similarity between the protein's structure and sequence. The result of MD simulation highlights on the RMSD, RMSF, Rg, PCA and energy plots which also conveys the similar type of motional behavior between them. The best complex formation for both the proteins in docking result also indicates for the first interaction site which is mainly the helix3 region of the DNA-binding domain. The overall computational analysis reveals that RTBP1 and NgTRF1 proteins display good amount of similarity in their physicochemical properties, structure, dynamics and binding mode.

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 ...

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.

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.

Variability within Systemic In Vivo Toxicity Studies (ASCCT)

EPA Science Inventory

In vivo studies have long been considered the gold standard for toxicology screening. Often time models developed in silico and/or using in vitro data to estimate points of departures (POD) are compared to the in vivo data to benchmark and evaluate quality and goodness of fit. ...

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

In silico approaches to study mass and energy flows in microbial consortia: a syntrophic case study

PubMed Central

2009-01-01

Background Three methods were developed for the application of stoichiometry-based network analysis approaches including elementary mode analysis to the study of mass and energy flows in microbial communities. Each has distinct advantages and disadvantages suitable for analyzing systems with different degrees of complexity and a priori knowledge. These approaches were tested and compared using data from the thermophilic, phototrophic mat communities from Octopus and Mushroom Springs in Yellowstone National Park (USA). The models were based on three distinct microbial guilds: oxygenic phototrophs, filamentous anoxygenic phototrophs, and sulfate-reducing bacteria. Two phases, day and night, were modeled to account for differences in the sources of mass and energy and the routes available for their exchange. Results The in silico models were used to explore fundamental questions in ecology including the prediction of and explanation for measured relative abundances of primary producers in the mat, theoretical tradeoffs between overall productivity and the generation of toxic by-products, and the relative robustness of various guild interactions. Conclusion The three modeling approaches represent a flexible toolbox for creating cellular metabolic networks to study microbial communities on scales ranging from cells to ecosystems. A comparison of the three methods highlights considerations for selecting the one most appropriate for a given microbial system. For instance, communities represented only by metagenomic data can be modeled using the pooled method which analyzes a community's total metabolic potential without attempting to partition enzymes to different organisms. Systems with extensive a priori information on microbial guilds can be represented using the compartmentalized technique, employing distinct control volumes to separate guild-appropriate enzymes and metabolites. If the complexity of a compartmentalized network creates an unacceptable computational burden, the nested analysis approach permits greater scalability at the cost of more user intervention through multiple rounds of pathway analysis. PMID:20003240

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

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

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

Development and implementation of a highly-multiplexed SNP array for genetic mapping in maritime pine and comparative mapping with loblolly pine

PubMed Central

2011-01-01

Background Single nucleotide polymorphisms (SNPs) are the most abundant source of genetic variation among individuals of a species. New genotyping technologies allow examining hundreds to thousands of SNPs in a single reaction for a wide range of applications such as genetic diversity analysis, linkage mapping, fine QTL mapping, association studies, marker-assisted or genome-wide selection. In this paper, we evaluated the potential of highly-multiplexed SNP genotyping for genetic mapping in maritime pine (Pinus pinaster Ait.), the main conifer used for commercial plantation in southwestern Europe. Results We designed a custom GoldenGate assay for 1,536 SNPs detected through the resequencing of gene fragments (707 in vitro SNPs/Indels) and from Sanger-derived Expressed Sequenced Tags assembled into a unigene set (829 in silico SNPs/Indels). Offspring from three-generation outbred (G2) and inbred (F2) pedigrees were genotyped. The success rate of the assay was 63.6% and 74.8% for in silico and in vitro SNPs, respectively. A genotyping error rate of 0.4% was further estimated from segregating data of SNPs belonging to the same gene. Overall, 394 SNPs were available for mapping. A total of 287 SNPs were integrated with previously mapped markers in the G2 parental maps, while 179 SNPs were localized on the map generated from the analysis of the F2 progeny. Based on 98 markers segregating in both pedigrees, we were able to generate a consensus map comprising 357 SNPs from 292 different loci. Finally, the analysis of sequence homology between mapped markers and their orthologs in a Pinus taeda linkage map, made it possible to align the 12 linkage groups of both species. Conclusions Our results show that the GoldenGate assay can be used successfully for high-throughput SNP genotyping in maritime pine, a conifer species that has a genome seven times the size of the human genome. This SNP-array will be extended thanks to recent sequencing effort using new generation sequencing technologies and will include SNPs from comparative orthologous sequences that were identified in the present study, providing a wider collection of anchor points for comparative genomics among the conifers. PMID:21767361

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

GenePattern | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

GenePattern is a genomic analysis platform that provides access to hundreds of tools for the analysis and visualization of multiple data types. A web-based interface provides easy access to these tools and allows the creation of multi-step analysis pipelines that enable reproducible in silico research. A new GenePattern Notebook environment allows users to combine GenePattern analyses with text, graphics, and code to create complete reproducible research narratives.

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

Impact of gastrointestinal disease states on oral drug absorption - implications for formulation design - a PEARRL review.

PubMed

Effinger, Angela; O'Driscoll, Caitriona M; McAllister, Mark; Fotaki, Nikoletta

2018-05-16

Drug product performance in patients with gastrointestinal (GI) diseases can be altered compared to healthy subjects due to pathophysiological changes. In this review, relevant differences in patients with inflammatory bowel diseases, coeliac disease, irritable bowel syndrome and short bowel syndrome are discussed and possible in vitro and in silico tools to predict drug product performance in this patient population are assessed. Drug product performance was altered in patients with GI diseases compared to healthy subjects, as assessed in a limited number of studies for some drugs. Underlying causes can be observed pathophysiological alterations such as the differences in GI transit time, the composition of the GI fluids and GI permeability. Additionally, alterations in the abundance of metabolising enzymes and transporter systems were observed. The effect of the GI diseases on each parameter is not always evident as it may depend on the location and the state of the disease. The impact of the pathophysiological change on drug bioavailability depends on the physicochemical characteristics of the drug, the pharmaceutical formulation and drug metabolism. In vitro and in silico methods to predict drug product performance in patients with GI diseases are currently limited but could be a useful tool to improve drug therapy. Development of suitable in vitro dissolution and in silico models for patients with GI diseases can improve their drug therapy. The likeliness of the models to provide accurate predictions depends on the knowledge of pathophysiological alterations, and thus, further assessment of physiological differences is essential. © 2018 Royal Pharmaceutical Society.

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.

Understanding the antiangiogenic effect of metronomic chemotherapy through a simple mathematical model

NASA Astrophysics Data System (ADS)

Rodrigues, Diego S.; Mancera, Paulo F. A.; Pinho, Suani T. R.

2016-12-01

Despite the current and increasingly successful fight against cancer, there are some important questions concerning the efficiency of its treatment - in particular, the design of oncology chemotherapy protocols. Seeking efficiency, schedules based on more frequent, low-doses of drugs, known as metronomic chemotherapy, have been proposed as an alternative to the classical standard protocol of chemotherapy administration. The in silico approach may be very useful for providing a comparative analysis of these two kinds of protocols. In so doing, we found that metronomic schedules are more effective in eliminating tumour cells mainly due to their chemotherapeutic action on endothelial cells and that more frequent, low drug doses also entail outcomes in which the survival time of patient is increased.

Reconstruction of metabolic networks from high-throughput metabolite profiling data: in silico analysis of red blood cell metabolism.

PubMed

Nemenman, Ilya; Escola, G Sean; Hlavacek, William S; Unkefer, Pat J; Unkefer, Clifford J; Wall, Michael E

2007-12-01

We investigate the ability of algorithms developed for reverse engineering of transcriptional regulatory networks to reconstruct metabolic networks from high-throughput metabolite profiling data. For benchmarking purposes, we generate synthetic metabolic profiles based on a well-established model for red blood cell metabolism. A variety of data sets are generated, accounting for different properties of real metabolic networks, such as experimental noise, metabolite correlations, and temporal dynamics. These data sets are made available online. We use ARACNE, a mainstream algorithm for reverse engineering of transcriptional regulatory networks from gene expression data, to predict metabolic interactions from these data sets. We find that the performance of ARACNE on metabolic data is comparable to that on gene expression data.

Cytochrome C oxydase deficiency: SURF1 gene investigation in patients with Leigh syndrome.

PubMed

Maalej, Marwa; Kammoun, Thouraya; Alila-Fersi, Olfa; Kharrat, Marwa; Ammar, Marwa; Felhi, Rahma; Mkaouar-Rebai, Emna; Keskes, Leila; Hachicha, Mongia; Fakhfakh, Faiza

2018-03-18

Leigh syndrome (LS) is a rare progressive neurodegenerative disorder occurring in infancy. The most common clinical signs reported in LS are growth retardation, optic atrophy, ataxia, psychomotor retardation, dystonia, hypotonia, seizures and respiratory disorders. The paper reported a manifestation of 3 Tunisian patients presented with LS syndrome. The aim of this study is the MT[HYPHEN]ATP6 and SURF1 gene screening in Tunisian patients affected with classical Leigh syndrome and the computational investigation of the effect of detected mutations on its structure and functions by clinical and bioinformatics analyses. After clinical investigations, three Tunisian patients were tested for mutations in both MT-ATP6 and SURF1 genes by direct sequencing followed by in silico analyses to predict the effects of sequence variation. The result of mutational analysis revealed the absence of mitochondrial mutations in MT-ATP6 gene and the presence of a known homozygous splice site mutation c.516-517delAG in sibling patients added to the presence of a novel double het mutations in LS patient (c.752-18 A > C/c. c.751 + 16G > A). In silico analyses of theses intronic variations showed that it could alters splicing processes as well as SURF1 protein translation. Leigh syndrome (LS) is a rare progressive neurodegenerative disorder occurring in infancy. The most common clinical signs reported in LS are growth retardation, optic atrophy, ataxia, psychomotor retardation, dystonia, hypotonia, seizures and respiratory disorders. The paper reported a manifestation of 3 Tunisian patients presented with LS syndrome. The aim of this study is MT-ATP6 and SURF1 genes screening in Tunisian patients affected with classical Leigh syndrome and the computational investigation of the effect of detected mutations on its structure and functions. After clinical investigations, three Tunisian patients were tested for mutations in both MT-ATP6 and SURF1 genes by direct sequencing followed by in silico analysis to predict the effects of sequence variation. The result of mutational analysis revealed the absence of mitochondrial mutations in MT-ATP6 gene and the presence of a known homozygous splice site mutation c.516-517delAG in sibling patients added to the presence of a novel double het mutations in LS patient (c.752-18 A>C/ c.751+16G>A). In silico analysis of theses intronic vaiations showed that it could alters splicing processes as well as SURF1 protein translation. Copyright © 2018 Elsevier Inc. All rights reserved.

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.

Genome-wide investigation and expression analysis of AP2-ERF gene family in salt tolerant common bean

PubMed Central

Kavas, Musa; Kizildogan, Aslihan; Gökdemir, Gökhan; Baloglu, Mehmet Cengiz

2015-01-01

Apetala2-ethylene-responsive element binding factor (AP2-ERF) superfamily with common AP2-DNA binding domain have developmentally and physiologically important roles in plants. Since common bean genome project has been completed recently, it is possible to identify all of the AP2-ERF genes in the common bean genome. In this study, a comprehensive genome-wide in silico analysis identified 180 AP2-ERF superfamily genes in common bean (Phaseolus vulgaris). Based on the amino acid alignment and phylogenetic analyses, superfamily members were classified into four subfamilies: DREB (54), ERF (95), AP2 (27) and RAV (3), as well as one soloist. The physical and chemical characteristics of amino acids, interaction between AP2-ERF proteins, cis elements of promoter region of AP2-ERF genes and phylogenetic trees were predicted and analyzed. Additionally, expression levels of AP2-ERF genes were evaluated by in silico and qRT-PCR analyses. In silico micro-RNA target transcript analyses identified nearly all PvAP2-ERF genes as targets of by 44 different plant species' miRNAs were identified in this study. The most abundant target genes were PvAP2/ERF-20-25-62-78-113-173. miR156, miR172 and miR838 were the most important miRNAs found in targeting and BLAST analyses. Interactome analysis revealed that the transcription factor PvAP2-ERF78, an ortholog of Arabidopsis At2G28550, was potentially interacted with at least 15 proteins, indicating that it was very important in transcriptional regulation. Here we present the first study to identify and characterize the AP2-ERF transcription factors in common bean using whole-genome analysis, and the findings may serve as a references for future functional research on the transcription factors in common bean. PMID:27152109

T-Reg Comparator: an analysis tool for the comparison of position weight matrices

PubMed Central

Roepcke, Stefan; Grossmann, Steffen; Rahmann, Sven; Vingron, Martin

2005-01-01

T-Reg Comparator is a novel software tool designed to support research into transcriptional regulation. Sequence motifs representing transcription factor binding sites are usually encoded as position weight matrices. The user inputs a set of such weight matrices or binding site sequences and our program matches them against the T-Reg database, which is presently built on data from the Transfac [E. Wingender (2004) In Silico Biol., 4, 55–61] and Jaspar [A. Sandelin, W. Alkema, P. Engstrom, W. W. Wasserman and B. Lenhard (2004) Nucleic Acids Res., 32, D91–D94]. Our tool delivers a detailed report on similarities between user-supplied motifs and motifs in the database. Apart from simple one-to-one relationships, T-Reg Comparator is also able to detect similarities between submatrices. In addition, we provide a user interface to a program for sequence scanning with weight matrices. Typical areas of application for T-Reg Comparator are motif and regulatory module finding and annotation of regulatory genomic regions. T-Reg Comparator is available at . PMID:15980506

T-Reg Comparator: an analysis tool for the comparison of position weight matrices.

PubMed

Roepcke, Stefan; Grossmann, Steffen; Rahmann, Sven; Vingron, Martin

2005-07-01

T-Reg Comparator is a novel software tool designed to support research into transcriptional regulation. Sequence motifs representing transcription factor binding sites are usually encoded as position weight matrices. The user inputs a set of such weight matrices or binding site sequences and our program matches them against the T-Reg database, which is presently built on data from the Transfac [E. Wingender (2004) In Silico Biol., 4, 55-61] and Jaspar [A. Sandelin, W. Alkema, P. Engstrom, W. W. Wasserman and B. Lenhard (2004) Nucleic Acids Res., 32, D91-D94]. Our tool delivers a detailed report on similarities between user-supplied motifs and motifs in the database. Apart from simple one-to-one relationships, T-Reg Comparator is also able to detect similarities between submatrices. In addition, we provide a user interface to a program for sequence scanning with weight matrices. Typical areas of application for T-Reg Comparator are motif and regulatory module finding and annotation of regulatory genomic regions. T-Reg Comparator is available at http://treg.molgen.mpg.de.

In silico evaluation of gadofosveset pharmacokinetics in different population groups using the Simcyp® simulator platform.

PubMed

Spanakis, Marios; Marias, Kostas

2014-12-01

Gadofosveset is a Gd-based contrast agent used for magnetic resonance imaging (MRI). Gadolinium kinetic distribution models are implemented in T1-weighted dynamic contrast-enhanced perfusion MRI for characterization of lesion sites in the body. Physiology changes in a disease state potentially can influence the pharmacokinetics of drugs and to this respect modify the distribution properties of contrast agents. This work focuses on the in silico modelling of pharmacokinetic properties of gadofosveset in different population groups through the application of physiologically-based pharmacokinetic models (PBPK) embedded in Simcyp® population pharmacokinetics platform. Physicochemical and pharmacokinetic properties of gadofosveset were introduced into Simcyp® simulator platform and a min-PBPK model was applied. In silico clinical trials were generated simulating the administration of the recommended dose for the contrast agent (i.v., 30 mg/kg) in population cohorts of healthy volunteers, obese, renal and liver impairment, and in a generated virtual oncology population. Results were evaluated regarding basic pharmacokinetic parameters of Cmax, AUC and systemic CL and differences were assessed through ANOVA and estimation of ratio of geometric mean between healthy volunteers and the other population groups. Simcyp® predicted a mean Cmax = 551.60 mg/l, a mean AUC = 4079.12 mg/L*h and a mean systemic CL = 0.56 L/h for the virtual population of healthy volunteers. Obese population showed a modulation in Cmax and CL, attributed to increased administered dose. In renal and liver impairment cohorts a significant modulation in Cmax, AUC and CL of gadofosveset is predicted. Oncology population exhibited statistical significant differences regarding AUC when compared with healthy volunteers. This work employed Simcyp® population pharmacokinetics platform in order to compute gadofosveset's pharmacokinetic profiles through PBPK models and in silico clinical trials and evaluate possible differences between population groups. The approach showed promising results that could provide new insights regarding administration of contrast agents in special population cohorts. In silico pharmacokinetics could further be used for evaluating of possible toxicity, interpretation of MRI PK image maps and development of novel contrast agents.

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.

Profiling the interaction mechanism of quinoline/quinazoline derivatives as MCHR1 antagonists: an in silico method.

PubMed

Wu, Mingwei; Li, Yan; Fu, Xinmei; Wang, Jinghui; Zhang, Shuwei; Yang, Ling

2014-09-01

Melanin concentrating hormone receptor 1 (MCHR1), a crucial regulator of energy homeostasis involved in the control of feeding and energy metabolism, is a promising target for treatment of obesity. In the present work, the up-to-date largest set of 181 quinoline/quinazoline derivatives as MCHR1 antagonists was subjected to both ligand- and receptor-based three-dimensional quantitative structure-activity (3D-QSAR) analysis applying comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The optimal predictable CoMSIA model exhibited significant validity with the cross-validated correlation coefficient (Q²) = 0.509, non-cross-validated correlation coefficient (R²(ncv)) = 0.841 and the predicted correlation coefficient (R²(pred)) = 0.745. In addition, docking studies and molecular dynamics (MD) simulations were carried out for further elucidation of the binding modes of MCHR1 antagonists. MD simulations in both water and lipid bilayer systems were performed. We hope that the obtained models and information may help to provide an insight into the interaction mechanism of MCHR1 antagonists and facilitate the design and optimization of novel antagonists as anti-obesity agents.

Computational and empirical studies predict Mycobacterium tuberculosis-specific T cells as a biomarker for infection outcome

DOE PAGES

Marino, Simeone; Gideon, Hannah P.; Gong, Chang; ...

2016-04-11

Identifying biomarkers for tuberculosis (TB) is an ongoing challenge in developing immunological correlates of infection outcome and protection. Biomarker discovery is also necessary for aiding design and testing of new treatments and vaccines. To effectively predict biomarkers for infection progression in any disease, including TB, large amounts of experimental data are required to reach statistical power and make accurate predictions. We took a two-pronged approach using both experimental and computational modeling to address this problem. We first collected 200 blood samples over a 2-year period from 28 non-human primates (NHP) infected with a low dose of Mycobacterium tuberculosis. We identifiedmore » T cells and the cytokines that they were producing (single and multiple) from each sample along with monkey status and infection progression data. Machine learning techniques were used to interrogate the experimental NHP datasets without identifying any potential TB biomarker. In parallel, we used our extensive novel NHP datasets to build and calibrate a multi-organ computational model that combines what is occurring at the site of infection (e.g., lung) at a single granuloma scale with blood level readouts that can be tracked in monkeys and humans. We then generated a large in silico repository of in silico granulomas coupled to lymph node and blood dynamics and developed an in silico tool to scale granuloma level results to a full host scale to identify what best predicts Mycobacterium tuberculosis (Mtb) infection outcomes. The analysis of in silico blood measures identifies Mtb-specific frequencies of effector T cell phenotypes at various time points post infection as promising indicators of infection outcome. As a result, we emphasize that pairing wetlab and computational approaches holds great promise to accelerate TB biomarker discovery.« less

Computational and empirical studies predict Mycobacterium tuberculosis-specific T cells as a biomarker for infection outcome

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

Marino, Simeone; Gideon, Hannah P.; Gong, Chang

Identifying biomarkers for tuberculosis (TB) is an ongoing challenge in developing immunological correlates of infection outcome and protection. Biomarker discovery is also necessary for aiding design and testing of new treatments and vaccines. To effectively predict biomarkers for infection progression in any disease, including TB, large amounts of experimental data are required to reach statistical power and make accurate predictions. We took a two-pronged approach using both experimental and computational modeling to address this problem. We first collected 200 blood samples over a 2-year period from 28 non-human primates (NHP) infected with a low dose of Mycobacterium tuberculosis. We identifiedmore » T cells and the cytokines that they were producing (single and multiple) from each sample along with monkey status and infection progression data. Machine learning techniques were used to interrogate the experimental NHP datasets without identifying any potential TB biomarker. In parallel, we used our extensive novel NHP datasets to build and calibrate a multi-organ computational model that combines what is occurring at the site of infection (e.g., lung) at a single granuloma scale with blood level readouts that can be tracked in monkeys and humans. We then generated a large in silico repository of in silico granulomas coupled to lymph node and blood dynamics and developed an in silico tool to scale granuloma level results to a full host scale to identify what best predicts Mycobacterium tuberculosis (Mtb) infection outcomes. The analysis of in silico blood measures identifies Mtb-specific frequencies of effector T cell phenotypes at various time points post infection as promising indicators of infection outcome. As a result, we emphasize that pairing wetlab and computational approaches holds great promise to accelerate TB biomarker discovery.« less

In vivo and in silico determination of essential genes of Campylobacter jejuni.

PubMed

Metris, Aline; Reuter, Mark; Gaskin, Duncan J H; Baranyi, Jozsef; van Vliet, Arnoud H M

2011-11-01

In the United Kingdom, the thermophilic Campylobacter species C. jejuni and C. coli are the most frequent causes of food-borne gastroenteritis in humans. While campylobacteriosis is usually a relatively mild infection, it has a significant public health and economic impact, and possible complications include reactive arthritis and the autoimmune diseases Guillain-Barré syndrome. The rapid developments in "omics" technologies have resulted in the availability of diverse datasets allowing predictions of metabolism and physiology of pathogenic micro-organisms. When combined, these datasets may allow for the identification of potential weaknesses that can be used for development of new antimicrobials to reduce or eliminate C. jejuni and C. coli from the food chain. A metabolic model of C. jejuni was constructed using the annotation of the NCTC 11168 genome sequence, a published model of the related bacterium Helicobacter pylori, and extensive literature mining. Using this model, we have used in silico Flux Balance Analysis (FBA) to determine key metabolic routes that are essential for generating energy and biomass, thus creating a list of genes potentially essential for growth under laboratory conditions. To complement this in silico approach, candidate essential genes have been determined using a whole genome transposon mutagenesis method. FBA and transposon mutagenesis (both this study and a published study) predict a similar number of essential genes (around 200). The analysis of the intersection between the three approaches highlights the shikimate pathway where genes are predicted to be essential by one or more method, and tend to be network hubs, based on a previously published Campylobacter protein-protein interaction network, and could therefore be targets for novel antimicrobial therapy. We have constructed the first curated metabolic model for the food-borne pathogen Campylobacter jejuni and have presented the resulting metabolic insights. We have shown that the combination of in silico and in vivo approaches could point to non-redundant, indispensable genes associated with the well characterised shikimate pathway, and also genes of unknown function specific to C. jejuni, which are all potential novel Campylobacter intervention targets.

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.

Identification and characterization of the autophagy-related genes Atg12 and Atg5 in hydra.

PubMed

Dixit, Nishikant S; Shravage, Bhupendra V; Ghaskadbi, Surendra

2017-01-01

Autophagy is an evolutionarily conserved process in eukaryotic cells that is involved in the degradation of cytoplasmic contents including organelles via the lysosome. Hydra is an early metazoan which exhibits simple tissue grade organization, a primitive nervous system, and is one of the classical non-bilaterian models extensively used in evo-devo research. Here, we describe the characterization of two core autophagy genes, Atg12 and Atg5, from hydra. In silico analyses including sequence similarity, domain analysis, and phylogenetic analysis demonstrate the conservation of these genes across eukaryotes. The predicted 3D structure of hydra Atg12 showed very little variance when compared to human Atg12 and yeast Atg12, whereas the hydra Atg5 predicted 3D structure was found to be variable, when compared with its human and yeast homologs. Strikingly, whole mount in situ hybridization showed high expression of Atg12 transcripts specifically in nematoblasts, whereas Atg5 transcripts were found to be expressed strongly in budding region and growing buds. This study may provide a framework to understand the evolution of autophagy networks in higher eukaryotes.

A Guideline to Family-Wide Comparative State-of-the-Art Quantitative RT-PCR Analysis Exemplified with a Brassicaceae Cross-Species Seed Germination Case Study[W][OA

PubMed Central

Graeber, Kai; Linkies, Ada; Wood, Andrew T.A.; Leubner-Metzger, Gerhard

2011-01-01

Comparative biology includes the comparison of transcriptome and quantitative real-time RT-PCR (qRT-PCR) data sets in a range of species to detect evolutionarily conserved and divergent processes. Transcript abundance analysis of target genes by qRT-PCR requires a highly accurate and robust workflow. This includes reference genes with high expression stability (i.e., low intersample transcript abundance variation) for correct target gene normalization. Cross-species qRT-PCR for proper comparative transcript quantification requires reference genes suitable for different species. We addressed this issue using tissue-specific transcriptome data sets of germinating Lepidium sativum seeds to identify new candidate reference genes. We investigated their expression stability in germinating seeds of L. sativum and Arabidopsis thaliana by qRT-PCR, combined with in silico analysis of Arabidopsis and Brassica napus microarray data sets. This revealed that reference gene expression stability is higher for a given developmental process between distinct species than for distinct developmental processes within a given single species. The identified superior cross-species reference genes may be used for family-wide comparative qRT-PCR analysis of Brassicaceae seed germination. Furthermore, using germinating seeds, we exemplify optimization of the qRT-PCR workflow for challenging tissues regarding RNA quality, transcript stability, and tissue abundance. Our work therefore can serve as a guideline for moving beyond Arabidopsis by establishing high-quality cross-species qRT-PCR. PMID:21666000

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.

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

DESIGN AND PERFORMANCE OF A XENOBIOTIC METABOLISM DATABASE MANAGER FOR METABOLIC SIMULATOR ENHANCEMENT AND CHEMICAL RISK ANALYSIS

EPA Science Inventory

A major uncertainty that has long been recognized in evaluating chemical toxicity is accounting for metabolic activation of chemicals resulting in increased toxicity. In silico approaches to predict chemical metabolism and to subsequently screen and prioritize chemicals for risk ...

In silico modeling and synthesis of phenyl and thienyl analogs of chalcones for potential leads as anti-bacterial agents

NASA Astrophysics Data System (ADS)

Kar, Swayamsiddha; Mishra, Rohit Kumar; Pathak, Ashutosh; Dikshit, Anupam; Golakoti, Nageswara Rao

2018-03-01

In the recent times, the common diseases like food poisoning, pneumonia, diarrhea etc. have been observed to be drug resistant. The present study deals with the synthesis of known chalcone derivatives using the Claisen-Schmidt condensation and further characterization using UV-vis, IR, 1H NMR, 13C NMR and mass spectrometry. These derivatives were first simulated for their anti-bacterial efficacy in silico and consequently confirmed in vitro to confirm the findings. One of the chalcones, 4-NDM-2‧-HC showed excellent in-vitro antibacterial activity with an IC90 0.43 mg/mL against Vibrio cholerae as compared to commercially available antibiotic gentamicin as the standard. Further, all these tested chalcone derivatives fulfill Lipinski's parameters and show tremendous drug likeness score, confirming their potential as antibacterial leads.

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.

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.

Number of Hydroxyl Groups on the B-Ring of Flavonoids Affects Their Antioxidant Activity and Interaction with Phorbol Ester Binding Site of PKCδ C1B Domain: In Vitro and in Silico Studies.

PubMed

Kongpichitchoke, Teeradate; Hsu, Jue-Liang; Huang, Tzou-Chi

2015-05-13

Although flavonoids have been reported for their benefits and nutraceutical potential use, the importance of their structure on their beneficial effects, especially on signal transduction mechanisms, has not been well clarified. In this study, three flavonoids, pinocembrin, naringenin, and eriodictyol, were chosen to determine the effect of hydroxyl groups on the B-ring of flavonoid structure on their antioxidant activity. In vitro assays, including DPPH scavenging activity, ROS quantification by flow cytometer, and proteins immunoblotting, and in silico analysis by molecular docking between the flavonoids and C1B domain of PKCδ phorbol ester binding site were both used to complete this study. Eriodictyol (10 μM), containing two hydroxyl groups on the B-ring, exhibited significantly higher (p < 0.05) antioxidant activity than pinocembrin and naringenin. The IC50 values of eriodictyol, naringenin, and pinocembrin were 17.4 ± 0.40, 30.2 ± 0.61, and 44.9 ± 0.57 μM, respectively. In addition, eriodictyol at 10 μM remarkably inhibited the phosphorylation of PKCδ at 63.4% compared with PMA-activated RAW264.7, whereas pinocembrin and naringenin performed inhibition activity at 76.8 and 72.6%, respectively. According to the molecular docking analysis, pinocembrin, naringenin, and eriodictyol showed -CDOCKER_energy values of 15.22, 16.95, and 21.49, respectively, reflecting that eriodictyol could bind with the binding site better than the other two flavonoids. Interestingly, eriodictyol had a remarkably different pose to bind with the kinase as a result of the two hydroxyl groups on its B-ring, which consequently contributed to greater antioxidant activity over pinocembrin and naringenin.

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.

Pesticides in mixture disrupt metabolic regulation: in silico and in vivo analysis of cumulative toxicity of mancozeb and imidacloprid on body weight of mice.

PubMed

Bhaskar, Rakesh; Mohanty, Banalata

2014-09-01

Pesticides acting as endocrine disrupting chemicals disrupt the homeostasis of body metabolism. The present study elucidated that the low dose coexposure of thyroid disrupting dithiocarbamate fungicide mancozeb (MCZ) and neonicotinoid insecticide imidacloprid (IMI) during lactation increased the risk of body weight gain in mice later in life. Body weight gain has been linked to pesticide-induced hypothyroidism and hyperprolactinemia and alteration of lipid profiles. In vivo results were substantiated with in silico molecular docking (MD) analysis that predicted the binding affinity of pesticides with thyroid hormone receptors (TRα and TRβ) and peroxisome proliferator activated receptor gamma (PPARγ), the major nuclear receptors of peripheral fat metabolism. Binding potency of MCZ and IMI was compared with that of T3, and its antagonist ethylene thiourea (ETU) as well as PPARγ agonist (rosiglitazone) and antagonist (HL005). MD simulation predicted that both MCZ and IMI may compete with T3 for binding with TRs. Imidazole group of IMI formed hydrogen bonds with TRs like that of ETU. MCZ may compete with rosiglitazone and HL005 for PPARγ, but IMI showed no affinity. Thus while both MCZ and IMI could disrupt the TRs functioning, MCZ alone may affect PPARγ. Coexposure of pesticides decreased the plasma thyroid hormones and increased the cholesterol and triglyceride. Individual pesticide exposure in low dose might not exert the threshold response to affect the receptors signaling further to cause hormonal/metabolic impairment. Thus, cumulative response of the mixture of thyroid disrupting pesticides can disrupt metabolic regulation through several pathways and contribute to gain in body weight. Copyright © 2014 Elsevier Inc. All rights reserved.

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.

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

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

Recent advances in the in silico modelling of UDP glucuronosyltransferase substrates.

PubMed

Sorich, Michael J; Smith, Paul A; Miners, John O; Mackenzie, Peter I; McKinnon, Ross A

2008-01-01

UDP glucurononosyltransferases (UGT) are a superfamily of enzymes that catalyse the conjugation of a range of structurally diverse drugs, environmental and endogenous chemicals with glucuronic acid. This process plays a significant role in the clearance and detoxification of many chemicals. Over the last decade the regulation and substrate profiles of UGT isoforms have been increasingly characterised. The resulting data has facilitated the prototyping of ligand based in silico models capable of predicting, and gaining insights into, binding affinity and the substrate- and regio- selectivity of glucuronidation by UGT isoforms. Pharmacophore modelling has produced particularly insightful models and quantitative structure-activity relationships based on machine learning algorithms result in accurate predictions. Simple structural chemical descriptors were found to capture much of the chemical information relevant to UGT metabolism. However, quantum chemical properties of molecules and the nucleophilic atoms in the molecule can enhance both the predictivity and chemical intuitiveness of structure-activity models. Chemical diversity analysis of known substrates has shown some bias towards chemicals with aromatic and aliphatic hydroxyl groups. Future progress in in silico development will depend on larger and more diverse high quality metabolic datasets. Furthermore, improved protein structure data on UGTs will enable the application of structural modelling techniques likely leading to greater insight into the binding and reactive processes of UGT catalysed glucuronidation.

CEQer: A Graphical Tool for Copy Number and Allelic Imbalance Detection from Whole-Exome Sequencing Data

PubMed Central

Piazza, Rocco; Magistroni, Vera; Pirola, Alessandra; Redaelli, Sara; Spinelli, Roberta; Redaelli, Serena; Galbiati, Marta; Valletta, Simona; Giudici, Giovanni; Cazzaniga, Giovanni; Gambacorti-Passerini, Carlo

2013-01-01

Copy number alterations (CNA) are common events occurring in leukaemias and solid tumors. Comparative Genome Hybridization (CGH) is actually the gold standard technique to analyze CNAs; however, CGH analysis requires dedicated instruments and is able to perform only low resolution Loss of Heterozygosity (LOH) analyses. Here we present CEQer (Comparative Exome Quantification analyzer), a new graphical, event-driven tool for CNA/allelic-imbalance (AI) coupled analysis of exome sequencing data. By using case-control matched exome data, CEQer performs a comparative digital exonic quantification to generate CNA data and couples this information with exome-wide LOH and allelic imbalance detection. This data is used to build mixed statistical/heuristic models allowing the identification of CNA/AI events. To test our tool, we initially used in silico generated data, then we performed whole-exome sequencing from 20 leukemic specimens and corresponding matched controls and we analyzed the results using CEQer. Taken globally, these analyses showed that the combined use of comparative digital exon quantification and LOH/AI allows generating very accurate CNA data. Therefore, we propose CEQer as an efficient, robust and user-friendly graphical tool for the identification of CNA/AI in the context of whole-exome sequencing data. PMID:24124457

Terminal Restriction Fragment Length Polymorphism Analysis Program, a Web-Based Research Tool for Microbial Community Analysis

PubMed Central

Marsh, Terence L.; Saxman, Paul; Cole, James; Tiedje, James

2000-01-01

Rapid analysis of microbial communities has proven to be a difficult task. This is due, in part, to both the tremendous diversity of the microbial world and the high complexity of many microbial communities. Several techniques for community analysis have emerged over the past decade, and most take advantage of the molecular phylogeny derived from 16S rRNA comparative sequence analysis. We describe a web-based research tool located at the Ribosomal Database Project web site (http://www.cme.msu.edu/RDP/html/analyses.html) that facilitates microbial community analysis using terminal restriction fragment length polymorphism of 16S ribosomal DNA. The analysis function (designated TAP T-RFLP) permits the user to perform in silico restriction digestions of the entire 16S sequence database and derive terminal restriction fragment sizes, measured in base pairs, from the 5′ terminus of the user-specified primer to the 3′ terminus of the restriction endonuclease target site. The output can be sorted and viewed either phylogenetically or by size. It is anticipated that the site will guide experimental design as well as provide insight into interpreting results of community analysis with terminal restriction fragment length polymorphisms. PMID:10919828

The antioxidant property of chitosan green tea polyphenols complex induces transglutaminase activation in wound healing.

PubMed

Qin, Yao; Guo, Xing Wei; Li, Lei; Wang, Hong Wei; Kim, Wook

2013-06-01

The present study examined, for the first time, the in vitro wound healing potential of chitosan green tea polyphenols (CGP) complex based on the activation of transglutaminase (TGM) genes in epidermal morphogenesis. Response surface methodology was applied to determine the optimal processing condition that gave maximum extraction of green tea polyphenols. The antioxidant activity, scavenging ability, and chelating ability were studied and expressed as average EC50 values of CGP and other treatments. In silico analysis and gene coexpression network was subjected to the TGM sequences analysis. The temporal expressions of TGMs were profiled by semi-quantitative reverse transcription (RT)-PCR technology within 10 days after wounding and 2 days postwounding. CGP showed the effectiveness of antioxidant properties, and the observations of histopathological photography showed advanced tissue granulation and epithelialization formation by CGP treatment. In silico and coexpression analysis confirmed the regulation via TGM gene family in dermatological tissues. RT-PCR demonstrated increased levels of TGM1-3 expression induced by CGP treatment. The efficacy of CGP in wound healing based on these results may be ascribed to its antioxidant properties and activation of the expression of TGMs, and is, thus, essential for the facilitated repair of skin injury.

Role of Alternative Polyadenylation during Adipogenic Differentiation: An In Silico Approach

PubMed Central

Spangenberg, Lucía; Correa, Alejandro; Dallagiovanna, Bruno; Naya, Hugo

2013-01-01

Post-transcriptional regulation of stem cell differentiation is far from being completely understood. Changes in protein levels are not fully correlated with corresponding changes in mRNAs; the observed differences might be partially explained by post-transcriptional regulation mechanisms, such as alternative polyadenylation. This would involve changes in protein binding, transcript usage, miRNAs and other non-coding RNAs. In the present work we analyzed the distribution of alternative transcripts during adipogenic differentiation and the potential role of miRNAs in post-transcriptional regulation. Our in silico analysis suggests a modest, consistent, bias in 3′UTR lengths during differentiation enabling a fine-tuned transcript regulation via small non-coding RNAs. Including these effects in the analyses partially accounts for the observed discrepancies in relative abundance of protein and mRNA. PMID:24143171

An in silico analysis of oxygen uptake of a mild COPD patient during rest and exercise using a portable oxygen concentrator

PubMed Central

Katz, Ira; Pichelin, Marine; Montesantos, Spyridon; Kang, Min-Yeong; Sapoval, Bernard; Zhu, Kaixian; Thevenin, Charles-Philippe; McCoy, Robert; Martin, Andrew R; Caillibotte, Georges

2016-01-01

Oxygen treatment based on intermittent-flow devices with pulse delivery modes available from portable oxygen concentrators (POCs) depends on the characteristics of the delivered pulse such as volume, pulse width (the time of the pulse to be delivered), and pulse delay (the time for the pulse to be initiated from the start of inhalation) as well as a patient’s breathing characteristics, disease state, and respiratory morphology. This article presents a physiological-based analysis of the performance, in terms of blood oxygenation, of a commercial POC at different settings using an in silico model of a COPD patient at rest and during exercise. The analysis encompasses experimental measurements of pulse volume, width, and time delay of the POC at three different settings and two breathing rates related to rest and exercise. These experimental data of device performance are inputs to a physiological-based model of oxygen uptake that takes into account the real dynamic nature of gas exchange to illustrate how device- and patient-specific factors can affect patient oxygenation. This type of physiological analysis that considers the true effectiveness of oxygen transfer to the blood, as opposed to delivery to the nose (or mouth), can be instructive in applying therapies and designing new devices. PMID:27729783

Analysis of ZP1 gene reveals differences in zona pellucida composition in carnivores.

PubMed

Moros-Nicolás, C; Leza, A; Chevret, P; Guillén-Martínez, A; González-Brusi, L; Boué, F; Lopez-Bejar, M; Ballesta, J; Avilés, M; Izquierdo-Rico, M J

2018-01-01

The zona pellucida (ZP) is an extracellular envelope that surrounds mammalian oocytes. This coat participates in the interaction between gametes, induction of the acrosome reaction, block of polyspermy and protection of the oviductal embryo. Previous studies suggested that carnivore ZP was formed by three glycoproteins (ZP2, ZP3 and ZP4), with ZP1 being a pseudogene. However, a recent study in the cat found that all four proteins were expressed. In the present study, in silico and molecular analyses were performed in several carnivores to clarify the ZP composition in this order of mammals. The in silico analysis demonstrated the presence of the ZP1 gene in five carnivores: cheetah, panda, polar bear, tiger and walrus, whereas in the Antarctic fur seal and the Weddell seal there was evidence of pseudogenisation. Molecular analysis showed the presence of four ZP transcripts in ferret ovaries (ZP1, ZP2, ZP3 and ZP4) and three in fox ovaries (ZP2, ZP3 and ZP4). Analysis of the fox ZP1 gene showed the presence of a stop codon. The results strongly suggest that all four ZP genes are expressed in most carnivores, whereas ZP1 pseudogenisation seems to have independently affected three families (Canidae, Otariidae and Phocidae) of the carnivore tree.

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.

DNA methylation regulated microRNAs in HPV-16-induced head and neck squamous cell carcinoma (HNSCC).

PubMed

Sannigrahi, M K; Sharma, Rajni; Singh, Varinder; Panda, Naresh K; Rattan, Vidya; Khullar, Madhu

2018-02-17

Epigenetic modifications have been reported to play an important role in regulating gene expression and these modifications become critical when they have a role in controlling another important layer of epigenetic regulation namely microRNAs. In the present study, we have identified the microRNAs that may be regulated by promoter DNA methylation and histone acetylation in Human papilloma virus-positive head and neck squamous cell carcinoma. HPV-negative cell line (UPCI:SCC-116) and HPV-16 +ve cell line (UPCI:SCC-090) were treated with methylation inhibitor (5-aza-2'-deoxycytidine, AZA) and acetylation inhibitor (Trichostatin-A, TSA), followed by micro-array analysis. The differentially expressed miRNAs were validated in control (n = 10), HPV-16 +ve (n = 30), and HPV -ve (n = 30) HNC, TCGA (n = 529) tissue samples, and two HPV -ve (SCC116 and Hacat) and two HPV +ve (SCC090 and SiHa) cell lines. Methylation-specific PCR (MSP) and chromatin immunoprecipitation assay (CHIP) were performed to validate their regulation. In silico and in vitro analyses of identified miRNAs were done to study putative pathways they target and their possible role in carcinogenesis. Among 10 miRNAs specifically up-regulated in microarray analysis of AZA-treated SCC090 cells, we observed significantly decreased expression of hsa-miR-181c-5p, hsa-miR-132-5p, hsa-miR-658 in HPV +ve HNC cohort, TCGA tissue samples, and cell lines as compared to their HPV -ve counterpart, and their promoter region also possesses CpG islands. MSP and analysis of TCGA data (MethHC) revealed increased frequency of methylation at the promoter of hsa-miR-132-5p that is negatively correlated with its expression. In TSA-treated SCC090 cells, out of 7 miRNAs, two namely Hsa-miR-129-2-3p and Hsa-miR-449a were found to be up-regulated as compared to HPV -ve cells. However, the levels of enrichment by anti-acetyl-H3 and anti-acetyl-H4 were significantly low in cell lines compared to respective controls and both were up-regulated in HPV +ve compared to HPV -ve TCGA tissue samples. In silico analysis revealed hsa-miR-132-5p targeted canonical β-catenin/wnt pathway and modulation of down-stream genes of the pathway was observed on over-expression/inhibition of hsa-miR-132-5p. This study suggests the role of epigenetic modifications in regulating expression of miRNAs in HPV +ve HNSCC.

A High-Resolution Comparative Chromosome Map of Cricetus cricetus and Peromyscus eremicus Reveals the Involvement of Constitutive Heterochromatin in Breakpoint Regions.

PubMed

Vieira-da-Silva, Ana; Louzada, Sandra; Adega, Filomena; Chaves, Raquel

2015-01-01

Compared to humans and other mammals, rodent genomes, specifically Muroidea species, underwent intense chromosome reshuffling in which many complex structural rearrangements occurred. This fact makes them preferential animal models for studying the process of karyotype evolution. Here, we present the first combined chromosome comparative maps between 2 Cricetidae species, Cricetus cricetus and Peromyscus eremicus, and the index species Mus musculus and Rattus norvegicus. Comparative chromosome painting was done using mouse and rat paint probes together with in silico analysis from the Ensembl genome browser database. Hereby, evolutionary events (inter- and intrachromosomal rearrangements) that occurred in C. cricetus and P. eremicus since the putative ancestral Muroidea genome could be inferred, and evolutionary breakpoint regions could be detected. A colocalization of constitutive heterochromatin and evolutionary breakpoint regions in each genome was observed. Our results suggest the involvement of constitutive heterochromatin in karyotype restructuring of these species, despite the different levels of conservation of the C. cricetus (derivative) and P. eremicus (conserved) genomes. © 2015 S. Karger AG, Basel.

In silico study of protein to protein interaction analysis of AMP-activated protein kinase and mitochondrial activity in three different farm animal species

NASA Astrophysics Data System (ADS)

Prastowo, S.; Widyas, N.

2018-03-01

AMP-activated protein kinase (AMPK) is cellular energy censor which works based on ATP and AMP concentration. This protein interacts with mitochondria in determine its activity to generate energy for cell metabolism purposes. For that, this paper aims to compare the protein to protein interaction of AMPK and mitochondrial activity genes in the metabolism of known animal farm (domesticated) that are cattle (Bos taurus), pig (Sus scrofa) and chicken (Gallus gallus). In silico study was done using STRING V.10 as prominent protein interaction database, followed with biological function comparison in KEGG PATHWAY database. Set of genes (12 in total) were used as input analysis that are PRKAA1, PRKAA2, PRKAB1, PRKAB2, PRKAG1, PRKAG2, PRKAG3, PPARGC1, ACC, CPT1B, NRF2 and SOD. The first 7 genes belong to gene in AMPK family, while the last 5 belong to mitochondrial activity genes. The protein interaction result shows 11, 8 and 5 metabolism pathways in Bos taurus, Sus scrofa and Gallus gallus, respectively. The top pathway in Bos taurus is AMPK signaling pathway (10 genes), Sus scrofa is Adipocytokine signaling pathway (8 genes) and Gallus gallus is FoxO signaling pathway (5 genes). Moreover, the common pathways found in those 3 species are Adipocytokine signaling pathway, Insulin signaling pathway and FoxO signaling pathway. Genes clustered in Adipocytokine and Insulin signaling pathway are PRKAA2, PPARGC1A, PRKAB1 and PRKAG2. While, in FoxO signaling pathway are PRKAA2, PRKAB1, PRKAG2. According to that, we found PRKAA2, PRKAB1 and PRKAG2 are the common genes. Based on the bioinformatics analysis, we can demonstrate that protein to protein interaction shows distinct different of metabolism in different species. However, further validation is needed to give a clear explanation.

Heat Shock70 Protein Genes and Genetic Susceptibility to Apical Periodontitis

PubMed Central

Maheshwari, Kanwal; Silva, Renato M.; Guajardo-Morales, Leticia; Garlet, Gustavo P.; Vieira, Alexandre R.; Letra, Ariadne

2016-01-01

Introduction Heat shock proteins (HSP) protect cells under adverse conditions such as infection, inflammation, and disease. The differential expression of HSPs in human periapical granulomas suggests a potential role for these proteins in periapical lesion development, which may contribute to different clinical outcomes. Therefore, we hypothesize that polymorphisms in HSP genes leading to perturbed gene expression and protein function may contribute to an individual’s susceptibility to periapical lesion development. Methods Subjects with deep carious lesions, with or without periapical lesions (≥ 3 mm) were recruited at the University of Texas School of Dentistry at Houston and at the University of Pittsburgh. Genomic DNA samples of 400 patients were sorted into 2 groups: 183 cases with deep carious lesions and periapical lesions (cases), and 217 cases with deep carious lesions but without periapical lesions (controls). Eight single nucleotide polymorphisms in HSPA4, HSPA6, HSPA1L, HSPA4L and HSPA9 genes were selected for genotyping. Genotypes were generated by endpoint analysis using Taqman chemistry in a real-time polymerase chain reaction assay. Allele and genotype frequencies were compared among cases and controls using chi-square and Fisher Exact tests as implemented in PLINK v.1.07. In silico analysis of SNP function was performed using Polymorphism Phenotyping V2 and MirSNP softwares. Results Overall, SNPs in HSPA1L and HSPA6 showed significant allelic association with cases of deep caries and periapical lesions (P<0.05). We also observed altered transmission of HSPA1L SNP haplotypes (P=0.03). In silico analysis of HSPA1L rs2075800 function showed that this SNP results in a glutamine to lysine substitution at position 602 of the protein and might affect the stability and function of the final protein. Conclusions Variations in HSPA1L and HSPA6 may be associated with periapical lesion formation in individuals with untreated deep carious lesions. Future studies could help predict host susceptibility to developing apical periodontitis. PMID:27567034

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.

Assessing the environmental fate of S-metolachlor, its commercial product Mercantor Gold® and their photoproducts using a water-sediment test and in silico methods.

PubMed

Gutowski, Lukasz; Baginska, Ewelina; Olsson, Oliver; Leder, Christoph; Kümmerer, Klaus

2015-11-01

Pesticides enter surface and groundwater by several routes in which partition to sediment contributes to their fate by abiotic (e.g. photolysis, hydrolysis) and biotic processes. Yet, little is known about S-metolachlor (SM) transformation in water-sediment systems. Therefore, a newly developed screening water-sediment test (WST) was applied to compare biodegradation and sorption processes between pure SM and Mercantor Gold® (MG), a commercial formulation of SM. Photolysis in water was performed by Xe lamp irradiation. Subsequently, the biodegradability of SM and MG photolysis mixtures was examined in WST. The primary elimination of SM from water phase was monitored and structures of its TPs resulting from biotransformation (bio-TPs) were elucidated by LC-MS/MS. SM was extracted from sediment in order to estimate the role of sorption in WST for its elimination. A set of in silico prediction software tools was applied for toxicity assessment of SM and its bio-TPs. Obtained results suggest that the MG adjuvants do not significantly affect biodegradation, but do influence diffusion of SM into sediment. 50% of SM could not be re-extracted from sediment with 0.01 M CaCl2 aqueous solution recommended in OECD test guideline for adsorption. Neither the parent compound nor the photo-TPs were biodegraded. However, new bio-TPs have been generated from SM and MG photo-TPs due to bacterial activity in the water-sediment interphase. Moreover, according to in silico assessment of the bio-TPs the biotransformation might lead to an increased toxicity to the water organisms compared with the SM. This might raise concerns of bio-TPs presence in the environment. Copyright © 2015 Elsevier Ltd. All rights reserved.

Computational Exploration of a Protein Receptor Binding Space with Student Proposed Peptide Ligands

ERIC Educational Resources Information Center

King, Matthew D.; Phillips, Paul; Turner, Matthew W.; Katz, Michael; Lew, Sarah; Bradburn, Sarah; Andersen, Tim; McDougal, Owen M.

2016-01-01

Computational molecular docking is a fast and effective "in silico" method for the analysis of binding between a protein receptor model and a ligand. The visualization and manipulation of protein to ligand binding in three-dimensional space represents a powerful tool in the biochemistry curriculum to enhance student learning. The…

In silico cloning, expression of Rieske-like apoprotein gene and protein subcellular localization in the Pacific oyster, Crassostrea gigas.

PubMed

He, Xiaocui; Zhang, Yang; Yu, Ziniu

2010-10-01

Rieske protein gene in the Pacific oyster Crassostrea gigas was obtained by in silico cloning for the first time, and its expression profiles and subcellular localization were determined, respectively. The full-length cDNA of Cgisp is 985 bp in length and contains a 5'- and 3'-untranslated regions of 35 and 161 bp, respectively, with an open reading frame of 786 bp encoding a protein of 262 amino acids. The predicted molecular weight of 30 kDa of Cgisp protein was verified by prokaryotic expression. Conserved Rieske [2Fe-2S] cluster binding sites and highly matched-pair tertiary structure with 3CWB_E (Gallus gallus) were revealed by homologous analysis and molecular modeling. Eleven putative SNP sites and two conserved hexapeptide sequences, box I (THLGC) and II (PCHGS), were detected by multiple alignments. Real-time PCR analysis showed that Cgisp is expressed in a wide range of tissues, with adductor muscle exhibiting the top expression level, suggesting its biological function of energy transduction. The GFP tagging Cgisp indicated a mitochondrial localization, further confirming its physiological function.

Development of a highly efficient oil degumming process using a novel phosphatidylinositol-specific phospholipase C enzyme.

PubMed

Cerminati, Sebastián; Eberhardt, Florencia; Elena, Claudia E; Peirú, Salvador; Castelli, María E; Menzella, Hugo G

2017-06-01

Enzymatic degumming using phospholipase C (PLC) enzymes may be used in environmentally friendly processes with improved oil recovery yields. In this work, phosphatidylinositol-specific phospholipase C (PIPLC) candidates obtained from an in silico analysis were evaluated for oil degumming. A PIPLC from Lysinibacillus sphaericus was shown to efficiently remove phosphatidylinositol from crude oil, and when combined with a second phosphatidylcholine and phosphatidylethanolamine-specific phospholipase C, the three major phospholipids were completely hydrolyzed, providing an extra yield of oil greater than 2.1%, compared to standard methods. A remarkably efficient fed-batch Escherichia coli fermentation process producing ∼14 g/L of the recombinant PIPLC enzyme was developed, which may facilitate the adoption of this cost-effective oil-refining process.

In silico site-directed mutagenesis informs species-specific predictions of chemical susceptibility derived from the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool

EPA Science Inventory

The Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool was developed to address needs for rapid, cost effective methods of species extrapolation of chemical susceptibility. Specifically, the SeqAPASS tool compares the primary sequence (Level 1), functiona...

In Silico Testing of an Artificial-Intelligence-Based Artificial Pancreas Designed for Use in the Intensive Care Unit Setting

PubMed Central

DeJournett, Leon; DeJournett, Jeremy

2016-01-01

Background: Effective glucose control in the intensive care unit (ICU) setting has the potential to decrease morbidity and mortality rates which should in turn lead to decreased health care expenditures. Current ICU-based glucose controllers are mathematically derived, and tend to be based on proportional integral derivative (PID) or model predictive control (MPC). Artificial intelligence (AI)–based closed loop glucose controllers may have the ability to achieve control that improves on the results achieved by either PID or MPC controllers. Method: We conducted an in silico analysis of an AI-based glucose controller designed for use in the ICU setting. This controller was tested using a mathematical model of the ICU patient’s glucose-insulin system. A total of 126 000 unique 5-day simulations were carried out, resulting in 107 million glucose values for analysis. Results: For the 7 control ranges tested, with a sensor error of ±10%, the following average results were achieved: (1) time in control range, 94.2%, (2) time in range 70-140 mg/dl, 97.8%, (3) time in hyperglycemic range (>140 mg/dl), 2.1%, and (4) time in hypoglycemic range (<70 mg/dl), 0.09%. In addition, the average coefficient of variation (CV) was 11.1%. Conclusions: This in silico study of an AI-based closed loop glucose controller shows that it may be able to improve on the results achieved by currently existing ICU-based PID/MPC controllers. If these results are confirmed in clinical testing, this AI-based controller could be used to create an artificial pancreas system for use in the ICU setting. PMID:27301982

In silico investigation of lavandulyl flavonoids for the development of potent fatty acid synthase-inhibitory prototypes.

PubMed

Oh, Joonseok; Liu, Haining; Park, Hyun Bong; Ferreira, Daneel; Jeong, Gil-Saeng; Hamann, Mark T; Doerksen, Robert J; Na, MinKyun

2017-01-01

Inhibition of fatty acid synthase (FAS) is regarded as a sensible therapeutic strategy for the development of optimal anti-cancer agents. Flavonoids exhibit potent anti-neoplastic properties. The MeOH extract of Sophora flavescens was subjected to chromatographic analyses such as VLC and HPLC for the purification of active flavonoids. The DP4 chemical-shift analysis protocol was employed to investigate the elusive chirality of the lavandulyl moiety of the purified polyphenols. Induced Fit docking protocols and per-residue analyses were utilized to scrutinize structural prerequisites for hampering FAS activity. The FAS-inhibitory activity of the purified flavonoids was assessed via the incorporation of [ 3 H] acetyl-CoA into palmitate. Six flavonoids, including lavandulyl flavanones, were purified and evaluated for FAS inhibition. The lavandulyl flavanone sophoraflavanone G (2) exhibited the highest potency (IC 50 of 6.7±0.2μM), which was more potent than the positive controls. Extensive molecular docking studies revealed the structural requirements for blocking FAS. Per-residue interaction analysis demonstrated that the lavandulyl functional group in the active flavonoids (1-3 and 5) significantly contributed to increasing their binding affinity towards the target enzyme. This research suggests a basis for the in silico design of a lavandulyl flavonoid-based architecture showing anti-cancer effects via enhancement of the binding potential to FAS. FAS inhibition by flavonoids and their derivatives may offer significant potential as an approach to lower the risk of various cancer diseases and related fatalities. In silico technologies with available FAS crystal structures may be of significant use in optimizing preliminary leads. Copyright © 2016 Elsevier B.V. All rights reserved.

In silico investigation of lavandulyl flavonoids for the development of potent fatty acid synthase-inhibitory prototypes

PubMed Central

Oh, Joonseok; Liu, Haining; Park, Hyun Bong; Ferreira, Daneel; Jeong, Gil-Saeng; Hamann, Mark T.; Doerksen, Robert J.; Na, MinKyun

2016-01-01

Background Inhibition of fatty acid synthase (FAS) is regarded as a sensible therapeutic strategy for the development of optimal anti-cancer agents. Flavonoids exhibit potent anti-neoplastic properties. Methods The MeOH extract of Sophora flavescens was subjected to chromatographic analyses such as VLC and HPLC for the purification of active flavonoids. The DP4 chemical-shift analysis protocol was employed to investigate the elusive chirality of the lavandulyl moiety of the purified polyphenols. Induced Fit docking protocols and per-residue analyses were utilized to scrutinize structural prerequisites for hampering FAS activity. The FAS-inhibitory activity of the purified flavonoids was assessed via the incorporation of [3H] acetyl-CoA into palmitate. Results Six flavonoids, including lavandulyl flavanones, were purified and evaluated for FAS inhibition. The lavandulyl flavanone sophoraflavanone G (2) exhibited the highest potency (IC50 of 6.7 ± 0.2 μM), which was more potent than the positive controls. Extensive molecular docking studies revealed the structural requirements for blocking FAS. Per-residue interaction analysis demonstrated that the lavandulyl functional group in the active flavonoids (1–3 and 5) significantly contributed to increasing their binding affinity towards the target enzyme. Conclusion This research suggests a basis for the in silico design of a lavandulyl flavonoid-based architecture showing anti-cancer effects via enhancement of the binding potential to FAS. General significance FAS inhibition by flavonoids and their derivatives may offer significant potential as an approach to lower the risk of various cancer diseases and related fatalities. In silico technologies with available FAS crystal structures may be of significant use in optimizing preliminary leads. PMID:27531709

In Silico Testing of an Artificial-Intelligence-Based Artificial Pancreas Designed for Use in the Intensive Care Unit Setting.

PubMed

DeJournett, Leon; DeJournett, Jeremy

2016-11-01

Effective glucose control in the intensive care unit (ICU) setting has the potential to decrease morbidity and mortality rates which should in turn lead to decreased health care expenditures. Current ICU-based glucose controllers are mathematically derived, and tend to be based on proportional integral derivative (PID) or model predictive control (MPC). Artificial intelligence (AI)-based closed loop glucose controllers may have the ability to achieve control that improves on the results achieved by either PID or MPC controllers. We conducted an in silico analysis of an AI-based glucose controller designed for use in the ICU setting. This controller was tested using a mathematical model of the ICU patient's glucose-insulin system. A total of 126 000 unique 5-day simulations were carried out, resulting in 107 million glucose values for analysis. For the 7 control ranges tested, with a sensor error of ±10%, the following average results were achieved: (1) time in control range, 94.2%, (2) time in range 70-140 mg/dl, 97.8%, (3) time in hyperglycemic range (>140 mg/dl), 2.1%, and (4) time in hypoglycemic range (<70 mg/dl), 0.09%. In addition, the average coefficient of variation (CV) was 11.1%. This in silico study of an AI-based closed loop glucose controller shows that it may be able to improve on the results achieved by currently existing ICU-based PID/MPC controllers. If these results are confirmed in clinical testing, this AI-based controller could be used to create an artificial pancreas system for use in the ICU setting. © 2016 Diabetes Technology Society.

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

In Silico and In Vitro Analysis of Bacoside A Aglycones and Its Derivatives as the Constituents Responsible for the Cognitive Effects of Bacopa monnieri

PubMed Central

Ramasamy, Seetha; Chin, Sek Peng; Sukumaran, Sri Devi; Buckle, Michael James Christopher; Kiew, Lik Voon; Chung, Lip Yong

2015-01-01

Bacopa monnieri has been used in Ayurvedic medicine to improve memory and cognition. The active constituent responsible for its pharmacological effects is bacoside A, a mixture of dammarane-type triterpenoid saponins containing sugar chains linked to a steroid aglycone skeleton. Triterpenoid saponins have been reported to be transformed in vivo to metabolites that give better biological activity and pharmacokinetic characteristics. Thus, the activities of the parent compounds (bacosides), aglycones (jujubogenin and pseudojujubogenin) and their derivatives (ebelin lactone and bacogenin A1) were compared using a combination of in silico and in vitro screening methods. The compounds were docked into 5-HT1A, 5-HT2A, D1, D2, M1 receptors and acetylcholinesterase (AChE) using AutoDock and their central nervous system (CNS) drug-like properties were determined using Discovery Studio molecular properties and ADMET descriptors. The compounds were screened in vitro using radioligand receptor binding and AChE inhibition assays. In silico studies showed that the parent bacosides were not able to dock into the chosen CNS targets and had poor molecular properties as a CNS drug. In contrast, the aglycones and their derivatives showed better binding affinity and good CNS drug-like properties, were well absorbed through the intestines and had good blood brain barrier (BBB) penetration. Among the compounds tested in vitro, ebelin lactone showed binding affinity towards M1 (Ki = 0.45 μM) and 5-HT2A (4.21 μM) receptors. Bacoside A and bacopaside X (9.06 μM) showed binding affinity towards the D1 receptor. None of the compounds showed any inhibitory activity against AChE. Since the stimulation of M1 and 5-HT2A receptors has been implicated in memory and cognition and ebelin lactone was shown to have the strongest binding energy, highest BBB penetration and binding affinity towards M1 and 5-HT2A receptors, we suggest that B. monnieri constituents may be transformed in vivo to the active form before exerting their pharmacological activity. PMID:25965066

In Silico and In Vitro Analysis of Bacoside A Aglycones and Its Derivatives as the Constituents Responsible for the Cognitive Effects of Bacopa monnieri.

PubMed

Ramasamy, Seetha; Chin, Sek Peng; Sukumaran, Sri Devi; Buckle, Michael James Christopher; Kiew, Lik Voon; Chung, Lip Yong

2015-01-01

Bacopa monnieri has been used in Ayurvedic medicine to improve memory and cognition. The active constituent responsible for its pharmacological effects is bacoside A, a mixture of dammarane-type triterpenoid saponins containing sugar chains linked to a steroid aglycone skeleton. Triterpenoid saponins have been reported to be transformed in vivo to metabolites that give better biological activity and pharmacokinetic characteristics. Thus, the activities of the parent compounds (bacosides), aglycones (jujubogenin and pseudojujubogenin) and their derivatives (ebelin lactone and bacogenin A1) were compared using a combination of in silico and in vitro screening methods. The compounds were docked into 5-HT1A, 5-HT2A, D1, D2, M1 receptors and acetylcholinesterase (AChE) using AutoDock and their central nervous system (CNS) drug-like properties were determined using Discovery Studio molecular properties and ADMET descriptors. The compounds were screened in vitro using radioligand receptor binding and AChE inhibition assays. In silico studies showed that the parent bacosides were not able to dock into the chosen CNS targets and had poor molecular properties as a CNS drug. In contrast, the aglycones and their derivatives showed better binding affinity and good CNS drug-like properties, were well absorbed through the intestines and had good blood brain barrier (BBB) penetration. Among the compounds tested in vitro, ebelin lactone showed binding affinity towards M1 (Ki = 0.45 μM) and 5-HT2A (4.21 μM) receptors. Bacoside A and bacopaside X (9.06 μM) showed binding affinity towards the D1 receptor. None of the compounds showed any inhibitory activity against AChE. Since the stimulation of M1 and 5-HT2A receptors has been implicated in memory and cognition and ebelin lactone was shown to have the strongest binding energy, highest BBB penetration and binding affinity towards M1 and 5-HT2A receptors, we suggest that B. monnieri constituents may be transformed in vivo to the active form before exerting their pharmacological activity.

Marine steroids as potential anticancer drug candidates: In silico investigation in search of inhibitors of Bcl-2 and CDK-4/Cyclin D1.

PubMed

Saikia, Surovi; Kolita, Bhaskor; Dutta, Partha P; Dutta, Deep J; Neipihoi; Nath, Shyamalendu; Bordoloi, Manobjyoti; Quan, Pham Minh; Thuy, Tran Thu; Phuong, Doan Lan; Long, Pham Quoc

2015-10-01

Star fishes (Asteroidea) are rich in polar steroids with diverse structural characteristics. The structural modifications of star fish steroids occur at 3β, 4β, 5α, 6α (or β), 7α (or β), 8, 15α (or β) and 16β positions of the steroidal nucleus and in the side chain. Widely found polar steroids in starfishes include polyhydroxysteroids, steroidal sulfates, glycosides, steroid oligoglycosides etc. Bioactivity of these steroids is less studied; only a few reports like antibacterial, cytotoxic activity etc. are available. In continuation of our search for bioactive molecules from natural sources, we undertook in silico screening of steroids from star fishes against Bcl-2 and CDK-4/Cyclin D1 - two important targets of progression and proliferation of cancer cells. We have screened 182 natural steroids from star fishes occurring in different parts of the world and their 282 soft-derivatives by in silico methods. Their physico-chemical properties, drug-likeliness, binding potential with the selected targets, ADMET (absorption, distribution, metabolism, toxicity) were predicted. Further, the results were compared with those of existing steroidal and non steroidal drugs and inhibitors of Bcl-2 and CDK-4/Cyclin D1. The results are promising and unveil that some of these steroids can be potent leads for cancer treatments. Copyright © 2015 Elsevier Inc. All rights reserved.

Effect of the pulmonary deposition and in vitro permeability on the prediction of plasma levels of inhaled budesonide formulation.

PubMed

Salar-Behzadi, Sharareh; Wu, Shengqian; Mercuri, Annalisa; Meindl, Claudia; Stranzinger, Sandra; Fröhlich, Eleonore

2017-10-30

The growing interest in the inhalable pharmaceutical products requires advanced approaches to safe and fast product development, such as in silico tools that can be used for estimating the bioavailability and toxicity of developed formulation. GastroPlus™ is one of the few available software packages for in silico simulation of PBPK profile of inhalable products. It contains a complementary module for calculating the lung deposition, the permeability and the systemic absorption of inhalable products. Experimental values of lung deposition and permeability can also be used. This study aims to assess the efficiency of simulation by applying experimental permeability and deposition values, using budesonide as a model substance. The lung deposition values were obtained from the literature, the lung permeability data were experimentally determined by culturing Calu-3 cells under air-liquid interface and submersed conditions to morphologically resemble bronchial and alveolar epithelial cells, respectively. A two-compartment PK model was created for i.v. administration and used as a background for the in silico simulation of the plasma profile of budesonide after inhalation. The predicted plasma profile was compared with the in vivo data from the literature and the effects of experimental lung deposition and permeability on prediction were assessed. The developed model was significantly improved by using realistic lung deposition data combined with experimental data for peripheral permeability. Copyright © 2017 Elsevier B.V. All rights reserved.

Estimating Likelihood of Fetal In Vivo Interactions Using In ...

EPA Pesticide Factsheets

Tox21/ToxCast efforts provide in vitro concentration-response data for thousands of compounds. Predicting whether chemical-biological interactions observed in vitro will occur in vivo is challenging. We hypothesize that using a modified model from the FDA guidance for drug interaction studies, Cmax/AC50 (i.e., maximal in vivo blood concentration over the half-maximal in in vitro activity concentration), will give a useful approximation for concentrations where in vivo interactions are likely. Further, for doses where maternal blood concentrations are likely to elicit an interaction (Cmax/AC50>0.1), where do the compounds accumulate in fetal tissues? In order to estimate these doses based on Tox21 data, in silico parameters of chemical fraction unbound in plasma and intrinsic hepatic clearance were estimated from ADMET predictor (Simulations-Plus Inc.) and used in the HTTK R-package to obtain Cmax values from a physiologically-based toxicokinetics model. In silico estimated Cmax values predicted in vivo human Cmax with median absolute error of 0.81 for 93 chemicals, giving confidence in the R-package and in silico estimates. A case example evaluating Cmax/AC50 values for peroxisome proliferator-activated receptor gamma (PPARγ) and glucocorticoid receptor revealed known compounds (glitazones and corticosteroids, respectively) highest on the list at pharmacological doses. Doses required to elicit likely interactions across all Tox21/ToxCast assays were compared to

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

Comparative sequence analysis of the X-inactivation center region in mouse, human, and bovine.

PubMed

Chureau, Corinne; Prissette, Marine; Bourdet, Agnès; Barbe, Valérie; Cattolico, Laurence; Jones, Louis; Eggen, André; Avner, Philip; Duret, Laurent

2002-06-01

We have sequenced to high levels of accuracy 714-kb and 233-kb regions of the mouse and bovine X-inactivation centers (Xic), respectively, centered on the Xist gene. This has provided the basis for a fully annotated comparative analysis of the mouse Xic with the 2.3-Mb orthologous region in human and has allowed a three-way species comparison of the core central region, including the Xist gene. These comparisons have revealed conserved genes, both coding and noncoding, conserved CpG islands and, more surprisingly, conserved pseudogenes. The distribution of repeated elements, especially LINE repeats, in the mouse Xic region when compared to the rest of the genome does not support the hypothesis of a role for these repeat elements in the spreading of X inactivation. Interestingly, an asymmetric distribution of LINE elements on the two DNA strands was observed in the three species, not only within introns but also in intergenic regions. This feature is suggestive of important transcriptional activity within these intergenic regions. In silico prediction followed by experimental analysis has allowed four new genes, Cnbp2, Ftx, Jpx, and Ppnx, to be identified and novel, widespread, complex, and apparently noncoding transcriptional activity to be characterized in a region 5' of Xist that was recently shown to attract histone modification early after the onset of X inactivation.

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

Pitfalls in genetic analysis of pheochromocytomas/paragangliomas-case report.

PubMed

Canu, Letizia; Rapizzi, Elena; Zampetti, Benedetta; Fucci, Rossella; Nesi, Gabriella; Richter, Susan; Qin, Nan; Giachè, Valentino; Bergamini, Carlo; Parenti, Gabriele; Valeri, Andrea; Ercolino, Tonino; Eisenhofer, Graeme; Mannelli, Massimo

2014-07-01

About 35% of patients with pheochromocytoma/paraganglioma carry a germline mutation in one of the 10 main susceptibility genes. The recent introduction of next-generation sequencing will allow the analysis of all these genes in one run. When positive, the analysis is generally unequivocal due to the association between a germline mutation and a concordant clinical presentation or positive family history. When genetic analysis reveals a novel mutation with no clinical correlates, particularly in the presence of a missense variant, the question arises whether the mutation is pathogenic or a rare polymorphism. We report the case of a 35-year-old patient operated for a pheochromocytoma who turned out to be a carrier of a novel SDHD (succinate dehydrogenase subunit D) missense mutation. With no positive family history or clinical correlates, we decided to perform additional analyses to test the clinical significance of the mutation. We performed in silico analysis, tissue loss of heterozygosity analysis, immunohistochemistry, Western blot analysis, SDH enzymatic assay, and measurement of the succinate/fumarate concentration ratio in the tumor tissue by tandem mass spectrometry. Although the in silico analysis gave contradictory results according to the different methods, all the other tests demonstrated that the SDH complex was conserved and normally active. We therefore came to the conclusion that the variant was a nonpathogenic polymorphism. Advancements in technology facilitate genetic analysis of patients with pheochromocytoma but also offer new challenges to the clinician who, in some cases, needs clinical correlates and/or functional tests to give significance to the results of the genetic assay.

FRET imaging and in silico simulation: analysis of the signaling network of nerve growth factor-induced neuritogenesis.

PubMed

Nakamura, Takeshi; Aoki, Kazuhiro; Matsuda, Michiyuki

2008-08-01

Genetically encoded probes based on Förster resonance energy transfer (FRET) enable us to decipher spatiotemporal information encoded in complex tissues such as the brain. Firstly, this review focuses on FRET probes wherein both the donor and acceptor are fluorescence proteins and are incorporated into a single molecule, i.e. unimolecular probes. Advantages of these probes lie in their easy loading into cells, the simple acquisition of FRET images, and the clear evaluation of data. Next, we introduce our recent study which encompasses FRET imaging and in silico simulation. In nerve growth factor-induced neurite outgrowth in PC12 cells, we found positive and negative signaling feedback loops. We propose that these feedback loops determine neurite-budding sites. We would like to emphasize that it is now time to accelerate crossover research in neuroscience, optics, and computational biology.

Identification of novel potential scaffold for class I HDACs inhibition: An in-silico protocol based on virtual screening, molecular dynamics, mathematical analysis and machine learning.

PubMed

Fan, Cong; Huang, Yanxin

2017-09-23

Histone deacetylases (HDACs) family has been widely reported as an important class of enzyme targets for cancer therapy. Much effort has been made in discovery of novel scaffolds for HDACs inhibition besides existing hydroxamic acids, cyclic peptides, benzamides, and short-chain fatty acids. Herein we set up an in-silico protocol which not only could detect potential Zn 2+ chelation bonds but also still adopted non-bonded model to be effective in discovery of Class I HDACs inhibitors, with little human's subjective visual judgment involved. We applied the protocol to screening of Chembridge database and selected out 7 scaffolds, 3 with probability of more than 99%. Biological assay results demonstrated that two of them exhibited HDAC-inhibitory activity and are thus considerable for structure modification to further improve their bio-activity. Copyright © 2017. Published by Elsevier Inc.

In Silico Studies of the Toxcast Chemicals Interacting with Biomolecular targets

EPA Science Inventory

Molecular docking, a structure-based in silico tool for chemical library pre-screening in drug discovery, can be used to explore the potential toxicity of environmental chemicals acting at specific biomelcular targets.

Utilization of Gastrointestinal Simulator, an in Vivo Predictive Dissolution Methodology, Coupled with Computational Approach To Forecast Oral Absorption of Dipyridamole.

PubMed

Matsui, Kazuki; Tsume, Yasuhiro; Takeuchi, Susumu; Searls, Amanda; Amidon, Gordon L

2017-04-03

Weakly basic drugs exhibit a pH-dependent dissolution profile in the gastrointestinal (GI) tract, which makes it difficult to predict their oral absorption profile. The aim of this study was to investigate the utility of the gastrointestinal simulator (GIS), a novel in vivo predictive dissolution (iPD) methodology, in predicting the in vivo behavior of the weakly basic drug dipyridamole when coupled with in silico analysis. The GIS is a multicompartmental dissolution apparatus, which represents physiological gastric emptying in the fasted state. Kinetic parameters for drug dissolution and precipitation were optimized by fitting a curve to the dissolved drug amount-time profiles in the United States Pharmacopeia apparatus II and GIS. Optimized parameters were incorporated into mathematical equations to describe the mass transport kinetics of dipyridamole in the GI tract. By using this in silico model, intraluminal drug concentration-time profile was simulated. The predicted profile of dipyridamole in the duodenal compartment adequately captured observed data. In addition, the plasma concentration-time profile was also predicted using pharmacokinetic parameters following intravenous administration. On the basis of the comparison with observed data, the in silico approach coupled with the GIS successfully predicted in vivo pharmacokinetic profiles. Although further investigations are still required to generalize, these results indicated that incorporating GIS data into mathematical equations improves the predictability of in vivo behavior of weakly basic drugs like dipyridamole.

Computational modeling and in-vitro/in-silico correlation of phospholipid-based prodrugs for targeted drug delivery in inflammatory bowel disease

NASA Astrophysics Data System (ADS)

Dahan, Arik; Markovic, Milica; Keinan, Shahar; Kurnikov, Igor; Aponick, Aaron; Zimmermann, Ellen M.; Ben-Shabat, Shimon

2017-11-01

Targeting drugs to the inflamed intestinal tissue(s) represents a major advancement in the treatment of inflammatory bowel disease (IBD). In this work we present a powerful in-silico modeling approach to guide the molecular design of novel prodrugs targeting the enzyme PLA2, which is overexpressed in the inflamed tissues of IBD patients. The prodrug consists of the drug moiety bound to the sn-2 position of phospholipid (PL) through a carbonic linker, aiming to allow PLA2 to release the free drug. The linker length dictates the affinity of the PL-drug conjugate to PLA2, and the optimal linker will enable maximal PLA2-mediated activation. Thermodynamic integration and Weighted Histogram Analysis Method (WHAM)/Umbrella Sampling method were used to compute the changes in PLA2 transition state binding free energy of the prodrug molecule (ΔΔGtr) associated with decreasing/increasing linker length. The simulations revealed that 6-carbons linker is the optimal one, whereas shorter or longer linkers resulted in decreased PLA2-mediated activation. These in-silico results were shown to be in excellent correlation with experimental in-vitro data. Overall, this modern computational approach enables optimization of the molecular design of novel prodrugs, which may allow targeting the free drug specifically to the diseased intestinal tissue of IBD patients.

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.

Effectiveness of atrial fibrillation rotor ablation is dependent on conduction velocity: An in-silico 3-dimensional modeling study

PubMed Central

Lim, Byounghyun; Hwang, Minki; Song, Jun-Seop; Ryu, Ah-Jin; Joung, Boyoung; Shim, Eun Bo; Ryu, Hyungon

2017-01-01

Background We previously reported that stable rotors are observed in in-silico human atrial fibrillation (AF) models, and are well represented by a dominant frequency (DF). In the current study, we hypothesized that the outcome of DF ablation is affected by conduction velocity (CV) conditions and examined this hypothesis using in-silico 3D-AF modeling. Methods We integrated 3D CT images of left atrium obtained from 10 patients with persistent AF (80% male, 61.8±13.5 years old) into in-silico AF model. We compared AF maintenance durations (max 300s), spatiotemporal stabilities of DF, phase singularity (PS) number, life-span of PS, and AF termination or defragmentation rates after virtual DF ablation with 5 different CV conditions (0.2, 0.3, 0.4, 0.5, and 0.6m/s). Results 1. AF maintenance duration (p<0.001), spatiotemporal mean variance of DF (p<0.001), and the number of PS (p = 0.023) showed CV dependent bimodal patterns (highest at CV0.4m/s and lowest at CV0.6m/s) consistently. 2. After 10% highest DF ablation, AF defragmentation rates were the lowest at CV0.4m/s (37.8%), but highest at CV0.5 and 0.6m/s (all 100%, p<0.001). 3. In the episodes with AF termination or defragmentation followed by 10% highest DF ablation, baseline AF maintenance duration was shorter (p<0.001), spatiotemporal mean variance of DF was lower (p = 0.014), and the number of PS was lower (p = 0.004) than those with failed AF defragmentation after DF ablation. Conclusion Virtual ablation of DF, which may indicate AF driver, was more likely to terminate or defragment AF with spatiotemporally stable DF, but not likely to do so in long-lasting and sustained AF conditions, depending on CV. PMID:29287119

Accessing biological actions of Ganoderma secondary metabolites by in silico profiling

PubMed Central

Grienke, Ulrike; Kaserer, Teresa; Pfluger, Florian; Mair, Christina E.; Langer, Thierry; Schuster, Daniela; Rollinger, Judith M.

2016-01-01

The species complex around the medicinal fungus Ganoderma lucidum Karst. (Ganodermataceae) is widely known in traditional medicines as well as in modern applications such as functional food or nutraceuticals. A considerable number of publications reflects its abundance and variety in biological actions either provoked by primary metabolites such as polysaccharides or secondary metabolites such as lanostane-type triterpenes. However, due to this remarkable amount of information, a rationalization of the individual Ganoderma constituents to biological actions on a molecular level is quite challenging. To overcome this issue, a database was generated containing meta-information, i.e. chemical structures and biological actions of hitherto identified Ganoderma constituents (279). This was followed by a computational approach subjecting this 3D multi-conformational molecular dataset to in silico parallel screening against an in-house collection of validated structure- and ligand-based 3D pharmacophore models. The predictive power of the evaluated in silico tools and hints from traditional application fields served as criteria for the model selection. Thus, we focused on representative druggable targets in the field of viral infections (5) and diseases related to the metabolic syndrome (22). The results obtained from this in silico approach were compared to bioactivity data available from the literature to distinguish between true and false positives or negatives. 89 and 197 Ganoderma compounds were predicted as ligands of at least one of the selected pharmacological targets in the antiviral and the metabolic syndrome screening, respectively. Among them only a minority of individual compounds (around 10%) has ever been investigated on these targets or for the associated biological activity. Accordingly, this study discloses putative ligand target interactions for a plethora of Ganoderma constituents in the empirically manifested field of viral diseases and metabolic syndrome which serve as a basis for future applications to access yet undiscovered biological actions of Ganoderma secondary metabolites on a molecular level. PMID:25457486

QSAR, molecular docking studies of thiophene and imidazopyridine derivatives as polo-like kinase 1 inhibitors

NASA Astrophysics Data System (ADS)

Cao, Shandong

2012-08-01

The purpose of the present study was to develop in silico models allowing for a reliable prediction of polo-like kinase inhibitors based on a large diverse dataset of 136 compounds. As an effective method, quantitative structure activity relationship (QSAR) was applied using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The proposed QSAR models showed reasonable predictivity of thiophene analogs (Rcv2=0.533, Rpred2=0.845) and included four molecular descriptors, namely IC3, RDF075m, Mor02m and R4e+. The optimal model for imidazopyridine derivatives (Rcv2=0.776, Rpred2=0.876) was shown to perform good in prediction accuracy, using GATS2m and BEHe1 descriptors. Analysis of the contour maps helped to identify structural requirements for the inhibitors and served as a basis for the design of the next generation of the inhibitor analogues. Docking studies were also employed to position the inhibitors into the polo-like kinase active site to determine the most probable binding mode. These studies may help to understand the factors influencing the binding affinity of chemicals and to develop alternative methods for prescreening and designing of polo-like kinase inhibitors.

A Computational Drug-Target Network for Yuanhu Zhitong Prescription

PubMed Central

Lu, Peng; Zhang, Fangbo; Yuan, Yuan; Wang, Songsong

2013-01-01

Yuanhu Zhitong prescription (YZP) is a typical and relatively simple traditional Chinese medicine (TCM), widely used in the clinical treatment of headache, gastralgia, and dysmenorrhea. However, the underlying molecular mechanism of action of YZP is not clear. In this study, based on the previous chemical and metabolite analysis, a complex approach including the prediction of the structure of metabolite, high-throughput in silico screening, and network reconstruction and analysis was developed to obtain a computational drug-target network for YZP. This was followed by a functional and pathway analysis by ClueGO to determine some of the pharmacologic activities. Further, two new pharmacologic actions, antidepressant and antianxiety, of YZP were validated by animal experiments using zebrafish and mice models. The forced swimming test and the tail suspension test demonstrated that YZP at the doses of 4 mg/kg and 8 mg/kg had better antidepressive activity when compared with the control group. The anxiolytic activity experiment showed that YZP at the doses of 100 mg/L, 150 mg/L, and 200 mg/L had significant decrease in diving compared to controls. These results not only shed light on the better understanding of the molecular mechanisms of YZP for curing diseases, but also provide some evidence for exploring the classic TCM formulas for new clinical application. PMID:23762151

CRISPRcompar: a website to compare clustered regularly interspaced short palindromic repeats.

PubMed

Grissa, Ibtissem; Vergnaud, Gilles; Pourcel, Christine

2008-07-01

Clustered regularly interspaced short palindromic repeat (CRISPR) elements are a particular family of tandem repeats present in prokaryotic genomes, in almost all archaea and in about half of bacteria, and which participate in a mechanism of acquired resistance against phages. They consist in a succession of direct repeats (DR) of 24-47 bp separated by similar sized unique sequences (spacers). In the large majority of cases, the direct repeats are highly conserved, while the number and nature of the spacers are often quite diverse, even among strains of a same species. Furthermore, the acquisition of new units (DR + spacer) was shown to happen almost exclusively on one side of the locus. Therefore, the CRISPR presents an interesting genetic marker for comparative and evolutionary analysis of closely related bacterial strains. CRISPRcompar is a web service created to assist biologists in the CRISPR typing process. Two tools facilitates the in silico investigation: CRISPRcomparison and CRISPRtionary. This website is freely accessible at http://crispr.u-psud.fr/CRISPRcompar/.

Ergot alkaloids: From witchcraft till in silico analysis. Multi-receptor analysis of ergotamine metabolites.

PubMed

Dellafiora, Luca; Dall'Asta, Chiara; Cozzini, Pietro

2015-01-01

The term Ergot is referred to the sclerotium of ascomycetes - a protective kernel produced during resting stage of some fungi - which replaces seeds of susceptible cereals and plants intended for human and animal diet. It contains various composition of tryptophan-derived toxins defined ergot alkaloids. Since sclerotia can be harvested and milled together with cereals, they represent a source of food and feed contamination after breakage and spreading of mycotoxins into the various milling fractions. The effects of ergot alkaloids, including those adverse for human health, have been known since the Middle Ages. Nevertheless, as recently stated by the European Food Safety Authority, further information is needed on metabolism and target receptors-binding of common alkaloids in food. Unfortunately, the experimental investigation is challenging due to the high costs in terms of time and money. This study was thus aimed at assessing whether the in silico modeling can be an effective tool to investigate the interaction between multiple serotonin receptors and a wide set of ergotamine metabolites, including experimentally detected molecules and predicted derivatives. Validated models provided precious insights about the effects exerted by metabolic modifications on the receptor-ligand interaction. Such structural information may be useful to support the design of further experimental analysis.

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.

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

In Vitro and In Silico Risk Assessment in Acquired Long QT Syndrome: The Devil Is in the Details.

PubMed

Lee, William; Windley, Monique J; Vandenberg, Jamie I; Hill, Adam P

2017-01-01

Acquired long QT syndrome, mostly as a result of drug block of the Kv11. 1 potassium channel in the heart, is characterized by delayed cardiac myocyte repolarization, prolongation of the T interval on the ECG, syncope and sudden cardiac death due to the polymorphic ventricular arrhythmia Torsade de Pointes (TdP). In recent years, efforts are underway through the Comprehensive in vitro proarrhythmic assay (CiPA) initiative, to develop better tests for this drug induced arrhythmia based in part on in silico simulations of pharmacological disruption of repolarization. However, drug binding to Kv11.1 is more complex than a simple binary molecular reaction, meaning simple steady state measures of potency are poor surrogates for risk. As a result, there is a plethora of mechanistic detail describing the drug/Kv11.1 interaction-such as drug binding kinetics, state preference, temperature dependence and trapping-that needs to be considered when developing in silico models for risk prediction. In addition to this, other factors, such as multichannel pharmacological profile and the nature of the ventricular cell models used in simulations also need to be considered in the search for the optimum in silico approach. Here we consider how much of mechanistic detail needs to be included for in silico models to accurately predict risk and further, how much of this detail can be retrieved from protocols that are practical to implement in high throughout screens as part of next generation of preclinical in silico drug screening approaches?

In silico analysis and experimental validation of azelastine hydrochloride (N4) targeting sodium taurocholate co-transporting polypeptide (NTCP) in HBV therapy.

PubMed

Fu, L-L; Liu, J; Chen, Y; Wang, F-T; Wen, X; Liu, H-Q; Wang, M-Y; Ouyang, L; Huang, J; Bao, J-K; Wei, Y-Q

2014-08-01

The aim of this study was to explore sodium taurocholate co-transporting polypeptide (NTCP) exerting its function with hepatitis B virus (HBV) and its targeted candidate compounds, in HBV therapy. Identification of NTCP as a novel HBV target for screening candidate small molecules, was used by phylogenetic analysis, network construction, molecular modelling, molecular docking and molecular dynamics (MD) simulation. In vitro virological examination, q-PCR, western blotting and cytotoxicity studies were used for validating efficacy of the candidate compound. We used the phylogenetic analysis of NTCP and constructed its protein-protein network. Also, we screened compounds from Drugbank and ZINC, among which five were validated for their authentication in HepG 2.2.15 cells. Then, we selected compound N4 (azelastine hydrochloride) as the most potent of them. This showed good inhibitory activity against HBsAg (IC50 = 7.5 μm) and HBeAg (IC50 = 3.7 μm), as well as high SI value (SI = 4.68). Further MD simulation results supported good interaction between compound N4 and NTCP. In silico analysis and experimental validation together demonstrated that compound N4 can target NTCP in HepG2.2.15 cells, which may shed light on exploring it as a potential anti-HBV drug. © 2014 John Wiley & Sons Ltd.

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 Strategies for Modeling Stereoselective Metabolism of Pyrethroids

EPA Science Inventory

In silico methods are invaluable tools to researchers seeking to understand and predict metabolic processes within PBPK models. Even though these methods have been successfully utilized to predict and quantify metabolic processes, there are many challenges involved. Stereochemica...

Metabolic engineering of Synechocystis sp. PCC 6803 for enhanced ethanol production based on flux balance analysis.

PubMed

Yoshikawa, Katsunori; Toya, Yoshihiro; Shimizu, Hiroshi

2017-05-01

Synechocystis sp. PCC 6803 is an attractive host for bio-ethanol production due to its ability to directly convert atmospheric carbon dioxide into ethanol using photosystems. To enhance ethanol production in Synechocystis sp. PCC 6803, metabolic engineering was performed based on in silico simulations, using the genome-scale metabolic model. Comprehensive reaction knockout simulations by flux balance analysis predicted that the knockout of NAD(P)H dehydrogenase enhanced ethanol production under photoautotrophic conditions, where ammonium is the nitrogen source. This deletion inhibits the re-oxidation of NAD(P)H, which is generated by ferredoxin-NADP + reductase and imposes re-oxidation in the ethanol synthesis pathway. The effect of deleting the ndhF1 gene, which encodes NADH dehydrogenase subunit 5, on ethanol production was experimentally evaluated using ethanol-producing strains of Synechocystis sp. PCC 6803. The ethanol titer of the ethanol-producing ∆ndhF1 strain increased by 145%, compared with that of the control strain.

Prediction and mechanism elucidation of analyte retention on phospholipid stationary phases (IAM-HPLC) by in silico calculated physico-chemical descriptors.

PubMed

Russo, Giacomo; Grumetto, Lucia; Barbato, Francesco; Vistoli, Giulio; Pedretti, Alessandro

2017-03-01

The present study proposes a method for an in silico calculation of phospholipophilicity. Phospholipophilicity is intended as the measure of analyte affinity for phospholipids; it is currently assessed by HPLC measures of analyte retention on phosphatidylcholine-like stationary phases (IAM - Immobilized Artificial Membrane) resulting in log k W IAM values. Due to the amphipathic and electrically charged nature of phospholipids, retention on these stationary phases results from complex mechanisms, being affected not only by lipophilicity (as measured by n-octanol/aqueous phase partition coefficients, log P) but also by the occurrence of polar and/or electrostatic intermolecular interaction forces. Differently from log P, to date no method has been proposed for in silico calculation of log k W IAM . The study is aimed both at shedding new light into the retention mechanism on IAM stationary phases and at offering a high-throughput method to achieve such values. A wide set of physico-chemical and topological properties were taken into account, yielding a robust final model including four in silico calculated parameters (lipophilicity, hydrophilic/lipophilic balance, molecular size, and molecule flexibility). The here presented model was based on the analysis of 205 experimentally determined values, taken from the literature and measured by a single research group to minimize the interlaboratory variability; such model is able to predict phospholipophilicity values on both the two IAM stationary phases to date marketed, i.e. IAM.PC.MG and IAM.PC.DD2, with a fairly good degree (r 2 =0.85) of accuracy. The present work allowed the development of a free on-line service aimed at calculating log k W IAM values of any molecule included in the PubChem database, which is freely available at http://nova.disfarm.unimi.it/logkwiam.htm. Copyright © 2016 Elsevier B.V. All rights reserved.

Practical application of in silico fragmentation based residue screening with ion mobility high-resolution mass spectrometry.

PubMed

Kaufmann, Anton; Butcher, Patrick; Maden, Kathry; Walker, Stephan; Widmer, Mirjam

2017-07-15

A screening concept for residues in complex matrices based on liquid chromatography coupled to ion mobility high-resolution mass spectrometry LC/IMS-HRMS is presented. The comprehensive four-dimensional data (chromatographic retention time, drift time, mass-to-charge and ion abundance) obtained in data-independent acquisition (DIA) mode was used for data mining. An in silico fragmenter utilizing a molecular structure database was used for suspect screening, instead of targeted screening with reference substances. The utilized data-independent acquisition mode relies on the MS E concept; where two constantly alternating HRMS scans (low and high fragmentation energy) are acquired. Peak deconvolution and drift time alignment of ions from the low (precursor ion) and high (product ion) energy scan result in relatively clean product ion spectra. A bond dissociation in silico fragmenter (MassFragment) supplied with mol files of compounds of interest was used to explain the observed product ions of each extracted candidate component (chromatographic peak). Two complex matrices (fish and bovine liver extract) were fortified with 98 veterinary drugs. Out of 98 screened compounds 94 could be detected with the in silico based screening approach. The high correlation among drift time and m/z value of equally charged ions was utilized for an orthogonal filtration (ranking). Such an orthogonal ion mobility based filter removes multiply charged ions (e.g. peptides and proteins from the matrix) as well as noise and artefacts. Most significantly, this filtration dramatically reduces false positive findings but hardly increases false negative findings. The proposed screening approach may offer new possibilities for applications where reference compounds are hardly or not at all commercially available. Such areas may be the analysis of metabolites of drugs, pyrrolizidine alkaloids, marine toxins, derivatives of sildenafil or novel designer drugs (new psychoactive substances). Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Particle Therapy for Non-Small Cell Lung Tumors: Where Do We Stand? A Systematic Review of the Literature

PubMed Central

Wink, Krista C. J.; Roelofs, Erik; Solberg, Timothy; Lin, Liyong; Simone, Charles B.; Jakobi, Annika; Richter, Christian; Lambin, Philippe; Troost, Esther G. C.

2014-01-01

This review article provides a systematic overview of the currently available evidence on the clinical effectiveness of particle therapy for the treatment of non-small cell lung cancer and summarizes findings of in silico comparative planning studies. Furthermore, technical issues and dosimetric uncertainties with respect to thoracic particle therapy are discussed. PMID:25401087

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 modelling of directed evolution: Implications for experimental design and stepwise evolution.

PubMed

Wedge, David C; Rowe, William; Kell, Douglas B; Knowles, Joshua

2009-03-07

We model the process of directed evolution (DE) in silico using genetic algorithms. Making use of the NK fitness landscape model, we analyse the effects of mutation rate, crossover and selection pressure on the performance of DE. A range of values of K, the epistatic interaction of the landscape, are considered, and high- and low-throughput modes of evolution are compared. Our findings suggest that for runs of or around ten generations' duration-as is typical in DE-there is little difference between the way in which DE needs to be configured in the high- and low-throughput regimes, nor across different degrees of landscape epistasis. In all cases, a high selection pressure (but not an extreme one) combined with a moderately high mutation rate works best, while crossover provides some benefit but only on the less rugged landscapes. These genetic algorithms were also compared with a "model-based approach" from the literature, which uses sequential fixing of the problem parameters based on fitting a linear model. Overall, we find that purely evolutionary techniques fare better than do model-based approaches across all but the smoothest landscapes.

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.

In Silico Syndrome Prediction for Coronary Artery Disease in Traditional Chinese Medicine

PubMed Central

Lu, Peng; Chen, Jianxin; Zhao, Huihui; Gao, Yibo; Luo, Liangtao; Zuo, Xiaohan; Shi, Qi; Yang, Yiping; Yi, Jianqiang; Wang, Wei

2012-01-01

Coronary artery disease (CAD) is the leading causes of deaths in the world. The differentiation of syndrome (ZHENG) is the criterion of diagnosis and therapeutic in TCM. Therefore, syndrome prediction in silico can be improving the performance of treatment. In this paper, we present a Bayesian network framework to construct a high-confidence syndrome predictor based on the optimum subset, that is, collected by Support Vector Machine (SVM) feature selection. Syndrome of CAD can be divided into asthenia and sthenia syndromes. According to the hierarchical characteristics of syndrome, we firstly label every case three types of syndrome (asthenia, sthenia, or both) to solve several syndromes with some patients. On basis of the three syndromes' classes, we design SVM feature selection to achieve the optimum symptom subset and compare this subset with Markov blanket feature select using ROC. Using this subset, the six predictors of CAD's syndrome are constructed by the Bayesian network technique. We also design Naïve Bayes, C4.5 Logistic, Radial basis function (RBF) network compared with Bayesian network. In a conclusion, the Bayesian network method based on the optimum symptoms shows a practical method to predict six syndromes of CAD in TCM. PMID:22567030

Structural insights into a key carotenogenesis related enzyme phytoene synthase of P. falciparum: a novel drug target for malaria.

PubMed

Agarwal, Shalini; Sharma, Vijeta; Phulera, Swastik; Abdin, M Z; Ayana, R; Singh, Shailja

2015-12-01

Carotenoids represent a diverse group of pigments derived from the common isoprenoid precursors and fulfill a variety of critical functions in plants and animals. Phytoene synthase (PSY), a transferase enzyme that catalyzes the first specific step in carotenoid biosynthesis plays a central role in the regulation of a number of essential functions mediated via carotenoids. PSYs have been deeply investigated in plants, bacteria and algae however in apicomplexans it is poorly studied. In an effort to characterize PSY in apicomplexans especially the malaria parasite Plasmodium falciparum (P. falciparum), a detailed bioinformatics analysis is undertaken. We have analysed the Phylogenetic relationship of PSY also referred to as octaprenyl pyrophosphate synthase (OPPS) in P. falciparum with other taxonomic groups. Further, we in silico characterized the secondary and tertiary structures of P. falciparum PSY/OPPS and compared the tertiary structures with crystal structure of Thermotoga maritima (T. maritima) OPPS. Our results evidenced the resemblance of P. falciparum PSY with the active site of T. maritima OPPS. Interestingly, the comparative structural analysis revealed an unconserved unique loop in P. falciparum OPPS/PSY. Such structural insights might contribute novel accessory functions to the protein thus, offering potential drug targets.

Rational design of methicillin resistance staphylococcus aureus inhibitors through 3D-QSAR, molecular docking and molecular dynamics simulations.

PubMed

Ballu, Srilata; Itteboina, Ramesh; Sivan, Sree Kanth; Manga, Vijjulatha

2018-04-01

Staphylococcus aureus is a gram positive bacterium. It is the leading cause of skin and respiratory infections, osteomyelitis, Ritter's disease, endocarditis, and bacteraemia in the developed world. We employed combined studies of 3D QSAR, molecular docking which are validated by molecular dynamics simulations and in silico ADME prediction have been performed on Isothiazoloquinolones inhibitors against methicillin resistance Staphylococcus aureus. Three-dimensional quantitative structure-activity relationship (3D-QSAR) study was applied using comparative molecular field analysis (CoMFA) with Q 2 of 0.578, R 2 of 0.988, and comparative molecular similarity indices analysis (CoMSIA) with Q 2 of 0.554, R 2 of 0.975. The predictive ability of these model was determined using a test set of molecules that gave acceptable predictive correlation (r 2 Pred) values 0.55 and 0.57 of CoMFA and CoMSIA respectively. Docking, simulations were employed to position the inhibitors into protein active site to find out the most probable binding mode and most reliable conformations. Developed models and Docking methods provide guidance to design molecules with enhanced activity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Sonochemical synthesis of novel magnesium 1,2,4-triazole-1-carbodithioate nanoparticles as antifungals

NASA Astrophysics Data System (ADS)

Gumber, Khushbu; Sidhu, Anjali; Kaur, Robinpreet

2017-04-01

Novel magnesium 1,2,4-triazole-1-carbodithioates were sonochemically synthesized as water-dispersable nanoparticles owing to their water insolubility. The two-step reaction protocol was followed to synthesize the novel triazole ligand system for complexation with magnesium metal due to its low biological toxicity. Different concentrations of Poly Vinyl Pyrrolidine were used to stabilize and standardise the size of nanoparticles, which were characterised by TEM analysis. UV-Visible and infrared spectroscopies were used to analyse the metal ligand interaction, and CHNS analysis was used to propose the structure of the metal complex. The spore germination inhibition technique was used to evaluate the antifungal potential of synthesized nano-complexes against two phytopathogenic test fungi viz . A. alternata and F. moniliforme. The nanoparticles had inflicted moderate in vitro inhibition of fungal growth, which was comparable to standard fungicide Indofil M-45. The in silico toxicity of the compounds was made using the Toxtree analysis software that indicated the compounds belong to class III group of toxicity, which was same as that of commercial standards of DTC.

The acceptance of in silico models for REACH: Requirements, barriers, and perspectives

PubMed Central

2011-01-01

In silico models have prompted considerable interest and debate because of their potential value in predicting the properties of chemical substances for regulatory purposes. The European REACH legislation promotes innovation and encourages the use of alternative methods, but in practice the use of in silico models is still very limited. There are many stakeholders influencing the regulatory trajectory of quantitative structure-activity relationships (QSAR) models, including regulators, industry, model developers and consultants. Here we outline some of the issues and challenges involved in the acceptance of these methods for regulatory purposes. PMID:21982269

Molecular level in silico studies for oncology. Direct models review

NASA Astrophysics Data System (ADS)

Psakhie, S. G.; Tsukanov, A. A.

2017-09-01

The combination of therapy and diagnostics in one process "theranostics" is a trend in a modern medicine, especially in oncology. Such an approach requires development and usage of multifunctional hybrid nanoparticles with a hierarchical structure. Numerical methods and mathematical models play a significant role in the design of the hierarchical nanoparticles and allow looking inside the nanoscale mechanisms of agent-cell interactions. The current position of in silico approach in biomedicine and oncology is discussed. The review of the molecular level in silico studies in oncology, which are using the direct models, is presented.

In silico screening of carbon-capture materials

NASA Astrophysics Data System (ADS)

Lin, Li-Chiang; Berger, Adam H.; Martin, Richard L.; Kim, Jihan; Swisher, Joseph A.; Jariwala, Kuldeep; Rycroft, Chris H.; Bhown, Abhoyjit S.; Deem, Michael W.; Haranczyk, Maciej; Smit, Berend

2012-07-01

One of the main bottlenecks to deploying large-scale carbon dioxide capture and storage (CCS) in power plants is the energy required to separate the CO2 from flue gas. For example, near-term CCS technology applied to coal-fired power plants is projected to reduce the net output of the plant by some 30% and to increase the cost of electricity by 60-80%. Developing capture materials and processes that reduce the parasitic energy imposed by CCS is therefore an important area of research. We have developed a computational approach to rank adsorbents for their performance in CCS. Using this analysis, we have screened hundreds of thousands of zeolite and zeolitic imidazolate framework structures and identified many different structures that have the potential to reduce the parasitic energy of CCS by 30-40% compared with near-term technologies.

Responses to auxin signals: an operating principle for dynamical sensitivity yet high resilience

PubMed Central

Bravi, B.; Martin, O. C.

2018-01-01

Plants depend on the signalling of the phytohormone auxin for their development and for responding to environmental perturbations. The associated biomolecular signalling network involves a negative feedback on Aux/IAA proteins which mediate the influence of auxin (the signal) on the auxin response factor (ARF) transcription factors (the drivers of the response). To probe the role of this feedback, we consider alternative in silico signalling networks implementing different operating principles. By a comparative analysis, we find that the presence of a negative feedback allows the system to have a far larger sensitivity in its dynamical response to auxin and that this sensitivity does not prevent the system from being highly resilient. Given this insight, we build a new biomolecular signalling model for quantitatively describing such Aux/IAA and ARF responses. PMID:29410878

In silico analysis of a therapeutic target in Leishmania infantum: the guanosine-diphospho-D-mannose pyrophosphorylase.

PubMed

Pomel, S; Rodrigo, J; Hendra, F; Cavé, C; Loiseau, P M

2012-02-01

Leishmaniases are tropical and sub-tropical diseases for which classical drugs (i.e. antimonials) exhibit toxicity and drug resistance. Such a situation requires to find new chemical series with antileishmanial activity. This work consists in analyzing the structure of a validated target in Leishmania: the GDP-mannose pyrophosphorylase (GDP-MP), an enzyme involved in glycosylation and essential for amastigote survival. By comparing both human and L. infantum GDP-MP 3D homology models, we identified (i) a common motif of amino acids that binds to the mannose moiety of the substrate and, interestingly, (ii) a motif that is specific to the catalytic site of the parasite enzyme. This motif could then be used to design compounds that specifically inhibit the leishmanial GDP-MP, without any effect on the human homolog.

DockScreen: A database of in silico biomolecular interactions to support computational toxicology

EPA Science Inventory

We have developed DockScreen, a database of in silico biomolecular interactions designed to enable rational molecular toxicological insight within a computational toxicology framework. This database is composed of chemical/target (receptor and enzyme) binding scores calculated by...

An "in silico" Bioinformatics Laboratory Manual for Bioscience Departments: "Prediction of Glycosylation Sites in Phosphoethanolamine Transferases"

ERIC Educational Resources Information Center

Alyuruk, Hakan; Cavas, Levent

2014-01-01

Genomics and proteomics projects have produced a huge amount of raw biological data including DNA and protein sequences. Although these data have been stored in data banks, their evaluation is strictly dependent on bioinformatics tools. These tools have been developed by multidisciplinary experts for fast and robust analysis of biological data.…

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...

in silico Whole Genome Sequencer & Analyzer (iWGS): a computational pipeline to guide the design and analysis of de novo genome sequencing studies

USDA-ARS?s Scientific Manuscript database

The availability of genomes across the tree of life is highly biased toward vertebrates, pathogens, human disease models, and organisms with relatively small and simple genomes. Recent progress in genomics has enabled the de novo decoding of the genome of virtually any organism, greatly expanding it...

In Silico Analysis of the Potential of the Active Compounds Fucoidan and Alginate Derived from Sargassum Sp. as Inhibitors of COX-1 and COX-2

PubMed Central

Dewi, Lestari

2016-01-01

Introduction: The enzyme cyclooxygenase (COX) is an enzyme that catalyzes the formation of one of the mediators of inflammation, the prostaglandins. Inhibition of COX allegedly can improve inflammation-induced pathological conditions. Aim: The purpose of the present study was to evaluate the potential of Sargassum sp. components, Fucoidan and alginate, as COX inhibitors. Material and methods: The study was conducted by means of a computational (in silico) method. It was performed in two main stages, the docking between COX-1 and COX-2 with Fucoidan, alginate and aspirin (for comparison) and the analysis of the amount of interactions formed and the residues directly involved in the process of interaction. Results: Our results showed that both Fucoidan and alginate had an excellent potential as inhibitors of COX-1 and COX-2. Fucoidan had a better potential as an inhibitor of COX than alginate. COX inhibition was expected to provide a more favorable effect on inflammation-related pathological conditions. Conclusion: The active compounds Fucoidan and alginate derived from Sargassum sp. were suspected to possess a good potential as inhibitors of COX-1 and COX-2. PMID:27594740

In Silico Analysis of the Potential of the Active Compounds Fucoidan and Alginate Derived from Sargassum Sp. as Inhibitors of COX-1 and COX-2.

PubMed

Dewi, Lestari

2016-06-01

The enzyme cyclooxygenase (COX) is an enzyme that catalyzes the formation of one of the mediators of inflammation, the prostaglandins. Inhibition of COX allegedly can improve inflammation-induced pathological conditions. The purpose of the present study was to evaluate the potential of Sargassum sp. components, Fucoidan and alginate, as COX inhibitors. The study was conducted by means of a computational (in silico) method. It was performed in two main stages, the docking between COX-1 and COX-2 with Fucoidan, alginate and aspirin (for comparison) and the analysis of the amount of interactions formed and the residues directly involved in the process of interaction. Our results showed that both Fucoidan and alginate had an excellent potential as inhibitors of COX-1 and COX-2. Fucoidan had a better potential as an inhibitor of COX than alginate. COX inhibition was expected to provide a more favorable effect on inflammation-related pathological conditions. The active compounds Fucoidan and alginate derived from Sargassum sp. were suspected to possess a good potential as inhibitors of COX-1 and COX-2.

Foundations of a query and simulation system for the modeling of biochemical and biological processes.

PubMed

Antoniotti, M; Park, F; Policriti, A; Ugel, N; Mishra, B

2003-01-01

The analysis of large amounts of data, produced as (numerical) traces of in vivo, in vitro and in silico experiments, has become a central activity for many biologists and biochemists. Recent advances in the mathematical modeling and computation of biochemical systems have moreover increased the prominence of in silico experiments; such experiments typically involve the simulation of sets of Differential Algebraic Equations (DAE), e.g., Generalized Mass Action systems (GMA) and S-systems. In this paper we reason about the necessary theoretical and pragmatic foundations for a query and simulation system capable of analyzing large amounts of such trace data. To this end, we propose to combine in a novel way several well-known tools from numerical analysis (approximation theory), temporal logic and verification, and visualization. The result is a preliminary prototype system: simpathica/xssys. When dealing with simulation data simpathica/xssys exploits the special structure of the underlying DAE, and reduces the search space in an efficient way so as to facilitate any queries about the traces. The proposed system is designed to give the user possibility to systematically analyze and simultaneously query different possible timed evolutions of the modeled system.

In Silico Study of Chromatographic Lipophilicity Parameters of 3-(4-Substituted Benzyl)-5-Phenylhydantoins.

PubMed

Sekulic, Tatjana Djakovic; Keleman, Svetlana; Tot, Kristina; Tot, Jadranka; Trisovic, Nemanja; Uscumlic, Gordana

2016-01-01

New synthesized compounds, particularly those with biological activity, are potential drug candidates. This article describes experimental studies performed to estimate lipophilicity parameters of new 3-(4-substituted benzyl)-5-phenylhydantoins. Lipophilicity, as one of the most important molecular characteristics for the activity, was determined using the reversed-phase liquid chromatography (RP-18 stationary phase and methanol-water mobile phase). Molecular structures were used to generate in silico data which were used to estimate pharmacokinetic properties of the investigated compounds. The results show that generally, the investigated compounds attain good bioavailability properties. A more detailed analysis shows that the presence of a nitro, methoxy and tert-butyl group in the molecule is indicated as unfavorable for the oral bioavailability of hydantoins. Multivariate exploratory analysis was used in order to visualize grouping patterns among molecular descriptors as well as among the investigated compounds. Molecular docking study performed for two hydantoins with the highest bioavailability scores shows high binding affinity to tyrosine kinase receptor IGF-1R. The results achieved can be useful as a template for future development and further derivation or modification to obtain more potent and selective antitumor agents.

p.Arg82Leu von Hippel-Lindau (VHL) Gene Mutation among Three Members of a Family with Familial Bilateral Pheochromocytoma in India: Molecular Analysis and In Silico Characterization

PubMed Central

John, Anulekha Mary; C, George Priya Doss; Ebenazer, Andrew; Seshadri, Mandalam Subramaniam; Nair, Aravindan; Rajaratnam, Simon; Pai, Rekha

2013-01-01

Various missense mutations in the VHL gene have been reported among patients with familial bilateral pheochromocytoma. However, the p.Arg82Leu mutation in the VHL gene described here among patients with familial bilateral pheochromocytoma, has never been reported previously in a germline configuration. Interestingly, long-term follow-up of these patients indicated that the mutation might have had little impact on the normal function of the VHL gene, since all of them have remained asymptomatic. We further attempted to correlate this information with the results obtained by in silico analysis of this mutation using SIFT, PhD-SNP SVM profile, MutPred, PolyPhen2, and SNPs&GO prediction tools. To gain, new mechanistic insight into the structural effect, we mapped the mutation on to 3D structure (PDB ID 1LM8). Further, we analyzed the structural level changes in time scale level with respect to native and mutant protein complexes by using 12 ns molecular dynamics simulation method. Though these methods predict the mutation to have a pathogenic potential, it remains to be seen if these patients will eventually develop symptomatic disease. PMID:23626751

Accumulation of multiple mutations in linezolid-resistant Staphylococcus epidermidis causing bloodstream infections; in silico analysis of L3 amino acid substitutions that might confer high-level linezolid resistance.

PubMed

Ikonomidis, Alexandros; Grapsa, Anastasia; Pavlioglou, Charikleia; Demiri, Antonia; Batarli, Alexandra; Panopoulou, Maria

2016-12-01

Fifty-six Staphylococcus epidermidis clinical isolates, showing high-level linezolid resistance and causing bacteremia in critically ill patients, were studied. All isolates belonged to ST22 clone and carried the T2504A and C2534T mutations in gene coding for 23SrRNA as well as the C189A, G208A, C209T and G384C missense mutations in L3 protein which resulted in Asp159Tyr, Gly152Asp and Leu94Val substitutions. Other silent mutations were also detected in genes coding for ribosomal proteins L3 and L22. In silico analysis of missense mutations showed that although L3 protein retained the sequence of secondary motifs, the tertiary structure was influenced. The observed alteration in L3 protein folding provides an indication on the putative role of L3-coding gene mutations in high-level linezolid resistance. Furthermore, linezolid pressure in health care settings where linezolid consumption is of high rates might lead to the selection of resistant mutants possessing L3 mutations that might confer high-level linezolid resistance.

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 regenerative medicine: how computational tools allow regulatory and financial challenges to be addressed in a volatile market

PubMed Central

Geris, L.; Guyot, Y.; Schrooten, J.; Papantoniou, I.

2016-01-01

The cell therapy market is a highly volatile one, due to the use of disruptive technologies, the current economic situation and the small size of the market. In such a market, companies as well as academic research institutes are in need of tools to advance their understanding and, at the same time, reduce their R&D costs, increase product quality and productivity, and reduce the time to market. An additional difficulty is the regulatory path that needs to be followed, which is challenging in the case of cell-based therapeutic products and should rely on the implementation of quality by design (QbD) principles. In silico modelling is a tool that allows the above-mentioned challenges to be addressed in the field of regenerative medicine. This review discusses such in silico models and focuses more specifically on the bioprocess. Three (clusters of) examples related to this subject are discussed. The first example comes from the pharmaceutical engineering field where QbD principles and their implementation through the use of in silico models are both a regulatory and economic necessity. The second example is related to the production of red blood cells. The described in silico model is mainly used to investigate the manufacturing process of the cell-therapeutic product, and pays special attention to the economic viability of the process. Finally, we describe the set-up of a model capturing essential events in the development of a tissue-engineered combination product in the context of bone tissue engineering. For each of the examples, a short introduction to some economic aspects is given, followed by a description of the in silico tool or tools that have been developed to allow the implementation of QbD principles and optimal design. PMID:27051516

In silico regenerative medicine: how computational tools allow regulatory and financial challenges to be addressed in a volatile market.

PubMed

Geris, L; Guyot, Y; Schrooten, J; Papantoniou, I

2016-04-06

The cell therapy market is a highly volatile one, due to the use of disruptive technologies, the current economic situation and the small size of the market. In such a market, companies as well as academic research institutes are in need of tools to advance their understanding and, at the same time, reduce their R&D costs, increase product quality and productivity, and reduce the time to market. An additional difficulty is the regulatory path that needs to be followed, which is challenging in the case of cell-based therapeutic products and should rely on the implementation of quality by design (QbD) principles. In silico modelling is a tool that allows the above-mentioned challenges to be addressed in the field of regenerative medicine. This review discusses such in silico models and focuses more specifically on the bioprocess. Three (clusters of) examples related to this subject are discussed. The first example comes from the pharmaceutical engineering field where QbD principles and their implementation through the use of in silico models are both a regulatory and economic necessity. The second example is related to the production of red blood cells. The described in silico model is mainly used to investigate the manufacturing process of the cell-therapeutic product, and pays special attention to the economic viability of the process. Finally, we describe the set-up of a model capturing essential events in the development of a tissue-engineered combination product in the context of bone tissue engineering. For each of the examples, a short introduction to some economic aspects is given, followed by a description of the in silico tool or tools that have been developed to allow the implementation of QbD principles and optimal design.

In Silico Study, Synthesis, and Cytotoxic Activities of Porphyrin Derivatives

PubMed Central

Kurniawan, Fransiska; Miura, Youhei; Kartasasmita, Rahmana Emran; Mutalib, Abdul

2018-01-01

Five known porphyrins, 5,10,15,20-tetrakis(p-tolyl)porphyrin (TTP), 5,10,15,20-tetrakis(p-bromophenyl)porphyrin (TBrPP), 5,10,15,20-tetrakis(p-aminophenyl)porphyrin (TAPP), 5,10,15-tris(tolyl)-20-mono(p-nitrophenyl)porphyrin (TrTMNP), 5,10,15-tris(tolyl)-20-mono(p-aminophenyl)porphyrin (TrTMAP), and three novel porphyrin derivatives, 5,15-di-[bis(3,4-ethylcarboxymethylenoxy)phenyl]-10,20-di(p-tolyl)porphyrin (DBECPDTP), 5,10-di-[bis(3,4-ethylcarboxymethylenoxy)phenyl]-15,20-di-(methylpyrazole-4-yl)porphyrin (cDBECPDPzP), 5,15-di-[bis(3,4-ethylcarboxymethylenoxy)phenyl]-10,20-di-(methylpyrazole-4-yl)porphyrin (DBECPDPzP), were used to study their interaction with protein targets (in silico study), and were synthesized. Their cytotoxic activities against cancer cell lines were tested using 3-(4,5-dimetiltiazol-2-il)-2,5-difeniltetrazolium bromide (MTT) assay. The interaction of porphyrin derivatives with carbonic anhydrase IX (CAIX) and REV-ERBβ proteins were studied by molecular docking and molecular dynamic simulation. In silico study results reveal that DBECPDPzP and TrTMNP showed the highest binding interaction with REV- ERBβ and CAIX, respectively, and both complexes of DBECPDPzP-REV-ERBβ and TrTMNP-CAIX showed good and comparable stability during molecular dynamic simulation. The studied porphyrins have selective growth inhibition activities against tested cancer cells and are categorized as marginally active compounds based on their IC50. PMID:29361701

Combining Basal–Bolus Insulin Infusion for Tight Postprandial Glucose Control: An in Silico Evaluation in Adults, Children, and Adolescents

PubMed Central

Revert, Ana; Rossetti, Paolo; Calm, Remei; Vehí, Josep; Bondia, Jorge

2010-01-01

Background Achieving good postprandial glycemic control, without triggering hypoglycemia events, is a challenge of treatment strategies for type 1 diabetes subjects. Continuous subcutaneous insulin infusion, the gold standard of therapy, is based on heuristic adjustments of both basal and prandial insulin. Some tools, such as bolus calculators, are available to aid patients in selecting a meal-related insulin dose. However, they are still based on empiric parameters such as the insulin-to-carbohydrate ratio and on the physicians’ and patients’ ability to fit bolus mode to meal composition. Method In this article, a nonheuristic method for assessment of prandial insulin administration is presented and evaluated. An algorithm based on set inversion via interval analysis is used to coordinate basal and bolus insulin infusions to deal with postprandial glucose excursions. The evaluation is carried out through an in silico study using the 30 virtual patients available in the educational version of the Food and Drug Administration-accepted University of Virginia simulator. Results obtained using the standard bolus strategy and different coordinated basal–bolus solutions provided by the algorithm are compared. Results Coordinated basal–bolus solutions improve postprandial glucose performance in most cases, mainly in terms of reducing hypoglycemia risk, but also increasing the percentage of time in normoglycemia. Moreover, glycemic variability is reduced considerably by using these innovative solutions. Conclusions The algorithm presented here is a robust nonheuristic alternative to deal with postprandial glycemic control. It is shown as a powerful tool that could be integrated in future smart insulin pumps. PMID:21129338

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

Ramachandran analysis of conserved glycyl residues in homologous proteins of known structure.

PubMed

Lakshmi, Balasubramanian; Sinduja, Chandrasekaran; Archunan, Govind; Srinivasan, Narayanaswamy

2014-06-01

High conservation of glycyl residues in homologous proteins is fairly frequent. It is commonly understood that glycine tends to be highly conserved either because of its unique Ramachandran angles or to avoid steric clash that would arise with a larger side chain. Using a database of aligned 3D structures of homologous proteins we identified conserved Gly in 288 alignment positions from 85 families. Ninety-six of these alignment positions correspond to conserved Gly residue with (φ, ψ) values allowed for non-glycyl residues. Reasons for this observation were investigated by in-silico mutation of these glycyl residues to Ala. We found in 94% of the cases a short contact exists between the C(β) atom of the introduced Ala with the atoms which are often distant in the primary structure. This suggests the lack of space even for a short side chain thereby explaining high conservation of glycyl residues even when they adopt (φ, ψ) values allowed for Ala. In 189 alignment positions, the conserved glycyl residues adopt (φ, ψ) values which are disallowed for Ala. In-silico mutation of these Gly residues to Ala almost always results in steric hindrance involving C(β) atom of Ala as one would expect by comparing Ramachandran maps for Ala and Gly. Rare occurrence of the disallowed glycyl conformations even in ultrahigh resolution protein structures are accompanied by short contacts in the crystal structures and such disallowed conformations are not conserved in the homologues. These observations raise the doubt on the accuracy of such glycyl conformations in proteins. © 2014 The Protein Society.

Identification of copy number variation in French dairy and beef breeds using next-generation sequencing.

PubMed

Letaief, Rabia; Rebours, Emmanuelle; Grohs, Cécile; Meersseman, Cédric; Fritz, Sébastien; Trouilh, Lidwine; Esquerré, Diane; Barbieri, Johanna; Klopp, Christophe; Philippe, Romain; Blanquet, Véronique; Boichard, Didier; Rocha, Dominique; Boussaha, Mekki

2017-10-24

Copy number variations (CNV) are known to play a major role in genetic variability and disease pathogenesis in several species including cattle. In this study, we report the identification and characterization of CNV in eight French beef and dairy breeds using whole-genome sequence data from 200 animals. Bioinformatics analyses to search for CNV were carried out using four different but complementary tools and we validated a subset of the CNV by both in silico and experimental approaches. We report the identification and localization of 4178 putative deletion-only, duplication-only and CNV regions, which cover 6% of the bovine autosomal genome; they were validated by two in silico approaches and/or experimentally validated using array-based comparative genomic hybridization and single nucleotide polymorphism genotyping arrays. The size of these variants ranged from 334 bp to 7.7 Mb, with an average size of ~ 54 kb. Of these 4178 variants, 3940 were deletions, 67 were duplications and 171 corresponded to both deletions and duplications, which were defined as potential CNV regions. Gene content analysis revealed that, among these variants, 1100 deletions and duplications encompassed 1803 known genes, which affect a wide spectrum of molecular functions, and 1095 overlapped with known QTL regions. Our study is a large-scale survey of CNV in eight French dairy and beef breeds. These CNV will be useful to study the link between genetic variability and economically important traits, and to improve our knowledge on the genomic architecture of cattle.

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.

Towards Coleoptera-specific high-throughput screening systems for compounds with ecdysone activity: development of EcR reporter assays using weevil (Anthonomus grandis)-derived cell lines and in silico analysis of ligand binding to A. grandis EcR ligand-binding pocket.

PubMed

Soin, Thomas; Iga, Masatoshi; Swevers, Luc; Rougé, Pierre; Janssen, Colin R; Smagghe, Guy

2009-08-01

Molting in insects is regulated by ecdysteroids and juvenile hormones. Several synthetic non-steroidal ecdysone agonists are on the market as insecticides. These ecdysone agonists are dibenzoylhydrazine (DBH) analogue compounds that manifest their toxicity via interaction with the ecdysone receptor (EcR). Of the four commercial available ecdysone agonists, three (tebufenozide, methoxyfenozide and chromafenozide) are highly lepidopteran specific, one (halofenozide) is used to control coleopteran and lepidopteran insects in turf and ornamentals. However, compared to the very high binding affinity of these DBH analogues to lepidopteran EcRs, halofenozide has a low binding affinity for coleopteran EcRs. For the discovery of ecdysone agonists that target non-lepidopteran insect groups, efficient screening systems that are based on the activation of the EcR are needed. We report here the development and evaluation of two coleopteran-specific reporter-based screening systems to discover and evaluate ecdysone agonists. The screening systems are based on the cell lines BRL-AG-3A and BRL-AG-3C that are derived from the weevil Anthonomus grandis, which can be efficiently transduced with an EcR reporter cassette for evaluation of induction of reporter activity by ecdysone agonists. We also cloned the almost full length coding sequence of EcR expressed in the cell line BRL-AG-3C and used it to make an initial in silico 3D-model of its ligand-binding pocket docked with ponasterone A and tebufenozide.

CisSERS: Customizable in silico sequence evaluation for restriction sites

DOE PAGES

Sharpe, Richard M.; Koepke, Tyson; Harper, Artemus; ...

2016-04-12

High-throughput sequencing continues to produce an immense volume of information that is processed and assembled into mature sequence data. Here, data analysis tools are urgently needed that leverage the embedded DNA sequence polymorphisms and consequent changes to restriction sites or sequence motifs in a high-throughput manner to enable biological experimentation. CisSERS was developed as a standalone open source tool to analyze sequence datasets and provide biologists with individual or comparative genome organization information in terms of presence and frequency of patterns or motifs such as restriction enzymes. Predicted agarose gel visualization of the custom analyses results was also integrated tomore » enhance the usefulness of the software. CisSERS offers several novel functionalities, such as handling of large and multiple datasets in parallel, multiple restriction enzyme site detection and custom motif detection features, which are seamlessly integrated with real time agarose gel visualization. Using a simple fasta-formatted file as input, CisSERS utilizes the REBASE enzyme database. Results from CisSERSenable the user to make decisions for designing genotyping by sequencing experiments, reduced representation sequencing, 3’UTR sequencing, and cleaved amplified polymorphic sequence (CAPS) molecular markers for large sample sets. CisSERS is a java based graphical user interface built around a perl backbone. Several of the applications of CisSERS including CAPS molecular marker development were successfully validated using wet-lab experimentation. Here, we present the tool CisSERSand results from in-silico and corresponding wet-lab analyses demonstrating that CisSERS is a technology platform solution that facilitates efficient data utilization in genomics and genetics studies.« less

Root Cell-Specific Regulators of Phosphate-Dependent Growth1[OPEN

PubMed Central

Ding, Wona

2017-01-01

Cellular specialization in abiotic stress responses is an important regulatory feature driving plant acclimation. Our in silico approach of iterative coexpression, interaction, and enrichment analyses predicted root cell-specific regulators of phosphate starvation response networks in Arabidopsis (Arabidopsis thaliana). This included three uncharacterized genes termed Phosphate starvation-induced gene interacting Root Cell Enriched (PRCE1, PRCE2, and PRCE3). Root cell-specific enrichment of 12 candidates was confirmed in promoter-GFP lines. T-DNA insertion lines of 11 genes showed changes in phosphate status and growth responses to phosphate availability compared with the wild type. Some mutants (cbl1, cipk2, prce3, and wdd1) displayed strong biomass gain irrespective of phosphate supply, while others (cipk14, mfs1, prce1, prce2, and s6k2) were able to sustain growth under low phosphate supply better than the wild type. Notably, root or shoot phosphate accumulation did not strictly correlate with organ growth. Mutant response patterns markedly differed from those of master regulators of phosphate homeostasis, PHOSPHATE STARVATION RESPONSE1 (PHR1) and PHOSPHATE2 (PHO2), demonstrating that negative growth responses in the latter can be overcome when cell-specific regulators are targeted. RNA sequencing analysis highlighted the transcriptomic plasticity in these mutants and revealed PHR1-dependent and -independent regulatory circuits with gene coexpression profiles that were highly correlated to the quantified physiological traits. The results demonstrate how in silico prediction of cell-specific, stress-responsive genes uncovers key regulators and how their manipulation can have positive impacts on plant growth under abiotic stress. PMID:28465462

CisSERS: Customizable in silico sequence evaluation for restriction sites

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

Sharpe, Richard M.; Koepke, Tyson; Harper, Artemus

High-throughput sequencing continues to produce an immense volume of information that is processed and assembled into mature sequence data. Here, data analysis tools are urgently needed that leverage the embedded DNA sequence polymorphisms and consequent changes to restriction sites or sequence motifs in a high-throughput manner to enable biological experimentation. CisSERS was developed as a standalone open source tool to analyze sequence datasets and provide biologists with individual or comparative genome organization information in terms of presence and frequency of patterns or motifs such as restriction enzymes. Predicted agarose gel visualization of the custom analyses results was also integrated tomore » enhance the usefulness of the software. CisSERS offers several novel functionalities, such as handling of large and multiple datasets in parallel, multiple restriction enzyme site detection and custom motif detection features, which are seamlessly integrated with real time agarose gel visualization. Using a simple fasta-formatted file as input, CisSERS utilizes the REBASE enzyme database. Results from CisSERSenable the user to make decisions for designing genotyping by sequencing experiments, reduced representation sequencing, 3’UTR sequencing, and cleaved amplified polymorphic sequence (CAPS) molecular markers for large sample sets. CisSERS is a java based graphical user interface built around a perl backbone. Several of the applications of CisSERS including CAPS molecular marker development were successfully validated using wet-lab experimentation. Here, we present the tool CisSERSand results from in-silico and corresponding wet-lab analyses demonstrating that CisSERS is a technology platform solution that facilitates efficient data utilization in genomics and genetics studies.« less

In silico Testing of Environmental Impact on Embryonic Vascular Development

EPA Science Inventory

Understanding risks to embryonic development from exposure to environmental chemicals is a significant challenge given the diverse chemical landscape and paucity of data for most of these compounds. EPA’s Virtual Embryo project is building in silico models of morphogenesis to tes...

TARGETED DELIVERY OF INHALED PHARMACEUTICALS USING AN IN SILICO DOSIMETRY MODEL

EPA Science Inventory

We present an in silico dosimetry model which can be used for inhalation toxicology (risk assessment of inhaled air pollutants) and aerosol therapy ( targeted delivery of inhaled drugs). This work presents scientific and clinical advances beyond the development of the original in...

Genome-wide analysis of copper, iron and zinc transporters in the arbuscular mycorrhizal fungus Rhizophagus irregularis.

PubMed

Tamayo, Elisabeth; Gómez-Gallego, Tamara; Azcón-Aguilar, Concepción; Ferrol, Nuria

2014-01-01

Arbuscular mycorrhizal fungi (AMF), belonging to the Glomeromycota, are soil microorganisms that establish mutualistic symbioses with the majority of higher plants. The efficient uptake of low mobility mineral nutrients by the fungal symbiont and their further transfer to the plant is a major feature of this symbiosis. Besides improving plant mineral nutrition, AMF can alleviate heavy metal toxicity to their host plants and are able to tolerate high metal concentrations in the soil. Nevertheless, we are far from understanding the key molecular determinants of metal homeostasis in these organisms. To get some insights into these mechanisms, a genome-wide analysis of Cu, Fe and Zn transporters was undertaken, making use of the recently published whole genome of the AMF Rhizophagus irregularis. This in silico analysis allowed identification of 30 open reading frames in the R. irregularis genome, which potentially encode metal transporters. Phylogenetic comparisons with the genomes of a set of reference fungi showed an expansion of some metal transporter families. Analysis of the published transcriptomic profiles of R. irregularis revealed that a set of genes were up-regulated in mycorrhizal roots compared to germinated spores and extraradical mycelium, which suggests that metals are important for plant colonization.

A novel ENU-induced mutation, peewee, causes dwarfism in the mouse

PubMed Central

Bon-Ryon, Lee; Kano, Kiyoshi; Young, Jay; John, Simon; Nishina, Patsy M; Naggert, Jurgen K; Naito, Kunihiko

2010-01-01

We identified a novel fertile, autosomal recessive mutation, called peewee and that results in dwarfing, in a region-specific ENU-induced mutagenesis. These mice at litter size were smaller those of other strains. Histological analysis revealed that the major organs appear normal, but abnormalities in cellular proliferation were observed in bone, liver and testis. Haplotype analysis localized the peewee gene to a 3.3-Mb region between D5Mit83 and D5Mit356.3. There are 18 genes in this linkage area, and we also performed in silico mapping using the PosMed℠ program, which searches for connections among keywords and genes in an interval, but no similar phenotype descriptions were found for these genes. In the peewee mutant compared to the normal, C57BL/6J mouse, only Slc10a4 expression was lower. Our preliminary mutation analysis examining the nucleotide sequence of three exons, two introns and an untranslated region of Slc10a4 did not find any sequence difference between the peewee mouse and the C57BL/6J mouse. Detailed analysis of peewee mice might provide novel molecular insights into the complex mechanisms regulating body growth. PMID:19513787

Comparative Genomic Analysis of Lactobacillus plantarum GB-LP1 Isolated from Traditional Korean Fermented Food.

PubMed

Yu, Jihyun; Ahn, Sojin; Kim, Kwondo; Caetano-Anolles, Kelsey; Lee, Chanho; Kang, Jungsun; Cho, Kyungjin; Yoon, Sook Hee; Kang, Dae-Kyung; Kim, Heebal

2017-08-28

As probiotics play an important role in maintaining a healthy gut flora environment through antitoxin activity and inhibition of pathogen colonization, they have been of interest to the medical research community for quite some time now. Probiotic bacteria such as Lactobacillus plantarum , which can be found in fermented food, are of particular interest given their easy accessibility. We performed whole-genome sequencing and genomic analysis on a GB-LP1 strain of L. plantarum isolated from Korean traditional fermented food; this strain is well known for its functions in immune response, suppression of pathogen growth, and antitoxin effects. The complete genome sequence of GB-LP1 is a single chromosome of 3,040,388 bp with 2,899 predicted open reading frames. Genomic analysis of GB-LP1 revealed two CRISPR regions and genes showing accelerated evolution, which may have antibiotic and antitoxin functions. The aim of the present study was to predict strain specific-genomic characteristics and assess the potential of this new strain as lactic acid bacteria at the genomic level using in silico analysis. These results provide insight into the L. plantarum species as well as confirm the possibility of its utility as a candidate probiotic.

A Meta-Analysis of Multiple Matched Copy Number and Transcriptomics Data Sets for Inferring Gene Regulatory Relationships

PubMed Central

Newton, Richard; Wernisch, Lorenz

2014-01-01

Inferring gene regulatory relationships from observational data is challenging. Manipulation and intervention is often required to unravel causal relationships unambiguously. However, gene copy number changes, as they frequently occur in cancer cells, might be considered natural manipulation experiments on gene expression. An increasing number of data sets on matched array comparative genomic hybridisation and transcriptomics experiments from a variety of cancer pathologies are becoming publicly available. Here we explore the potential of a meta-analysis of thirty such data sets. The aim of our analysis was to assess the potential of in silico inference of trans-acting gene regulatory relationships from this type of data. We found sufficient correlation signal in the data to infer gene regulatory relationships, with interesting similarities between data sets. A number of genes had highly correlated copy number and expression changes in many of the data sets and we present predicted potential trans-acted regulatory relationships for each of these genes. The study also investigates to what extent heterogeneity between cell types and between pathologies determines the number of statistically significant predictions available from a meta-analysis of experiments. PMID:25148247

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

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

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.

Comprehensive in silico allergenicity assessment of novel protein engineered chimeric Cry proteins for safe deployment in crops.

PubMed

Rathinam, Maniraj; Singh, Shweta; Pattanayak, Debasis; Sreevathsa, Rohini

2017-08-02

Development of chimeric Cry toxins by protein engineering of known and validated proteins is imperative for enhancing the efficacy and broadening the insecticidal spectrum of these genes. Expression of novel Cry proteins in food crops has however created apprehensions with respect to the safety aspects. To clarify this, premarket evaluation consisting of an array of analyses to evaluate the unintended effects is a prerequisite to provide safety assurance to the consumers. Additionally, series of bioinformatic tools as in silico aids are being used to evaluate the likely allergenic reaction of the proteins based on sequence and epitope similarity with known allergens. In the present study, chimeric Cry toxins developed through protein engineering were evaluated for allergenic potential using various in silico algorithms. Major emphasis was on the validation of allergenic potential on three aspects of paramount significance viz., sequence-based homology between allergenic proteins, validation of conformational epitopes towards identification of food allergens and physico-chemical properties of amino acids. Additionally, in vitro analysis pertaining to heat stability of two of the eight chimeric proteins and pepsin digestibility further demonstrated the non-allergenic potential of these chimeric toxins. The study revealed for the first time an all-encompassing evaluation that the recombinant Cry proteins did not show any potential similarity with any known allergens with respect to the parameters generally considered for a protein to be designated as an allergen. These novel chimeric proteins hence can be considered safe to be introgressed into plants.

Flux analysis of the human proximal colon using anaerobic digestion model 1.

PubMed

Motelica-Wagenaar, Anne Marieke; Nauta, Arjen; van den Heuvel, Ellen G H M; Kleerebezem, Robbert

2014-08-01

The colon can be regarded as an anaerobic digestive compartment within the gastro intestinal tract (GIT). An in silico model simulating the fluxes in the human proximal colon was developed on basis of the anaerobic digestion model 1 (ADM1), which is traditionally used to model waste conversion to biogas. Model calibration was conducted using data from in vitro fermentation of the proximal colon (TIM-2), and, amongst others, supplemented with the bio kinetics of prebiotic galactooligosaccharides (GOS) fermentation. The impact of water and solutes absorption by the host was also included. Hydrolysis constants of carbohydrates and proteins were estimated based on total short chain fatty acids (SCFA) and ammonia production in vitro. Model validation was established using an independent dataset of a different in vitro model: an in vitro three-stage continuous culture system. The in silico model was shown to provide quantitative insight in the microbial community structure in terms of functional groups, and the substrate and product fluxes between these groups as well as the host, as a function of the substrate composition, pH and the solids residence time (SRT). The model confirms the experimental observation that methanogens are washed out at low pH or low SRT-values. The in silico model is proposed as useful tool in the design of experimental setups for in vitro experiments by giving insight in fermentation processes in the proximal human colon. Copyright © 2014. Published by Elsevier Ltd.

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

Evaluation of in silico pharmacokinetic properties and in vitro cytotoxic activity of selected newly synthesized N-succinimide derivatives.

PubMed

Milosevic, Natasa P; Kojic, Vesna; Curcic, Jelena; Jakimov, Dimitar; Milic, Natasa; Banjac, Nebojsa; Uscumlic, Gordana; Kaliszan, Roman

2017-04-15

Design of a new drug entity is usually preceded by analysis of quantitative structure activity (properties) relationships, QSA(P)R. Six newly synthesized succinimide derivatives have been determined for (i) in silico physico-chemical descriptors, pharmacokinetic and toxicity predictors, (ii) in vitro biological activity on four different carcinoma cell lines and on normal fetal lung cells and (iii) lipophilicity on liquid chromatography. All compounds observed were predicted for good permeability and solubility, good oral absorption rate and moderate volume of distribution as well as for modest blood brain permeation, followed by acceptable observed toxicity. In silico determined lipophilicity, permeability through jejunum and aqueous solubility were correlated with experimentally obtained lipophilic constants (by use of high pressure liquid chromatography) and linear correlations were obtained. Absorption rate and volume of distribution were predicted by chromatographic lipophilicity measurements while permeation through blood bran barrier was predicted dominantly by molecular size defined with molecular weight. Five compounds have demonstrated antiproliferative activity toward cervix carcinoma HeLa cell lines; three were cytotoxic against breast carcinoma MCF-7 cells, while one inhibited proliferation of colon carcinoma HT-29 cell lines. Only one compound was cytotoxic toward normal cell lines, while other compounds were proven as safe. Antiproliferative potential against HeLa cells was described as exponential function of lipophilicity. Based on obtained results, lead compounds were selected. Copyright © 2017 Elsevier B.V. All rights reserved.

Polymer physics predicts the effects of structural variants on chromatin architecture.

PubMed

Bianco, Simona; Lupiáñez, Darío G; Chiariello, Andrea M; Annunziatella, Carlo; Kraft, Katerina; Schöpflin, Robert; Wittler, Lars; Andrey, Guillaume; Vingron, Martin; Pombo, Ana; Mundlos, Stefan; Nicodemi, Mario

2018-05-01

Structural variants (SVs) can result in changes in gene expression due to abnormal chromatin folding and cause disease. However, the prediction of such effects remains a challenge. Here we present a polymer-physics-based approach (PRISMR) to model 3D chromatin folding and to predict enhancer-promoter contacts. PRISMR predicts higher-order chromatin structure from genome-wide chromosome conformation capture (Hi-C) data. Using the EPHA4 locus as a model, the effects of pathogenic SVs are predicted in silico and compared to Hi-C data generated from mouse limb buds and patient-derived fibroblasts. PRISMR deconvolves the folding complexity of the EPHA4 locus and identifies SV-induced ectopic contacts and alterations of 3D genome organization in homozygous or heterozygous states. We show that SVs can reconfigure topologically associating domains, thereby producing extensive rewiring of regulatory interactions and causing disease by gene misexpression. PRISMR can be used to predict interactions in silico, thereby providing a tool for analyzing the disease-causing potential of SVs.

Non-invasive pressure difference estimation from PC-MRI using the work-energy equation

PubMed Central

Donati, Fabrizio; Figueroa, C. Alberto; Smith, Nicolas P.; Lamata, Pablo; Nordsletten, David A.

2015-01-01

Pressure difference is an accepted clinical biomarker for cardiovascular disease conditions such as aortic coarctation. Currently, measurements of pressure differences in the clinic rely on invasive techniques (catheterization), prompting development of non-invasive estimates based on blood flow. In this work, we propose a non-invasive estimation procedure deriving pressure difference from the work-energy equation for a Newtonian fluid. Spatial and temporal convergence is demonstrated on in silico Phase Contrast Magnetic Resonance Image (PC-MRI) phantoms with steady and transient flow fields. The method is also tested on an image dataset generated in silico from a 3D patient-specific Computational Fluid Dynamics (CFD) simulation and finally evaluated on a cohort of 9 subjects. The performance is compared to existing approaches based on steady and unsteady Bernoulli formulations as well as the pressure Poisson equation. The new technique shows good accuracy, robustness to noise, and robustness to the image segmentation process, illustrating the potential of this approach for non-invasive pressure difference estimation. PMID:26409245

Docking studies of antidepressants against single crystal structure of tryptophan 2, 3-dioxygenase using Molegro Virtual Docker software.

PubMed

Dawood, Shazia; Zarina, Shamshad; Bano, Samina

2014-09-01

Tryptophan 2, 3-dioxygenase (TDO) a heme containing enzyme found in mammalian liver is responsible for tryptophan (Trp) catabolism. Trp is an essential amino acid that is degraded in to N-formylkynurenine by the action of TDO. The protein ligand interaction plays a significant role in structural based drug designing. The current study illustrates the binding of established antidepressants (ADs) against TDO enzyme using in-silico docking studies. For this purpose, Fluoxetine, Paroxetine, Sertraline, Fluvoxamine, Seproxetine, Citalopram, Moclobamide, Hyperforin and Amoxepine were selected. In-silico docking studies were carried out using Molegro Virtual Docker (MVD) software. Docking results show that all ADs fit well in the active site of TDO moreover Hyperforin and Paroxetine exhibited high docking scores of -152.484k cal/mol and -139.706k cal/mol, respectively. It is concluded that Hyperforin and Paroxetine are possible lead molecules because of their high docking scores as compared to other ADs examined. Therefore, these two ADs stand as potent inhibitors of TDO enzyme.

Comparative multi-omics systems analysis of Escherichia coli strains B and K-12.

PubMed

Yoon, Sung Ho; Han, Mee-Jung; Jeong, Haeyoung; Lee, Choong Hoon; Xia, Xiao-Xia; Lee, Dae-Hee; Shim, Ji Hoon; Lee, Sang Yup; Oh, Tae Kwang; Kim, Jihyun F

2012-05-25

Elucidation of a genotype-phenotype relationship is critical to understand an organism at the whole-system level. Here, we demonstrate that comparative analyses of multi-omics data combined with a computational modeling approach provide a framework for elucidating the phenotypic characteristics of organisms whose genomes are sequenced. We present a comprehensive analysis of genome-wide measurements incorporating multifaceted holistic data - genome, transcriptome, proteome, and phenome - to determine the differences between Escherichia coli B and K-12 strains. A genome-scale metabolic network of E. coli B was reconstructed and used to identify genetic bases of the phenotypes unique to B compared with K-12 through in silico complementation testing. This systems analysis revealed that E. coli B is well-suited for production of recombinant proteins due to a greater capacity for amino acid biosynthesis, fewer proteases, and lack of flagella. Furthermore, E. coli B has an additional type II secretion system and a different cell wall and outer membrane composition predicted to be more favorable for protein secretion. In contrast, E. coli K-12 showed a higher expression of heat shock genes and was less susceptible to certain stress conditions. This integrative systems approach provides a high-resolution system-wide view and insights into why two closely related strains of E. coli, B and K-12, manifest distinct phenotypes. Therefore, systematic understanding of cellular physiology and metabolism of the strains is essential not only to determine culture conditions but also to design recombinant hosts.

Comparative multi-omics systems analysis of Escherichia coli strains B and K-12

PubMed Central

2012-01-01

Background Elucidation of a genotype-phenotype relationship is critical to understand an organism at the whole-system level. Here, we demonstrate that comparative analyses of multi-omics data combined with a computational modeling approach provide a framework for elucidating the phenotypic characteristics of organisms whose genomes are sequenced. Results We present a comprehensive analysis of genome-wide measurements incorporating multifaceted holistic data - genome, transcriptome, proteome, and phenome - to determine the differences between Escherichia coli B and K-12 strains. A genome-scale metabolic network of E. coli B was reconstructed and used to identify genetic bases of the phenotypes unique to B compared with K-12 through in silico complementation testing. This systems analysis revealed that E. coli B is well-suited for production of recombinant proteins due to a greater capacity for amino acid biosynthesis, fewer proteases, and lack of flagella. Furthermore, E. coli B has an additional type II secretion system and a different cell wall and outer membrane composition predicted to be more favorable for protein secretion. In contrast, E. coli K-12 showed a higher expression of heat shock genes and was less susceptible to certain stress conditions. Conclusions This integrative systems approach provides a high-resolution system-wide view and insights into why two closely related strains of E. coli, B and K-12, manifest distinct phenotypes. Therefore, systematic understanding of cellular physiology and metabolism of the strains is essential not only to determine culture conditions but also to design recombinant hosts. PMID:22632713

Binding site exploration of CCR5 using in silico methodologies: a 3D-QSAR approach.

PubMed

Gadhe, Changdev G; Kothandan, Gugan; Cho, Seung Joo

2013-01-01

Chemokine receptor 5 (CCR5) is an important receptor used by human immunodeficiency virus type 1 (HIV-1) to gain viral entry into host cell. In this study, we used a combined approach of comparative modeling, molecular docking, and three dimensional quantitative structure activity relationship (3D-QSAR) analyses to elucidate detailed interaction of CCR5 with their inhibitors. Docking study of the most potent inhibitor from a series of compounds was done to derive the bioactive conformation. Parameters such as random selection, rational selection, different charges and grid spacing were utilized in the model development to check their performance on the model predictivity. Final comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were chosen based on the rational selection method, Gasteiger-Hückel charges and a grid spacing of 0.5 Å. Rational model for CoMFA (q(2) = 0.722, r(2) = 0.884, Q(2) = 0.669) and CoMSIA (q(2) = 0.712, r(2) = 0.825, Q(2) = 0.522) was obtained with good statistics. Mapping of contour maps onto CCR5 interface led us to better understand of the ligand-protein interaction. Docking analysis revealed that the Glu283 is crucial for interaction. Two new amino acid residues, Tyr89 and Thr167 were identified as important in ligand-protein interaction. No site directed mutagenesis studies on these residues have been reported.

AN IN SILICO INVESTIGATION OF THE ENANTIOSELECTIVE METABOLISM RATES OF TRIAZOLE FUGICIDES

EPA Science Inventory

The objective of this work is to use in silico methods such as ab initio quantum and classical force-field methods to explore and develop an understanding for the enantioselective metabolism rates experimentally observed in the triazole fungicide bromuconazole. This directed stud...

In silico assessment of biomedical products: The conundrum of rare but not so rare events in two case studies.

PubMed

Viceconti, Marco; Cobelli, Claudio; Haddad, Tarek; Himes, Adam; Kovatchev, Boris; Palmer, Mark

2017-05-01

In silico clinical trials, defined as "The use of individualized computer simulation in the development or regulatory evaluation of a medicinal product, medical device, or medical intervention," have been proposed as a possible strategy to reduce the regulatory costs of innovation and the time to market for biomedical products. We review some of the the literature on this topic, focusing in particular on those applications where the current practice is recognized as inadequate, as for example, the detection of unexpected severe adverse events too rare to be detected in a clinical trial, but still likely enough to be of concern. We then describe with more details two case studies, two successful applications of in silico clinical trial approaches, one relative to the University of Virginia/Padova simulator that the Food and Drug Administration has accepted as possible replacement for animal testing in the preclinical assessment of artificial pancreas technologies, and the second, an investigation of the probability of cardiac lead fracture, where a Bayesian network was used to combine in vivo and in silico observations, suggesting a whole new strategy of in silico-augmented clinical trials, to be used to increase the numerosity where recruitment is impossible, or to explore patients' phenotypes that are unlikely to appear in the trial cohort, but are still frequent enough to be of concern.

Improved intra-array and interarray normalization of peptide microarray phosphorylation for phosphorylome and kinome profiling by rational selection of relevant spots

PubMed Central

Scholma, Jetse; Fuhler, Gwenny M.; Joore, Jos; Hulsman, Marc; Schivo, Stefano; List, Alan F.; Reinders, Marcel J. T.; Peppelenbosch, Maikel P.; Post, Janine N.

2016-01-01

Massive parallel analysis using array technology has become the mainstay for analysis of genomes and transcriptomes. Analogously, the predominance of phosphorylation as a regulator of cellular metabolism has fostered the development of peptide arrays of kinase consensus substrates that allow the charting of cellular phosphorylation events (often called kinome profiling). However, whereas the bioinformatical framework for expression array analysis is well-developed, no advanced analysis tools are yet available for kinome profiling. Especially intra-array and interarray normalization of peptide array phosphorylation remain problematic, due to the absence of “housekeeping” kinases and the obvious fallacy of the assumption that different experimental conditions should exhibit equal amounts of kinase activity. Here we describe the development of analysis tools that reliably quantify phosphorylation of peptide arrays and that allow normalization of the signals obtained. We provide a method for intraslide gradient correction and spot quality control. We describe a novel interarray normalization procedure, named repetitive signal enhancement, RSE, which provides a mathematical approach to limit the false negative results occuring with the use of other normalization procedures. Using in silico and biological experiments we show that employing such protocols yields superior insight into cellular physiology as compared to classical analysis tools for kinome profiling. PMID:27225531

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.

VIRTUAL LIVER: AN IN SILICO FRAMEWORK FOR ANALYZING CHEMICAL-INDUCED HEPATOTOXICITY

EPA Science Inventory

The US EPA Virtual Liver (v-LiverTM) is an in silico framework for the dose-dependent perturbation of normal hepatic functions by chemicals using in vitro data. The framework consists of a computable knowledge-base (KB) to infer putative pathways in hepatotoxicity and a cellular...

In silico models for development of insect repellents

USDA-ARS?s Scientific Manuscript database

In silico modeling a common term to describe computer-assisted molecular modeling has been used to make remarkable advances in mechanistic drug design and in the discovery of new potential bioactive chemical entities in recent years. The goal of this chapter will be to focus on new, next-generation ...

IN SILICO METHODOLOGIES FOR PREDICTIVE EVALUATION OF TOXICITY BASED ON INTEGRATION OF DATABASES

EPA Science Inventory

In silico methodologies for predictive evaluation of toxicity based on integration of databases

Chihae Yang1 and Ann M. Richard2, 1LeadScope, Inc. 1245 Kinnear Rd. Columbus, OH. 43212 2National Health & Environmental Effects Research Lab, U.S. EPA, Research Triangle Park, ...

Development of a Computational (in silico) Model of Ocular Teratogenesis

EPA Science Inventory

EPA’s ToxCast™ project is profiling the in vitro bioactivity of chemical compounds to assess pathway-level and cell-based signatures that are highly correlated with observed in vivo toxicity. In silico models provide a framework for interpreting the in vitro results and for simul...

Advances in In Vitro and In Silico Tools for Toxicokinetic Dose Modeling and Predictive Toxicology (WC10)

EPA Science Inventory

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 lan...

Lactucaxanthin - a potential anti-diabetic carotenoid from lettuce (Lactuca sativa) inhibits α-amylase and α-glucosidase activity in vitro and in diabetic rats.

PubMed

Gopal, Sowmya Shree; Lakshmi, Magisetty Jhansi; Sharavana, Gurunathan; Sathaiah, Gunaseelan; Sreerama, Yadahally N; Baskaran, Vallikannan

2017-03-22

Intestinal and pancreatic α-amylase and α-glucosidase inhibitors offer an approach to lower the levels of post-prandial hyperglycemia through the control of dietary starch breakdown in digestion. This study hypothesized that lactucaxanthin (Lxn) in lettuce (Lactuca sativa) inhibits the activity of α-amylase and α-glucosidase. In this study, the interaction of Lxn with α-amylase and α-glucosidase in silico and its inhibitory effect on these enzymes were studied using in vitro and STZ-induced diabetic rat models. Lxn was isolated from lettuce with 96% purity confirmed by HPLC and LCMS. The in silico analysis showed that Lxn has a lower binding energy (-6.05 and -6.34 kcal mol -1 ) with α-amylase and α-glucosidase compared to their synthetic inhibitors, acarbose (-0.21 kcal mol -1 ) and miglitol (-2.78 kcal mol -1 ), respectively. In vitro α-amylase and α-glucosidase inhibition assays revealed that Lxn had IC 50 values of 435.5 μg mL -1 and 1.84 mg mL -1 , but acarbose has values of 2.5 and 16.19 μg mL -1 . The in vivo results showed an increased activity for α-amylase and α-glucosidase in the intestine (4.7 and 1.30 fold, p < 0.05) and pancreas (1.3 and 1.48 fold, p < 0.05) of STZ induced diabetic rats compared to normal rats. Whereas the activity decreased (p < 0.05) in the Lxn fed diabetic rats, except for the intestinal α-glucosidase activity (1.69 ± 0.12 PNP per min per mg protein). This was confirmed by the low blood glucose level (239.4 ± 18.2 mg dL -1 ) in diabetic rats fed Lxn compared to the diabetic group (572.2 ± 30.5 mg dL -1 , p < 0.05). Lxn significantly inhibited (p < 0.05) the activity of α-amylase and α-glucosidase and could be of medical and nutritional relevance in the treatment of diabetes.

Leucine/Pd-loaded (5,5) single-walled carbon nanotube matrix as a novel nanobiosensors for in silico detection of protein.

PubMed

Yoosefian, Mehdi; Etminan, Nazanin

2018-06-01

We have designed a novel nanobiosensor for in silico detecting proteins based on leucine/Pd-loaded single-walled carbon nanotube matrix. Density functional theory at the B3LYP/6-31G (d) level of theory was realized to analyze the geometrical and electronic structure of the proposed nanobiosensor. The solvent effects were investigated using the Tomasi's polarized continuum model. Atoms-in-molecules theory was used to study the nature of interactions by calculating the electron density ρ(r) and Laplacian at the bond critical points. Natural bond orbital analysis was performed to achieve a deep understanding of the nature of the interactions. The biosensor has potential application for high sensitive and rapid response to protein due to the chemical adsorption of L-leucine amino acid onto Pd-loaded single-walled carbon nanotube and reactive functional groups that can incorporate in hydrogen binding, hydrophobic interactions and van der Waals forces with the protein surface in detection process.

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

Cloud Infrastructures for In Silico Drug Discovery: Economic and Practical Aspects

PubMed Central

Clematis, Andrea; Quarati, Alfonso; Cesini, Daniele; Milanesi, Luciano; Merelli, Ivan

2013-01-01

Cloud computing opens new perspectives for small-medium biotechnology laboratories that need to perform bioinformatics analysis in a flexible and effective way. This seems particularly true for hybrid clouds that couple the scalability offered by general-purpose public clouds with the greater control and ad hoc customizations supplied by the private ones. A hybrid cloud broker, acting as an intermediary between users and public providers, can support customers in the selection of the most suitable offers, optionally adding the provisioning of dedicated services with higher levels of quality. This paper analyses some economic and practical aspects of exploiting cloud computing in a real research scenario for the in silico drug discovery in terms of requirements, costs, and computational load based on the number of expected users. In particular, our work is aimed at supporting both the researchers and the cloud broker delivering an IaaS cloud infrastructure for biotechnology laboratories exposing different levels of nonfunctional requirements. PMID:24106693

In silico characterization and transcriptomic analysis of nif family genes from Anabaena sp. PCC7120.

PubMed

Singh, Shilpi; Shrivastava, Alok Kumar

2017-10-01

In silico approaches in conjunction with morphology, nitrogenase activity, and qRT-PCR explore the impact of selected abiotic stressor such as arsenic, salt, cadmium, copper, and butachlor on nitrogen fixing (nif family) genes of diazotrophic cyanobacterium Anabaena sp. PCC7120. A total of 19 nif genes are present within the Anabaena genome that is involved in the process of nitrogen fixation. Docking studies revealed the interaction between these nif gene-encoded proteins and the selected abiotic stressors which were further validated through decreased heterocyst frequency, fragmentation of filaments, and downregulation of nitrogenase activity under these stresses indicating towards their toxic impact on nitrogen fixation potential of filamentous cyanobacterium Anabaena sp. PCC7120. Another appealing finding of this study is even though having similar binding energy and similar interacting residues between arsenic/salt and copper/cadmium to nif-encoded proteins, arsenic and cadmium are more toxic than salt and copper for nitrogenase activity of Anabaena which is crucial for growth and yield of rice paddy and soil reclamation.

Java web tools for PCR, in silico PCR, and oligonucleotide assembly and analysis.

PubMed

Kalendar, Ruslan; Lee, David; Schulman, Alan H

2011-08-01

The polymerase chain reaction is fundamental to molecular biology and is the most important practical molecular technique for the research laboratory. We have developed and tested efficient tools for PCR primer and probe design, which also predict oligonucleotide properties based on experimental studies of PCR efficiency. The tools provide comprehensive facilities for designing primers for most PCR applications and their combinations, including standard, multiplex, long-distance, inverse, real-time, unique, group-specific, bisulphite modification assays, Overlap-Extension PCR Multi-Fragment Assembly, as well as a programme to design oligonucleotide sets for long sequence assembly by ligase chain reaction. The in silico PCR primer or probe search includes comprehensive analyses of individual primers and primer pairs. It calculates the melting temperature for standard and degenerate oligonucleotides including LNA and other modifications, provides analyses for a set of primers with prediction of oligonucleotide properties, dimer and G-quadruplex detection, linguistic complexity, and provides a dilution and resuspension calculator. Copyright © 2011 Elsevier Inc. All rights reserved.

The Possible Mechanism of Idiosyncratic Lapatinib-Induced Liver Injury in Patients Carrying Human Leukocyte Antigen-DRB1*07:01

PubMed Central

Hirasawa, Makoto; Hagihara, Katsunobu; Okudaira, Noriko; Izumi, Takashi

2015-01-01

Idiosyncratic lapatinib-induced liver injury has been reported to be associated with human leukocyte antigen (HLA)-DRB1*07:01. In order to investigate its mechanism, interaction of lapatinib with HLA-DRB1*07:01 and its ligand peptide derived from tetanus toxoid, has been evaluated in vitro. Here we show that lapatinib enhances binding of the ligand peptide to HLA-DRB1*07:01. Furthermore in silico molecular dynamics analysis revealed that lapatinib could change the β chain helix in the HLA-DRB1*07:01 specifically to form a tightly closed binding groove structure and modify a large part of the binding groove. These results indicate that lapatinib affects the ligand binding to HLA-DRB1*07:01 and idiosyncratic lapatinib-induced liver injury might be triggered by this mechanism. This is the first report showing that the clinically available drug can enhance the binding of ligand peptide to HLA class II molecules in vitro and in silico. PMID:26098642

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

The challenges of informatics in synthetic biology: from biomolecular networks to artificial organisms

PubMed Central

Ramoni, Marco F.

2010-01-01

The field of synthetic biology holds an inspiring vision for the future; it integrates computational analysis, biological data and the systems engineering paradigm in the design of new biological machines and systems. These biological machines are built from basic biomolecular components analogous to electrical devices, and the information flow among these components requires the augmentation of biological insight with the power of a formal approach to information management. Here we review the informatics challenges in synthetic biology along three dimensions: in silico, in vitro and in vivo. First, we describe state of the art of the in silico support of synthetic biology, from the specific data exchange formats, to the most popular software platforms and algorithms. Next, we cast in vitro synthetic biology in terms of information flow, and discuss genetic fidelity in DNA manipulation, development strategies of biological parts and the regulation of biomolecular networks. Finally, we explore how the engineering chassis can manipulate biological circuitries in vivo to give rise to future artificial organisms. PMID:19906839

‘Candidatus Phytoplasma luffae’, a novel taxon associated with a witches’-broom disease of loofah, Luffa aegyptica Mill

USDA-ARS?s Scientific Manuscript database

The phytoplasma associated with witches’ broom disease of loofah (Luffa aegyptica Mill., syn. L.uffa cylindrica (L.) M.J. Roem.) in Taiwan was classified in group 16SrVIII, subgroup A (16SrVIII-A), based on results from actual and in silico RFLP analysis of 16S rRNA gene sequences. Nucleotide sequ...

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.

In Silico Pattern-Based Analysis of the Human Cytomegalovirus Genome

PubMed Central

Rigoutsos, Isidore; Novotny, Jiri; Huynh, Tien; Chin-Bow, Stephen T.; Parida, Laxmi; Platt, Daniel; Coleman, David; Shenk, Thomas

2003-01-01

More than 200 open reading frames (ORFs) from the human cytomegalovirus genome have been reported as potentially coding for proteins. We have used two pattern-based in silico approaches to analyze this set of putative viral genes. With the help of an objective annotation method that is based on the Bio-Dictionary, a comprehensive collection of amino acid patterns that describes the currently known natural sequence space of proteins, we have reannotated all of the previously reported putative genes of the human cytomegalovirus. Also, with the help of MUSCA, a pattern-based multiple sequence alignment algorithm, we have reexamined the original human cytomegalovirus gene family definitions. Our analysis of the genome shows that many of the coded proteins comprise amino acid combinations that are unique to either the human cytomegalovirus or the larger group of herpesviruses. We have confirmed that a surprisingly large portion of the analyzed ORFs encode membrane proteins, and we have discovered a significant number of previously uncharacterized proteins that are predicted to be G-protein-coupled receptor homologues. The analysis also indicates that many of the encoded proteins undergo posttranslational modifications such as hydroxylation, phosphorylation, and glycosylation. ORFs encoding proteins with similar functional behavior appear in neighboring regions of the human cytomegalovirus genome. All of the results of the present study can be found and interactively explored online (http://cbcsrv.watson.ibm.com/virus/). PMID:12634390

In silico pattern-based analysis of the human cytomegalovirus genome.

PubMed

Rigoutsos, Isidore; Novotny, Jiri; Huynh, Tien; Chin-Bow, Stephen T; Parida, Laxmi; Platt, Daniel; Coleman, David; Shenk, Thomas

2003-04-01

More than 200 open reading frames (ORFs) from the human cytomegalovirus genome have been reported as potentially coding for proteins. We have used two pattern-based in silico approaches to analyze this set of putative viral genes. With the help of an objective annotation method that is based on the Bio-Dictionary, a comprehensive collection of amino acid patterns that describes the currently known natural sequence space of proteins, we have reannotated all of the previously reported putative genes of the human cytomegalovirus. Also, with the help of MUSCA, a pattern-based multiple sequence alignment algorithm, we have reexamined the original human cytomegalovirus gene family definitions. Our analysis of the genome shows that many of the coded proteins comprise amino acid combinations that are unique to either the human cytomegalovirus or the larger group of herpesviruses. We have confirmed that a surprisingly large portion of the analyzed ORFs encode membrane proteins, and we have discovered a significant number of previously uncharacterized proteins that are predicted to be G-protein-coupled receptor homologues. The analysis also indicates that many of the encoded proteins undergo posttranslational modifications such as hydroxylation, phosphorylation, and glycosylation. ORFs encoding proteins with similar functional behavior appear in neighboring regions of the human cytomegalovirus genome. All of the results of the present study can be found and interactively explored online (http://cbcsrv.watson.ibm.com/virus/).

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.

Computational modeling in melanoma for novel drug discovery.

PubMed

Pennisi, Marzio; Russo, Giulia; Di Salvatore, Valentina; Candido, Saverio; Libra, Massimo; Pappalardo, Francesco

2016-06-01

There is a growing body of evidence highlighting the applications of computational modeling in the field of biomedicine. It has recently been applied to the in silico analysis of cancer dynamics. In the era of precision medicine, this analysis may allow the discovery of new molecular targets useful for the design of novel therapies and for overcoming resistance to anticancer drugs. According to its molecular behavior, melanoma represents an interesting tumor model in which computational modeling can be applied. Melanoma is an aggressive tumor of the skin with a poor prognosis for patients with advanced disease as it is resistant to current therapeutic approaches. This review discusses the basics of computational modeling in melanoma drug discovery and development. Discussion includes the in silico discovery of novel molecular drug targets, the optimization of immunotherapies and personalized medicine trials. Mathematical and computational models are gradually being used to help understand biomedical data produced by high-throughput analysis. The use of advanced computer models allowing the simulation of complex biological processes provides hypotheses and supports experimental design. The research in fighting aggressive cancers, such as melanoma, is making great strides. Computational models represent the key component to complement these efforts. Due to the combinatorial complexity of new drug discovery, a systematic approach based only on experimentation is not possible. Computational and mathematical models are necessary for bringing cancer drug discovery into the era of omics, big data and personalized medicine.

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.

In vitro and in silico derived relative effect potencies of ah-receptor-mediated effects by PCDD/Fs and PCBs in rat, mouse, and guinea pig CALUX cell lines.

PubMed

Ghorbanzadeh, Mehdi; van Ede, Karin I; Larsson, Malin; van Duursen, Majorie B M; Poellinger, Lorenz; Lücke-Johansson, Sandra; Machala, Miroslav; Pěnčíková, Kateřina; Vondráček, Jan; van den Berg, Martin; Denison, Michael S; Ringsted, Tine; Andersson, Patrik L

2014-07-21

For a better understanding of species-specific relative effect potencies (REPs), responses of dioxin-like compounds (DLCs) were assessed. REPs were calculated using chemical-activated luciferase gene expression assays (CALUX) derived from guinea pig, rat, and mouse cell lines. Almost all 20 congeners tested in the rodent cell lines were partial agonists and less efficacious than 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). For this reason, REPs were calculated for each congener using concentrations at which 20% of the maximal TCDD response was reached (REP20TCDD). REP20TCDD values obtained for PCDD/Fs were comparable with their toxic equivalency factors assigned by the World Health Organization (WHO-TEF), while those for PCBs were in general lower than the WHO-TEF values. Moreover, the guinea pig cell line was the most sensitive as indicated by the 20% effect concentrations of TCDD of 1.5, 5.6, and 11.0 pM for guinea pig, rat, and mouse cells, respectively. A similar response pattern was observed using multivariate statistical analysis between the three CALUX assays and the WHO-TEFs. The mouse assay showed minor deviation due to higher relative induction potential for 2,3,7,8-tetrachlorodibenzofuran and 2,3,4,6,7,8-hexachlorodibenzofuran and lower for 1,2,3,4,6,7,8-heptachlorodibenzofuran and 3,3',4,4',5-pentachlorobiphenyl (PCB126). 2,3,7,8-Tetrachlorodibenzofuran was more than two times more potent in the mouse assay as compared with that of rat and guinea pig cells, while measured REP20TCDD for PCB126 was lower in mouse cells (0.05) as compared with that of the guinea pig (0.2) and rat (0.07). In order to provide REP20TCDD values for all WHO-TEF assigned compounds, quantitative structure-activity relationship (QSAR) models were developed. The QSAR models showed that specific electronic properties and molecular surface characteristics play important roles in the AhR-mediated response. In silico derived REP20TCDD values were generally consistent with the WHO-TEFs with a few exceptions. The QSAR models indicated that, e.g., 1,2,3,7,8-pentachlorodibenzofuran and 1,2,3,7,8,9-hexachlorodibenzofuran were more potent than given by their assigned WHO-TEF values, and the non-ortho PCB 81 was predicted, based on the guinea-pig model, to be 1 order of magnitude above its WHO-TEF value. By combining in vitro and in silico approaches, REPs were established for all WHO-TEF assigned compounds (except OCDD), which will provide future guidance in testing AhR-mediated responses of DLCs and to increase our understanding of species variation in AhR-mediated effects.

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 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.

Computational Analysis of the Ligand Binding Site of the Extracellular ATP Receptor, DORN1

DOE PAGES

Nguyen, Cuong The; Tanaka, Kiwamu; Cao, Yangrong; ...

2016-09-01

DORN1 (also known as P2K1) is a plant receptor for extracellular ATP, which belongs to a large gene family of legume-type (L-type) lectin receptor kinases. Extracellular ATP binds to DORN1 with strong affinity through its lectin domain, and the binding triggers a variety of intracellular activities in response to biotic and abiotic stresses. However, information on the tertiary structure of the ligand binding site of DORN1is lacking, which hampers efforts to fully elucidate the mechanism of receptor action. Available data of the crystal structures from more than 50 L-type lectins enable us to perform an in silico study of molecularmore » interaction between DORN1 and ATP. In this study, we employed a computational approach to develop a tertiary structure model of the DORN1 lectin domain. A blind docking analysis demonstrated that ATP binds to a cavity made by four loops (defined as loops A B, C and D) of the DORN1 lectin domain with high affinity. In silico target docking of ATP to the DORN1 binding site predicted interaction with 12 residues, located on the four loops, via hydrogen bonds and hydrophobic interactions. The ATP binding pocket is structurally similar in location to the carbohydrate binding pocket of the canonical L-type lectins. However, four of the residues predicted to interact with ATP are not conserved between DORN1 and the other carbohydrate-binding lectins, suggesting that diversifying selection acting on these key residues may have led to the ATP binding activity of DORN1. Finally, the in silico model was validated by in vitro ATP binding assays using the purified extracellular lectin domain of wild-type DORN1, as well as mutated DORN1 lacking key ATP binding residues.« less

Computational Analysis of the Ligand Binding Site of the Extracellular ATP Receptor, DORN1

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

Nguyen, Cuong The; Tanaka, Kiwamu; Cao, Yangrong

DORN1 (also known as P2K1) is a plant receptor for extracellular ATP, which belongs to a large gene family of legume-type (L-type) lectin receptor kinases. Extracellular ATP binds to DORN1 with strong affinity through its lectin domain, and the binding triggers a variety of intracellular activities in response to biotic and abiotic stresses. However, information on the tertiary structure of the ligand binding site of DORN1is lacking, which hampers efforts to fully elucidate the mechanism of receptor action. Available data of the crystal structures from more than 50 L-type lectins enable us to perform an in silico study of molecularmore » interaction between DORN1 and ATP. In this study, we employed a computational approach to develop a tertiary structure model of the DORN1 lectin domain. A blind docking analysis demonstrated that ATP binds to a cavity made by four loops (defined as loops A B, C and D) of the DORN1 lectin domain with high affinity. In silico target docking of ATP to the DORN1 binding site predicted interaction with 12 residues, located on the four loops, via hydrogen bonds and hydrophobic interactions. The ATP binding pocket is structurally similar in location to the carbohydrate binding pocket of the canonical L-type lectins. However, four of the residues predicted to interact with ATP are not conserved between DORN1 and the other carbohydrate-binding lectins, suggesting that diversifying selection acting on these key residues may have led to the ATP binding activity of DORN1. Finally, the in silico model was validated by in vitro ATP binding assays using the purified extracellular lectin domain of wild-type DORN1, as well as mutated DORN1 lacking key ATP binding residues.« less

In silico modelling of radiation effects towards personalised treatment in radiotherapy

NASA Astrophysics Data System (ADS)

Marcu, Loredana G.; Marcu, David

2017-12-01

In silico models applied in medical physics are valuable tools to assist in treatment optimization and personalization, which represent the ultimate goal of today's radiotherapy. Next to several biological and biophysical factors that influence tumour response to ionizing radiation, hypoxia and cancer stem cells are critical parameters that dictate the final outcome. The current work presents the results of an in silico model of tumour growth and response to radiation developed using Monte Carlo techniques. We are presenting the impact of partial oxygen tension and repopulation via cancer stem cells on tumour control after photon irradiation, highlighting some of the gaps that clinical research needs to fill for better customized treatment.

TSCAN: Pseudo-time reconstruction and evaluation in single-cell RNA-seq analysis

PubMed Central

Ji, Zhicheng; Ji, Hongkai

2016-01-01

When analyzing single-cell RNA-seq data, constructing a pseudo-temporal path to order cells based on the gradual transition of their transcriptomes is a useful way to study gene expression dynamics in a heterogeneous cell population. Currently, a limited number of computational tools are available for this task, and quantitative methods for comparing different tools are lacking. Tools for Single Cell Analysis (TSCAN) is a software tool developed to better support in silico pseudo-Time reconstruction in Single-Cell RNA-seq ANalysis. TSCAN uses a cluster-based minimum spanning tree (MST) approach to order cells. Cells are first grouped into clusters and an MST is then constructed to connect cluster centers. Pseudo-time is obtained by projecting each cell onto the tree, and the ordered sequence of cells can be used to study dynamic changes of gene expression along the pseudo-time. Clustering cells before MST construction reduces the complexity of the tree space. This often leads to improved cell ordering. It also allows users to conveniently adjust the ordering based on prior knowledge. TSCAN has a graphical user interface (GUI) to support data visualization and user interaction. Furthermore, quantitative measures are developed to objectively evaluate and compare different pseudo-time reconstruction methods. TSCAN is available at https://github.com/zji90/TSCAN and as a Bioconductor package. PMID:27179027

Comparative genome analysis of Alkhumra hemorrhagic fever virus with Kyasanur forest disease and tick-borne encephalitis viruses by the in silico approach.

PubMed

Palanisamy, Navaneethan; Akaberi, Dario; Lennerstrand, Johan; Lundkvist, Åke

2018-05-10

Alkhumra hemorrhagic fever virus (AHFV), a relatively new member of the Flaviviruses, was discovered in Saudi Arabia 23 years ago. AHFV is classified in the tick-borne encephalitis virus serocomplex, along with the Kyasanur forest disease virus (KFDV) and tick-borne encephalitis virus (TBEV). Currently, very little is known about the pathologies of AHFV. In this study, using the available genome information of AHFV, KFDV and TBEV, we have predicted and compared the following aspects of these viruses: evolution, nucleotide and protein compositions, recombination, codon frequency, substitution rate, N- and O-glycosylation sites, signal peptide and cleavage site, transmembrane region, secondary structure of 5' and 3' UTRs and RNA-RNA interactions. Additionally, we have modeled the 3D protease and RNA-dependent RNA polymerase structures for AHFV, KFDV and TBEV. Recombination analysis showed no evidence of recombination in the AHFV genome with that of either KFDV or TBEV, although single break point analysis showed that nucleotide position 7399 (in the NS4B) is a breakpoint location. AHFV, KFDV and TBEV are very similar in terms of codon frequency, the number of transmembrane regions, properties of the polyprotein, RNA-RNA interaction sequences, NS3 protease and NS5 polymerase structures and 5' UTR structure. Using genome sequences, we showed the similarities between these closely- related viruses on several different areas.

TSCAN: Pseudo-time reconstruction and evaluation in single-cell RNA-seq analysis.

PubMed

Ji, Zhicheng; Ji, Hongkai

2016-07-27

When analyzing single-cell RNA-seq data, constructing a pseudo-temporal path to order cells based on the gradual transition of their transcriptomes is a useful way to study gene expression dynamics in a heterogeneous cell population. Currently, a limited number of computational tools are available for this task, and quantitative methods for comparing different tools are lacking. Tools for Single Cell Analysis (TSCAN) is a software tool developed to better support in silico pseudo-Time reconstruction in Single-Cell RNA-seq ANalysis. TSCAN uses a cluster-based minimum spanning tree (MST) approach to order cells. Cells are first grouped into clusters and an MST is then constructed to connect cluster centers. Pseudo-time is obtained by projecting each cell onto the tree, and the ordered sequence of cells can be used to study dynamic changes of gene expression along the pseudo-time. Clustering cells before MST construction reduces the complexity of the tree space. This often leads to improved cell ordering. It also allows users to conveniently adjust the ordering based on prior knowledge. TSCAN has a graphical user interface (GUI) to support data visualization and user interaction. Furthermore, quantitative measures are developed to objectively evaluate and compare different pseudo-time reconstruction methods. TSCAN is available at https://github.com/zji90/TSCAN and as a Bioconductor package. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

PubMed

Pandi, Narayanan Sathiya; Suganya, Sivagurunathan; Rajendran, Suriliyandi

2013-10-04

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, 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. Copyright © 2013 Elsevier Inc. All rights reserved.

Robustness of atomistic Gō models in predicting native-like folding intermediates

NASA Astrophysics Data System (ADS)

Estácio, S. G.; Fernandes, C. S.; Krobath, H.; Faísca, P. F. N.; Shakhnovich, E. I.

2012-08-01

Gō models are exceedingly popular tools in computer simulations of protein folding. These models are native-centric, i.e., they are directly constructed from the protein's native structure. Therefore, it is important to understand up to which extent the atomistic details of the native structure dictate the folding behavior exhibited by Gō models. Here we address this challenge by performing exhaustive discrete molecular dynamics simulations of a Gō potential combined with a full atomistic protein representation. In particular, we investigate the robustness of this particular type of Gō models in predicting the existence of intermediate states in protein folding. We focus on the N47G mutational form of the Spc-SH3 folding domain (x-ray structure) and compare its folding pathway with that of alternative native structures produced in silico. Our methodological strategy comprises equilibrium folding simulations, structural clustering, and principal component analysis.

Effect of neohesperidin dihydrochalcone on the activity and stability of alpha-amylase: a comparative study on bacterial, fungal, and mammalian enzymes.

PubMed

Kashani-Amin, Elaheh; Ebrahim-Habibi, Azadeh; Larijani, Bagher; Moosavi-Movahedi, Ali Akbar

2015-10-01

Neohesperidin dihydrochalcone (NHDC) was recently introduced as an activator of mammalian alpha-amylase. In the current study, the effect of NHDC has been investigated on bacterial and fungal alpha-amylases. Enzyme assays and kinetic analysis demonstrated the capability of NHDC to significantly activate both tested alpha-amylases. The ligand activation pattern was found to be more similar between the fungal and mammalian enzyme in comparison with the bacterial one. Further, thermostability experiments indicated a stability increase in the presence of NHDC for the bacterial enzyme. In silico (docking) test locates a putative binding site for NHDC on alpha-amylase surface in domain B. This domain shows differences in various alpha-amylase types, and the different behavior of the ligand toward the studied enzymes may be attributed to this fact. Copyright © 2015 John Wiley & Sons, Ltd.

Synthesis and in silico studies of novel sulfonamides having oxadiazole ring: As β-glucuronidase inhibitors.

PubMed

Taha, Muhammad; Baharudin, Mohd Syukri; Ismail, Nor Hadiani; Selvaraj, Manikandan; Salar, Uzma; Alkadi, Khaled A A; Khan, Khalid Mohammed

2017-04-01

Novel sulfonamides having oxadiazole ring were synthesized by multistep reaction and evaluated to check in vitro β-glucuronidase inhibitory activity. Luckily, except compound 13, all compounds were found to demonstrate good inhibitory activity in the range of IC 50 =2.40±0.01-58.06±1.60μM when compared to the standard d-saccharic acid 1,4-lactone (IC 50 =48.4±1.25μM). Structure activity relationship was also presented. However, in order to ensure the SAR as well as the molecular interactions of compounds with the active site of enzyme, molecular docking studies on most active compounds 19, 16, 4 and 6 was carried out. All derivatives were fully characterized by 1 H NMR, 13 C NMR and EI-MS spectroscopic techniques. CHN analysis was also presented. Copyright © 2017 Elsevier Inc. All rights reserved.

Regulation of transcriptional activators by DNA-binding domain ubiquitination

PubMed Central

Landré, Vivien; Revi, Bhindu; Mir, Maria Gil; Verma, Chandra; Hupp, Ted R; Gilbert, Nick; Ball, Kathryn L

2017-01-01

Ubiquitin is a key component of the regulatory network that maintains gene expression in eukaryotes, yet the molecular mechanism(s) by which non-degradative ubiquitination modulates transcriptional activator (TA) function is unknown. Here endogenous p53, a stress-activated transcription factor required to maintain health, is stably monoubiquitinated, following pathway activation by IR or Nutlin-3 and localized to the nucleus where it becomes tightly associated with chromatin. Comparative structure–function analysis and in silico modelling demonstrate a direct role for DNA-binding domain (DBD) monoubiquitination in TA activation. When attached to the DBD of either p53, or a second TA IRF-1, ubiquitin is orientated towards, and makes contact with, the DNA. The contact is made between a predominantly cationic surface on ubiquitin and the anionic DNA. Our data demonstrate an unexpected role for ubiquitin in the mechanism of TA-activity enhancement and provides insight into a new level of transcriptional regulation. PMID:28362432

Synthesis, anti-inflammatory evaluation in vivo and docking studies of some new 5-(benzo[b]furan-2-ylmethyl)-6-methyl-pyridazin-3(2H)-one derivatives

NASA Astrophysics Data System (ADS)

Boukharsa, Youness; Lakhlili, Wiame; El harti, Jaouad; Meddah, Bouchra; Tiendrebeogo, Ramata Yvette; Taoufik, Jamal; El Abbes Faouzi, My; Ibrahimi, Azeddine; Ansar, M'hammed

2018-02-01

Seven novel 5-(benzo[b]furan-2-ylmethyl)-6-methyl-pyridazin-3(2H)-one derivatives (6a to 6g) have been synthesized by the condensation of appropriate 3-(benzofuran-2-ylmethylene)-4-oxopentanoic acid and hydrazine hydrate in ethanol. Structures of all compounds were elucidated by elemental analysis, IR, 1H NMR and 13C NMR. These compounds were tested for their anti-inflammatory activity in carrageenan-induced rat paw edema model. In silico molecular docking study has been executed to study the binding interactions of the synthesized compounds with COX-2 protein. Compounds 6a, 6b, 6e and 6g showed a good anti-inflammatory activity at 50 mg/kg compared with the indometacin at 10 mg/kg and the aspirin at 150 mg/kg and good binding affinity with COX-2.

An in silico approach helped to identify the best experimental design, population, and outcome for future randomized clinical trials.

PubMed

Bajard, Agathe; Chabaud, Sylvie; Cornu, Catherine; Castellan, Anne-Charlotte; Malik, Salma; Kurbatova, Polina; Volpert, Vitaly; Eymard, Nathalie; Kassai, Behrouz; Nony, Patrice

2016-01-01

The main objective of our work was to compare different randomized clinical trial (RCT) experimental designs in terms of power, accuracy of the estimation of treatment effect, and number of patients receiving active treatment using in silico simulations. A virtual population of patients was simulated and randomized in potential clinical trials. Treatment effect was modeled using a dose-effect relation for quantitative or qualitative outcomes. Different experimental designs were considered, and performances between designs were compared. One thousand clinical trials were simulated for each design based on an example of modeled disease. According to simulation results, the number of patients needed to reach 80% power was 50 for crossover, 60 for parallel or randomized withdrawal, 65 for drop the loser (DL), and 70 for early escape or play the winner (PW). For a given sample size, each design had its own advantage: low duration (parallel, early escape), high statistical power and precision (crossover), and higher number of patients receiving the active treatment (PW and DL). Our approach can help to identify the best experimental design, population, and outcome for future RCTs. This may be particularly useful for drug development in rare diseases, theragnostic approaches, or personalized medicine. Copyright © 2016 Elsevier Inc. All rights reserved.

Preliminary safety assessment of C-8 xylitol monoester and xylitol phosphate esters.

PubMed

Silveira, J E P S; Pereda, M C V; Nogueira, C; Dieamant, G; Cesar, C K M; Assanome, K M; Silva, M S; Torello, C O; Queiroz, M L S; Eberlin, S

2016-02-01

Most of the cosmetic compounds with preservative properties available in the market pose some risks concerning safety, such as the possibility of causing sensitization. Due to the fact that there are few options, the proper development of new molecules with this purpose is needed. Xylitol is a natural sugar, and the antimicrobial properties of xylitol-derived compounds have already been described in the literature. C-8 xylitol monoester and xylitol phosphate esters may be useful for the development of skincare products. As an initial screen for safety of chemicals, the combination of in silico methods and in vitro testing can aid in prioritizing resources in toxicological investigations while reducing the ethical and monetary costs that are related to animal and human testing. This study was designed to evaluate the safety of C-8 xylitol monoester and xylitol phosphate esters regarding carcinogenicity, mutagenicity, skin and eye irritation/corrosion and sensitization through alternative methods. For the initial safety assessment, quantitative structure-activity relationship methodology was used. The prediction of the parameters carcinogenicity/mutagenicity, skin and eye irritation/corrosion and sensitization was generated from the chemical structure. The analysis also comprised physical-chemical properties, Cramer rules, threshold of toxicological concern and Michael reaction. In silico results of candidate molecules were compared to 19 compounds with preservative properties that are available in the market. Additionally, in vitro tests (Ames test for mutagenicity, cytotoxicity and phototoxicity tests and hen's egg test--chorioallantoic membrane for irritation) were performed to complement the evaluation. In silico evaluation of both molecules presented no structural alerts related to eye and skin irritation, corrosion and sensitization, but some alerts for micronucleus and carcinogenicity were detected. However, by comparison, C-8 xylitol monoester, xylitol phosphate esters showed similar or better results than the compounds available in the market. Concerning experimental data, phototoxicity and mutagenicity results were negative. As expected for compounds with preservative activity, xylitol-derived substances presented positive result in cytotoxicity test. In hen's egg test, both molecules were irritants. Our results suggested that xylitol-derived compounds appear to be suitable candidates for preservative systems in cosmetics. © 2015 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

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.

Predicting dermal penetration for ToxCast chemicals using in silico estimates for diffusion in combination with physiologically based pharmacokinetic (PBPK) modeling.

EPA Science Inventory

Predicting dermal penetration for ToxCast chemicals using in silico estimates for diffusion in combination with physiologically based pharmacokinetic (PBPK) modeling.Evans, M.V., Sawyer, M.E., Isaacs, K.K, and Wambaugh, J.With the development of efficient high-throughput (HT) in ...

IN SILICO APPROACHES TO MECHANISTIC AND PREDICTIVE TOXICOLOGY: AN INTRODUCTION TO BIOINFORMATICS FOR TOXICOLOGISTS. (R827402)

EPA Science Inventory

Abstract

Bioinformatics, or in silico biology, is a rapidly growing field that encompasses the theory and application of computational approaches to model, predict, and explain biological function at the molecular level. This information rich field requires new ...

In silico design and screening of hypothetical MOF-74 analogs and their experimental synthesis

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

Witman, Matthew; Ling, Sanliang; Anderson, Samantha

2016-01-01

We present thein silico designof MOFs exhibiting 1-dimensional rod topologies by enumerating MOF-74-type analogs based on the PubChem Compounds database. We simulate the adsorption behavior of CO 2in the generated analogs and experimentally validate a novel MOF-74 analog, Mg 2(olsalazine).

Large Dataset of Acute Oral Toxicity Data Created for Testing in Silico Models (ASCCT meeting)

EPA Science Inventory

Acute toxicity data is a common requirement for substance registration in the US. Currently only data derived from animal tests are accepted by regulatory agencies, and the standard in vivo tests use lethality as the endpoint. Non-animal alternatives such as in silico models are ...

Structure-function studies of BPP-BrachyNH2 and synthetic analogues thereof with Angiotensin I-Converting Enzyme.

PubMed

Arcanjo, Daniel D R; Vasconcelos, Andreanne G; Nascimento, Lucas A; Mafud, Ana Carolina; Plácido, Alexandra; Alves, Michel M M; Delerue-Matos, Cristina; Bemquerer, Marcelo P; Vale, Nuno; Gomes, Paula; Oliveira, Eduardo B; Lima, Francisco C A; Mascarenhas, Yvonne P; Carvalho, Fernando Aécio A; Simonsen, Ulf; Ramos, Ricardo M; Leite, José Roberto S A

2017-10-20

The vasoactive proline-rich oligopeptide termed BPP-BrachyNH 2 (H-WPPPKVSP-NH 2 ) induces in vitro inhibitory activity of angiotensin I-converting enzyme (ACE) in rat blood serum. In the present study, the removal of N-terminal tryptophan or C-terminal proline from BPP-BrachyNH 2 was investigated in order to predict which structural components are important or required for interaction with ACE. Furthermore, the toxicological profile was assessed by in silico prediction and in vitro MTT assay. Two BPP-BrachyNH 2 analogues (des-Trp 1 -BPP-BrachyNH 2 and des-Pro 8 -BPP-BrachyNH 2 ) were synthesized, and in vitro and in silico ACE inhibitory activity and toxicological profile were assessed. The des-Trp 1 -BPP-BrachyNH 2 and des-Pro 8 -BPP-BrachyNH 2 were respectively 3.2- and 29.5-fold less active than the BPP-BrachyNH 2 -induced ACE inhibitory activity. Molecular Dynamic and Molecular Mechanics Poisson-Boltzmann Surface Area simulations (MM-PBSA) demonstrated that the ACE/BBP-BrachyNH 2 complex showed lower binding and van der Wall energies than the ACE/des-Pro 8 -BPP-BrachyNH 2 complex, therefore having better stability. The removal of the N-terminal tryptophan increased the in silico predicted toxicological effects and cytotoxicity when compared with BPP-BrachyNH 2 or des-Pro 8 -BPP-BrachyNH 2 . Otherwise, des-Pro 8 -BPP-BrachyNH 2 was 190-fold less cytotoxic than BPP-BrachyNH 2 . Thus, the removal of C-terminal proline residue was able to markedly decrease both the BPP-BrachyNH 2 -induced ACE inhibitory and cytotoxic effects assessed by in vitro and in silico approaches. In conclusion, the aminoacid sequence of BPP-BrachyNH 2 is essential for its ACE inhibitory activity and associated with an acceptable toxicological profile. The perspective of the interactions of BPP-BrachyNH 2 with ACE found in the present study can be used for development of drugs with differential therapeutic profile than current ACE inhibitors. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

In silico identification and comparative analysis of differentially expressed genes in human and mouse tissues

PubMed Central

Pao, Sheng-Ying; Lin, Win-Li; Hwang, Ming-Jing

2006-01-01

Background Screening for differentially expressed genes on the genomic scale and comparative analysis of the expression profiles of orthologous genes between species to study gene function and regulation are becoming increasingly feasible. Expressed sequence tags (ESTs) are an excellent source of data for such studies using bioinformatic approaches because of the rich libraries and tremendous amount of data now available in the public domain. However, any large-scale EST-based bioinformatics analysis must deal with the heterogeneous, and often ambiguous, tissue and organ terms used to describe EST libraries. Results To deal with the issue of tissue source, in this work, we carefully screened and organized more than 8 million human and mouse ESTs into 157 human and 108 mouse tissue/organ categories, to which we applied an established statistic test using different thresholds of the p value to identify genes differentially expressed in different tissues. Further analysis of the tissue distribution and level of expression of human and mouse orthologous genes showed that tissue-specific orthologs tended to have more similar expression patterns than those lacking significant tissue specificity. On the other hand, a number of orthologs were found to have significant disparity in their expression profiles, hinting at novel functions, divergent regulation, or new ortholog relationships. Conclusion Comprehensive statistics on the tissue-specific expression of human and mouse genes were obtained in this very large-scale, EST-based analysis. These statistical results have been organized into a database, freely accessible at our website , for easy searching of human and mouse tissue-specific genes and for investigating gene expression profiles in the context of comparative genomics. Comparative analysis showed that, although highly tissue-specific genes tend to exhibit similar expression profiles in human and mouse, there are significant exceptions, indicating that orthologous genes, while sharing basic genomic properties, could result in distinct phenotypes. PMID:16626500

In Silico Investigations of the Anti-Catabolic Effects of Pamidronate and Denosumab on Multiple Myeloma-Induced Bone Disease

PubMed Central

Wang, Yan; Lin, Bo

2012-01-01

It is unclear whether the new anti-catabolic agent denosumab represents a viable alternative to the widely used anti-catabolic agent pamidronate in the treatment of Multiple Myeloma (MM)-induced bone disease. This lack of clarity primarily stems from the lack of sufficient clinical investigations, which are costly and time consuming. However, in silico investigations require less time and expense, suggesting that they may be a useful complement to traditional clinical investigations. In this paper, we aim to (i) develop integrated computational models that are suitable for investigating the effects of pamidronate and denosumab on MM-induced bone disease and (ii) evaluate the responses to pamidronate and denosumab treatments using these integrated models. To achieve these goals, pharmacokinetic models of pamidronate and denosumab are first developed and then calibrated and validated using different clinical datasets. Next, the integrated computational models are developed by incorporating the simulated transient concentrations of pamidronate and denosumab and simulations of their actions on the MM-bone compartment into the previously proposed MM-bone model. These integrated models are further calibrated and validated by different clinical datasets so that they are suitable to be applied to investigate the responses to the pamidronate and denosumab treatments. Finally, these responses are evaluated by quantifying the bone volume, bone turnover, and MM-cell density. This evaluation identifies four denosumab regimes that potentially produce an overall improved bone-related response compared with the recommended pamidronate regime. This in silico investigation supports the idea that denosumab represents an appropriate alternative to pamidronate in the treatment of MM-induced bone disease. PMID:23028650

Screening for single nucleotide variants, small indels and exon deletions with a next-generation sequencing based gene panel approach for Usher syndrome

PubMed Central

Krawitz, Peter M; Schiska, Daniela; Krüger, Ulrike; Appelt, Sandra; Heinrich, Verena; Parkhomchuk, Dmitri; Timmermann, Bernd; Millan, Jose M; Robinson, Peter N; Mundlos, Stefan; Hecht, Jochen; Gross, Manfred

2014-01-01

Usher syndrome is an autosomal recessive disorder characterized both by deafness and blindness. For the three clinical subtypes of Usher syndrome causal mutations in altogether 12 genes and a modifier gene have been identified. Due to the genetic heterogeneity of Usher syndrome, the molecular analysis is predestined for a comprehensive and parallelized analysis of all known genes by next-generation sequencing (NGS) approaches. We describe here the targeted enrichment and deep sequencing for exons of Usher genes and compare the costs and workload of this approach compared to Sanger sequencing. We also present a bioinformatics analysis pipeline that allows us to detect single-nucleotide variants, short insertions and deletions, as well as copy number variations of one or more exons on the same sequence data. Additionally, we present a flexible in silico gene panel for the analysis of sequence variants, in which newly identified genes can easily be included. We applied this approach to a cohort of 44 Usher patients and detected biallelic pathogenic mutations in 35 individuals and monoallelic mutations in eight individuals of our cohort. Thirty-nine of the sequence variants, including two heterozygous deletions comprising several exons of USH2A, have not been reported so far. Our NGS-based approach allowed us to assess single-nucleotide variants, small indels, and whole exon deletions in a single test. The described diagnostic approach is fast and cost-effective with a high molecular diagnostic yield. PMID:25333064

Screening for single nucleotide variants, small indels and exon deletions with a next-generation sequencing based gene panel approach for Usher syndrome.

PubMed

Krawitz, Peter M; Schiska, Daniela; Krüger, Ulrike; Appelt, Sandra; Heinrich, Verena; Parkhomchuk, Dmitri; Timmermann, Bernd; Millan, Jose M; Robinson, Peter N; Mundlos, Stefan; Hecht, Jochen; Gross, Manfred

2014-09-01

Usher syndrome is an autosomal recessive disorder characterized both by deafness and blindness. For the three clinical subtypes of Usher syndrome causal mutations in altogether 12 genes and a modifier gene have been identified. Due to the genetic heterogeneity of Usher syndrome, the molecular analysis is predestined for a comprehensive and parallelized analysis of all known genes by next-generation sequencing (NGS) approaches. We describe here the targeted enrichment and deep sequencing for exons of Usher genes and compare the costs and workload of this approach compared to Sanger sequencing. We also present a bioinformatics analysis pipeline that allows us to detect single-nucleotide variants, short insertions and deletions, as well as copy number variations of one or more exons on the same sequence data. Additionally, we present a flexible in silico gene panel for the analysis of sequence variants, in which newly identified genes can easily be included. We applied this approach to a cohort of 44 Usher patients and detected biallelic pathogenic mutations in 35 individuals and monoallelic mutations in eight individuals of our cohort. Thirty-nine of the sequence variants, including two heterozygous deletions comprising several exons of USH2A, have not been reported so far. Our NGS-based approach allowed us to assess single-nucleotide variants, small indels, and whole exon deletions in a single test. The described diagnostic approach is fast and cost-effective with a high molecular diagnostic yield.

In-silico and in-vitro anti-cancer potential of a curcumin analogue (1E, 6E)-1, 7-di (1H-indol-3-yl) hepta-1, 6-diene-3, 5-dione.

PubMed

Sufi, Shamim Akhtar; Adigopula, Lakshmi Narayana; Syed, Safiulla Basha; Mukherjee, Victor; Coumar, Mohane S; Rao, H Surya Prakash; Rajagopalan, Rukkumani

2017-01-01

Previously we showed that BDMC, an analogue of curcumin suppresses growth of human breast and laryngeal cancer cell line by causing apoptosis. Here, we demonstrate the enhanced anti-cancer activity of a heterocyclic ring (indole) incorporated curcumin analogue ((1E, 6E)-1, 7-di (1H-indol-3-yl) hepta-1, 6-diene-3, 5-Dione), ICA in short, in comparison to curcumin. ICA was synthesized by a one pot condensation reaction. Anti-cancer potential of ICA was assessed in three human cancer cell lines of different origin (Lung adenocarcinoma (A549), leukemia (K562) and colon cancer (SW480)) by MTT assay. Mode of cell death was determined by acridine orange-ethidium bromide (Ao-Eb) staining. Putative cellular targets of ICA were investigated by molecular docking studies. Cell cycle analysis following curcumin or ICA treatment in SW480 cell line was carried out by flow cytometry. Expression levels of Cyclin D1 and apoptotic markers, such as Caspase 3, 8 and 9 were studied by western blot analysis in SW480 cell line treated with or without ICA and curcumin. The yield of ICA synthesis was found to be 69% with a purity of 98%. ICA demonstrated promising anti-cancer activity compared to curcumin alone, as discerned by MTT assay. ICA was non-toxic to the cell line of normal origin. We further observed that ICA is ∼2 fold more potent than curcumin in inhibiting the growth of SW480 cells. Ao-Eb staining revealed that ICA could induce apoptosis in all the cell lines tested. Molecular docking studies suggest that ICA may possibly exhibit its anticancer effect by inhibiting EGFR in A549, Bcr-Abl in K562 and GSK-3β kinase in SW480 cell line. Moreover, ICA showed strong binding avidity for Bcl-2 protein in silico, which could result in induction of apoptosis. Cell cycle analysis revealed that both curcumin and ICA induced concomitant cell cycle arrest at G0/G1 and G2/M phase. Western blot shows that ICA could effectively down regulate the expression of cell cycle protein cyclin D1, while promoting the activation of Caspase 3, 8 and 9 when compared to curcumin in human colon cancer cell line SW480. The result of this study indicates that ICA could hold promise to be a potential anti-cancer agent. Since ICA has shown encouraging results in terms of its anti-cancer activity compared to curcumin, further research is necessary to fully delineate the underlying molecular mechanism of its anticancer potential. Copyright © 2016 Elsevier Masson SAS. 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.

Novel proteases from the genome of the carnivorous plant Drosera capensis: structural prediction and comparative analysis

PubMed Central

Butts, Carter T.; Bierma, Jan C.; Martin, Rachel W.

2016-01-01

In his 1875 monograph on insectivorous plants, Darwin described the feeding reactions of Drosera flypaper traps and predicted that their secretions contained a “ferment” similar to mammalian pepsin, an aspartic protease. Here we report a high-quality draft genome sequence for the cape sundew, Drosera capensis, the first genome of a carnivorous plant from order Caryophyllales, which also includes the Venus flytrap (Dionaea) and the tropical pitcher plants (Nepenthes). This species was selected in part for its hardiness and ease of cultivation, making it an excellent model organism for further investigations of plant carnivory. Analysis of predicted protein sequences yields genes encoding proteases homologous to those found in other plants, some of which display sequence and structural features that suggest novel functionalities. Because the sequence similarity to proteins of known structure is in most cases too low for traditional homology modeling, 3D structures of representative proteases are predicted using comparative modeling with all-atom refinement. Although the overall folds and active residues for these proteins are conserved, we find structural and sequence differences consistent with a diversity of substrate recognition patterns. Finally, we predict differences in substrate specificities using in silico experiments, providing targets for structure/function studies of novel enzymes with biological and technological significance. PMID:27353064

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.

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

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

The in silico screening and X-ray structure analysis of the inhibitor complex of Plasmodium falciparum orotidine 5'-monophosphate decarboxylase.

PubMed

Takashima, Yasuhide; Mizohata, Eiichi; Krungkrai, Sudaratana R; Fukunishi, Yoshifumi; Kinoshita, Takayoshi; Sakata, Tsuneaki; Matsumura, Hiroyoshi; Krungkrai, Jerapan; Horii, Toshihiro; Inoue, Tsuyoshi

2012-08-01

Orotidine 5'-monophosphate decarboxylase from Plasmodium falciparum (PfOMPDC) catalyses the final step in the de novo synthesis of uridine 5'-monophosphate (UMP) from orotidine 5'-monophosphate (OMP). A defective PfOMPDC enzyme is lethal to the parasite. Novel in silico screening methods were performed to select 14 inhibitors against PfOMPDC, with a high hit rate of 9%. X-ray structure analysis of PfOMPDC in complex with one of the inhibitors, 4-(2-hydroxy-4-methoxyphenyl)-4-oxobutanoic acid, was carried out to at 2.1 Å resolution. The crystal structure revealed that the inhibitor molecule occupied a part of the active site that overlaps with the phosphate-binding region in the OMP- or UMP-bound complexes. Space occupied by the pyrimidine and ribose rings of OMP or UMP was not occupied by this inhibitor. The carboxyl group of the inhibitor caused a dramatic movement of the L1 and L2 loops that play a role in the recognition of the substrate and product molecules. Combining part of the inhibitor molecule with moieties of the pyrimidine and ribose rings of OMP and UMP represents a suitable avenue for further development of anti-malarial drugs.

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.

Exploring the immune signalling pathway-related genes of the cattle tick Rhipicephalus microplus: From molecular characterization to transcriptional profile upon microbial challenge.

PubMed

Rosa, Rafael D; Capelli-Peixoto, Janaína; Mesquita, Rafael D; Kalil, Sandra P; Pohl, Paula C; Braz, Glória R; Fogaça, Andrea C; Daffre, Sirlei

2016-06-01

In dipteran insects, invading pathogens are selectively recognized by four major pathways, namely Toll, IMD, JNK, and JAK/STAT, and trigger the activation of several immune effectors. Although substantial advances have been made in understanding the immunity of model insects such as Drosophila melanogaster, knowledge on the activation of immune responses in other arthropods such as ticks remains limited. Herein, we have deepened our understanding of the intracellular signalling pathways likely to be involved in tick immunity by combining a large-scale in silico approach with high-throughput gene expression analysis. Data from in silico analysis revealed that although both the Toll and JAK/STAT signalling pathways are evolutionarily conserved across arthropods, ticks lack central components of the D. melanogaster IMD pathway. Moreover, we show that tick immune signalling-associated genes are constitutively transcribed in BME26 cells (a cell lineage derived from embryos of the cattle tick Rhipicephalus microplus) and exhibit different transcriptional patterns in response to microbial challenge. Interestingly, Anaplasma marginale, a pathogen that is naturally transmitted by R. microplus, causes downregulation of immune-related genes, suggesting that this pathogen may manipulate the tick immune system, favouring its survival and vector colonization. Copyright © 2015 Elsevier Ltd. All rights reserved.

Thermal heterogeneity within aqueous materials quantified by 1H NMR spectroscopy: Multiparametric validation in silico and in vitro

NASA Astrophysics Data System (ADS)

Lutz, Norbert W.; Bernard, Monique

2018-02-01

We recently suggested a new paradigm for statistical analysis of thermal heterogeneity in (semi-)aqueous materials by 1H NMR spectroscopy, using water as a temperature probe. Here, we present a comprehensive in silico and in vitro validation that demonstrates the ability of this new technique to provide accurate quantitative parameters characterizing the statistical distribution of temperature values in a volume of (semi-)aqueous matter. First, line shape parameters of numerically simulated water 1H NMR spectra are systematically varied to study a range of mathematically well-defined temperature distributions. Then, corresponding models based on measured 1H NMR spectra of agarose gel are analyzed. In addition, dedicated samples based on hydrogels or biological tissue are designed to produce temperature gradients changing over time, and dynamic NMR spectroscopy is employed to analyze the resulting temperature profiles at sub-second temporal resolution. Accuracy and consistency of the previously introduced statistical descriptors of temperature heterogeneity are determined: weighted median and mean temperature, standard deviation, temperature range, temperature mode(s), kurtosis, skewness, entropy, and relative areas under temperature curves. Potential and limitations of this method for quantitative analysis of thermal heterogeneity in (semi-)aqueous materials are discussed in view of prospective applications in materials science as well as biology and medicine.

In Silico Analysis of Putrefaction Pathways in Bacteria and Its Implication in Colorectal Cancer

PubMed Central

Kaur, Harrisham; Das, Chandrani; Mande, Sharmila S.

2017-01-01

Fermentation of undigested proteins in human gastrointestinal tract (gut) by the resident microbiota, a process called bacterial putrefaction, can sometimes disrupt the gut homeostasis. In this process, essential amino acids (e.g., histidine, tryptophan, etc.) that are required by the host may be utilized by the gut microbes. In addition, some of the products of putrefaction, like ammonia, putrescine, cresol, indole, phenol, etc., have been implicated in the disease pathogenesis of colorectal cancer (CRC). We have investigated bacterial putrefaction pathways that are known to be associated with such metabolites. Results of the comprehensive in silico analysis of the selected putrefaction pathways across bacterial genomes revealed presence of these pathways in limited bacterial groups. Majority of these bacteria are commonly found in human gut. These include Bacillus, Clostridium, Enterobacter, Escherichia, Fusobacterium, Salmonella, etc. Interestingly, while pathogens utilize almost all the analyzed pathways, commensals prefer putrescine and H2S production pathways for metabolizing the undigested proteins. Further, comparison of the putrefaction pathways in the gut microbiomes of healthy, carcinoma and adenoma datasets indicate higher abundances of putrefying bacteria in the carcinoma stage of CRC. The insights obtained from the present study indicate utilization of possible microbiome-based therapies to minimize the adverse effects of gut microbiome in enteric diseases. PMID:29163445

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.

A One Pot Synthesis of Novel Bioactive Tri-Substitute-Condensed-Imidazopyridines that Targets Snake Venom Phospholipase A2

PubMed Central

Anilkumar, Nirvanappa C.; Sundaram, Mahalingam S.; Mohan, Chakrabhavi Dhananjaya; Rangappa, Shobith; Bulusu, Krishna C.; Fuchs, Julian E.; Girish, Kesturu S.; Bender, Andreas; Basappa; Rangappa, Kanchugarakoppal S.

2015-01-01

Drugs such as necopidem, saripidem, alpidem, zolpidem, and olprinone contain nitrogen-containing bicyclic, condensed-imidazo[1,2-α]pyridines as bioactive scaffolds. In this work, we report a high-yield one pot synthesis of 1-(2-methyl-8-aryl-substitued-imidazo[1,2-α]pyridin-3-yl)ethan-1-onefor the first-time. Subsequently, we performed in silico mode-of-action analysis and predicted that the synthesized imidazopyridines targets Phospholipase A2 (PLA2). In vitro analysis confirmed the predicted target PLA2 for the novel imidazopyridine derivative1-(2-Methyl-8-naphthalen-1-yl-imidazo [1,2-α]pyridine-3-yl)-ethanone (compound 3f) showing significant inhibitory activity towards snake venom PLA2 with an IC50 value of 14.3 μM. Evidently, the molecular docking analysis suggested that imidazopyridine compound was able to bind to the active site of the PLA2 with strong affinity, whose affinity values are comparable to nimesulide. Furthermore, we estimated the potential for oral bioavailability by Lipinski's Rule of Five. Hence, it is concluded that the compound 3f could be a lead molecule against snake venom PLA2. PMID:26196520

Massive Exploration of Perturbed Conditions of the Blood Coagulation Cascade through GPU Parallelization

PubMed Central

Cazzaniga, Paolo; Nobile, Marco S.; Besozzi, Daniela; Bellini, Matteo; Mauri, Giancarlo

2014-01-01

The introduction of general-purpose Graphics Processing Units (GPUs) is boosting scientific applications in Bioinformatics, Systems Biology, and Computational Biology. In these fields, the use of high-performance computing solutions is motivated by the need of performing large numbers of in silico analysis to study the behavior of biological systems in different conditions, which necessitate a computing power that usually overtakes the capability of standard desktop computers. In this work we present coagSODA, a CUDA-powered computational tool that was purposely developed for the analysis of a large mechanistic model of the blood coagulation cascade (BCC), defined according to both mass-action kinetics and Hill functions. coagSODA allows the execution of parallel simulations of the dynamics of the BCC by automatically deriving the system of ordinary differential equations and then exploiting the numerical integration algorithm LSODA. We present the biological results achieved with a massive exploration of perturbed conditions of the BCC, carried out with one-dimensional and bi-dimensional parameter sweep analysis, and show that GPU-accelerated parallel simulations of this model can increase the computational performances up to a 181× speedup compared to the corresponding sequential simulations. PMID:25025072

A linear programming approach to reconstructing subcellular structures from confocal images for automated generation of representative 3D cellular models.

PubMed

Wood, Scott T; Dean, Brian C; Dean, Delphine

2013-04-01

This paper presents a novel computer vision algorithm to analyze 3D stacks of confocal images of fluorescently stained single cells. The goal of the algorithm is to create representative in silico model structures that can be imported into finite element analysis software for mechanical characterization. Segmentation of cell and nucleus boundaries is accomplished via standard thresholding methods. Using novel linear programming methods, a representative actin stress fiber network is generated by computing a linear superposition of fibers having minimum discrepancy compared with an experimental 3D confocal image. Qualitative validation is performed through analysis of seven 3D confocal image stacks of adherent vascular smooth muscle cells (VSMCs) grown in 2D culture. The presented method is able to automatically generate 3D geometries of the cell's boundary, nucleus, and representative F-actin network based on standard cell microscopy data. These geometries can be used for direct importation and implementation in structural finite element models for analysis of the mechanics of a single cell to potentially speed discoveries in the fields of regenerative medicine, mechanobiology, and drug discovery. Copyright © 2012 Elsevier B.V. All rights reserved.

Integrated analysis of long non-coding RNAs in human gastric cancer: An in silico study.

PubMed

Han, Weiwei; Zhang, Zhenyu; He, Bangshun; Xu, Yijun; Zhang, Jun; Cao, Weijun

2017-01-01

Accumulating evidence highlights the important role of long non-coding RNAs (lncRNAs) in a large number of biological processes. However, the knowledge of genome scale expression of lncRNAs and their potential biological function in gastric cancer is still lacking. Using RNA-seq data from 420 gastric cancer patients in The Cancer Genome Atlas (TCGA), we identified 1,294 lncRNAs differentially expressed in gastric cancer compared with adjacent normal tissues. We also found 247 lncRNAs differentially expressed between intestinal subtype and diffuse subtype. Survival analysis revealed 33 lncRNAs independently associated with patient overall survival, of which 6 lncRNAs were validated in the internal validation set. There were 181 differentially expressed lncRNAs located in the recurrent somatic copy number alterations (SCNAs) regions and their correlations between copy number and RNA expression level were also analyzed. In addition, we inferred the function of lncRNAs by construction of a co-expression network for mRNAs and lncRNAs. Together, this study presented an integrative analysis of lncRNAs in gastric cancer and provided a valuable resource for further functional research of lncRNAs in gastric cancer.

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

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.

Surface proteome mining for identification of potential vaccine candidates against Campylobacter jejuni: an in silico approach.

PubMed

Mehla, Kusum; Ramana, Jayashree

2017-01-01

Campylobacter jejuni remains a major cause of human gastroenteritis with estimated annual incidence rate of 450 million infections worldwide. C. jejuni is a major burden to public health in both socioeconomically developing and industrialized nations. Virulence determinants involved in C. jejuni pathogenesis are multifactorial in nature and not yet fully understood. Despite the completion of the first C. jejuni genome project in 2000, there are currently no vaccines in the market against this pathogen. Traditional vaccinology approach is an arduous and time extensive task. Omics techniques coupled with sequencing data have engaged researcher's attention to reduce the time and resources applied in the process of vaccine development. Recently, there has been remarkable increase in development of in silico analysis tools for efficiently mining biological information obscured in the genome. In silico approaches have been crucial for combating infectious diseases by accelerating the pace of vaccine development. This study employed a range of bioinformatics approaches for proteome scale identification of peptide vaccine candidates. Whole proteome of C. jejuni was investigated for varied properties like antigenicity, allergenicity, major histocompatibility class (MHC)-peptide interaction, immune cell processivity, HLA distribution, conservancy, and population coverage. Predicted epitopes were further tested for binding in MHC groove using computational docking studies. The predicted epitopes were conserved; covered more than 80 % of the world population and were presented by MHC-I supertypes. We conclude by underscoring that the epitopes predicted are believed to expedite the development of successful vaccines to control or prevent C. jejuni infections albeit the results need to be experimentally validated.

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.

Structure-guided fragment-based in silico drug design of dengue protease inhibitors.

PubMed

Knehans, Tim; Schüller, Andreas; Doan, Danny N; Nacro, Kassoum; Hill, Jeffrey; Güntert, Peter; Madhusudhan, M S; Weil, Tanja; Vasudevan, Subhash G

2011-03-01

An in silico fragment-based drug design approach was devised and applied towards the identification of small molecule inhibitors of the dengue virus (DENV) NS2B-NS3 protease. Currently, no DENV protease co-crystal structure with bound inhibitor and fully formed substrate binding site is available. Therefore a homology model of DENV NS2B-NS3 protease was generated employing a multiple template spatial restraints method and used for structure-based design. A library of molecular fragments was derived from the ZINC screening database with help of the retrosynthetic combinatorial analysis procedure (RECAP). 150,000 molecular fragments were docked to the DENV protease homology model and the docking poses were rescored using a target-specific scoring function. High scoring fragments were assembled to small molecule candidates by an implicit linking cascade. The cascade included substructure searching and structural filters focusing on interactions with the S1 and S2 pockets of the protease. The chemical space adjacent to the promising candidates was further explored by neighborhood searching. A total of 23 compounds were tested experimentally and two compounds were discovered to inhibit dengue protease (IC(50) = 7.7 μM and 37.9 μM, respectively) and the related West Nile virus protease (IC(50) = 6.3 μM and 39.0 μM, respectively). This study demonstrates the successful application of a structure-guided fragment-based in silico drug design approach for dengue protease inhibitors providing straightforward hit generation using a combination of homology modeling, fragment docking, chemical similarity and structural filters.

Structure-guided fragment-based in silico drug design of dengue protease inhibitors

NASA Astrophysics Data System (ADS)

Knehans, Tim; Schüller, Andreas; Doan, Danny N.; Nacro, Kassoum; Hill, Jeffrey; Güntert, Peter; Madhusudhan, M. S.; Weil, Tanja; Vasudevan, Subhash G.

2011-03-01

An in silico fragment-based drug design approach was devised and applied towards the identification of small molecule inhibitors of the dengue virus (DENV) NS2B-NS3 protease. Currently, no DENV protease co-crystal structure with bound inhibitor and fully formed substrate binding site is available. Therefore a homology model of DENV NS2B-NS3 protease was generated employing a multiple template spatial restraints method and used for structure-based design. A library of molecular fragments was derived from the ZINC screening database with help of the retrosynthetic combinatorial analysis procedure (RECAP). 150,000 molecular fragments were docked to the DENV protease homology model and the docking poses were rescored using a target-specific scoring function. High scoring fragments were assembled to small molecule candidates by an implicit linking cascade. The cascade included substructure searching and structural filters focusing on interactions with the S1 and S2 pockets of the protease. The chemical space adjacent to the promising candidates was further explored by neighborhood searching. A total of 23 compounds were tested experimentally and two compounds were discovered to inhibit dengue protease (IC50 = 7.7 μM and 37.9 μM, respectively) and the related West Nile virus protease (IC50 = 6.3 μM and 39.0 μM, respectively). This study demonstrates the successful application of a structure-guided fragment-based in silico drug design approach for dengue protease inhibitors providing straightforward hit generation using a combination of homology modeling, fragment docking, chemical similarity and structural filters.

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.

Computational prediction and biochemical characterization of novel RNA aptamers to Rift Valley fever virus nucleocapsid protein.

PubMed

Ellenbecker, Mary; St Goddard, Jeremy; Sundet, Alec; Lanchy, Jean-Marc; Raiford, Douglas; Lodmell, J Stephen

2015-10-01

Rift Valley fever virus (RVFV) is a potent human and livestock pathogen endemic to sub-Saharan Africa and the Arabian Peninsula that has potential to spread to other parts of the world. Although there is no proven effective and safe treatment for RVFV infections, a potential therapeutic target is the virally encoded nucleocapsid protein (N). During the course of infection, N binds to viral RNA, and perturbation of this interaction can inhibit viral replication. To gain insight into how N recognizes viral RNA specifically, we designed an algorithm that uses a distance matrix and multidimensional scaling to compare the predicted secondary structures of known N-binding RNAs, or aptamers, that were isolated and characterized in previous in vitro evolution experiment. These aptamers did not exhibit overt sequence or predicted structure similarity, so we employed bioinformatic methods to propose novel aptamers based on analysis and clustering of secondary structures. We screened and scored the predicted secondary structures of novel randomly generated RNA sequences in silico and selected several of these putative N-binding RNAs whose secondary structures were similar to those of known N-binding RNAs. We found that overall the in silico generated RNA sequences bound well to N in vitro. Furthermore, introduction of these RNAs into cells prior to infection with RVFV inhibited viral replication in cell culture. This proof of concept study demonstrates how the predictive power of bioinformatics and the empirical power of biochemistry can be jointly harnessed to discover, synthesize, and test new RNA sequences that bind tightly to RVFV N protein. The approach would be easily generalizable to other applications. Copyright © 2015 Elsevier Ltd. All rights reserved.

Optimized hydrophobic interactions and hydrogen bonding at the target-ligand interface leads the pathways of drug-designing.

PubMed

Patil, Rohan; Das, Suranjana; Stanley, Ashley; Yadav, Lumbani; Sudhakar, Akulapalli; Varma, Ashok K

2010-08-16

Weak intermolecular interactions such as hydrogen bonding and hydrophobic interactions are key players in stabilizing energetically-favored ligands, in an open conformational environment of protein structures. However, it is still poorly understood how the binding parameters associated with these interactions facilitate a drug-lead to recognize a specific target and improve drugs efficacy. To understand this, comprehensive analysis of hydrophobic interactions, hydrogen bonding and binding affinity have been analyzed at the interface of c-Src and c-Abl kinases and 4-amino substituted 1H-pyrazolo [3, 4-d] pyrimidine compounds. In-silico docking studies were performed, using Discovery Studio software modules LigandFit, CDOCKER and ZDOCK, to investigate the role of ligand binding affinity at the hydrophobic pocket of c-Src and c-Abl kinase. Hydrophobic and hydrogen bonding interactions of docked molecules were compared using LigPlot program. Furthermore, 3D-QSAR and MFA calculations were scrutinized to quantify the role of weak interactions in binding affinity and drug efficacy. The in-silico method has enabled us to reveal that a multi-targeted small molecule binds with low affinity to its respective targets. But its binding affinity can be altered by integrating the conformationally favored functional groups at the active site of the ligand-target interface. Docking studies of 4-amino-substituted molecules at the bioactive cascade of the c-Src and c-Abl have concluded that 3D structural folding at the protein-ligand groove is also a hallmark for molecular recognition of multi-targeted compounds and for predicting their biological activity. The results presented here demonstrate that hydrogen bonding and optimized hydrophobic interactions both stabilize the ligands at the target site, and help alter binding affinity and drug efficacy.

Optimized Hydrophobic Interactions and Hydrogen Bonding at the Target-Ligand Interface Leads the Pathways of Drug-Designing

PubMed Central

Stanley, Ashley; Yadav, Lumbani; Sudhakar, Akulapalli; Varma, Ashok K.

2010-01-01

Background Weak intermolecular interactions such as hydrogen bonding and hydrophobic interactions are key players in stabilizing energetically-favored ligands, in an open conformational environment of protein structures. However, it is still poorly understood how the binding parameters associated with these interactions facilitate a drug-lead to recognize a specific target and improve drugs efficacy. To understand this, comprehensive analysis of hydrophobic interactions, hydrogen bonding and binding affinity have been analyzed at the interface of c-Src and c-Abl kinases and 4-amino substituted 1H-pyrazolo [3, 4-d] pyrimidine compounds. Methodology In-silico docking studies were performed, using Discovery Studio software modules LigandFit, CDOCKER and ZDOCK, to investigate the role of ligand binding affinity at the hydrophobic pocket of c-Src and c-Abl kinase. Hydrophobic and hydrogen bonding interactions of docked molecules were compared using LigPlot program. Furthermore, 3D-QSAR and MFA calculations were scrutinized to quantify the role of weak interactions in binding affinity and drug efficacy. Conclusions The in-silico method has enabled us to reveal that a multi-targeted small molecule binds with low affinity to its respective targets. But its binding affinity can be altered by integrating the conformationally favored functional groups at the active site of the ligand-target interface. Docking studies of 4-amino-substituted molecules at the bioactive cascade of the c-Src and c-Abl have concluded that 3D structural folding at the protein-ligand groove is also a hallmark for molecular recognition of multi-targeted compounds and for predicting their biological activity. The results presented here demonstrate that hydrogen bonding and optimized hydrophobic interactions both stabilize the ligands at the target site, and help alter binding affinity and drug efficacy. PMID:20808434

Structure based classification for bile salt export pump (BSEP) inhibitors using comparative structural modeling of human BSEP

NASA Astrophysics Data System (ADS)

Jain, Sankalp; Grandits, Melanie; Richter, Lars; Ecker, Gerhard F.

2017-06-01

The bile salt export pump (BSEP) actively transports conjugated monovalent bile acids from the hepatocytes into the bile. This facilitates the formation of micelles and promotes digestion and absorption of dietary fat. Inhibition of BSEP leads to decreased bile flow and accumulation of cytotoxic bile salts in the liver. A number of compounds have been identified to interact with BSEP, which results in drug-induced cholestasis or liver injury. Therefore, in silico approaches for flagging compounds as potential BSEP inhibitors would be of high value in the early stage of the drug discovery pipeline. Up to now, due to the lack of a high-resolution X-ray structure of BSEP, in silico based identification of BSEP inhibitors focused on ligand-based approaches. In this study, we provide a homology model for BSEP, developed using the corrected mouse P-glycoprotein structure (PDB ID: 4M1M). Subsequently, the model was used for docking-based classification of a set of 1212 compounds (405 BSEP inhibitors, 807 non-inhibitors). Using the scoring function ChemScore, a prediction accuracy of 81% on the training set and 73% on two external test sets could be obtained. In addition, the applicability domain of the models was assessed based on Euclidean distance. Further, analysis of the protein-ligand interaction fingerprints revealed certain functional group-amino acid residue interactions that could play a key role for ligand binding. Though ligand-based models, due to their high speed and accuracy, remain the method of choice for classification of BSEP inhibitors, structure-assisted docking models demonstrate reasonably good prediction accuracies while additionally providing information about putative protein-ligand interactions.

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

TLR9 agonists oppositely modulate DNA repair genes in tumor versus immune cells and enhance chemotherapy effects.

PubMed

Sommariva, Michele; De Cecco, Loris; De Cesare, Michelandrea; Sfondrini, Lucia; Ménard, Sylvie; Melani, Cecilia; Delia, Domenico; Zaffaroni, Nadia; Pratesi, Graziella; Uva, Valentina; Tagliabue, Elda; Balsari, Andrea

2011-10-15

Synthetic oligodeoxynucleotides expressing CpG motifs (CpG-ODN) are a Toll-like receptor 9 (TLR9) agonist that can enhance the antitumor activity of DNA-damaging chemotherapy and radiation therapy in preclinical mouse models. We hypothesized that the success of these combinations is related to the ability of CpG-ODN to modulate genes involved in DNA repair. We conducted an in silico analysis of genes implicated in DNA repair in data sets obtained from murine colon carcinoma cells in mice injected intratumorally with CpG-ODN and from splenocytes in mice treated intraperitoneally with CpG-ODN. CpG-ODN treatment caused downregulation of DNA repair genes in tumors. Microarray analyses of human IGROV-1 ovarian carcinoma xenografts in mice treated intraperitoneally with CpG-ODN confirmed in silico findings. When combined with the DNA-damaging drug cisplatin, CpG-ODN significantly increased the life span of mice compared with individual treatments. In contrast, CpG-ODN led to an upregulation of genes involved in DNA repair in immune cells. Cisplatin-treated patients with ovarian carcinoma as well as anthracycline-treated patients with breast cancer who are classified as "CpG-like" for the level of expression of CpG-ODN modulated DNA repair genes have a better outcome than patients classified as "CpG-untreated-like," indicating the relevance of these genes in the tumor cell response to DNA-damaging drugs. Taken together, the findings provide evidence that the tumor microenvironment can sensitize cancer cells to DNA-damaging chemotherapy, thereby expanding the benefits of CpG-ODN therapy beyond induction of a strong immune response.

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.

Family-Based Benchmarking of Copy Number Variation Detection Software.

PubMed

Nutsua, Marcel Elie; Fischer, Annegret; Nebel, Almut; Hofmann, Sylvia; Schreiber, Stefan; Krawczak, Michael; Nothnagel, Michael

2015-01-01

The analysis of structural variants, in particular of copy-number variations (CNVs), has proven valuable in unraveling the genetic basis of human diseases. Hence, a large number of algorithms have been developed for the detection of CNVs in SNP array signal intensity data. Using the European and African HapMap trio data, we undertook a comparative evaluation of six commonly used CNV detection software tools, namely Affymetrix Power Tools (APT), QuantiSNP, PennCNV, GLAD, R-gada and VEGA, and assessed their level of pair-wise prediction concordance. The tool-specific CNV prediction accuracy was assessed in silico by way of intra-familial validation. Software tools differed greatly in terms of the number and length of the CNVs predicted as well as the number of markers included in a CNV. All software tools predicted substantially more deletions than duplications. Intra-familial validation revealed consistently low levels of prediction accuracy as measured by the proportion of validated CNVs (34-60%). Moreover, up to 20% of apparent family-based validations were found to be due to chance alone. Software using Hidden Markov models (HMM) showed a trend to predict fewer CNVs than segmentation-based algorithms albeit with greater validity. PennCNV yielded the highest prediction accuracy (60.9%). Finally, the pairwise concordance of CNV prediction was found to vary widely with the software tools involved. We recommend HMM-based software, in particular PennCNV, rather than segmentation-based algorithms when validity is the primary concern of CNV detection. QuantiSNP may be used as an additional tool to detect sets of CNVs not detectable by the other tools. Our study also reemphasizes the need for laboratory-based validation, such as qPCR, of CNVs predicted in silico.

Novel SNPs and INDEL polymorphisms in the 3'UTR of DGAT1 gene: in silico analyses and a possible association.

PubMed

Rosse, Izinara da Cruz; Steinberg, Raphael da Silva; Coimbra, Roney Santos; Peixoto, Maria Gabriela Campolina Diniz; Verneque, Rui Silva; Machado, Marco Antonio; Fonseca, Cleusa Graça; Carvalho, Maria Raquel Santos

2014-07-01

Diacylglycerol-O-acyltransferase (DGAT1) gene encodes the rate-limiting enzyme of triglyceride synthesis. A polymorphism in this gene, DGAT1 K232A, has been associated with milk production and composition in taurine breeds. However, this polymorphism is not a good tool for ascertaining the effects of this QTL in Bos indicus (Zebu), since the frequency of the DGAT1 232A allele is too low in these breeds. We sequenced the 3'-untranslated region of DGAT1 gene in a sample of bulls of the breeds Guzerá (Bos indicus) and Holstein (Bos taurus) and, using in silico analysis, we searched for genetic variation, evolutionary conservation, regulatory elements, and possible substitution effects. Six single nucleotide (SNPs) and one insertion-deletion (INDEL) polymorphisms were found in the Guzerá bulls. Additionally, we developed a preliminary association study, using this INDEL polymorphism as a genetic marker. A significant association was detected (P ≤ 0.05) between the INDEL (DGAT1 3'UTR INDEL) and the breeding values (BV) for protein, fat, and milk yields over a 305-day lactation period. The DGAT1 3' UTR INDEL genotype I/I (I, for insertion) was associated with lower BVs (-38.77 kg for milk, -1.86 kg for fat, and -1.48 kg for protein yields), when compared to the genotype I/D (D, for deletion). I/D genotype was lower D/D genotype (-34.98 kg milk, -1.73 kg fat, and -1.09 kg protein yields). This study reports the first polymorphism of DGAT1 3'UTR in the Guzerá breed, as well as its association with BV for milk protein, fat, and milk yields.

An integrated molecular modeling approach for in silico design of new tetracyclic derivatives as ALK inhibitors.

PubMed

Peddi, Saikiran Reddy; Sivan, Sree Kanth; Manga, Vijjulatha

2016-10-01

Anaplastic lymphoma kinase (ALK), a promising therapeutic target for treatment of human cancers, is a receptor tyrosine kinase that instigates the activation of several signal transduction pathways. In the present study, in silico methods have been employed in order to explore the structural features and functionalities of a series of tetracyclic derivatives displaying potent inhibitory activity toward ALK. Initially docking was performed using GLIDE 5.6 to probe the bioactive conformation of all the compounds and to understand the binding modes of inhibitors. The docking results revealed that ligand interaction with Met 1199 plays a crucial role in binding of inhibitors to ALK. Further to establish a robust 3D-QSAR model using CoMFA and CoMSIA methods, the whole dataset was divided into three splits. Model obtained from Split 3 showed high accuracy ([Formula: see text] of 0.700 and 0.682, [Formula: see text] of 0.971 and 0.974, [Formula: see text] of 0.673 and 0.811, respectively for CoMFA and CoMSIA). The key structural requirements for enhancing the inhibitory activity were derived from CoMFA and CoMSIA contours in combination with site map analysis. Substituting small electronegative groups at Position 8 by replacing either morpholine or piperidine rings and maintaining hydrophobic character at Position 9 in tetracyclic derivatives can enhance the inhibitory potential. Finally, we performed molecular dynamics simulations in order to investigate the stability of protein ligand interactions and MM/GBSA calculations to compare binding free energies of co-crystal ligand and newly designed molecule N1. Based on the coherence of outcome of various molecular modeling studies, a set of 11 new molecules having potential predicted inhibitory activity were designed.

Molecular dynamics simulation studies and in vitro site directed mutagenesis of avian beta-defensin Apl_AvBD2

PubMed Central

2010-01-01

Background Defensins comprise a group of antimicrobial peptides, widely recognized as important elements of the innate immune system in both animals and plants. Cationicity, rather than the secondary structure, is believed to be the major factor defining the antimicrobial activity of defensins. To test this hypothesis and to improve the activity of the newly identified avian β-defensin Apl_AvBD2 by enhancing the cationicity, we performed in silico site directed mutagenesis, keeping the predicted secondary structure intact. Molecular dynamics (MD) simulation studies were done to predict the activity. Mutant proteins were made by in vitro site directed mutagenesis and recombinant protein expression, and tested for antimicrobial activity to confirm the results obtained in MD simulation analysis. Results MD simulation revealed subtle, but critical, structural variations between the wild type Apl_AvBD2 and the more cationic in silico mutants, which were not detected in the initial structural prediction by homology modelling. The C-terminal cationic 'claw' region, important in antimicrobial activity, which was intact in the wild type, showed changes in shape and orientation in all the mutant peptides. Mutant peptides also showed increased solvent accessible surface area and more number of hydrogen bonds with the surrounding water molecules. In functional studies, the Escherichia coli expressed, purified recombinant mutant proteins showed total loss of antimicrobial activity compared to the wild type protein. Conclusion The study revealed that cationicity alone is not the determining factor in the microbicidal activity of antimicrobial peptides. Factors affecting the molecular dynamics such as hydrophobicity, electrostatic interactions and the potential for oligomerization may also play fundamental roles. It points to the usefulness of MD simulation studies in successful engineering of antimicrobial peptides for improved activity and other desirable functions. PMID:20122244

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.

Chronic obstructive lung disease "expert system": validation of a predictive tool for assisting diagnosis.

PubMed

Braido, Fulvio; Santus, Pierachille; Corsico, Angelo Guido; Di Marco, Fabiano; Melioli, Giovanni; Scichilone, Nicola; Solidoro, Paolo

2018-01-01

The purposes of this study were development and validation of an expert system (ES) aimed at supporting the diagnosis of chronic obstructive lung disease (COLD). A questionnaire and a WebFlex code were developed and validated in silico. An expert panel pilot validation on 60 cases and a clinical validation on 241 cases were performed. The developed questionnaire and code validated in silico resulted in a suitable tool to support the medical diagnosis. The clinical validation of the ES was performed in an academic setting that included six different reference centers for respiratory diseases. The results of the ES expressed as a score associated with the risk of suffering from COLD were matched and compared with the final clinical diagnoses. A set of 60 patients were evaluated by a pilot expert panel validation with the aim of calculating the sample size for the clinical validation study. The concordance analysis between these preliminary ES scores and diagnoses performed by the experts indicated that the accuracy was 94.7% when both experts and the system confirmed the COLD diagnosis and 86.3% when COLD was excluded. Based on these results, the sample size of the validation set was established in 240 patients. The clinical validation, performed on 241 patients, resulted in ES accuracy of 97.5%, with confirmed COLD diagnosis in 53.6% of the cases and excluded COLD diagnosis in 32% of the cases. In 11.2% of cases, a diagnosis of COLD was made by the experts, although the imaging results showed a potential concomitant disorder. The ES presented here (COLD ES ) is a safe and robust supporting tool for COLD diagnosis in primary care settings.

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.

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.

Comparative genomics of metabolic capacities of regulons controlled by cis-regulatory RNA motifs in bacteria.

PubMed

Sun, Eric I; Leyn, Semen A; Kazanov, Marat D; Saier, Milton H; Novichkov, Pavel S; Rodionov, Dmitry A

2013-09-02

In silico comparative genomics approaches have been efficiently used for functional prediction and reconstruction of metabolic and regulatory networks. Riboswitches are metabolite-sensing structures often found in bacterial mRNA leaders controlling gene expression on transcriptional or translational levels.An increasing number of riboswitches and other cis-regulatory RNAs have been recently classified into numerous RNA families in the Rfam database. High conservation of these RNA motifs provides a unique advantage for their genomic identification and comparative analysis. A comparative genomics approach implemented in the RegPredict tool was used for reconstruction and functional annotation of regulons controlled by RNAs from 43 Rfam families in diverse taxonomic groups of Bacteria. The inferred regulons include ~5200 cis-regulatory RNAs and more than 12000 target genes in 255 microbial genomes. All predicted RNA-regulated genes were classified into specific and overall functional categories. Analysis of taxonomic distribution of these categories allowed us to establish major functional preferences for each analyzed cis-regulatory RNA motif family. Overall, most RNA motif regulons showed predictable functional content in accordance with their experimentally established effector ligands. Our results suggest that some RNA motifs (including thiamin pyrophosphate and cobalamin riboswitches that control the cofactor metabolism) are widespread and likely originated from the last common ancestor of all bacteria. However, many more analyzed RNA motifs are restricted to a narrow taxonomic group of bacteria and likely represent more recent evolutionary innovations. The reconstructed regulatory networks for major known RNA motifs substantially expand the existing knowledge of transcriptional regulation in bacteria. The inferred regulons can be used for genetic experiments, functional annotations of genes, metabolic reconstruction and evolutionary analysis. The obtained genome-wide collection of reference RNA motif regulons is available in the RegPrecise database (http://regprecise.lbl.gov/).

Helicobacter pylori HP1512 Is a Nickel-Responsive NikR-Regulated Outer Membrane Protein▿

PubMed Central

Davis, Gregg S.; Flannery, Erika L.; Mobley, Harry L. T.

2006-01-01

Helicobacter pylori is dependent upon the production of the highly abundant and active metalloenzyme urease for colonization of the human stomach. Thus, H. pylori has an absolute requirement for the transition metal nickel, a required cofactor for urease. To investigate the contribution of genes that are factors in this process, microarray analysis comparing the transcriptome of wild-type H. pylori 26695 cultured in brucella broth containing fetal calf serum (BBF) alone or supplemented with 100 μM NiCl2 suggested that HP1512 is repressed in the presence of 100 μM supplemental nickel. When measured by comparative real-time quantitative PCR (qPCR), HP1512 transcription was reduced 43-fold relative to the value for the wild type when cultured in BBF supplemented with 10 μM NiCl2. When grown in unsupplemented BBF, urease activity of an HP1512::cat mutant was significantly reduced compared to the wild type, 4.9 ± 0.5 μmol/min/mg of protein (n = 7) and 17.1 ± 4.9 μmol/min/mg of protein (n = 13), respectively (P < 0.0001). In silico analysis of the HP1511-HP1512 (HP1511-1512) intergenic region identified a putative NikR operator upstream of HP1512. Gel shift analysis with purified recombinant NikR verified nickel-dependent binding of H. pylori NikR to the HP1511-1512 intergenic region. Furthermore, comparative real-time qPCR of four nickel-related genes suggests that mutation of HP1512 results in reduced intracellular nickel concentration relative to wild-type H. pylori 26695. Taken together, these data suggest that HP1512 encodes a NikR-nickel-regulated outer membrane protein. PMID:17030579

Meta-Analysis of Global Transcriptomics Suggests that Conserved Genetic Pathways are Responsible for Quercetin and Tannic Acid Mediated Longevity in C. elegans

PubMed Central

Pietsch, Kerstin; Saul, Nadine; Swain, Suresh C.; Menzel, Ralph; Steinberg, Christian E. W.; Stürzenbaum, Stephen R.

2012-01-01

Recent research has highlighted that the polyphenols Quercetin and Tannic acid are capable of extending the lifespan of Caenorhabditis elegans. To gain a deep understanding of the underlying molecular genetics, we analyzed the global transcriptional patterns of nematodes exposed to three concentrations of Quercetin or Tannic acid, respectively. By means of an intricate meta-analysis it was possible to compare the transcriptomes of polyphenol exposure to recently published datasets derived from (i) longevity mutants or (ii) infection. This detailed comparative in silico analysis facilitated the identification of compound specific and overlapping transcriptional profiles and allowed the prediction of putative mechanistic models of Quercetin and Tannic acid mediated longevity. Lifespan extension due to Quercetin was predominantly driven by the metabolome, TGF-beta signaling, Insulin-like signaling, and the p38 MAPK pathway and Tannic acid’s impact involved, in part, the amino acid metabolism and was modulated by the TGF-beta and the p38 MAPK pathways. DAF-12, which integrates TGF-beta and Insulin-like downstream signaling, and genetic players of the p38 MAPK pathway therefore seem to be crucial regulators for both polyphenols. Taken together, this study underlines how meta-analyses can provide an insight of molecular events that go beyond the traditional categorization into gene ontology-terms and Kyoto encyclopedia of genes and genomes-pathways. It also supports the call to expand the generation of comparative and integrative databases, an effort that is currently still in its infancy. PMID:22493606

Synthesis, spectroscopic characterization, DFT studies and antifungal activity of (E)-4-amino-5-[N'-(2-nitro-benzylidene)-hydrazino]-2,4-dihydro-[1,2,4]triazole-3-thione

NASA Astrophysics Data System (ADS)

Joshi, Rachana; Pandey, Nidhi; Yadav, Swatantra Kumar; Tilak, Ragini; Mishra, Hirdyesh; Pokharia, Sandeep

2018-07-01

The hydrazino Schiff base (E)-4-amino-5-[N'-(2-nitro-benzylidene)-hydrazino]-2,4-dihydro-[1,2,4]triazole-3-thione was synthesized and structurally characterized by elemental analysis, FT-IR, Raman, 1H and 13C-NMR and UV-Vis studies. A density functional theory (DFT) based electronic structure calculations were accomplished at B3LYP/6-311++G(d,p) level of theory. A comparative analysis of calculated vibrational frequencies with experimental vibrational frequencies was carried out and significant bands were assigned. The results indicate a good correlation (R2 = 0.9974) between experimental and theoretical IR frequencies. The experimental 1H and 13C-NMR resonance signals were also compared to the calculated values. The theoretical UV-Vis spectral studies were carried out using time dependent-DFT method in gas phase and IEFPCM model in solvent field calculation. The geometrical parameters were calculated in the gas phase. Atomic charges at selected atoms were calculated by Mulliken population analysis (MPA), Hirshfeld population analysis (HPA) and Natural population analysis (NPA) schemes. The molecular electrostatic potential (MEP) map was calculated to assign reactive site on the surface of the molecule. The conceptual-DFT based global and local reactivity descriptors were calculated to obtain an insight into the reactivity behaviour. The frontier molecular orbital analysis was carried out to study the charge transfer within the molecule. The detailed natural bond orbital (NBO) analysis was performed to obtain an insight into the intramolecular conjugative electronic interactions. The titled compound was screened for in vitro antifungal activity against four fungal strains and the results obtained are explained through in silico molecular docking studies.

Analysis of Pfizer compounds in EPA's ToxCast chemicals-assay space.

PubMed

Shah, Falgun; Greene, Nigel

2014-01-21

The U.S. Environmental Protection Agency (EPA) launched the ToxCast program in 2007 with the goal of evaluating high-throughput in vitro assays to prioritize chemicals that need toxicity testing. Their goal was to develop predictive bioactivity signatures for toxic compounds using a set of in vitro assays and/or in silico properties. In 2009, Pfizer joined the ToxCast initiative by contributing 52 compounds with preclinical and clinical data for profiling across the multiple assay platforms available. Here, we describe the initial analysis of the Pfizer subset of compounds within the ToxCast chemical (n = 1814) and in vitro assay (n = 486) space. An analysis of the hit rate of Pfizer compounds in the ToxCast assay panel allowed us to focus our mining of assays potentially most relevant to the attrition of our compounds. We compared the bioactivity profile of Pfizer compounds to other compounds in the ToxCast chemical space to gain insights into common toxicity pathways. Additionally, we explored the similarity in the chemical and biological spaces between drug-like compounds and environmental chemicals in ToxCast and compared the in vivo profiles of a subset of failed pharmaceuticals having high similarity in both spaces. We found differences in the chemical and biological spaces of pharmaceuticals compared to environmental chemicals, which may question the applicability of bioactivity signatures developed exclusively based on the latter to drug-like compounds if used without prior validation with the ToxCast Phase-II chemicals. Finally, our analysis has allowed us to identify novel interactions for our compounds in particular with multiple nuclear receptors that were previously not known. This insight may help us to identify potential liabilities with future novel compounds.

Metagenomic analysis of sediments under seaports influence in the Equatorial Atlantic Ocean.

PubMed

Tavares, Tallita Cruz Lopes; Normando, Leonardo Ribeiro Oliveira; de Vasconcelos, Ana Tereza Ribeiro; Gerber, Alexandra Lehmkuhl; Agnez-Lima, Lucymara Fassarella; Melo, Vânia Maria Maciel

2016-07-01

Maritime ports are anthropogenic interventions capable of causing serious alterations in coastal ecosystems. In this study, we examined the benthic microbial diversity and community structure under the influence of two maritime ports, Mucuripe (MUC) and Pecém (PEC), at Equatorial Atlantic Ocean in Northeast Brazil. Those seaports differ in architecture, time of functioning, cargo handling and contamination. The microbiomes from MUC and PEC were also compared in silico to 11 other globally distributed marine microbiomes. The comparative analysis of operational taxonomic units (OTUs) retrieved by PCR-DGGE showed that MUC presents greater richness and β diversity of Bacteria and Archaea than PEC. In line with these results, metagenomic analysis showed that MUC and PEC benthic microbial communities share the main common bacterial phyla found in coastal environments, although can be distinguish by greater abundance of Cyanobacteria in MUC and Deltaproteobacteria in PEC. Both ports differed in Archaea composition, being PEC port sediments dominated by Thaumarchaeota. The microbiomes showed little divergence in their potential metabolic pathways, although shifts on the microbial taxonomic signatures involved in nitrogen and sulphur metabolic pathways were observed. The comparative analysis of different benthic marine metagenomes from Brazil, Australia and Mexico grouped them by the geographic location rather than by the type of ecosystem, although at phylum level seaport sediments share a core microbiome constituted by Proteobacteria, Cyanobacteria, Actinobacteria, Tenericuteres, Firmicutes, Bacteriodetes and Euryarchaeota. Our results suggest that multiple physical and chemical factors acting on sediments as a result of at least 60years of port operation play a role in shaping the benthic microbial communities at taxonomic level, but not at functional level. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

In silico mapping of quantitative trait loci in maize.

PubMed

Parisseaux, B; Bernardo, R

2004-08-01

Quantitative trait loci (QTL) are most often detected through designed mapping experiments. An alternative approach is in silico mapping, whereby genes are detected using existing phenotypic and genomic databases. We explored the usefulness of in silico mapping via a mixed-model approach in maize (Zea mays L.). Specifically, our objective was to determine if the procedure gave results that were repeatable across populations. Multilocation data were obtained from the 1995-2002 hybrid testing program of Limagrain Genetics in Europe. Nine heterotic patterns comprised 22,774 single crosses. These single crosses were made from 1,266 inbreds that had data for 96 simple sequence repeat (SSR) markers. By a mixed-model approach, we estimated the general combining ability effects associated with marker alleles in each heterotic pattern. The numbers of marker loci with significant effects--37 for plant height, 24 for smut [Ustilago maydis (DC.) Cda.] resistance, and 44 for grain moisture--were consistent with previous results from designed mapping experiments. Each trait had many loci with small effects and few loci with large effects. For smut resistance, a marker in bin 8.05 on chromosome 8 had a significant effect in seven (out of a maximum of 18) instances. For this major QTL, the maximum effect of an allele substitution ranged from 5.4% to 41.9%, with an average of 22.0%. We conclude that in silico mapping via a mixed-model approach can detect associations that are repeatable across different populations. We speculate that in silico mapping will be more useful for gene discovery than for selection in plant breeding programs. Copyright 2004 Springer-Verlag

Heterogeneous expression pattern of tandem duplicated sHsps genes during fruit ripening in two tomato species

NASA Astrophysics Data System (ADS)

Arce, DP; Krsticevic, FJ; Ezpeleta, J.; Ponce, SD; Pratta, GR; Tapia, E.

2016-04-01

The small heat shock proteins (sHSPs) have been found to play a critical role in physiological stress conditions in protecting proteins from irreversible aggregation. To characterize the gene expression profile of four sHsps with a tandem gene structure arrangement in the domesticated Solanum lycopersicum (Heinz 1706) genome and its wild close relative Solanum pimpinellifolium (LA1589), differential gene expression analysis using RNA-Seq was conducted in three ripening stages in both cultivars fruits. Gene promoter analysis was performed to explain the heterogeneous pattern of gene expression found for these tandem duplicated sHsps. In silico analysis results contribute to refocus wet experiment analysis in tomato sHsp family proteins.