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.

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

Genome wide in silico characterization of Dof gene families of pigeonpea (Cajanus cajan (L) Millsp.).

PubMed

Malviya, N; Gupta, S; Singh, V K; Yadav, M K; Bisht, N C; Sarangi, B K; Yadav, D

2015-02-01

The DNA binding with One Finger (Dof) protein is a plant specific transcription factor involved in the regulation of wide range of processes. The analysis of whole genome sequence of pigeonpea has identified 38 putative Dof genes (CcDof) distributed on 8 chromosomes. A total of 17 out of 38 CcDof genes were found to be intronless. A comprehensive in silico characterization of CcDof gene family including the gene structure, chromosome location, protein motif, phylogeny, gene duplication and functional divergence has been attempted. The phylogenetic analysis resulted in 3 major clusters with closely related members in phylogenetic tree revealed common motif distribution. The in silico cis-regulatory element analysis revealed functional diversity with predominance of light responsive and stress responsive elements indicating the possibility of these CcDof genes to be associated with photoperiodic control and biotic and abiotic stress. The duplication pattern showed that tandem duplication is predominant over segmental duplication events. The comparative phylogenetic analysis of these Dof proteins along with 78 soybean, 36 Arabidopsis and 30 rice Dof proteins revealed 7 major clusters. Several groups of orthologs and paralogs were identified based on phylogenetic tree constructed. Our study provides useful information for functional characterization of CcDof genes.

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.

In Silico Analysis for the Study of Botulinum Toxin Structure

NASA Astrophysics Data System (ADS)

Suzuki, Tomonori; Miyazaki, Satoru

2010-01-01

Protein-protein interactions play many important roles in biological function. Knowledge of protein-protein complex structure is required for understanding the function. The determination of protein-protein complex structure by experimental studies remains difficult, therefore computational prediction of protein structures by structure modeling and docking studies is valuable method. In addition, MD simulation is also one of the most popular methods for protein structure modeling and characteristics. Here, we attempt to predict protein-protein complex structure and property using some of bioinformatic methods, and we focus botulinum toxin complex as target structure.

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.

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

PubMed

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

2012-12-24

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

In silico design of ligand triggered RNA switches.

PubMed

Findeiß, Sven; Hammer, Stefan; Wolfinger, Michael T; Kühnl, Felix; Flamm, Christoph; Hofacker, Ivo L

2018-04-13

This contribution sketches a work flow to design an RNA switch that is able to adapt two structural conformations in a ligand-dependent way. A well characterized RNA aptamer, i.,e., knowing its K d and adaptive structural features, is an essential ingredient of the described design process. We exemplify the principles using the well-known theophylline aptamer throughout this work. The aptamer in its ligand-binding competent structure represents one structural conformation of the switch while an alternative fold that disrupts the binding-competent structure forms the other conformation. To keep it simple we do not incorporate any regulatory mechanism to control transcription or translation. We elucidate a commonly used design process by explicitly dissecting and explaining the necessary steps in detail. We developed a novel objective function which specifies the mechanistics of this simple, ligand-triggered riboswitch and describe an extensive in silico analysis pipeline to evaluate important kinetic properties of the designed sequences. This protocol and the developed software can be easily extended or adapted to fit novel design scenarios and thus can serve as a template for future needs. Copyright © 2018. Published by Elsevier Inc.

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

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.

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.

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

PubMed

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

2016-01-01

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

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

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 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.

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.

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.

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

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.

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.

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.

Implementation of an ADME enabling selection and visualization tool for drug discovery.

PubMed

Stoner, Chad L; Gifford, Eric; Stankovic, Charles; Lepsy, Christopher S; Brodfuehrer, Joanne; Prasad, J V N Vara; Surendran, Narayanan

2004-05-01

The pharmaceutical industry has large investments in compound library enrichment, high throughput biological screening, and biopharmaceutical (ADME) screening. As the number of compounds submitted for in vitro ADME screens increases, data analysis, interpretation, and reporting will become rate limiting in providing ADME-structure-activity relationship information to guide the synthetic strategy for chemical series. To meet these challenges, a software tool was developed and implemented that enables scientists to explore in vitro and in silico ADME and chemistry data in a multidimensional framework. The present work integrates physicochemical and ADME data, encompassing results for Caco-2 permeability, human liver microsomal half-life, rat liver microsomal half-life, kinetic solubility, measured log P, rule of 5 descriptors (molecular weight, hydrogen bond acceptors, hydrogen bond donors, calculated log P), polar surface area, chemical stability, and CYP450 3A4 inhibition. To facilitate interpretation of this data, a semicustomized software solution using Spotfire was designed that allows for multidimensional data analysis and visualization. The solution also enables simultaneous viewing and export of chemical structures with the corresponding ADME properties, enabling a more facile analysis of ADME-structure-activity relationship. In vitro and in silico ADME data were generated for 358 compounds from a series of human immunodeficiency virus protease inhibitors, resulting in a data set of 5370 experimental values which were subsequently analyzed and visualized using the customized Spotfire application. Implementation of this analysis and visualization tool has accelerated the selection of molecules for further development based on optimum ADME characteristics, and provided medicinal chemistry with specific, data driven structural recommendations for improvements in the ADME profile. Copyright 2004 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 93: 1131-1141, 2004

UV-visible degradation of boscalid--structural characterization of photoproducts and potential toxicity using in silico tests.

PubMed

Lassalle, Yannick; Kinani, Aziz; Rifai, Ahmad; Souissi, Yasmine; Clavaguera, Carine; Bourcier, Sophie; Jaber, Farouk; Bouchonnet, Stéphane

2014-05-30

Boscalid is a carboximide fungicide mainly used for vineyard protection as well as for tomato, apple, blueberry and various ornamental cultivations. The structural elucidation of by-products arising from the UV-visible photodegradation of boscalid has been investigated by gas chromatography/multi-stage mass spectrometry (GC/MS(n) ) and liquid chromatography/tandem mass spectrometry (LC/MS/MS) couplings. The potential toxicities of transformation products were estimated by in silico calculations. Aqueous solutions of boscalid were irradiated up to 150 min in a self-made reactor equipped with a mercury lamp. Analyses were carried out using a gas chromatograph coupled with an ion trap mass spectrometer operated in both electron ionization (EI) and chemical ionization (CI) modes and a liquid chromatograph coupled with a quadrupole time-of-flight (Q-TOF) mass spectrometer operated in electrospray ionization (ESI) mode. Multiple-stage collision-induced dissociation (CID) experiments were performed to establish dissociation pathways of ions. The QSAR (Quantitative Structure-Activity Relationship) T.E.S.T. program allowed the estimation of the toxicities of the by-products. Eight photoproducts were investigated. Chemical structures were proposed not only on the interpretation of multi-stage CID experiments, but also on kinetics data. These structures led us to suggest photodegradation pathways. Three photoproducts were finally detected in Lebanon in a real sample of grape leaves for which routine analysis had led to the detection of boscalid at 4 mg kg(-1). With one exception, the structures proposed for the photoproducts on the basis of mass spectra interpretation have not been reported in previous studies. In silico toxicity predictions showed that two photoproducts are potentially more toxic than the parent compound considering oral rat LD50 while five photoproducts may induce mutagenic toxicity. With the exception of one compound, all photoproducts may potentially induce developmental toxicity. Copyright © 2014 John Wiley & Sons, Ltd.

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

In Silico Synthesis of Synthetic Receptors: A Polymerization Algorithm.

PubMed

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

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2010-02-01

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

In silico fragment-based drug design.

PubMed

Konteatis, Zenon D

2010-11-01

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

In silico 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.

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

PubMed

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

2007-12-01

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

Three dimensional electron microscopy and in silico tools for macromolecular structure determination

PubMed Central

Borkotoky, Subhomoi; Meena, Chetan Kumar; Khan, Mohammad Wahab; Murali, Ayaluru

2013-01-01

Recently, structural biology witnessed a major tool - electron microscopy - in solving the structures of macromolecules in addition to the conventional techniques, X-ray crystallography and nuclear magnetic resonance (NMR). Three dimensional transmission electron microscopy (3DTEM) is one of the most sophisticated techniques for structure determination of molecular machines. Known to give the 3-dimensional structures in its native form with literally no upper limit on size of the macromolecule, this tool does not need the crystallization of the protein. Combining the 3DTEM data with in silico tools, one can have better refined structure of a desired complex. In this review we are discussing about the recent advancements in three dimensional electron microscopy and tools associated with it. PMID:27092033

Nonlinear optical studies and structure-activity relationship of chalcone derivatives with in silico insights

NASA Astrophysics Data System (ADS)

Kar, Swayamsiddha; Adithya, K. S.; Shankar, Pruthvik; Jagadeesh Babu, N.; Srivastava, Sailesh; Nageswara Rao, G.

2017-07-01

Nine chalcones were prepared via Claisen-Schmidt condensation, and characterized by UV-vis, IR, 1H NMR, 13C NMR and mass spectrometry. One of the representative member 4-NDM-TC has been studied via single crystal XRD and the TGA/DTA technique. SHG efficiency and NLO susceptibilities of the chalcones have been evaluated by the Kurtz and Perry method and Degenerate Four Wave Mixing techniques respectively. 3-Cl-4‧-HC was noted to possess SHG efficiency 1.37 times that of urea while 4-NDM-TC returned the highest third order NLO susceptibilities with respect to CS2. In silico studies help evaluate various physical parameters, in correlating the observed activities. In conclusion, the structure-activity relationship was derived based on the in silico and experimental results for the third order NLO susceptibilities.

The Prediction of Botulinum Toxin Structure Based on in Silico and in Vitro Analysis

NASA Astrophysics Data System (ADS)

Suzuki, Tomonori; Miyazaki, Satoru

2011-01-01

Many of biological system mediated through protein-protein interactions. Knowledge of protein-protein complex structure is required for understanding the function. The determination of huge size and flexible protein-protein complex structure by experimental studies remains difficult, costly and five-consuming, therefore computational prediction of protein structures by homolog modeling and docking studies is valuable method. In addition, MD simulation is also one of the most powerful methods allowing to see the real dynamics of proteins. Here, we predict protein-protein complex structure of botulinum toxin to analyze its property. These bioinformatics methods are useful to report the relation between the flexibility of backbone structure and the activity.

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.

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.

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

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.

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.

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.

Structural elucidation of estrus urinary lipocalin protein (EULP) and evaluating binding affinity with pheromones using molecular docking and fluorescence study

PubMed Central

Rajesh, Durairaj; Muthukumar, Subramanian; Saibaba, Ganesan; Siva, Durairaj; Akbarsha, Mohammad Abdulkader; Gulyás, Balázs; Padmanabhan, Parasuraman; Archunan, Govindaraju

2016-01-01

Transportation of pheromones bound with carrier proteins belonging to lipocalin superfamily is known to prolong chemo-signal communication between individuals belonging to the same species. Members of lipocalin family (MLF) proteins have three structurally conserved motifs for delivery of hydrophobic molecules to the specific recognizer. However, computational analyses are critically required to validate and emphasize the sequence and structural annotation of MLF. This study focused to elucidate the evolution, structural documentation, stability and binding efficiency of estrus urinary lipocalin protein (EULP) with endogenous pheromones adopting in-silico and fluorescence study. The results revealed that: (i) EULP perhaps originated from fatty acid binding protein (FABP) revealed in evolutionary analysis; (ii) Dynamic simulation study shows that EULP is highly stable at below 0.45 Å of root mean square deviation (RMSD); (iii) Docking evaluation shows that EULP has higher binding energy with farnesol and 2-iso-butyl-3-methoxypyrazine (IBMP) than 2-naphthol; and (iv) Competitive binding and quenching assay revealed that purified EULP has good binding interaction with farnesol. Both, In-silico and experimental studies showed that EULP is an efficient binding partner to pheromones. The present study provides impetus to create a point mutation for increasing longevity of EULP to develop pheromone trap for rodent pest management. PMID:27782155

Structural elucidation of estrus urinary lipocalin protein (EULP) and evaluating binding affinity with pheromones using molecular docking and fluorescence study.

PubMed

Rajesh, Durairaj; Muthukumar, Subramanian; Saibaba, Ganesan; Siva, Durairaj; Akbarsha, Mohammad Abdulkader; Gulyás, Balázs; Padmanabhan, Parasuraman; Archunan, Govindaraju

2016-10-26

Transportation of pheromones bound with carrier proteins belonging to lipocalin superfamily is known to prolong chemo-signal communication between individuals belonging to the same species. Members of lipocalin family (MLF) proteins have three structurally conserved motifs for delivery of hydrophobic molecules to the specific recognizer. However, computational analyses are critically required to validate and emphasize the sequence and structural annotation of MLF. This study focused to elucidate the evolution, structural documentation, stability and binding efficiency of estrus urinary lipocalin protein (EULP) with endogenous pheromones adopting in-silico and fluorescence study. The results revealed that: (i) EULP perhaps originated from fatty acid binding protein (FABP) revealed in evolutionary analysis; (ii) Dynamic simulation study shows that EULP is highly stable at below 0.45 Å of root mean square deviation (RMSD); (iii) Docking evaluation shows that EULP has higher binding energy with farnesol and 2-iso-butyl-3-methoxypyrazine (IBMP) than 2-naphthol; and (iv) Competitive binding and quenching assay revealed that purified EULP has good binding interaction with farnesol. Both, In-silico and experimental studies showed that EULP is an efficient binding partner to pheromones. The present study provides impetus to create a point mutation for increasing longevity of EULP to develop pheromone trap for rodent pest management.

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.

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

Development of an artificial neural network model for risk assessment of skin sensitization using human cell line activation test, direct peptide reactivity assay, KeratinoSens™ and in silico structure alert parameter.

PubMed

Hirota, Morihiko; Ashikaga, Takao; Kouzuki, Hirokazu

2018-04-01

It is important to predict the potential of cosmetic ingredients to cause skin sensitization, and in accordance with the European Union cosmetic directive for the replacement of animal tests, several in vitro tests based on the adverse outcome pathway have been developed for hazard identification, such as the direct peptide reactivity assay, KeratinoSens™ and the human cell line activation test. Here, we describe the development of an artificial neural network (ANN) prediction model for skin sensitization risk assessment based on the integrated testing strategy concept, using direct peptide reactivity assay, KeratinoSens™, human cell line activation test and an in silico or structure alert parameter. We first investigated the relationship between published murine local lymph node assay EC3 values, which represent skin sensitization potency, and in vitro test results using a panel of about 134 chemicals for which all the required data were available. Predictions based on ANN analysis using combinations of parameters from all three in vitro tests showed a good correlation with local lymph node assay EC3 values. However, when the ANN model was applied to a testing set of 28 chemicals that had not been included in the training set, predicted EC3s were overestimated for some chemicals. Incorporation of an additional in silico or structure alert descriptor (obtained with TIMES-M or Toxtree software) in the ANN model improved the results. Our findings suggest that the ANN model based on the integrated testing strategy concept could be useful for evaluating the skin sensitization potential. Copyright © 2017 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 .

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.

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.

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.

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 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.

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

DOE PAGES

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

2017-04-09

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

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

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

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

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

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

PubMed

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

2017-04-09

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

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

PubMed Central

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

2017-01-01

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

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

PubMed

León, Darryl A; Cànaves, Jaume M

2003-12-01

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

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2016-11-15

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

Informing the Selection of Screening Hit Series with in Silico Absorption, Distribution, Metabolism, Excretion, and Toxicity Profiles.

PubMed

Sanders, John M; Beshore, Douglas C; Culberson, J Christopher; Fells, James I; Imbriglio, Jason E; Gunaydin, Hakan; Haidle, Andrew M; Labroli, Marc; Mattioni, Brian E; Sciammetta, Nunzio; Shipe, William D; Sheridan, Robert P; Suen, Linda M; Verras, Andreas; Walji, Abbas; Joshi, Elizabeth M; Bueters, Tjerk

2017-08-24

High-throughput screening (HTS) has enabled millions of compounds to be assessed for biological activity, but challenges remain in the prioritization of hit series. While biological, absorption, distribution, metabolism, excretion, and toxicity (ADMET), purity, and structural data are routinely used to select chemical matter for further follow-up, the scarcity of historical ADMET data for screening hits limits our understanding of early hit compounds. Herein, we describe a process that utilizes a battery of in-house quantitative structure-activity relationship (QSAR) models to generate in silico ADMET profiles for hit series to enable more complete characterizations of HTS chemical matter. These profiles allow teams to quickly assess hit series for desirable ADMET properties or suspected liabilities that may require significant optimization. Accordingly, these in silico data can direct ADMET experimentation and profoundly impact the progression of hit series. Several prospective examples are presented to substantiate the value of this approach.

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.

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.

Comprehensive Peptide Ion Structure Studies Using Ion Mobility Techniques: Part 1. An Advanced Protocol for Molecular Dynamics Simulations and Collision Cross-Section Calculation.

PubMed

Ghassabi Kondalaji, Samaneh; Khakinejad, Mahdiar; Tafreshian, Amirmahdi; J Valentine, Stephen

2017-05-01

Collision cross-section (CCS) measurements with a linear drift tube have been utilized to study the gas-phase conformers of a model peptide (acetyl-PAAAAKAAAAKAAAAKAAAAK). Extensive molecular dynamics (MD) simulations have been conducted to derive an advanced protocol for the generation of a comprehensive pool of in-silico structures; both higher energy and more thermodynamically stable structures are included to provide an unbiased sampling of conformational space. MD simulations at 300 K are applied to the in-silico structures to more accurately describe the gas-phase transport properties of the ion conformers including their dynamics. Different methods used previously for trajectory method (TM) CCS calculation employing the Mobcal software [1] are evaluated. A new method for accurate CCS calculation is proposed based on clustering and data mining techniques. CCS values are calculated for all in-silico structures, and those with matching CCS values are chosen as candidate structures. With this approach, more than 300 candidate structures with significant structural variation are produced; although no final gas-phase structure is proposed here, in a second installment of this work, gas-phase hydrogen deuterium exchange data will be utilized as a second criterion to select among these structures as well as to propose relative populations for these ion conformers. Here the need to increase conformer diversity and accurate CCS calculation is demonstrated and the advanced methods are discussed. Graphical Abstract ᅟ.

Comprehensive Peptide Ion Structure Studies Using Ion Mobility Techniques: Part 1. An Advanced Protocol for Molecular Dynamics Simulations and Collision Cross-Section Calculation

NASA Astrophysics Data System (ADS)

Ghassabi Kondalaji, Samaneh; Khakinejad, Mahdiar; Tafreshian, Amirmahdi; J. Valentine, Stephen

2017-05-01

Collision cross-section (CCS) measurements with a linear drift tube have been utilized to study the gas-phase conformers of a model peptide (acetyl-PAAAAKAAAAKAAAAKAAAAK). Extensive molecular dynamics (MD) simulations have been conducted to derive an advanced protocol for the generation of a comprehensive pool of in-silico structures; both higher energy and more thermodynamically stable structures are included to provide an unbiased sampling of conformational space. MD simulations at 300 K are applied to the in-silico structures to more accurately describe the gas-phase transport properties of the ion conformers including their dynamics. Different methods used previously for trajectory method (TM) CCS calculation employing the Mobcal software [1] are evaluated. A new method for accurate CCS calculation is proposed based on clustering and data mining techniques. CCS values are calculated for all in-silico structures, and those with matching CCS values are chosen as candidate structures. With this approach, more than 300 candidate structures with significant structural variation are produced; although no final gas-phase structure is proposed here, in a second installment of this work, gas-phase hydrogen deuterium exchange data will be utilized as a second criterion to select among these structures as well as to propose relative populations for these ion conformers. Here the need to increase conformer diversity and accurate CCS calculation is demonstrated and the advanced methods are discussed.

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.

In silico genotoxicity of coumarins: application of the Phenol-Explorer food database to functional food science.

PubMed

Guardado Yordi, E; Matos, M J; Pérez Martínez, A; Tornes, A C; Santana, L; Molina, E; Uriarte, E

2017-08-01

Coumarins are a group of phytochemicals that may be beneficial or harmful to health depending on their type and dosage and the matrix that contains them. Some of these compounds have been proven to display pro-oxidant and clastogenic activities. Therefore, in the current work, we have studied the coumarins that are present in food sources extracted from the Phenol-Explorer database in order to predict their clastogenic activity and identify the structure-activity relationships and genotoxic structural alerts using alternative methods in the field of computational toxicology. It was necessary to compile information on the type and amount of coumarins in different food sources through the analysis of databases of food composition available online. A virtual screening using a clastogenic model and different software, such as MODESLAB, ChemDraw and STATISTIC, was performed. As a result, a table of food composition was prepared and qualitative information from this data was extracted. The virtual screening showed that the esterified substituents inactivate molecules, while the methoxyl and hydroxyl substituents contribute to their activity and constitute, together with the basic structures of the studied subclasses, clastogenic structural alerts. Chemical subclasses of simple coumarins and furocoumarins were classified as active (xanthotoxin, isopimpinellin, esculin, scopoletin, scopolin and bergapten). In silico genotoxicity was mainly predicted for coumarins found in beer, sherry, dried parsley, fresh parsley and raw celery stalks. The results obtained can be interesting for the future design of functional foods and dietary supplements. These studies constitute a reference for the genotoxic chemoinformatic analysis of bioactive compounds present in databases of food composition.

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.

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

PubMed

Tyagi, Sadhna; Pleiss, Juergen

2006-06-25

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

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

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

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

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.

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

Efficient HIV-1 inhibition by a 16 nt-long RNA aptamer designed by combining in vitro selection and in silico optimisation strategies

PubMed Central

Sánchez-Luque, Francisco J.; Stich, Michael; Manrubia, Susanna; Briones, Carlos; Berzal-Herranz, Alfredo

2014-01-01

The human immunodeficiency virus type-1 (HIV-1) genome contains multiple, highly conserved structural RNA domains that play key roles in essential viral processes. Interference with the function of these RNA domains either by disrupting their structures or by blocking their interaction with viral or cellular factors may seriously compromise HIV-1 viability. RNA aptamers are amongst the most promising synthetic molecules able to interact with structural domains of viral genomes. However, aptamer shortening up to their minimal active domain is usually necessary for scaling up production, what requires very time-consuming, trial-and-error approaches. Here we report on the in vitro selection of 64 nt-long specific aptamers against the complete 5′-untranslated region of HIV-1 genome, which inhibit more than 75% of HIV-1 production in a human cell line. The analysis of the selected sequences and structures allowed for the identification of a highly conserved 16 nt-long stem-loop motif containing a common 8 nt-long apical loop. Based on this result, an in silico designed 16 nt-long RNA aptamer, termed RNApt16, was synthesized, with sequence 5′-CCCCGGCAAGGAGGGG-3′. The HIV-1 inhibition efficiency of such an aptamer was close to 85%, thus constituting the shortest RNA molecule so far described that efficiently interferes with HIV-1 replication. PMID:25175101

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

PubMed

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

2015-08-14

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

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

PubMed

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

2018-01-01

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

Transcripts with in silico predicted RNA structure are enriched everywhere in the mouse brain

PubMed Central

2012-01-01

Background Post-transcriptional control of gene expression is mostly conducted by specific elements in untranslated regions (UTRs) of mRNAs, in collaboration with specific binding proteins and RNAs. In several well characterized cases, these RNA elements are known to form stable secondary structures. RNA secondary structures also may have major functional implications for long noncoding RNAs (lncRNAs). Recent transcriptional data has indicated the importance of lncRNAs in brain development and function. However, no methodical efforts to investigate this have been undertaken. Here, we aim to systematically analyze the potential for RNA structure in brain-expressed transcripts. Results By comprehensive spatial expression analysis of the adult mouse in situ hybridization data of the Allen Mouse Brain Atlas, we show that transcripts (coding as well as non-coding) associated with in silico predicted structured probes are highly and significantly enriched in almost all analyzed brain regions. Functional implications of these RNA structures and their role in the brain are discussed in detail along with specific examples. We observe that mRNAs with a structure prediction in their UTRs are enriched for binding, transport and localization gene ontology categories. In addition, after manual examination we observe agreement between RNA binding protein interaction sites near the 3’ UTR structures and correlated expression patterns. Conclusions Our results show a potential use for RNA structures in expressed coding as well as noncoding transcripts in the adult mouse brain, and describe the role of structured RNAs in the context of intracellular signaling pathways and regulatory networks. Based on this data we hypothesize that RNA structure is widely involved in transcriptional and translational regulatory mechanisms in the brain and ultimately plays a role in brain function. PMID:22651826

Evolving phenotypic networks in silico.

PubMed

François, Paul

2014-11-01

Evolved gene networks are constrained by natural selection. Their structures and functions are consequently far from being random, as exemplified by the multiple instances of parallel/convergent evolution. One can thus ask if features of actual gene networks can be recovered from evolutionary first principles. I review a method for in silico evolution of small models of gene networks aiming at performing predefined biological functions. I summarize the current implementation of the algorithm, insisting on the construction of a proper "fitness" function. I illustrate the approach on three examples: biochemical adaptation, ligand discrimination and vertebrate segmentation (somitogenesis). While the structure of the evolved networks is variable, dynamics of our evolved networks are usually constrained and present many similar features to actual gene networks, including properties that were not explicitly selected for. In silico evolution can thus be used to predict biological behaviours without a detailed knowledge of the mapping between genotype and phenotype. Copyright © 2014 The Author. Published by Elsevier Ltd.. All rights reserved.

In silico Identification of Ergosterol as a Novel Fungal Metabolite Enhancing RuBisCO Activity in Lycopersicum esculentum.

PubMed

Mitra, Joyeeta; Narad, Priyanka; Sengupta, Abhishek; Sharma, P D; Paul, P K

2016-09-01

RuBisCO (EC 4.1.1.39), a key enzyme found in stroma of chloroplast, is important for fixing atmospheric CO2 in plants. Alterations in the activity of RuBisCO could influence photosynthetic yield. Therefore, to understand the activity of the protein, knowledge about its structure is pertinent. Though the structure of Nicotiana RuBisCO has been modeled, the structure of tomato RuBisCO is still unknown. RuBisCO extracted from chloroplasts of tomato leaves was subjected to MALDI-TOF-TOF followed by Mascot Search. The protein sequence based on gene identification numbers was subjected to in silico model construction, characterization and docking studies. The primary structure analysis revealed that protein was stable, neutral, hydrophilic and has an acidic pI. The result though indicates a 90 % homology with other members of Solanaceae but differs from the structure of Arabidopsis RuBisCO. Different ligands were docked to assess the activity of RuBisCO against these metabolite components. Out of the number of modulators tested, ergosterol had the maximum affinity (E = -248.08) with RuBisCO. Ergosterol is a major cell wall component of fungi and has not been reported to be naturally found in plants. It is a known immune elicitor in plants. The current study throws light on its role in affecting RuBisCO activity in plants, thereby bringing changes in the photosynthetic rate.

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

PubMed

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

2016-01-01

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

Ligation site in proteins recognized in silico

PubMed Central

Brylinski, Michal; Konieczny, Leszek; Roterman, Irena

2006-01-01

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

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

PubMed

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

2016-01-01

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

In silico modeling to predict drug-induced phospholipidosis

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

Choi, Sydney S.; Kim, Jae S.; Valerio, Luis G., E-mail: luis.valerio@fda.hhs.gov

2013-06-01

Drug-induced phospholipidosis (DIPL) is a preclinical finding during pharmaceutical drug development that has implications on the course of drug development and regulatory safety review. A principal characteristic of drugs inducing DIPL is known to be a cationic amphiphilic structure. This provides evidence for a structure-based explanation and opportunity to analyze properties and structures of drugs with the histopathologic findings for DIPL. In previous work from the FDA, in silico quantitative structure–activity relationship (QSAR) modeling using machine learning approaches has shown promise with a large dataset of drugs but included unconfirmed data as well. In this study, we report the constructionmore » and validation of a battery of complementary in silico QSAR models using the FDA's updated database on phospholipidosis, new algorithms and predictive technologies, and in particular, we address high performance with a high-confidence dataset. The results of our modeling for DIPL include rigorous external validation tests showing 80–81% concordance. Furthermore, the predictive performance characteristics include models with high sensitivity and specificity, in most cases above ≥ 80% leading to desired high negative and positive predictivity. These models are intended to be utilized for regulatory toxicology applied science needs in screening new drugs for DIPL. - Highlights: • New in silico models for predicting drug-induced phospholipidosis (DIPL) are described. • The training set data in the models is derived from the FDA's phospholipidosis database. • We find excellent predictivity values of the models based on external validation. • The models can support drug screening and regulatory decision-making on DIPL.« less

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.

In Silico and In Vitro Investigations of the Mutability of Disease-Causing Missense Mutation Sites in Spermine Synthase

PubMed Central

Zhang, Zhe; Norris, Joy; Schwartz, Charles; Alexov, Emil

2011-01-01

Background Spermine synthase (SMS) is a key enzyme controlling the concentration of spermidine and spermine in the cell. The importance of SMS is manifested by the fact that single missense mutations were found to cause Snyder-Robinson Syndrome (SRS). At the same time, currently there are no non-synonymous single nucleoside polymorphisms, nsSNPs (harmless mutations), found in SMS, which may imply that the SMS does not tolerate amino acid substitutions, i.e. is not mutable. Methodology/Principal Findings To investigate the mutability of the SMS, we carried out in silico analysis and in vitro experiments of the effects of amino acid substitutions at the missense mutation sites (G56, V132 and I150) that have been shown to cause SRS. Our investigation showed that the mutation sites have different degree of mutability depending on their structural micro-environment and involvement in the function and structural integrity of the SMS. It was found that the I150 site does not tolerate any mutation, while V132, despite its key position at the interface of SMS dimer, is quite mutable. The G56 site is in the middle of the spectra, but still quite sensitive to charge residue replacement. Conclusions/Significance The performed analysis showed that mutability depends on the detail of the structural and functional factors and cannot be predicted based on conservation of wild type properties alone. Also, harmless nsSNPs can be expected to occur even at sites at which missense mutations were found to cause diseases. PMID:21647366

PEGylated substrates of NSP4 protease: A tool to study protease specificity

NASA Astrophysics Data System (ADS)

Wysocka, Magdalena; Gruba, Natalia; Grzywa, Renata; Giełdoń, Artur; Bąchor, Remigiusz; Brzozowski, Krzysztof; Sieńczyk, Marcin; Dieter, Jenne; Szewczuk, Zbigniew; Rolka, Krzysztof; Lesner, Adam

2016-03-01

Herein we present the synthesis of a novel type of peptidomimetics composed of repeating diaminopropionic acid residues modified with structurally diverse heterobifunctional polyethylene glycol chains (abbreviated as DAPEG). Based on the developed compounds, a library of fluorogenic substrates was synthesized. Further library deconvolution towards human neutrophil serine protease 4 (NSP4) yielded highly sensitive and selective internally quenched peptidomimetic substrates. In silico analysis of the obtained peptidomimetics revealed the presence of an interaction network with distant subsites located on the enzyme surface.

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

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

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 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.

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.

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.

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.

In Silico Analysis of Single Nucleotide Polymorphism (SNPs) in Human β-Globin Gene

PubMed Central

Alanazi, Mohammed; Abduljaleel, Zainularifeen; Khan, Wajahatullah; Warsy, Arjumand S.; Elrobh, Mohamed; Khan, Zahid; Amri, Abdullah Al; Bazzi, Mohammad D.

2011-01-01

Single amino acid substitutions in the globin chain are the most common forms of genetic variations that produce hemoglobinopathies- the most widespread inherited disorders worldwide. Several hemoglobinopathies result from homozygosity or compound heterozygosity to beta-globin (HBB) gene mutations, such as that producing sickle cell hemoglobin (HbS), HbC, HbD and HbE. Several of these mutations are deleterious and result in moderate to severe hemolytic anemia, with associated complications, requiring lifelong care and management. Even though many hemoglobinopathies result from single amino acid changes producing similar structural abnormalities, there are functional differences in the generated variants. Using in silico methods, we examined the genetic variations that can alter the expression and function of the HBB gene. Using a sequence homology-based Sorting Intolerant from Tolerant (SIFT) server we have searched for the SNPs, which showed that 200 (80%) non-synonymous polymorphism were found to be deleterious. The structure-based method via PolyPhen server indicated that 135 (40%) non-synonymous polymorphism may modify protein function and structure. The Pupa Suite software showed that the SNPs will have a phenotypic consequence on the structure and function of the altered protein. Structure analysis was performed on the key mutations that occur in the native protein coded by the HBB gene that causes hemoglobinopathies such as: HbC (E→K), HbD (E→Q), HbE (E→K) and HbS (E→V). Atomic Non-Local Environment Assessment (ANOLEA), Yet Another Scientific Artificial Reality Application (YASARA), CHARMM-GUI webserver for macromolecular dynamics and mechanics, and Normal Mode Analysis, Deformation and Refinement (NOMAD-Ref) of Gromacs server were used to perform molecular dynamics simulations and energy minimization calculations on β-Chain residue of the HBB gene before and after mutation. Furthermore, in the native and altered protein models, amino acid residues were determined and secondary structures were observed for solvent accessibility to confirm the protein stability. The functional study in this investigation may be a good model for additional future studies. PMID:22028795

In Silico Identification Software (ISIS): A Machine Learning Approach to Tandem Mass Spectral Identification of Lipids

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

Kangas, Lars J.; Metz, Thomas O.; Isaac, Georgis

2012-05-15

Liquid chromatography-mass spectrometry-based metabolomics has gained importance in the life sciences, yet it is not supported by software tools for high throughput identification of metabolites based on their fragmentation spectra. An algorithm (ISIS: in silico identification software) and its implementation are presented and show great promise in generating in silico spectra of lipids for the purpose of structural identification. Instead of using chemical reaction rate equations or rules-based fragmentation libraries, the algorithm uses machine learning to find accurate bond cleavage rates in a mass spectrometer employing collision-induced dissocia-tion tandem mass spectrometry. A preliminary test of the algorithm with 45 lipidsmore » from a subset of lipid classes shows both high sensitivity and specificity.« less

Principles and Overview of Sampling Methods for Modeling Macromolecular Structure and Dynamics

PubMed Central

Moffatt, Ryan; Ma, Buyong; Nussinov, Ruth

2016-01-01

Investigation of macromolecular structure and dynamics is fundamental to understanding how macromolecules carry out their functions in the cell. Significant advances have been made toward this end in silico, with a growing number of computational methods proposed yearly to study and simulate various aspects of macromolecular structure and dynamics. This review aims to provide an overview of recent advances, focusing primarily on methods proposed for exploring the structure space of macromolecules in isolation and in assemblies for the purpose of characterizing equilibrium structure and dynamics. In addition to surveying recent applications that showcase current capabilities of computational methods, this review highlights state-of-the-art algorithmic techniques proposed to overcome challenges posed in silico by the disparate spatial and time scales accessed by dynamic macromolecules. This review is not meant to be exhaustive, as such an endeavor is impossible, but rather aims to balance breadth and depth of strategies for modeling macromolecular structure and dynamics for a broad audience of novices and experts. PMID:27124275

Principles and Overview of Sampling Methods for Modeling Macromolecular Structure and Dynamics.

PubMed

Maximova, Tatiana; Moffatt, Ryan; Ma, Buyong; Nussinov, Ruth; Shehu, Amarda

2016-04-01

Investigation of macromolecular structure and dynamics is fundamental to understanding how macromolecules carry out their functions in the cell. Significant advances have been made toward this end in silico, with a growing number of computational methods proposed yearly to study and simulate various aspects of macromolecular structure and dynamics. This review aims to provide an overview of recent advances, focusing primarily on methods proposed for exploring the structure space of macromolecules in isolation and in assemblies for the purpose of characterizing equilibrium structure and dynamics. In addition to surveying recent applications that showcase current capabilities of computational methods, this review highlights state-of-the-art algorithmic techniques proposed to overcome challenges posed in silico by the disparate spatial and time scales accessed by dynamic macromolecules. This review is not meant to be exhaustive, as such an endeavor is impossible, but rather aims to balance breadth and depth of strategies for modeling macromolecular structure and dynamics for a broad audience of novices and experts.

In silico insights into protein-protein interactions and folding dynamics of the saposin-like domain of Solanum tuberosum aspartic protease.

PubMed

De Moura, Dref C; Bryksa, Brian C; Yada, Rickey Y

2014-01-01

The plant-specific insert is an approximately 100-residue domain found exclusively within the C-terminal lobe of some plant aspartic proteases. Structurally, this domain is a member of the saposin-like protein family, and is involved in plant pathogen defense as well as vacuolar targeting of the parent protease molecule. Similar to other members of the saposin-like protein family, most notably saposins A and C, the recently resolved crystal structure of potato (Solanum tuberosum) plant-specific insert has been shown to exist in a substrate-bound open conformation in which the plant-specific insert oligomerizes to form homodimers. In addition to the open structure, a closed conformation also exists having the classic saposin fold of the saposin-like protein family as observed in the crystal structure of barley (Hordeum vulgare L.) plant-specific insert. In the present study, the mechanisms of tertiary and quaternary conformation changes of potato plant-specific insert were investigated in silico as a function of pH. Umbrella sampling and determination of the free energy change of dissociation of the plant-specific insert homodimer revealed that increasing the pH of the system to near physiological levels reduced the free energy barrier to dissociation. Furthermore, principal component analysis was used to characterize conformational changes at both acidic and neutral pH. The results indicated that the plant-specific insert may adopt a tertiary structure similar to the characteristic saposin fold and suggest a potential new structural motif among saposin-like proteins. To our knowledge, this acidified PSI structure presents the first example of an alternative saposin-fold motif for any member of the large and diverse SAPLIP family.

In Silico Insights into Protein-Protein Interactions and Folding Dynamics of the Saposin-Like Domain of Solanum tuberosum Aspartic Protease

PubMed Central

De Moura, Dref C.; Bryksa, Brian C.; Yada, Rickey Y.

2014-01-01

The plant-specific insert is an approximately 100-residue domain found exclusively within the C-terminal lobe of some plant aspartic proteases. Structurally, this domain is a member of the saposin-like protein family, and is involved in plant pathogen defense as well as vacuolar targeting of the parent protease molecule. Similar to other members of the saposin-like protein family, most notably saposins A and C, the recently resolved crystal structure of potato (Solanum tuberosum) plant-specific insert has been shown to exist in a substrate-bound open conformation in which the plant-specific insert oligomerizes to form homodimers. In addition to the open structure, a closed conformation also exists having the classic saposin fold of the saposin-like protein family as observed in the crystal structure of barley (Hordeum vulgare L.) plant-specific insert. In the present study, the mechanisms of tertiary and quaternary conformation changes of potato plant-specific insert were investigated in silico as a function of pH. Umbrella sampling and determination of the free energy change of dissociation of the plant-specific insert homodimer revealed that increasing the pH of the system to near physiological levels reduced the free energy barrier to dissociation. Furthermore, principal component analysis was used to characterize conformational changes at both acidic and neutral pH. The results indicated that the plant-specific insert may adopt a tertiary structure similar to the characteristic saposin fold and suggest a potential new structural motif among saposin-like proteins. To our knowledge, this acidified PSI structure presents the first example of an alternative saposin-fold motif for any member of the large and diverse SAPLIP family. PMID:25188221

Proteins and Their Interacting Partners: An Introduction to Protein-Ligand Binding Site Prediction Methods.

PubMed

Roche, Daniel Barry; Brackenridge, Danielle Allison; McGuffin, Liam James

2015-12-15

Elucidating the biological and biochemical roles of proteins, and subsequently determining their interacting partners, can be difficult and time consuming using in vitro and/or in vivo methods, and consequently the majority of newly sequenced proteins will have unknown structures and functions. However, in silico methods for predicting protein-ligand binding sites and protein biochemical functions offer an alternative practical solution. The characterisation of protein-ligand binding sites is essential for investigating new functional roles, which can impact the major biological research spheres of health, food, and energy security. In this review we discuss the role in silico methods play in 3D modelling of protein-ligand binding sites, along with their role in predicting biochemical functionality. In addition, we describe in detail some of the key alternative in silico prediction approaches that are available, as well as discussing the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated Model EvaluatiOn (CAMEO) projects, and their impact on developments in the field. Furthermore, we discuss the importance of protein function prediction methods for tackling 21st century problems.

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

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.

Flux analysis and metabolomics for systematic metabolic engineering of microorganisms.

PubMed

Toya, Yoshihiro; Shimizu, Hiroshi

2013-11-01

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

In silico gene expression analysis – an overview

PubMed Central

Murray, David; Doran, Peter; MacMathuna, Padraic; Moss, Alan C

2007-01-01

Efforts aimed at deciphering the molecular basis of complex disease are underpinned by the availability of high throughput strategies for the identification of biomolecules that drive the disease process. The completion of the human genome-sequencing project, coupled to major technological developments, has afforded investigators myriad opportunities for multidimensional analysis of biological systems. Nowhere has this research explosion been more evident than in the field of transcriptomics. Affordable access and availability to the technology that supports such investigations has led to a significant increase in the amount of data generated. As most biological distinctions are now observed at a genomic level, a large amount of expression information is now openly available via public databases. Furthermore, numerous computational based methods have been developed to harness the power of these data. In this review we provide a brief overview of in silico methodologies for the analysis of differential gene expression such as Serial Analysis of Gene Expression and Digital Differential Display. The performance of these strategies, at both an operational and result/output level is assessed and compared. The key considerations that must be made when completing an in silico expression analysis are also presented as a roadmap to facilitate biologists. Furthermore, to highlight the importance of these in silico methodologies in contemporary biomedical research, examples of current studies using these approaches are discussed. The overriding goal of this review is to present the scientific community with a critical overview of these strategies, so that they can be effectively added to the tool box of biomedical researchers focused on identifying the molecular mechanisms of disease. PMID:17683638

Molecular identification of aiiA homologous gene from endophytic Enterobacter species and in silico analysis of putative tertiary structure of AHL-lactonase.

PubMed

Rajesh, P S; Rai, V Ravishankar

2014-01-03

The aiiA homologous gene known to encode AHL- lactonase enzyme which hydrolyze the N-acylhomoserine lactone (AHL) quorum sensing signaling molecules produced by Gram negative bacteria. In this study, the degradation of AHL molecules was determined by cell-free lysate of endophytic Enterobacter species. The percentage of quorum quenching was confirmed and quantified by HPLC method (p<0.0001). Amplification and sequence BLAST analysis showed the presence of aiiA homologous gene in endophytic Enterobacter asburiae VT65, Enterobacter aerogenes VT66 and Enterobacter ludwigii VT70 strains. Sequence alignment analysis revealed the presence of two zinc binding sites, "HXHXDH" motif as well as tyrosine residue at the position 194. Based on known template available at Swiss-Model, putative tertiary structure of AHL-lactonase was constructed. The result showed that novel endophytic strains of Enterobacter genera encode the novel aiiA homologous gene and its structural importance for future study. Copyright © 2013 Elsevier Inc. All rights reserved.

In silico toxicology for the pharmaceutical sciences

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

Valerio, Luis G., E-mail: Luis.Valerio@fda.hhs.go

2009-12-15

The applied use of in silico technologies (a.k.a. computational toxicology, in silico toxicology, computer-assisted tox, e-tox, i-drug discovery, predictive ADME, etc.) for predicting preclinical toxicological endpoints, clinical adverse effects, and metabolism of pharmaceutical substances has become of high interest to the scientific community and the public. The increased accessibility of these technologies for scientists and recent regulations permitting their use for chemical risk assessment supports this notion. The scientific community is interested in the appropriate use of such technologies as a tool to enhance product development and safety of pharmaceuticals and other xenobiotics, while ensuring the reliability and accuracy ofmore » in silico approaches for the toxicological and pharmacological sciences. For pharmaceutical substances, this means active and impurity chemicals in the drug product may be screened using specialized software and databases designed to cover these substances through a chemical structure-based screening process and algorithm specific to a given software program. A major goal for use of these software programs is to enable industry scientists not only to enhance the discovery process but also to ensure the judicious use of in silico tools to support risk assessments of drug-induced toxicities and in safety evaluations. However, a great amount of applied research is still needed, and there are many limitations with these approaches which are described in this review. Currently, there is a wide range of endpoints available from predictive quantitative structure-activity relationship models driven by many different computational software programs and data sources, and this is only expected to grow. For example, there are models based on non-proprietary and/or proprietary information specific to assessing potential rodent carcinogenicity, in silico screens for ICH genetic toxicity assays, reproductive and developmental toxicity, theoretical prediction of human drug metabolism, mechanisms of action for pharmaceuticals, and newer models for predicting human adverse effects. How accurate are these approaches is both a statistical issue and challenge in toxicology. In this review, fundamental concepts and the current capabilities and limitations of this technology will be critically addressed.« less

IN SILICO MODELLING OF HAZARDOUS ENDPOINTS: CURRENT PROBLEMS AND PROSPECTIVES

EPA Science Inventory

The primary hurdles for Quantitative Structure-Activity Relationships (QSARs) to overcome their acceptance for regulatory purposes will be discussed. They include (a) the development of more mechanistic representations of chemical structure, (b) the classification of toxicity pa...

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.

BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling.

PubMed

Feng, Song; Ollivier, Julien F; Swain, Peter S; Soyer, Orkun S

2015-10-30

Systems biologists aim to decipher the structure and dynamics of signaling and regulatory networks underpinning cellular responses; synthetic biologists can use this insight to alter existing networks or engineer de novo ones. Both tasks will benefit from an understanding of which structural and dynamic features of networks can emerge from evolutionary processes, through which intermediary steps these arise, and whether they embody general design principles. As natural evolution at the level of network dynamics is difficult to study, in silico evolution of network models can provide important insights. However, current tools used for in silico evolution of network dynamics are limited to ad hoc computer simulations and models. Here we introduce BioJazz, an extendable, user-friendly tool for simulating the evolution of dynamic biochemical networks. Unlike previous tools for in silico evolution, BioJazz allows for the evolution of cellular networks with unbounded complexity by combining rule-based modeling with an encoding of networks that is akin to a genome. We show that BioJazz can be used to implement biologically realistic selective pressures and allows exploration of the space of network architectures and dynamics that implement prescribed physiological functions. BioJazz is provided as an open-source tool to facilitate its further development and use. Source code and user manuals are available at: http://oss-lab.github.io/biojazz and http://osslab.lifesci.warwick.ac.uk/BioJazz.aspx. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

ACFIS: a web server for fragment-based drug discovery

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-07-08

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

DG-AMMOS: a new tool to generate 3d conformation of small molecules using distance geometry and automated molecular mechanics optimization for in silico screening.

PubMed

Lagorce, David; Pencheva, Tania; Villoutreix, Bruno O; Miteva, Maria A

2009-11-13

Discovery of new bioactive molecules that could enter drug discovery programs or that could serve as chemical probes is a very complex and costly endeavor. Structure-based and ligand-based in silico screening approaches are nowadays extensively used to complement experimental screening approaches in order to increase the effectiveness of the process and facilitating the screening of thousands or millions of small molecules against a biomolecular target. Both in silico screening methods require as input a suitable chemical compound collection and most often the 3D structure of the small molecules has to be generated since compounds are usually delivered in 1D SMILES, CANSMILES or in 2D SDF formats. Here, we describe the new open source program DG-AMMOS which allows the generation of the 3D conformation of small molecules using Distance Geometry and their energy minimization via Automated Molecular Mechanics Optimization. The program is validated on the Astex dataset, the ChemBridge Diversity database and on a number of small molecules with known crystal structures extracted from the Cambridge Structural Database. A comparison with the free program Balloon and the well-known commercial program Omega generating the 3D of small molecules is carried out. The results show that the new free program DG-AMMOS is a very efficient 3D structure generator engine. DG-AMMOS provides fast, automated and reliable access to the generation of 3D conformation of small molecules and facilitates the preparation of a compound collection prior to high-throughput virtual screening computations. The validation of DG-AMMOS on several different datasets proves that generated structures are generally of equal quality or sometimes better than structures obtained by other tested methods.

Experimental verification, and domain definition, of structural alerts for protein binding: epoxides, lactones, nitroso, nitros, aldehydes and ketones.

PubMed

Nelms, M D; Cronin, M T D; Schultz, T W; Enoch, S J

2013-01-01

This study outlines how a combination of in chemico and Tetrahymena pyriformis data can be used to define the applicability domain of selected structural alerts within the profilers of the OECD QSAR Toolbox. Thirty-three chemicals were profiled using the OECD and OASIS profilers, enabling the applicability domain of six structural alerts to be defined, the alerts being: epoxides, lactones, nitrosos, nitros, aldehydes and ketones. Analysis of the experimental data showed the applicability domains for the epoxide, nitroso, aldehyde and ketone structural alerts to be well defined. In contrast, the data showed the applicability domains for the lactone and nitro structural alerts needed modifying. The accurate definition of the applicability domain for structural alerts within in silico profilers is important due to their use in the chemical category in predictive and regulatory toxicology. This study highlights the importance of utilizing multiple profilers in category formation.

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

PubMed

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

2013-01-01

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

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

PubMed Central

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

2013-01-01

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

Genomic characterization of EmsB microsatellite loci in Echinococcus multilocularis.

PubMed

Valot, Benoît; Knapp, Jenny; Umhang, Gérald; Grenouillet, Frédéric; Millon, Laurence

2015-06-01

EmsB is a molecular marker applied to Echinococcus multilocularis genotyping studies. This marker has largely been used to investigate the epidemiology of the parasite in different endemic foci. The present study has lifted the veil on the genetic structure of this microsatellite. By in silico analysis on the E. multilocularis genome the microsatellite was described in about 40 copies on the chromosome 5 of the parasite. Similar structure was found in the relative parasite Echinococcus granulosus, where the microsatellite was firstly described. The present study completes the first investigations made on the EmsB microsatellite origins and confirms the reliability of this highly discriminant molecular marker. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

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.

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.

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

PubMed

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

2018-03-01

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

In vitro pepsin resistance of proteins: Effect of non-reduced SDS-PAGE analysis on fragment observation.

PubMed

Pickles, Juliette; Rafiq, Samera; Cochrane, Stella A; Lalljie, Anja

2014-01-01

The introduction of novel proteins to food products carries with it the need to assess the potential allergenicity of such materials. Resistance to in vitro pepsin digestion is one parameter considered in such a risk assessment using a weight of evidence approach; however, the methodology used to investigate this has not been fully standardised. In vitro pepsin resistance assays typically involve SDS-PAGE performed under reducing conditions, with limited published data available on the assay using non-reducing conditions despite the need to consider non-reducing analysis techniques having been highlighted by regulatory bodies such as the European Food Safety Authority (EFSA). The purpose of the work reported here was to investigate the applicability of (and additional insight provided by) non-reducing analyses, by digesting a set of proteins using a ring-trial validated method, with analysis by SDS-PAGE under both reducing and non-reducing conditions. In silico prediction of digest fragments was also investigated. Significant differences were observed between results under reduced and non-reduced conditions for proteins in which disulphide bonds have a major role in protein structure, such as ribulose 1,5-diphosphate carboxylase (RUBISCO) and bovine serum albumin. For proteins with no or few disulphide bonds, no significant differences were seen in the results. Structural information such as disulphide bond numbers and positions should be considered during experimental design, as a non-reduced approach may be appropriate for some proteins. The in silico approach was a useful tool to suggest potential digest fragments, however the predictions were not always confirmed in vitro and should be considered a guide only.

Integrating in Silico and in Vitro Approaches To Predict Drug Accessibility to the Central Nervous System.

PubMed

Zhang, Yan-Yan; Liu, Houfu; Summerfield, Scott G; Luscombe, Christopher N; Sahi, Jasminder

2016-05-02

Estimation of uptake across the blood-brain barrier (BBB) is key to designing central nervous system (CNS) therapeutics. In silico approaches ranging from physicochemical rules to quantitative structure-activity relationship (QSAR) models are utilized to predict potential for CNS penetration of new chemical entities. However, there are still gaps in our knowledge of (1) the relationship between marketed human drug derived CNS-accessible chemical space and preclinical neuropharmacokinetic (neuroPK) data, (2) interpretability of the selected physicochemical descriptors, and (3) correlation of the in vitro human P-glycoprotein (P-gp) efflux ratio (ER) and in vivo rodent unbound brain-to-blood ratio (Kp,uu), as these are assays routinely used to predict clinical CNS exposure, during drug discovery. To close these gaps, we explored the CNS druglike property boundaries of 920 market oral drugs (315 CNS and 605 non-CNS) and 846 compounds (54 CNS drugs and 792 proprietary GlaxoSmithKline compounds) with available rat Kp,uu data. The exact permeability coefficient (Pexact) and P-gp ER were determined for 176 compounds from the rat Kp,uu data set. Receiver operating characteristic curves were performed to evaluate the predictive power of human P-gp ER for rat Kp,uu. Our data demonstrates that simple physicochemical rules (most acidic pKa ≥ 9.5 and TPSA < 100) in combination with P-gp ER < 1.5 provide mechanistic insights for filtering BBB permeable compounds. For comparison, six classification modeling methods were investigated using multiple sets of in silico molecular descriptors. We present a random forest model with excellent predictive power (∼0.75 overall accuracy) using the rat neuroPK data set. We also observed good concordance between the structural interpretation results and physicochemical descriptor importance from the Kp,uu classification QSAR model. In summary, we propose a novel, hybrid in silico/in vitro approach and an in silico screening model for the effective development of chemical series with the potential to achieve optimal CNS exposure.

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

Use of Molecular Dynamics for the Refinement of an Electrostatic Model for the In Silico Design of a Polymer Antidote for the Anticoagulant Fondaparinux

PubMed Central

Kwok, Ezra; Gopaluni, Bhushan; Kizhakkedathu, Jayachandran N.

2013-01-01

Molecular dynamics (MD) simulations results are herein incorporated into an electrostatic model used to determine the structure of an effective polymer-based antidote to the anticoagulant fondaparinux. In silico data for the polymer or its cationic binding groups has not, up to now, been available, and experimental data on the structure of the polymer-fondaparinux complex is extremely limited. Consequently, the task of optimizing the polymer structure is a daunting challenge. MD simulations provided a means to gain microscopic information on the interactions of the binding groups and fondaparinux that would have otherwise been inaccessible. This was used to refine the electrostatic model and improve the quantitative model predictions of binding affinity. Once refined, the model provided guidelines to improve electrostatic forces between candidate polymers and fondaparinux in order to increase association rate constants. PMID:27006916

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

PubMed

Dziuba, Bartłomiej; Dziuba, Marta

2014-08-20

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

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

PubMed Central

Dziuba, Bartłomiej; Dziuba, Marta

2014-01-01

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

The Disruptive Effect of Lysozyme on the Bacterial Cell Wall Explored by an "In-Silico" Structural Outlook

ERIC Educational Resources Information Center

Primo, Emiliano D.; Otero, Lisandro H.; Ruiz, Francisco; Klinke, Sebastián; Giordano, Walter

2018-01-01

The bacterial cell wall, a structural unit of peptidoglycan polymer comprised of glycan strands consisting of a repeating disaccharide motif [N-acetylglucosamine (NAG) and N-acetylmuramylpentapeptide (NAM pentapeptide)], encases bacteria and provides structural integrity and protection. Lysozymes are enzymes that break down the bacterial cell wall…

Structural models for the design of novel antiviral agents against Greek Goat Encephalitis

PubMed Central

Papageorgiou, Louis; Loukatou, Styliani; Koumandou, Vassiliki Lila; Makałowski, Wojciech; Megalooikonomou, Vasileios

2014-01-01

The Greek Goat Encephalitis virus (GGE) belongs to the Flaviviridae family of the genus Flavivirus. The GGE virus constitutes an important pathogen of livestock that infects the goat’s central nervous system. The viral enzymes of GGE, helicase and RNA-dependent RNA polymerase (RdRP), are ideal targets for inhibitor design, since those enzymes are crucial for the virus’ survival, proliferation and transmission. In an effort to understand the molecular structure underlying the functions of those viral enzymes, the three dimensional structures of GGE NS3 helicase and NS5 RdRP have been modelled. The models were constructed in silico using conventional homology modelling techniques and the known 3D crystal structures of solved proteins from closely related species as templates. The established structural models of the GGE NS3 helicase and NS5 RdRP have been evaluated for their viability using a repertoire of in silico tools. The goal of this study is to present the 3D conformations of the GGE viral enzymes as reliable structural models that could provide the platform for the design of novel anti-GGE agents. PMID:25392762

Discovery of novel Trypanosoma brucei phosphodiesterase B1 inhibitors by virtual screening against the unliganded TbrPDEB1 crystal structure

PubMed Central

Jansen, Chimed; Wang, Huanchen; Kooistra, Albert J.; de Graaf, Chris; Orrling, Kristina; Tenor, Hermann; Seebeck, Thomas; Bailey, David; de Esch, Iwan J.P.; Ke, Hengming; Leurs, Rob

2013-01-01

Trypanosoma brucei cyclic nucleotide phosphodiesterase B1 (TbrPDEB1) and TbrPDEB2 have recently been validated as new therapeutic targets for human African Trypanosomiasis by both genetic and pharmacological means. In this study we report the crystal structure of the catalytic domain of the unliganded TbrPDEB1 and its use for the in silico screening for new TbrPDEB1 inhibitors with novel scaffolds. The TbrPDEB1 crystal structure shows the characteristic folds of human PDE enzymes, but also contains the parasite-specific P-pocket found in the structures of Leishmania major PDEB1 and Trypanosoma cruzi PDEC. The unliganded TbrPDEB1 X-ray structure was subjected to a structure-based in silico screening approach that combines molecular docking simulations with a protein-ligand interaction fingerprint (IFP) scoring method. This approach identified, six novel TbrPDEB1 inhibitors with IC50 values of 10–80 μM, which may be further optimized as potential selective TbrPDEB inhibitors. PMID:23409953

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.

Towards unsupervised polyaromatic hydrocarbons structural assignment from SA-TIMS-FTMS data.

PubMed

Benigni, Paolo; Marin, Rebecca; Fernandez-Lima, Francisco

2015-10-01

With the advent of high resolution ion mobility analyzers and their coupling to ultrahigh resolution mass spectrometers, there is a need to further develop a theoretical workflow capable of correlating experimental accurate mass and mobility measurements with tridimensional candidate structures. In the present work, a general workflow is described for unsupervised tridimensional structural assignment based on accurate mass measurements, mobility measurements, in silico 2D-3D structure generation, and theoretical mobility calculations. In particular, the potential of this workflow will be shown for the analysis of polyaromatic hydrocarbons from Coal Tar SRM 1597a using selected accumulation - trapped ion mobility spectrometry (SA-TIMS) coupled to Fourier transform-ion cyclotron resonance mass spectrometry (FT-ICR MS). The proposed workflow can be adapted to different IMS scenarios, can utilize different collisional cross-section calculators and has the potential to include MS n and IMS n measurements for faster and more accurate tridimensional structural assignment.

In-silico analysis of gymnemagenin from Gymnema sylvestre (Retz.) R.Br. with targets related to diabetes.

PubMed

Rathore, Poonam K; Arathy, V; Attimarad, Vijaylaxmi S; Kumar, Pramod; Roy, Subarna

2016-02-21

Diabetes is a metabolic disorder characterized by higher than normal glucose in the blood. Most oral hypoglycemic drugs available in market produce adverse side effects which have resulted in continued search for new therapeutic agents with little or no side effects. Herbal drugs are considered relatively safer alternatives and Gymnema sylvestre is one of the most well established natural remedy for diabetes and is traded worldwide under several brands. In the present study an attempt has been made to use in silico techniques to understand and predict the drug likeliness of gymnemagenin, one of the key constituents of G. sylvestre against 15 proteins having key role in carbohydrate metabolism. Gymnemagenin was found to dock well with crystallographic structures of 7 of the 15 selected targets and was found even better than the two known clinically used antidiabetic compounds, repaglinide and sitagliptin taken in the study for comparison. Gymnemagenin therefore can be considered further for development into a potent anti-diabetic drug. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

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.

In silico Analysis of HIV-1 Env-gp120 Reveals Structural Bases for Viral Adaptation in Growth-Restrictive Cells

PubMed Central

Yokoyama, Masaru; Nomaguchi, Masako; Doi, Naoya; Kanda, Tadahito; Adachi, Akio; Sato, Hironori

2016-01-01

Variable V1/V2 and V3 loops on human immunodeficiency virus type 1 (HIV-1) envelope-gp120 core play key roles in modulating viral competence to recognize two infection receptors, CD4 and chemokine-receptors. However, molecular bases for the modulation largely remain unclear. To address these issues, we constructed structural models for a full-length gp120 in CD4-free and -bound states. The models showed topologies of gp120 surface loop that agree with those in reported structural data. Molecular dynamics simulation showed that in the unliganded state, V1/V2 loop settled into a thermodynamically stable arrangement near V3 loop for conformational masking of V3 tip, a potent neutralization epitope. In the CD4-bound state, however, V1/V2 loop was rearranged near the bound CD4 to support CD4 binding. In parallel, cell-based adaptation in the absence of anti-viral antibody pressures led to the identification of amino acid substitutions that individually enhance viral entry and growth efficiencies in association with reduced sensitivity to CCR5 antagonist TAK-779. Notably, all these substitutions were positioned on the receptors binding surfaces in V1/V2 or V3 loop. In silico structural studies predicted some physical changes of gp120 by substitutions with alterations in viral replication phenotypes. These data suggest that V1/V2 loop is critical for creating a gp120 structure that masks co-receptor binding site compatible with maintenance of viral infectivity, and for tuning a functional balance of gp120 between immune escape ability and infectivity to optimize HIV-1 replication fitness. PMID:26903989

Prediction of functionally significant single nucleotide polymorphisms in PTEN tumor suppressor gene: An in silico approach.

PubMed

Khan, Imran; Ansari, Irfan A; Singh, Pratichi; Dass J, Febin Prabhu

2017-09-01

The phosphatase and tensin homolog (PTEN) gene plays a crucial role in signal transduction by negatively regulating the PI3K signaling pathway. It is the most frequent mutated gene in many human-related cancers. Considering its critical role, a functional analysis of missense mutations of PTEN gene was undertaken in this study. Thirty five nonsynonymous single nucleotide polymorphisms (nsSNPs) within the coding region of the PTEN gene were selected for our in silico investigation, and five nsSNPs (G129E, C124R, D252G, H61D, and R130G) were found to be deleterious based on combinatorial predictions of different computational tools. Moreover, molecular dynamics (MD) simulation was performed to investigate the conformational variation between native and all the five mutant PTEN proteins having predicted deleterious nsSNPs. The results of MD simulation of all mutant models illustrated variation in structural attributes such as root-mean-square deviation, root-mean-square fluctuation, radius of gyration, and total energy; which depicts the structural stability of PTEN protein. Furthermore, mutant PTEN protein structures also showed a significant variation in the solvent accessible surface area and hydrogen bond frequencies from the native PTEN structure. In conclusion, results of this study have established the deleterious effect of the all the five predicted nsSNPs on the PTEN protein structure. Thus, results of the current study can pave a new platform to sort out nsSNPs that can be undertaken for the confirmation of their phenotype and their correlation with diseased status in case of control studies. © 2016 International Union of Biochemistry and Molecular Biology, Inc.

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

PubMed

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

2017-11-01

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

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.

In silico prediction of cytochrome P450-mediated drug metabolism.

PubMed

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

2011-06-01

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

In silico 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

Here, we present the in silico design of metal-organic frameworks (MOFs) exhibiting 1-dimensional rod topologies. We then introduce an algorithm for construction of this family of MOF topologies, and illustrate its application for enumerating MOF-74-type analogs. Furthermore, we perform a broad search for new linkers that satisfy the topological requirements of MOF-74 and consider the largest database of known chemical space for organic compounds, the PubChem database. Our in silico crystal assembly, when combined with dispersion-corrected density functional theory (DFT) calculations, is demonstrated to generate a hypothetical library of open-metal site containing MOF-74 analogs in the 1-D rod topology frommore » which we can simulate the adsorption behavior of CO 2 . We conclude that these hypothetical structures have synthesizable potential through computational identification and experimental validation of a novel MOF-74 analog, Mg 2 (olsalazine).« less

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

DOE PAGES

Witman, Matthew; Ling, Sanliang; Anderson, Samantha; ...

2016-06-21

Here, we present the in silico design of metal-organic frameworks (MOFs) exhibiting 1-dimensional rod topologies. We then introduce an algorithm for construction of this family of MOF topologies, and illustrate its application for enumerating MOF-74-type analogs. Furthermore, we perform a broad search for new linkers that satisfy the topological requirements of MOF-74 and consider the largest database of known chemical space for organic compounds, the PubChem database. Our in silico crystal assembly, when combined with dispersion-corrected density functional theory (DFT) calculations, is demonstrated to generate a hypothetical library of open-metal site containing MOF-74 analogs in the 1-D rod topology frommore » which we can simulate the adsorption behavior of CO 2 . We conclude that these hypothetical structures have synthesizable potential through computational identification and experimental validation of a novel MOF-74 analog, Mg 2 (olsalazine).« less

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

PubMed

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

2018-05-01

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

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.

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

PubMed

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

2017-03-15

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

Designing green derivatives of β-blocker Metoprolol: a tiered approach for green and sustainable pharmacy and chemistry.

PubMed

Rastogi, Tushar; Leder, Christoph; Kümmerer, Klaus

2014-09-01

The presences of micro-pollutants (active pharmaceutical ingredients, APIs) are increasingly seen as a challenge of the sustainable management of water resources worldwide due to ineffective effluent treatment and other measures for their input prevention. Therefore, novel approaches are needed like designing greener pharmaceuticals, i.e. better biodegradability in the environment. This study addresses a tiered approach of implementing green and sustainable chemistry principles for theoretically designing better biodegradable and pharmacologically improved pharmaceuticals. Photodegradation process coupled with LC-MS(n) analysis and in silico tools such as quantitative structure-activity relationships (QSAR) analysis and molecular docking proved to be a very significant approach for the preliminary stages of designing chemical structures that would fit into the "benign by design" concept in the direction of green and sustainable pharmacy. Metoprolol (MTL) was used as an example, which itself is not readily biodegradable under conditions found in sewage treatment and the aquatic environment. The study provides the theoretical design of new derivatives of MTL which might have the same or improved pharmacological activity and are more degradable in the environment than MTL. However, the in silico toxicity prediction by QSAR of those photo-TPs indicated few of them might be possibly mutagenic and require further testing. This novel approach of theoretically designing 'green' pharmaceuticals can be considered as a step forward towards the green and sustainable pharmacy field. However, more knowledge and further experience have to be collected on the full scope, opportunities and limitations of this approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

PubMed

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

2012-01-01

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

Cardio-vascular safety beyond hERG: in silico modelling of a guinea pig right atrium assay

NASA Astrophysics Data System (ADS)

Fenu, Luca A.; Teisman, Ard; De Buck, Stefan S.; Sinha, Vikash K.; Gilissen, Ron A. H. J.; Nijsen, Marjoleen J. M. A.; Mackie, Claire E.; Sanderson, Wendy E.

2009-12-01

As chemists can easily produce large numbers of new potential drug candidates, there is growing demand for high capacity models that can help in driving the chemistry towards efficacious and safe candidates before progressing towards more complex models. Traditionally, the cardiovascular (CV) safety domain plays an important role in this process, as many preclinical CV biomarkers seem to have high prognostic value for the clinical outcome. Throughout the industry, traditional ion channel binding data are generated to drive the early selection process. Although this assay can generate data at high capacity, it has the disadvantage of producing high numbers of false negatives. Therefore, our company applies the isolated guinea pig right atrium (GPRA) assay early-on in discovery. This functional multi-channel/multi-receptor model seems much more predictive in identifying potential CV liabilities. Unfortunately however, its capacity is limited, and there is no room for full automation. We assessed the correlation between ion channel binding and the GPRA's Rate of Contraction (RC), Contractile Force (CF), and effective refractory frequency (ERF) measures assay using over six thousand different data points. Furthermore, the existing experimental knowledge base was used to develop a set of in silico classification models attempting to mimic the GPRA inhibitory activity. The Naïve Bayesian classifier was used to built several models, using the ion channel binding data or in silico computed properties and structural fingerprints as descriptors. The models were validated on an independent and diverse test set of 200 reference compounds. Performances were assessed on the bases of their overall accuracy, sensitivity and specificity in detecting both active and inactive molecules. Our data show that all in silico models are highly predictive of actual GPRA data, at a level equivalent or superior to the ion channel binding assays. Furthermore, the models were interpreted in terms of the descriptors used to highlight the undesirable areas in the explored chemical space, specifically regions of low polarity, high lipophilicity and high molecular weight. In conclusion, we developed a predictive in silico model of a complex physiological assay based on a large and high quality set of experimental data. This model allows high throughput in silico safety screening based on chemical structure within a given chemical space.

Synthesis, crystal structure analysis, molecular docking studies and density functional theory predictions of the local reactive properties and degradation properties of a novel halochalcone

NASA Astrophysics Data System (ADS)

Arshad, Suhana; Pillai, Renjith Raveendran; Zainuri, Dian Alwani; Khalib, Nuridayanti Che; Razak, Ibrahim Abdul; Armaković, Stevan; Armaković, Sanja J.

2017-09-01

In the present study, single crystals of E)-3-(3,5-dichlorophenyl)-1-(4-fluorophenyl)prop-2-en-1-one, were prepared and structurally characterized by single crystal X-ray diffraction analysis. The molecular structure crystallized in monoclinic crystal system with P21/c space group. Sensitivity of the title molecule towards electrophilic attacks has been examined by calculations of average localized ionization energies (ALIE) and their mapping to electron density surface. Further determination of atoms that could be important reactive centres has been performed by calculations of Fukui functions. Sensitivity of title molecule towards autoxidation and hydrolysis mechanisms has been assessed by calculations of bond dissociation energies and radial distribution functions (RDF), respectively. Also, in order to explore possible binding mode of the title compound towards Dihydrofolate reductase enzyme, we have utilized in silico molecular docking to explore possible binding modes of the title compound with the DHFR enzyme.

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.

Limitations of in silico predictability of specificity of co-immobilised cytochromes P450 and mimics in food-bioprocessing.

PubMed

Wiseman, Alan

2003-04-01

Cytochromes P450 (EC 1.14.14.1) are mixed function oxidases (oxygenases) that can catalyse redox bioconversions of food components. Also, efficacious removal of undesirable components can be achieved using solid-support immobilised enzyme (IME) of a selection from 2700 isoforms of cytochromes P450 (CYP). Cytochromes P450 co-immobilised with other enzymes, or protein receptors, may be used to confer a secondary order of regio- or stereo-specificity of chiral bioconversion: these can be predictable in silico by utilisation of QSARs (quantitative structure/activity relationships).

In silico analysis of fragile histidine triad involved in regression of carcinoma.

PubMed

Rasheed, Muhammad Asif; Tariq, Fatima; Afzal, Sara; Mannanv, Shazia

2017-04-01

Hepatocellular carcinoma (HCCa) is a primary malignancy of the liver. Many different proteins are involved in HCCa including insulin growth factor (IGF) II , signal transducers and activators of transcription (STAT) 3, STAT4, mothers against decapentaplegic homolog 4 (SMAD 4), fragile histidine triad (FHIT) and selective internal radiation therapy (SIRT) etc. The present study is based on the bioinformatics analysis of FHIT protein in order to understand the proteomics aspect and improvement of the diagnosis of the disease based on the protein. Different information related to protein were gathered from different databases, including National Centre for Biotechnology Information (NCBI) Gene, Protein and Online Mendelian Inheritance in Man (OMIM) databases, Uniprot database, String database and Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Moreover, the structure of the protein and evaluation of the quality of the structure were included from Easy modeler programme. Hence, this analysis not only helped to gather information related to the protein at one place, but also analysed the structure and quality of the protein to conclude that the protein has a role in carcinoma.

Ketide Synthase (KS) Domain Prediction and Analysis of Iterative Type II PKS Gene in Marine Sponge-Associated Actinobacteria Producing Biosurfactants and Antimicrobial Agents

PubMed Central

Selvin, Joseph; Sathiyanarayanan, Ganesan; Lipton, Anuj N.; Al-Dhabi, Naif Abdullah; Valan Arasu, Mariadhas; Kiran, George S.

2016-01-01

The important biological macromolecules, such as lipopeptide and glycolipid biosurfactant producing marine actinobacteria were analyzed and their potential linkage between type II polyketide synthase (PKS) genes was explored. A unique feature of type II PKS genes is their high amino acid (AA) sequence homology and conserved gene organization. These enzymes mediate the biosynthesis of polyketide natural products with enormous structural complexity and chemical nature by combinatorial use of various domains. Therefore, deciphering the order of AA sequence encoded by PKS domains tailored the chemical structure of polyketide analogs still remains a great challenge. The present work deals with an in vitro and in silico analysis of PKS type II genes from five actinobacterial species to correlate KS domain architecture and structural features. Our present analysis reveals the unique protein domain organization of iterative type II PKS and KS domain of marine actinobacteria. The findings of this study would have implications in metabolic pathway reconstruction and design of semi-synthetic genomes to achieve rational design of novel natural products. PMID:26903957

In silico assembly and nanomechanical characterization of carbon nanotube buckypaper.

PubMed

Cranford, Steven W; Buehler, Markus J

2010-07-02

Carbon nanotube sheets or films, also known as 'buckypaper', have been proposed for use in actuating, structural and filtration systems, based in part on their unique and robust mechanical properties. Computational modeling of such a fibrous nanostructure is hindered by both the random arrangement of the constituent elements as well as the time- and length-scales accessible to atomistic level molecular dynamics modeling. Here we present a novel in silico assembly procedure based on a coarse-grain model of carbon nanotubes, used to attain a representative mesoscopic buckypaper model that circumvents the need for probabilistic approaches. By variation in assembly parameters, including the initial nanotube density and ratio of nanotube type (single- and double-walled), the porosity of the resulting buckypaper can be varied threefold, from approximately 0.3 to 0.9. Further, through simulation of nanoindentation, the Young's modulus is shown to be tunable through manipulation of nanotube type and density over a range of approximately 0.2-3.1 GPa, in good agreement with experimental findings of the modulus of assembled carbon nanotube films. In addition to carbon nanotubes, the coarse-grain model and assembly process can be adapted for other fibrous nanostructures such as electrospun polymeric composites, high performance nonwoven ballistic materials, or fibrous protein aggregates, facilitating the development and characterization of novel nanomaterials and composites as well as the analysis of biological materials such as protein fiber films and bulk structures.

Structural model of the hUbA1-UbcH10 quaternary complex: in silico and experimental analysis of the protein-protein interactions between E1, E2 and ubiquitin.

PubMed

Correale, Stefania; de Paola, Ivan; Morgillo, Carmine Marco; Federico, Antonella; Zaccaro, Laura; Pallante, Pierlorenzo; Galeone, Aldo; Fusco, Alfredo; Pedone, Emilia; Luque, F Javier; Catalanotti, Bruno

2014-01-01

UbcH10 is a component of the Ubiquitin Conjugation Enzymes (Ubc; E2) involved in the ubiquitination cascade controlling the cell cycle progression, whereby ubiquitin, activated by E1, is transferred through E2 to the target protein with the involvement of E3 enzymes. In this work we propose the first three dimensional model of the tetrameric complex formed by the human UbA1 (E1), two ubiquitin molecules and UbcH10 (E2), leading to the transthiolation reaction. The 3D model was built up by using an experimentally guided incremental docking strategy that combined homology modeling, protein-protein docking and refinement by means of molecular dynamics simulations. The structural features of the in silico model allowed us to identify the regions that mediate the recognition between the interacting proteins, revealing the active role of the ubiquitin crosslinked to E1 in the complex formation. Finally, the role of these regions involved in the E1-E2 binding was validated by designing short peptides that specifically interfere with the binding of UbcH10, thus supporting the reliability of the proposed model and representing valuable scaffolds for the design of peptidomimetic compounds that can bind selectively to Ubcs and inhibit the ubiquitylation process in pathological disorders.

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

In silico assembly and nanomechanical characterization of carbon nanotube buckypaper

NASA Astrophysics Data System (ADS)

Cranford, Steven W.; Buehler, Markus J.

2010-07-01

Carbon nanotube sheets or films, also known as 'buckypaper', have been proposed for use in actuating, structural and filtration systems, based in part on their unique and robust mechanical properties. Computational modeling of such a fibrous nanostructure is hindered by both the random arrangement of the constituent elements as well as the time- and length-scales accessible to atomistic level molecular dynamics modeling. Here we present a novel in silico assembly procedure based on a coarse-grain model of carbon nanotubes, used to attain a representative mesoscopic buckypaper model that circumvents the need for probabilistic approaches. By variation in assembly parameters, including the initial nanotube density and ratio of nanotube type (single- and double-walled), the porosity of the resulting buckypaper can be varied threefold, from approximately 0.3 to 0.9. Further, through simulation of nanoindentation, the Young's modulus is shown to be tunable through manipulation of nanotube type and density over a range of approximately 0.2-3.1 GPa, in good agreement with experimental findings of the modulus of assembled carbon nanotube films. In addition to carbon nanotubes, the coarse-grain model and assembly process can be adapted for other fibrous nanostructures such as electrospun polymeric composites, high performance nonwoven ballistic materials, or fibrous protein aggregates, facilitating the development and characterization of novel nanomaterials and composites as well as the analysis of biological materials such as protein fiber films and bulk structures.

Effect of mutation at the interface of Trp-repressor dimeric protein: a steered molecular dynamics simulation.

PubMed

Miño, German; Baez, Mauricio; Gutierrez, Gonzalo

2013-09-01

The strength of key interfacial contacts that stabilize protein-protein interactions have been studied by computer simulation. Experimentally, changes in the interface are evaluated by generating specific mutations at one or more points of the protein structure. Here, such an evaluation is performed by means of steered molecular dynamics and use of a dimeric model of tryptophan repressor and in-silico mutants as a test case. Analysis of four particular cases shows that, in principle, it is possible to distinguish between wild-type and mutant forms by examination of the total energy and force-extension profiles. In particular, detailed atomic level structural analysis indicates that specific mutations at the interface of the dimeric model (positions 19 and 39) alter interactions that appear in the wild-type form of tryptophan repressor, reducing the energy and force required to separate both subunits.

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.

Structure Elucidation of Coxsackievirus A16 in Complex with GPP3 Informs a Systematic Review of Highly Potent Capsid Binders to Enteroviruses.

PubMed

De Colibus, Luigi; Wang, Xiangxi; Tijsma, Aloys; Neyts, Johan; Spyrou, John A B; Ren, Jingshan; Grimes, Jonathan M; Puerstinger, Gerhard; Leyssen, Pieter; Fry, Elizabeth E; Rao, Zihe; Stuart, David I

2015-10-01

The replication of enterovirus 71 (EV71) and coxsackievirus A16 (CVA16), which are the major cause of hand, foot and mouth disease (HFMD) in children, can be inhibited by the capsid binder GPP3. Here, we present the crystal structure of CVA16 in complex with GPP3, which clarifies the role of the key residues involved in interactions with the inhibitor. Based on this model, in silico docking was performed to investigate the interactions with the two next-generation capsid binders NLD and ALD, which we show to be potent inhibitors of a panel of enteroviruses with potentially interesting pharmacological properties. A meta-analysis was performed using the available structural information to obtain a deeper insight into those structural features required for capsid binders to interact effectively and also those that confer broad-spectrum anti-enterovirus activity.

Emerging Issues in Genotoxicity and Carcinogenicity with Implications for Structure Activity Analyses

EPA Science Inventory

In silico systems for the prediction of the ability of chemicals to induce carcinogenicity in rodents have generally relied on knowledge of the structure and physical-chemical features of the compound, as well as the mutagenic and genotoxic features of the compound in various bio...

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

Isolation and in silico analysis of a novel H+-pyrophosphatase gene orthologue from the halophytic grass Leptochloa fusca

NASA Astrophysics Data System (ADS)

Rauf, Muhammad; Saeed, Nasir A.; Habib, Imran; Ahmed, Moddassir; Shahzad, Khurram; Mansoor, Shahid; Ali, Rashid

2017-02-01

Structure prediction can provide information about function and active sites of protein which helps to design new functional proteins. H+-pyrophosphatase is transmembrane protein involved in establishing proton motive force for active transport of Na+ across membrane by Na+/H+ antiporters. A full length novel H+-pyrophosphatase gene was isolated from halophytic grass Leptochloa fusca using RT-PCR and RACE method. Full length LfVP1 gene sequence of 2292 nucleotides encodes protein of 764 amino acids. DNA and protein sequences were used for characterization using bioinformatics tools. Various important potential sites were predicted by PROSITE webserver. Primary structural analysis showed LfVP1 as stable protein and Grand average hydropathy (GRAVY) indicated that LfVP1 protein has good hydrosolubility. Secondary structure analysis showed that LfVP1 protein sequence contains significant proportion of alpha helix and random coil. Protein membrane topology suggested the presence of 14 transmembrane domains and presence of catalytic domain in TM3. Three dimensional structure from LfVP1 protein sequence also indicated the presence of 14 transmembrane domains and hydrophobicity surface model showed amino acid hydrophobicity. Ramachandran plot showed that 98% amino acid residues were predicted in the favored region.

Theoretical investigations of two adamantane derivatives: A combined X-ray, DFT, QTAIM analysis and molecular docking

NASA Astrophysics Data System (ADS)

Al-Wahaibi, Lamya H.; Sujay, Subramaniam; Muthu, Gangadharan Ganesh; El-Emam, Ali A.; Venkataramanan, Natarajan S.; Al-Omary, Fatmah A. M.; Ghabbour, Hazem A.; Percino, Judith; Thamotharan, Subbiah

2018-05-01

A detailed structural analysis of two adamantane derivatives namely, ethyl 2-[(Z)-1-(adamantan-1-yl)-3-(phenyl)isothioureido]acetate I and ethyl 2-[(Z)-1-(adamantan-1-yl)-3-(4-fluorophenyl)isothioureido]acetate II is carried out to understand the effect of fluorine substitution. The introduction of fluorine atom alters the crystal packing and is completely different from its parent compound. The fluorine substitution drastically reduced the intermolecular H⋯H contacts and this reduction is compensated by intermolecular F⋯H and F⋯F contacts. The relative contributions of various intermolecular contacts present in these structures were quantified using Hirshfeld surface analysis. Energetically significant molecular pairs were identified from the crystal structures of these compounds using PIXEL method. The structures of I and II are optimized in gas and solvent phases using the B3LYP-D3/6-311++G(d,p) level of theory. The quantum theory of atoms-in-molecules (QTAIM) analysis was carried out to estimate the strengths of various intermolecular contacts present in these molecular dimers. The results suggest that the Hsbnd H bonding take part in the stabilization of crystal structures. The experimental and theoretical UV-Vis results show the variations in HOMO and LUMO energy levels. In silico docking analysis indicates that both compounds I and II may exhibit inhibitory activity against 11-β-hydroxysteroid dehydrogenase 1 (11-β-HSD1).

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

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.

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.

Designing Isoform-selective Inhibitors Against Classical HDACs for Effective Anticancer Therapy: Insight and Perspectives from In Silico.

PubMed

Ganai, Shabir Ahmad

2018-01-01

Histone deacetylase inhibitors, the small molecules modulating the biological activity of histone deacetylases are emerging as potent chemotherapeutic agents. Despite their considerable therapeutic benefits in disease models, the lack of isoform specificity culminates in debilitating off target effects, raising serious concerns regarding their applicability. This emphasizes the pressing and unmet medical need of designing isoform selective inhibitors for safe and effective anticancer therapy. Keeping these grim facts in view, the current article sheds light on structural basis of off-targeting. Furthermore, the article discusses extensively the role of in silico strategies such as Molecular Docking, Molecular Dynamics Simulation and Energetically-optimized structure based pharmacophore approach in designing on-target inhibitors against classical HDACs. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Integrating in silico prediction methods, molecular docking, and molecular dynamics simulation to predict the impact of ALK missense mutations in structural perspective.

PubMed

Doss, C George Priya; Chakraborty, Chiranjib; Chen, Luonan; Zhu, Hailong

2014-01-01

Over the past decade, advancements in next generation sequencing technology have placed personalized genomic medicine upon horizon. Understanding the likelihood of disease causing mutations in complex diseases as pathogenic or neutral remains as a major task and even impossible in the structural context because of its time consuming and expensive experiments. Among the various diseases causing mutations, single nucleotide polymorphisms (SNPs) play a vital role in defining individual's susceptibility to disease and drug response. Understanding the genotype-phenotype relationship through SNPs is the first and most important step in drug research and development. Detailed understanding of the effect of SNPs on patient drug response is a key factor in the establishment of personalized medicine. In this paper, we represent a computational pipeline in anaplastic lymphoma kinase (ALK) for SNP-centred study by the application of in silico prediction methods, molecular docking, and molecular dynamics simulation approaches. Combination of computational methods provides a way in understanding the impact of deleterious mutations in altering the protein drug targets and eventually leading to variable patient's drug response. We hope this rapid and cost effective pipeline will also serve as a bridge to connect the clinicians and in silico resources in tailoring treatments to the patients' specific genotype.

Impact of distance-based metric learning on classification and visualization model performance and structure-activity landscapes.

PubMed

Kireeva, Natalia V; Ovchinnikova, Svetlana I; Kuznetsov, Sergey L; Kazennov, Andrey M; Tsivadze, Aslan Yu

2014-02-01

This study concerns large margin nearest neighbors classifier and its multi-metric extension as the efficient approaches for metric learning which aimed to learn an appropriate distance/similarity function for considered case studies. In recent years, many studies in data mining and pattern recognition have demonstrated that a learned metric can significantly improve the performance in classification, clustering and retrieval tasks. The paper describes application of the metric learning approach to in silico assessment of chemical liabilities. Chemical liabilities, such as adverse effects and toxicity, play a significant role in drug discovery process, in silico assessment of chemical liabilities is an important step aimed to reduce costs and animal testing by complementing or replacing in vitro and in vivo experiments. Here, to our knowledge for the first time, a distance-based metric learning procedures have been applied for in silico assessment of chemical liabilities, the impact of metric learning on structure-activity landscapes and predictive performance of developed models has been analyzed, the learned metric was used in support vector machines. The metric learning results have been illustrated using linear and non-linear data visualization techniques in order to indicate how the change of metrics affected nearest neighbors relations and descriptor space.

Impact of distance-based metric learning on classification and visualization model performance and structure-activity landscapes

NASA Astrophysics Data System (ADS)

Kireeva, Natalia V.; Ovchinnikova, Svetlana I.; Kuznetsov, Sergey L.; Kazennov, Andrey M.; Tsivadze, Aslan Yu.

2014-02-01

This study concerns large margin nearest neighbors classifier and its multi-metric extension as the efficient approaches for metric learning which aimed to learn an appropriate distance/similarity function for considered case studies. In recent years, many studies in data mining and pattern recognition have demonstrated that a learned metric can significantly improve the performance in classification, clustering and retrieval tasks. The paper describes application of the metric learning approach to in silico assessment of chemical liabilities. Chemical liabilities, such as adverse effects and toxicity, play a significant role in drug discovery process, in silico assessment of chemical liabilities is an important step aimed to reduce costs and animal testing by complementing or replacing in vitro and in vivo experiments. Here, to our knowledge for the first time, a distance-based metric learning procedures have been applied for in silico assessment of chemical liabilities, the impact of metric learning on structure-activity landscapes and predictive performance of developed models has been analyzed, the learned metric was used in support vector machines. The metric learning results have been illustrated using linear and non-linear data visualization techniques in order to indicate how the change of metrics affected nearest neighbors relations and descriptor space.

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.

SCRIPDB: a portal for easy access to syntheses, chemicals and reactions in patents

PubMed Central

Heifets, Abraham; Jurisica, Igor

2012-01-01

The patent literature is a rich catalog of biologically relevant chemicals; many public and commercial molecular databases contain the structures disclosed in patent claims. However, patents are an equally rich source of metadata about bioactive molecules, including mechanism of action, disease class, homologous experimental series, structural alternatives, or the synthetic pathways used to produce molecules of interest. Unfortunately, this metadata is discarded when chemical structures are deposited separately in databases. SCRIPDB is a chemical structure database designed to make this metadata accessible. SCRIPDB provides the full original patent text, reactions and relationships described within any individual patent, in addition to the molecular files common to structural databases. We discuss how such information is valuable in medical text mining, chemical image analysis, reaction extraction and in silico pharmaceutical lead optimization. SCRIPDB may be searched by exact chemical structure, substructure or molecular similarity and the results may be restricted to patents describing synthetic routes. SCRIPDB is available at http://dcv.uhnres.utoronto.ca/SCRIPDB. PMID:22067445

A mechanistic insight into the amyloidogenic structure of hIAPP peptide revealed from sequence analysis and molecular dynamics simulation.

PubMed

Chakraborty, Sandipan; Chatterjee, Barnali; Basu, Soumalee

2012-07-01

A collective approach of sequence analysis, phylogenetic tree and in silico prediction of amyloidogenecity using bioinformatics tools have been used to correlate the observed species-specific variations in IAPP sequences with the amyloid forming propensity. Observed substitution patterns indicate that probable changes in local hydrophobicity are instrumental in altering the aggregation propensity of the peptide. In particular, residues at 17th, 22nd and 23rd positions of the IAPP peptide are found to be crucial for amyloid formation. Proline25 primarily dictates the observed non-amyloidogenecity in rodents. Furthermore, extensive molecular dynamics simulation of 0.24 μs have been carried out with human IAPP (hIAPP) fragment 19-27, the portion showing maximum sequence variation across different species, to understand the native folding characteristic of this region. Principal component analysis in combination with free energy landscape analysis illustrates a four residue turn spanning from residue 22 to 25. The results provide a structural insight into the intramolecular β-sheet structure of amylin which probably is the template for nucleation of fibril formation and growth, a pathogenic feature of type II diabetes. Copyright © 2012 Elsevier B.V. All rights reserved.

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.

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.

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.

COMPUTER-AIDED DRUG DISCOVERY AND DEVELOPMENT (CADDD): in silico-chemico-biological approach

PubMed Central

Kapetanovic, I.M.

2008-01-01

It is generally recognized that drug discovery and development are very time and resources consuming processes. There is an ever growing effort to apply computational power to the combined chemical and biological space in order to streamline drug discovery, design, development and optimization. In biomedical arena, computer-aided or in silico design is being utilized to expedite and facilitate hit identification, hit-to-lead selection, optimize the absorption, distribution, metabolism, excretion and toxicity profile and avoid safety issues. Commonly used computational approaches include ligand-based drug design (pharmacophore, a 3-D spatial arrangement of chemical features essential for biological activity), structure-based drug design (drug-target docking), and quantitative structure-activity and quantitative structure-property relationships. Regulatory agencies as well as pharmaceutical industry are actively involved in development of computational tools that will improve effectiveness and efficiency of drug discovery and development process, decrease use of animals, and increase predictability. It is expected that the power of CADDD will grow as the technology continues to evolve. PMID:17229415

QSAR Methods.

PubMed

Gini, Giuseppina

2016-01-01

In this chapter, we introduce the basis of computational chemistry and discuss how computational methods have been extended to some biological properties and toxicology, in particular. Since about 20 years, chemical experimentation is more and more replaced by modeling and virtual experimentation, using a large core of mathematics, chemistry, physics, and algorithms. Then we see how animal experiments, aimed at providing a standardized result about a biological property, can be mimicked by new in silico methods. Our emphasis here is on toxicology and on predicting properties through chemical structures. Two main streams of such models are available: models that consider the whole molecular structure to predict a value, namely QSAR (Quantitative Structure Activity Relationships), and models that find relevant substructures to predict a class, namely SAR. The term in silico discovery is applied to chemical design, to computational toxicology, and to drug discovery. We discuss how the experimental practice in biological science is moving more and more toward modeling and simulation. Such virtual experiments confirm hypotheses, provide data for regulation, and help in designing new chemicals.

Lead discovery and in silico 3D structure modeling of tumorigenic FAM72A (p17).

PubMed

Pramanik, Subrata; Kutzner, Arne; Heese, Klaus

2015-01-01

FAM72A (p17) is a novel neuronal protein that has been linked to tumorigenic effects in non-neuronal tissue. Using state of the art in silico physicochemical analyses (e.g., I-TASSER, RaptorX, and Modeller), we determined the three-dimensional (3D) protein structure of FAM72A and further identified potential ligand-protein interactions. Our data indicate a Zn(2+)/Fe(3+)-containing 3D protein structure, based on a 3GA3_A model template, which potentially interacts with the organic molecule RSM ((2s)-2-(acetylamino)-N-methyl-4-[(R)-methylsulfinyl] butanamide). The discovery of RSM may serve as potential lead for further anti-FAM72A drug screening tests in the pharmaceutical industry because interference with FAM72A's activities via RSM-related molecules might be a novel option to influence the tumor suppressor protein p53 signaling pathways for the treatment of various types of cancers.

Building scientific confidence in metabolic similarity in read-across through the use of in vitro, in silico and analytical data

EPA Science Inventory

The underlying principle of read-across is that the biological activity of a chemical is inherent in its molecular structure. Analogues are typically identified by structural similarity then evaluated on the basis of their bioavailability, reactivity and metabolic similarity. Whi...

20180312 - Building scientific confidence in metabolic similarity in read-across through the use of in vitro, in silico and analytical data (SOT)

EPA Science Inventory

The underlying principle of read-across is that the biological activity of a chemical is inherent in its molecular structure. Analogues are typically identified by structural similarity then evaluated on the basis of their bioavailability, reactivity and metabolic similarity. Whi...

In silico modeling techniques for predicting the tertiary structure of human H4 receptor.

PubMed

Zaid, Hilal; Raiyn, Jamal; Osman, Midhat; Falah, Mizied; Srouji, Samer; Rayan, Anwar

2016-01-01

First cloned in 2000, the human Histamine H4 Receptor (hH4R) is the last member of the histamine receptors family discovered so far, it belongs to the GPCR super-family and is involved in a wide variety of immunological and inflammatory responses. Potential hH4R antagonists are proposed to have therapeutic potential for the treatment of allergies, inflammation, asthma and colitis. So far, no hH4R ligands have been successfully introduced to the pharmaceutical market, which creates a strong demand for new selective ligands to be developed. in silico techniques and structural based modeling are likely to facilitate the achievement of this goal. In this review paper we attempt to cover the fundamental concepts of hH4R structure modeling and its implementations in drug discovery and development, especially those that have been experimentally tested and to highlight some ideas that are currently being discussed on the dynamic nature of hH4R and GPCRs, in regards to computerized techniques for 3-D structure modeling.

In silico design of porous polymer networks: high-throughput screening for methane storage materials.

PubMed

Martin, Richard L; Simon, Cory M; Smit, Berend; Haranczyk, Maciej

2014-04-02

Porous polymer networks (PPNs) are a class of advanced porous materials that combine the advantages of cheap and stable polymers with the high surface areas and tunable chemistry of metal-organic frameworks. They are of particular interest for gas separation or storage applications, for instance, as methane adsorbents for a vehicular natural gas tank or other portable applications. PPNs are self-assembled from distinct building units; here, we utilize commercially available chemical fragments and two experimentally known synthetic routes to design in silico a large database of synthetically realistic PPN materials. All structures from our database of 18,000 materials have been relaxed with semiempirical electronic structure methods and characterized with Grand-canonical Monte Carlo simulations for methane uptake and deliverable (working) capacity. A number of novel structure-property relationships that govern methane storage performance were identified. The relationships are translated into experimental guidelines to realize the ideal PPN structure. We found that cooperative methane-methane attractions were present in all of the best-performing materials, highlighting the importance of guest interaction in the design of optimal materials for methane storage.

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

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.

Structural insight of dopamine β-hydroxylase, a drug target for complex traits, and functional significance of exonic single nucleotide polymorphisms.

PubMed

Kapoor, Abhijeet; Shandilya, Manish; Kundu, Suman

2011-01-01

Human dopamine β-hydroxylase (DBH) is an important therapeutic target for complex traits. Several single nucleotide polymorphisms (SNPs) have also been identified in DBH with potential adverse physiological effect. However, difficulty in obtaining diffractable crystals and lack of a suitable template for modeling the protein has ensured that neither crystallographic three-dimensional structure nor computational model for the enzyme is available to aid rational drug design, prediction of functional significance of SNPs or analytical protein engineering. Adequate biochemical information regarding human DBH, structural coordinates for peptidylglycine alpha-hydroxylating monooxygenase and computational data from a partial model of rat DBH were used along with logical manual intervention in a novel way to build an in silico model of human DBH. The model provides structural insight into the active site, metal coordination, subunit interface, substrate recognition and inhibitor binding. It reveals that DOMON domain potentially promotes tetramerization, while substrate dopamine and a potential therapeutic inhibitor nepicastat are stabilized in the active site through multiple hydrogen bonding. Functional significance of several exonic SNPs could be described from a structural analysis of the model. The model confirms that SNP resulting in Ala318Ser or Leu317Pro mutation may not influence enzyme activity, while Gly482Arg might actually do so being in the proximity of the active site. Arg549Cys may cause abnormal oligomerization through non-native disulfide bond formation. Other SNPs like Glu181, Glu250, Lys239 and Asp290 could potentially inhibit tetramerization thus affecting function. The first three-dimensional model of full-length human DBH protein was obtained in a novel manner with a set of experimental data as guideline for consistency of in silico prediction. Preliminary physicochemical tests validated the model. The model confirms, rationalizes and provides structural basis for several biochemical data and claims testable hypotheses regarding function. It provides a reasonable template for drug design as well.

Using argument notation to engineer biological simulations with increased confidence

PubMed Central

Alden, Kieran; Andrews, Paul S.; Polack, Fiona A. C.; Veiga-Fernandes, Henrique; Coles, Mark C.; Timmis, Jon

2015-01-01

The application of computational and mathematical modelling to explore the mechanics of biological systems is becoming prevalent. To significantly impact biological research, notably in developing novel therapeutics, it is critical that the model adequately represents the captured system. Confidence in adopting in silico approaches can be improved by applying a structured argumentation approach, alongside model development and results analysis. We propose an approach based on argumentation from safety-critical systems engineering, where a system is subjected to a stringent analysis of compliance against identified criteria. We show its use in examining the biological information upon which a model is based, identifying model strengths, highlighting areas requiring additional biological experimentation and providing documentation to support model publication. We demonstrate our use of structured argumentation in the development of a model of lymphoid tissue formation, specifically Peyer's Patches. The argumentation structure is captured using Artoo (www.york.ac.uk/ycil/software/artoo), our Web-based tool for constructing fitness-for-purpose arguments, using a notation based on the safety-critical goal structuring notation. We show how argumentation helps in making the design and structured analysis of a model transparent, capturing the reasoning behind the inclusion or exclusion of each biological feature and recording assumptions, as well as pointing to evidence supporting model-derived conclusions. PMID:25589574

Using argument notation to engineer biological simulations with increased confidence.

PubMed

Alden, Kieran; Andrews, Paul S; Polack, Fiona A C; Veiga-Fernandes, Henrique; Coles, Mark C; Timmis, Jon

2015-03-06

The application of computational and mathematical modelling to explore the mechanics of biological systems is becoming prevalent. To significantly impact biological research, notably in developing novel therapeutics, it is critical that the model adequately represents the captured system. Confidence in adopting in silico approaches can be improved by applying a structured argumentation approach, alongside model development and results analysis. We propose an approach based on argumentation from safety-critical systems engineering, where a system is subjected to a stringent analysis of compliance against identified criteria. We show its use in examining the biological information upon which a model is based, identifying model strengths, highlighting areas requiring additional biological experimentation and providing documentation to support model publication. We demonstrate our use of structured argumentation in the development of a model of lymphoid tissue formation, specifically Peyer's Patches. The argumentation structure is captured using Artoo (www.york.ac.uk/ycil/software/artoo), our Web-based tool for constructing fitness-for-purpose arguments, using a notation based on the safety-critical goal structuring notation. We show how argumentation helps in making the design and structured analysis of a model transparent, capturing the reasoning behind the inclusion or exclusion of each biological feature and recording assumptions, as well as pointing to evidence supporting model-derived conclusions.

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

An in silico approach to investigate the source of the controversial interpretations about the phenotypic results of the human AhR-gene G1661A polymorphism.

PubMed

Aftabi, Younes; Colagar, Abasalt Hosseinzadeh; Mehrnejad, Faramarz

2016-03-21

Aryl hydrocarbon receptor (AhR) acts as an enhancer binding ligand-activated intracellular receptor. Chromatin remodeling components and general transcription factors such as TATA-binding protein (TBP) are evoked on AhR-target genes by interaction with its flexible transactivation domain (TAD). AhR-G1661A single nucleotide polymorphism (SNP: rs2066853) causes an arginine to lysine substitution in the acidic sub-domain of TAD at position 554 (R554K). Although, numerous studies associate the SNP with some abnormalities such as cancer, other reliable investigations refuse the associations. Consequently, the interpretation of the phenotypic results of G1661A-transition has been controversial. In this study, an in silico analysis were performed to investigate the possible effects of the transition on AhR-mRNA, protein structure, interaction properties and modifications. The analysis revealed that the R554K substitution affects secondary structure and solvent accessibility of adjacent residues. Also, it causes to decreasing of the AhR stability; altering the hydropathy features of the local sequence and changing the pattern of the residues at the binding site of the TAD-acidic sub-domain. Generating of new sites for ubiquitination and acetylation for AhR-K554 variant respectively at positions 544 and 560 was predicted. Our findings intensify the idea that the AhR-G1661A transition may affects AhR-TAD interactions, especially with the TBP, which influence AhR-target genes expression. However, the previously reported flexibility of the modular TAD could act as an intervening factor, moderate the SNP effects and causes distinct outcomes in different individuals and tissues. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

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.

Evaluating the mutagenic potential of aerosol organic compounds using informatics-based screening

NASA Astrophysics Data System (ADS)

Decesari, Stefano; Kovarich, Simona; Pavan, Manuela; Bassan, Arianna; Ciacci, Andrea; Topping, David

2018-02-01

Whilst general policy objectives to reduce airborne particulate matter (PM) health effects are to reduce exposure to PM as a whole, emerging evidence suggests that more detailed metrics associating impacts with different aerosol components might be needed. Since it is impossible to conduct toxicological screening on all possible molecular species expected to occur in aerosol, in this study we perform a proof-of-concept evaluation on the information retrieved from in silico toxicological predictions, in which a subset (N = 104) of secondary organic aerosol (SOA) compounds were screened for their mutagenicity potential. An extensive database search showed that experimental data are available for 13 % of the compounds, while reliable predictions were obtained for 82 %. A multivariate statistical analysis of the compounds based on their physico-chemical, structural, and mechanistic properties showed that 80 % of the compounds predicted as mutagenic were grouped into six clusters, three of which (five-membered lactones from monoterpene oxidation, oxygenated multifunctional compounds from substituted benzene oxidation, and hydroperoxides from several precursors) represent new candidate groups of compounds for future toxicological screenings. These results demonstrate that coupling model-generated compositions to in silico toxicological screening might enable more comprehensive exploration of the mutagenic potential of specific SOA components.

Predicting human blood viscosity in silico

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

Fedosov, Dmitry A.; Pan, Wenxiao; Caswell, Bruce

2011-07-05

Cellular suspensions such as blood are a part of living organisms and their rheological and flow characteristics determine and affect majority of vital functions. The rheological and flow properties of cell suspensions are determined by collective dynamics of cells, their structure or arrangement, cell properties and interactions. We study these relations for blood in silico using a mesoscopic particle-based method and two different models (multi-scale/low-dimensional) of red blood cells. The models yield accurate quantitative predictions of the dependence of blood viscosity on shear rate and hematocrit. We explicitly model cell aggregation interactions and demonstrate the formation of reversible rouleaux structuresmore » resulting in a tremendous increase of blood viscosity at low shear rates and yield stress, in agreement with experiments. The non-Newtonian behavior of such cell suspensions (e.g., shear thinning, yield stress) is analyzed and related to the suspension’s microstructure, deformation and dynamics of single cells. We provide the flrst quantitative estimates of normal stress differences and magnitude of aggregation forces in blood. Finally, the flexibility of the cell models allows them to be employed for quantitative analysis of a much wider class of complex fluids including cell, capsule, and vesicle suspensions.« less

A practical guidance for Cramer class determination.

PubMed

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

2015-12-01

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

Structural bioinformatics of the human spliceosomal proteome

PubMed Central

Korneta, Iga; Magnus, Marcin; Bujnicki, Janusz M.

2012-01-01

In this work, we describe the results of a comprehensive structural bioinformatics analysis of the spliceosomal proteome. We used fold recognition analysis to complement prior data on the ordered domains of 252 human splicing proteins. Examples of newly identified domains include a PWI domain in the U5 snRNP protein 200K (hBrr2, residues 258–338), while examples of previously known domains with a newly determined fold include the DUF1115 domain of the U4/U6 di-snRNP protein 90K (hPrp3, residues 540–683). We also established a non-redundant set of experimental models of spliceosomal proteins, as well as constructed in silico models for regions without an experimental structure. The combined set of structural models is available for download. Altogether, over 90% of the ordered regions of the spliceosomal proteome can be represented structurally with a high degree of confidence. We analyzed the reduced spliceosomal proteome of the intron-poor organism Giardia lamblia, and as a result, we proposed a candidate set of ordered structural regions necessary for a functional spliceosome. The results of this work will aid experimental and structural analyses of the spliceosomal proteins and complexes, and can serve as a starting point for multiscale modeling of the structure of the entire spliceosome. PMID:22573172

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

PubMed

Hala, D

2017-03-21

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

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

PubMed Central

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

2007-01-01

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

In-silico analysis for RNA-interference mechanism of α-synuclein to treat Parkinson's disease.

PubMed

Seema, S; Seenivasagam, R; Hemavathi, K

2013-01-01

Parkinson's Disease (PD) causing mutations in α-synuclein gene are ALA30PRO, GLU46LYS and ALA53THR. The conformational changes in proteins with respect to all the three mutations were analysed. These were used to predict the structures of Short Interfering RNA (siRNA) antisense strand and siRNA region. The siRNA binds with the argonaute protein forming RNA Induced Silencing Complex (RISC). Then, siRNA antisense-strand was attached to RISC. The structure of dicer (RNase-III-enzyme) cleaves double-stranded RNA (dsRNA) into two siRNA-strands. Incorporation of single siRNA-strand into RISC guides to pair with the complementary α-synuclein target-messenger RNA (mRNA) thereby enabling it to cleave the target.

In silico Exploration of the Conformational Universe of GPCRs.

PubMed

Rodríguez-Espigares, Ismael; Kaczor, Agnieszka A; Selent, Jana

2016-07-01

The structural plasticity of G protein coupled receptors (GPCRs) leads to a conformational universe going from inactive to active receptor states with several intermediate states. Many of them have not been captured yet and their role for GPCR activation is not well understood. The study of this conformational space and the transition dynamics between different receptor populations is a major challenge in molecular biophysics. The rational design of effector molecules that target such receptor populations allows fine-tuning receptor signalling with higher specificity to produce drugs with safer therapeutic profiles. In this minireview, we outline highly conserved receptor regions which are considered determinant for the establishment of distinct receptor states. We then discuss in-silico approaches such as dimensionality reduction methods and Markov State Models to explore the GPCR conformational universe and exploit the obtained conformations through structure-based drug design. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Discovering Novel Alternaria solani Succinate Dehydrogenase Inhibitors by In Silico Modeling and Virtual Screening Strategies to Combat Early Blight

NASA Astrophysics Data System (ADS)

Iftikhar, Sehrish; Shahid, Ahmad A.; Halim, Sobia A.; Wolters, Pieter J.; Vleeshouwers, Vivianne G. A. A.; Khan, Ajmal; Al-Harrasi, Ahmed; Ahmad, Shahbaz

2017-11-01

Alternaria blight is an important foliage disease caused by Alternaria solani. The enzyme Succinate dehydrogenase (SDH) is a potential drug target because of its role in tricarboxylic acid cycle. Hence targeting Alternaria solani SDH enzyme could be efficient tool to design novel fungicides against A. solani. We employed computational methodologies to design new SDH inhibitors using homology modeling; pharmacophore modeling and structure based virtual screening protocol. The three dimensional SDH model showed good stereo-chemical and structural properties. Based on virtual screening results twelve commercially available compounds were purchased and tested in vitro and in vivo. The compounds were found to inhibit mycelial growth of A. solani. Moreover in vitro trials showed that inhibitory effects were enhanced with increase in concentrations. Similarly increased disease control was observed in pre-treated potato tubers. Hence the applied in silico strategy led us to identify new and novel fungicides.

Discovering Novel Alternaria solani Succinate Dehydrogenase Inhibitors by in Silico Modeling and Virtual Screening Strategies to Combat Early Blight

PubMed Central

Iftikhar, Sehrish; Shahid, Ahmad A.; Halim, Sobia A.; Wolters, Pieter J.; Vleeshouwers, Vivianne G. A. A.; Khan, Ajmal; Al-Harrasi, Ahmed; Ahmad, Shahbaz

2017-01-01

Alternaria blight is an important foliage disease caused by Alternaria solani. The enzyme Succinate dehydrogenase (SDH) is a potential drug target because of its role in tricarboxylic acid cycle. Hence targeting Alternaria solani SDH enzyme could be efficient tool to design novel fungicides against A. solani. We employed computational methodologies to design new SDH inhibitors using homology modeling; pharmacophore modeling and structure based virtual screening. The three dimensional SDH model showed good stereo-chemical and structural properties. Based on virtual screening results twelve commercially available compounds were purchased and tested in vitro and in vivo. The compounds were found to inhibit mycelial growth of A. solani. Moreover in vitro trials showed that inhibitory effects were enhanced with increase in concentrations. Similarly increased disease control was observed in pre-treated potato tubers. Hence the applied in silico strategy led us to identify novel fungicides. PMID:29204422

In silico modeling of the yeast protein and protein family interaction network

NASA Astrophysics Data System (ADS)

Goh, K.-I.; Kahng, B.; Kim, D.

2004-03-01

Understanding of how protein interaction networks of living organisms have evolved or are organized can be the first stepping stone in unveiling how life works on a fundamental ground. Here we introduce an in silico ``coevolutionary'' model for the protein interaction network and the protein family network. The essential ingredient of the model includes the protein family identity and its robustness under evolution, as well as the three previously proposed: gene duplication, divergence, and mutation. This model produces a prototypical feature of complex networks in a wide range of parameter space, following the generalized Pareto distribution in connectivity. Moreover, we investigate other structural properties of our model in detail with some specific values of parameters relevant to the yeast Saccharomyces cerevisiae, showing excellent agreement with the empirical data. Our model indicates that the physical constraints encoded via the domain structure of proteins play a crucial role in protein interactions.

Crystallographic Snapshots of the Complete Catalytic Cycle of the Unregulated Aspartate Transcarbamoylase from Bacillus subtilis

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

K Harris; G Cockrell; D Puleo

2011-12-31

Here, we report high-resolution X-ray structures of Bacillus subtilis aspartate transcarbamoylase (ATCase), an enzyme that catalyzes one of the first reactions in pyrimidine nucleotide biosynthesis. Structures of the enzyme have been determined in the absence of ligands, in the presence of the substrate carbamoyl phosphate, and in the presence of the bisubstrate/transition state analog N-phosphonacetyl-L-aspartate. Combining the structural data with in silico docking and electrostatic calculations, we have been able to visualize each step in the catalytic cycle of ATCase, from the ordered binding of the substrates, to the formation and decomposition of the tetrahedral intermediate, to the ordered releasemore » of the products from the active site. Analysis of the conformational changes associated with these steps provides a rationale for the lack of cooperativity in trimeric ATCases that do not possess regulatory subunits.« less

Centromeric chromatin and its dynamics in plants.

PubMed

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

2015-07-01

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

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.

Rational Design, Synthesis and Evaluation of γ-CD-Containing Cross-Linked Polyvinyl Alcohol Hydrogel as a Prednisone Delivery Platform.

PubMed

Marican, Adolfo; Avila-Salas, Fabián; Valdés, Oscar; Wehinger, Sergio; Villaseñor, Jorge; Fuentealba, Natalia; Arenas-Salinas, Mauricio; Argandoña, Yerko; Carrasco-Sánchez, Verónica; Durán-Lara, Esteban F

2018-03-07

This study describes the in-silico rational design, synthesis and evaluation of cross-linked polyvinyl alcohol hydrogels containing γ-cyclodextrin (γ-CDHSAs) as platforms for the sustained release of prednisone (PDN). Through in-silico studies using semi-empirical quantum mechanical calculations, the effectiveness of 20 dicarboxylic acids to generate a specific cross-linked hydrogel capable of supporting different amounts of γ-cyclodextrin (γ-CD) was evaluated. According to the interaction energies calculated with the in-silico studies, the hydrogel made from PVA cross-linked with succinic acids (SA) was shown to be the best candidate for containing γ-CD. Later, molecular dynamics simulation studies were performed in order to evaluate the intermolecular interactions between PDN and three cross-linked hydrogel formulations with different proportions of γ-CD (2.44%, 4.76% and 9.1%). These three cross-linked hydrogels were synthesized and characterized. The loading and the subsequent release of PDN from the hydrogels were investigated. The in-silico and experimental results showed that the interaction between PDN and γ-CDHSA was mainly produced with the γ-CDs linked to the hydrogels. Thus, the unique structures and properties of γ-CDHSA demonstrated an interesting multiphasic profile that could be utilized as a promising drug carrier for controlled, sustained and localized release of PDN.

Rational Design, Synthesis and Evaluation of γ-CD-Containing Cross-Linked Polyvinyl Alcohol Hydrogel as a Prednisone Delivery Platform

PubMed Central

Marican, Adolfo; Valdés, Oscar; Wehinger, Sergio; Villaseñor, Jorge; Fuentealba, Natalia; Argandoña, Yerko; Carrasco-Sánchez, Verónica

2018-01-01

This study describes the in-silico rational design, synthesis and evaluation of cross-linked polyvinyl alcohol hydrogels containing γ-cyclodextrin (γ-CDHSAs) as platforms for the sustained release of prednisone (PDN). Through in-silico studies using semi-empirical quantum mechanical calculations, the effectiveness of 20 dicarboxylic acids to generate a specific cross-linked hydrogel capable of supporting different amounts of γ-cyclodextrin (γ-CD) was evaluated. According to the interaction energies calculated with the in-silico studies, the hydrogel made from PVA cross-linked with succinic acids (SA) was shown to be the best candidate for containing γ-CD. Later, molecular dynamics simulation studies were performed in order to evaluate the intermolecular interactions between PDN and three cross-linked hydrogel formulations with different proportions of γ-CD (2.44%, 4.76% and 9.1%). These three cross-linked hydrogels were synthesized and characterized. The loading and the subsequent release of PDN from the hydrogels were investigated. The in-silico and experimental results showed that the interaction between PDN and γ-CDHSA was mainly produced with the γ-CDs linked to the hydrogels. Thus, the unique structures and properties of γ-CDHSA demonstrated an interesting multiphasic profile that could be utilized as a promising drug carrier for controlled, sustained and localized release of PDN. PMID:29518980

Genetic Profiles of Korean Patients With Glucose-6-Phosphate Dehydrogenase Deficiency

PubMed Central

Lee, Jaewoong; Choi, Hayoung; Kim, Jiyeon; Kwon, Ahlm; Jang, Woori; Chae, Hyojin; Kim, Myungshin; Kim, Yonggoo; Lee, Jae Wook; Chung, Nack-Gyun

2017-01-01

Background We describe the genetic profiles of Korean patients with glucose-6-phosphate dehydrogenase (G6PD) deficiencies and the effects of G6PD mutations on protein stability and enzyme activity on the basis of in silico analysis. Methods In parallel with a genetic analysis, the pathogenicity of G6PD mutations detected in Korean patients was predicted in silico. The simulated effects of G6PD mutations were compared to the WHO classes based on G6PD enzyme activity. Four previously reported mutations and three newly diagnosed patients with missense mutations were estimated. Results One novel mutation (p.Cys385Gly, labeled G6PD Kangnam) and two known mutations [p.Ile220Met (G6PD São Paulo) and p.Glu416Lys (G6PD Tokyo)] were identified in this study. G6PD mutations identified in Koreans were also found in Brazil (G6PD São Paulo), Poland (G6PD Seoul), United States of America (G6PD Riley), Mexico (G6PD Guadalajara), and Japan (G6PD Tokyo). Several mutations occurred at the same nucleotide, but resulted in different amino acid residue changes in different ethnic populations (p.Ile380 variant, G6PD Calvo Mackenna; p.Cys385 variants, Tomah, Madrid, Lynwood; p.Arg387 variant, Beverly Hills; p.Pro396 variant, Bari; and p.Pro396Ala in India). On the basis of the in silico analysis, Class I or II mutations were predicted to be highly deleterious, and the effects of one Class IV mutation were equivocal. Conclusions The genetic profiles of Korean individuals with G6PD mutations indicated that the same mutations may have arisen by independent mutational events, and were not derived from shared ancestral mutations. The in silico analysis provided insight into the role of G6PD mutations in enzyme function and stability. PMID:28028996

Genetic Profiles of Korean Patients With Glucose-6-Phosphate Dehydrogenase Deficiency.

PubMed

Lee, Jaewoong; Park, Joonhong; Choi, Hayoung; Kim, Jiyeon; Kwon, Ahlm; Jang, Woori; Chae, Hyojin; Kim, Myungshin; Kim, Yonggoo; Lee, Jae Wook; Chung, Nack Gyun; Cho, Bin

2017-03-01

We describe the genetic profiles of Korean patients with glucose-6-phosphate dehydrogenase (G6PD) deficiencies and the effects of G6PD mutations on protein stability and enzyme activity on the basis of in silico analysis. In parallel with a genetic analysis, the pathogenicity of G6PD mutations detected in Korean patients was predicted in silico. The simulated effects of G6PD mutations were compared to the WHO classes based on G6PD enzyme activity. Four previously reported mutations and three newly diagnosed patients with missense mutations were estimated. One novel mutation (p.Cys385Gly, labeled G6PD Kangnam) and two known mutations [p.Ile220Met (G6PD São Paulo) and p.Glu416Lys (G6PD Tokyo)] were identified in this study. G6PD mutations identified in Koreans were also found in Brazil (G6PD São Paulo), Poland (G6PD Seoul), United States of America (G6PD Riley), Mexico (G6PD Guadalajara), and Japan (G6PD Tokyo). Several mutations occurred at the same nucleotide, but resulted in different amino acid residue changes in different ethnic populations (p.Ile380 variant, G6PD Calvo Mackenna; p.Cys385 variants, Tomah, Madrid, Lynwood; p.Arg387 variant, Beverly Hills; p.Pro396 variant, Bari; and p.Pro396Ala in India). On the basis of the in silico analysis, Class I or II mutations were predicted to be highly deleterious, and the effects of one Class IV mutation were equivocal. The genetic profiles of Korean individuals with G6PD mutations indicated that the same mutations may have arisen by independent mutational events, and were not derived from shared ancestral mutations. The in silico analysis provided insight into the role of G6PD mutations in enzyme function and stability.

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.

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.

Protein and Peptide Gas-phase Structure Investigation Using Collision Cross Section Measurements and Hydrogen Deuterium Exchange

NASA Astrophysics Data System (ADS)

Khakinejad, Mahdiar

Protein and peptide gas-phase structure analysis provides the opportunity to study these species outside of their explicit environment where the interaction network with surrounding molecules makes the analysis difficult [1]. Although gas-phase structure analysis offers a unique opportunity to study the intrinsic behavior of these biomolecules [2-4], proteins and peptides exhibit very low vapor pressures [2]. Peptide and protein ions can be rendered in the gas-phase using electrospray ionization (ESI) [5]. There is a growing body of literature that shows proteins and peptides can maintain solution structures during the process of ESI and these structures can persist for a few hundred milliseconds [6-9]. Techniques for monitoring gas-phase protein and peptide ion structures are categorized as physical probes and chemical probes. Collision cross section (CCS) measurement, being a physical probe, is a powerful method to investigate gas-phase structure size [3, 7, 10-15]; however, CCS values alone do not establish a one to one relation with structure(i.e., the CCS value is an orientationally averaged value [15-18]. Here we propose the utility of gas-phase hydrogen deuterium exchange (HDX) as a second criterion of structure elucidation. The proposed approach incudes extensive MD simulations to sample biomolecular ion conformation space with the production of numerous, random in-silico structures. Subsequently a CCS can be calculated for these structures and theoretical CCS values are compared with experimental values to produce a pool of candidate structures. Utilizing a chemical reaction model based on the gas-phase HDX mechanism, the HDX kinetics behavior of these candidate structures are predicted and compared to experimental results to nominate the best in-silico structures which match (chemically and physically) with experimental observations. For the predictive approach to succeed, an extensive technique and method development is essential. To combine CCS measurements and gas-phase HDX studies at the amino acid residue level, for the first time a drift tube is connected to a linear ion trap (LIT) with electron transfer dissociation (ETD) capability[19, 20]. In this manner CCS and per-residue deuterium uptake measurements for a model peptide carried out successfully[19]. In this study, the gas-phase conformations of electrosprayed ions of the model peptide KKDDDDIIKIIK have been examined. Using ion structures obtained from molecular dynamics (MD) simulation and considering charge-site/exchange-site density the level of the maximum total deuterium uptake for the gas-phase ions is explained. Also a new hydrogen accessibility scoring (HAS) model that includes two distance calculations (charge site to carbonyl group and carbonyl group to exchange site) is applied to the in-silico structures to describe the expected HDX behavior for these structures. Further investigation to improve the accuracy of the model is accomplished by a "per-residue" HDX kinetics study of the model peptide [21]. In this study, the ion residence time and the deuterium uptake of each residue is measured at different partial pressures of D2O. Subsequently the contribution each residue to the overall HDX rate of the intact peptide ion is calculated. These rate contributions of the residues exhibit a better fit to HAS than their maximum deuterium uptake. Proteins and peptides with very frequent acidic residue in their sequence provide very poor signal levels when employing positive polarity ESI. Also, the comparison of protonated and deprotonated ions of these biomolecules offers the potential to provide a better structural characterization [22]. Per-residue deuterium uptake values resulting from collision-induced dissociation (CID) of the model peptide KKDDDDIIKIIK were used to investigated the degree of hydrogen deuterium scrambling for deprotonated ions [23]. Remarkably, limited isotopic scrambling was observed in this study of this small model peptide. This data and the per-residue deuterium uptake of the triply-protonated model peptide Acetyl-PAAAAKAAAAKAAAAKAAAAK are exploited to propose a lemma to allocate protonation and deprotonation sites for peptide ions in the gas-phase. Insulin ions, as a small protein model system, are examined to investigate the relation of the maximum deuterium uptake value for each insulin chain to the exposed surface area of each insulin subunit [22]. The results show that the methodology can be applied on the protein complexes to provide information about the exposed surface area of each subunit.

In Silico Design of Smart Binders to Anthrax PA

DTIC Science & Technology

2012-09-01

nanosecond(ns) molecular dynamics simulation in the NPT ensemble (constant particle number, pressure, and temperature) at 300K, with the CHARMM force...protective antigen (PA). Before the docking runs, the DS23 peptide was simulated using molecular dynamics to generate an ensemble of structures...structure), we do not see a large amount of structural change when using molecular dynamics after Rosetta docking. We note that this RMSD does not take

GeneSilico protein structure prediction meta-server.

PubMed

Kurowski, Michal A; Bujnicki, Janusz M

2003-07-01

Rigorous assessments of protein structure prediction have demonstrated that fold recognition methods can identify remote similarities between proteins when standard sequence search methods fail. It has been shown that the accuracy of predictions is improved when refined multiple sequence alignments are used instead of single sequences and if different methods are combined to generate a consensus model. There are several meta-servers available that integrate protein structure predictions performed by various methods, but they do not allow for submission of user-defined multiple sequence alignments and they seldom offer confidentiality of the results. We developed a novel WWW gateway for protein structure prediction, which combines the useful features of other meta-servers available, but with much greater flexibility of the input. The user may submit an amino acid sequence or a multiple sequence alignment to a set of methods for primary, secondary and tertiary structure prediction. Fold-recognition results (target-template alignments) are converted into full-atom 3D models and the quality of these models is uniformly assessed. A consensus between different FR methods is also inferred. The results are conveniently presented on-line on a single web page over a secure, password-protected connection. The GeneSilico protein structure prediction meta-server is freely available for academic users at http://genesilico.pl/meta.

GeneSilico protein structure prediction meta-server

PubMed Central

Kurowski, Michal A.; Bujnicki, Janusz M.

2003-01-01

Rigorous assessments of protein structure prediction have demonstrated that fold recognition methods can identify remote similarities between proteins when standard sequence search methods fail. It has been shown that the accuracy of predictions is improved when refined multiple sequence alignments are used instead of single sequences and if different methods are combined to generate a consensus model. There are several meta-servers available that integrate protein structure predictions performed by various methods, but they do not allow for submission of user-defined multiple sequence alignments and they seldom offer confidentiality of the results. We developed a novel WWW gateway for protein structure prediction, which combines the useful features of other meta-servers available, but with much greater flexibility of the input. The user may submit an amino acid sequence or a multiple sequence alignment to a set of methods for primary, secondary and tertiary structure prediction. Fold-recognition results (target-template alignments) are converted into full-atom 3D models and the quality of these models is uniformly assessed. A consensus between different FR methods is also inferred. The results are conveniently presented on-line on a single web page over a secure, password-protected connection. The GeneSilico protein structure prediction meta-server is freely available for academic users at http://genesilico.pl/meta. PMID:12824313

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

RNA-SSPT: RNA Secondary Structure Prediction Tools.

PubMed

Ahmad, Freed; Mahboob, Shahid; Gulzar, Tahsin; Din, Salah U; Hanif, Tanzeela; Ahmad, Hifza; Afzal, Muhammad

2013-01-01

The prediction of RNA structure is useful for understanding evolution for both in silico and in vitro studies. Physical methods like NMR studies to predict RNA secondary structure are expensive and difficult. Computational RNA secondary structure prediction is easier. Comparative sequence analysis provides the best solution. But secondary structure prediction of a single RNA sequence is challenging. RNA-SSPT is a tool that computationally predicts secondary structure of a single RNA sequence. Most of the RNA secondary structure prediction tools do not allow pseudoknots in the structure or are unable to locate them. Nussinov dynamic programming algorithm has been implemented in RNA-SSPT. The current studies shows only energetically most favorable secondary structure is required and the algorithm modification is also available that produces base pairs to lower the total free energy of the secondary structure. For visualization of RNA secondary structure, NAVIEW in C language is used and modified in C# for tool requirement. RNA-SSPT is built in C# using Dot Net 2.0 in Microsoft Visual Studio 2005 Professional edition. The accuracy of RNA-SSPT is tested in terms of Sensitivity and Positive Predicted Value. It is a tool which serves both secondary structure prediction and secondary structure visualization purposes.

RNA-SSPT: RNA Secondary Structure Prediction Tools

PubMed Central

Ahmad, Freed; Mahboob, Shahid; Gulzar, Tahsin; din, Salah U; Hanif, Tanzeela; Ahmad, Hifza; Afzal, Muhammad

2013-01-01

The prediction of RNA structure is useful for understanding evolution for both in silico and in vitro studies. Physical methods like NMR studies to predict RNA secondary structure are expensive and difficult. Computational RNA secondary structure prediction is easier. Comparative sequence analysis provides the best solution. But secondary structure prediction of a single RNA sequence is challenging. RNA-SSPT is a tool that computationally predicts secondary structure of a single RNA sequence. Most of the RNA secondary structure prediction tools do not allow pseudoknots in the structure or are unable to locate them. Nussinov dynamic programming algorithm has been implemented in RNA-SSPT. The current studies shows only energetically most favorable secondary structure is required and the algorithm modification is also available that produces base pairs to lower the total free energy of the secondary structure. For visualization of RNA secondary structure, NAVIEW in C language is used and modified in C# for tool requirement. RNA-SSPT is built in C# using Dot Net 2.0 in Microsoft Visual Studio 2005 Professional edition. The accuracy of RNA-SSPT is tested in terms of Sensitivity and Positive Predicted Value. It is a tool which serves both secondary structure prediction and secondary structure visualization purposes. PMID:24250115

Dipeptidyl peptidase-II from probiotic Pediococcus acidilactici: Purification and functional characterization.

PubMed

Gandhi, Dimpi; Chanalia, Preeti; Attri, Pooja; Dhanda, Suman

2016-12-01

Dipeptidylpeptidase-II (DPP-II, E.C. 3.4.14.2), an exopeptidase was purified 15.4 fold with specific activity and yield of 15.4U/mg/mL and 14.68% respectively by a simple two step procedure from a probiotic Pediococcus acidilactici. DPP-II is 38.7KDa homodimeric serine peptidase with involvement of His and subunit mass of 18.9KDa. The enzyme exhibited optimal activity at pH 7.0 and 37°C with activation energy of 24.97kJ/mol. The enzyme retained more than 90% activity upto 50°C thus adding industrial importance. DPP-II hydrolysed Lys-Ala-4mβNA with K M of 50μM and V max of 30.8nmol/mL/min. In-silico characterization studies of DPP-II on the basis of peptide fragments obtained by MALDI-TOF revealed an evolutionary relationship between DPP-II of prokaryotes and phosphate binding proteins. Secondary and three-dimensional structure of enzyme was also deduced by in-silico approach. Functional studies of DPP-II by TLC and HPLC-analysis of collagen degraded products revealed that enzyme action released free amino acids and other metabolites. Microscopic and SDS-PAGE analysis of enzyme treated analysis of chicken's chest muscle (meat) hydrolysis revealed change and hydrolysis of myofibrils. This may affect the flavor and texture of meat thereby suggesting its role in meat tenderization. Being a protein of LAB (Lactic acid bacteria), it is also expected to be safe. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

A combined experimental and in silico characterization to highlight additional structural features and properties of a potentially new drug

NASA Astrophysics Data System (ADS)

Bastos, Isadora T. S.; Costa, Fanny N.; Silva, Tiago F.; Barreiro, Eliezer J.; Lima, Lídia M.; Braz, Delson; Lombardo, Giuseppe M.; Punzo, Francesco; Ferreira, Fabio F.; Barroso, Regina C.

2017-10-01

LASSBio-1755 is a new cycloalkyl-N-acylhydrazone parent compound designed for the development of derivatives with antinociceptive and anti-inflammatory activities. Although single crystal X-ray diffraction has been considered as the golden standard in structure determination, we successfully used X-ray powder diffraction data in the structural determination of new synthesized compounds, in order to overcome the bottle-neck due to the difficulties experienced in harvesting good quality single crystals of the compounds. We therefore unequivocally assigned the relative configuration (E) to the imine double bond and a s-cis conformation of the amide function of the N-acylhydrazone compound. These features are confirmed by a computational analysis performed on the basis of molecular dynamics calculations, which are extended not only to the structural characteristics but also to the analysis of the anisotropic atomic displacement parameters, a further information - missed in a typical powder diffraction analysis. The so inferred data were used to perform additional cycles of refinement and eventually generate a new cif file with additional physical information. Furthermore, crystal morphology prediction was performed, which is in agreement with the experimental images acquired by scanning electron microscopy, thus providing useful information on possible alternative paths for better crystallization strategies.

Application of computational methods for the design of BACE-1 inhibitors: validation of in silico modelling.

PubMed

Bajda, Marek; Jończyk, Jakub; Malawska, Barbara; Filipek, Sławomir

2014-03-24

β-Secretase (BACE-1) constitutes an important target for search of anti-Alzheimer's drugs. The first inhibitors of this enzyme were peptidic compounds with high molecular weight and low bioavailability. Therefore, the search for new efficient non-peptidic inhibitors has been undertaken by many scientific groups. We started our work from the development of in silico methodology for the design of novel BACE-1 ligands. It was validated on the basis of crystal structures of complexes with inhibitors, redocking, cross-docking and training/test sets of reference ligands. The presented procedure of assessment of the novel compounds as β-secretase inhibitors could be widely used in the design process.

Evaluation of a focused virtual library of heterobifunctional ligands for Clostridium difficile toxins.

PubMed

Sanhueza, Carlos A; Cartmell, Jonathan; El-Hawiet, Amr; Szpacenko, Adam; Kitova, Elena N; Daneshfar, Rambod; Klassen, John S; Lang, Dean E; Eugenio, Luiz; Ng, Kenneth K-S; Kitov, Pavel I; Bundle, David R

2015-01-07

A focused library of virtual heterobifunctional ligands was generated in silico and a set of ligands with recombined fragments was synthesized and evaluated for binding to Clostridium difficile toxins. The position of the trisaccharide fragment was used as a reference for filtering docked poses during virtual screening to match the trisaccharide ligand in a crystal structure. The peptoid, a diversity fragment probing the protein surface area adjacent to a known binding site, was generated by a multi-component Ugi reaction. Our approach combines modular fragment-based design with in silico screening of synthetically feasible compounds and lays the groundwork for future efforts in development of composite bifunctional ligands for large clostridial toxins.

Toward Fully in Silico Melting Point Prediction Using Molecular Simulations

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

Zhang, Y; Maginn, EJ

2013-03-01

Melting point is one of the most fundamental and practically important properties of a compound. Molecular computation of melting points. However, all of these methods simulation methods have been developed for the accurate need an experimental crystal structure as input, which means that such calculations are not really predictive since the melting point can be measured easily in experiments once a crystal structure is known. On the other hand, crystal structure prediction (CSP) has become an active field and significant progress has been made, although challenges still exist. One of the main challenges is the existence of many crystal structuresmore » (polymorphs) that are very close in energy. Thermal effects and kinetic factors make the situation even more complicated, such that it is still not trivial to predict experimental crystal structures. In this work, we exploit the fact that free energy differences are often small between crystal structures. We show that accurate melting point predictions can be made by using a reasonable crystal structure from CSP as a starting point for a free energy-based melting point calculation. The key is that most crystal structures predicted by CSP have free energies that are close to that of the experimental structure. The proposed method was tested on two rigid molecules and the results suggest that a fully in silico melting point prediction method is possible.« less

Novel Non-Peptide Inhibitors against SmCL1 of Schistosoma mansoni: In Silico Elucidation, Implications and Evaluation via Knowledge Based Drug Discovery

PubMed Central

Zafar, Atif; Ahmad, Sabahuddin; Rizvi, Asim; Ahmad, Masood

2015-01-01

Schistosomiasis is a major endemic disease known for excessive mortality and morbidity in developing countries. Because praziquantel is the only drug available for its treatment, the risk of drug resistance emphasizes the need to discover new drugs for this disease. Cathepsin SmCL1 is the critical target for drug design due to its essential role in the digestion of host proteins for growth and development of Schistosoma mansoni. Inhibiting the function of SmCL1 could control the wide spread of infections caused by S. mansoni in humans. With this objective, a homology modeling approach was used to obtain theoretical three-dimensional (3D) structure of SmCL1. In order to find the potential inhibitors of SmCL1, a plethora of in silico techniques were employed to screen non-peptide inhibitors against SmCL1 via structure-based drug discovery protocol. Receiver operating characteristic (ROC) curve analysis and molecular dynamics (MD) simulation were performed on the results of docked protein-ligand complexes to identify top ranking molecules against the modelled 3D structure of SmCL1. MD simulation results suggest the phytochemical Simalikalactone-D as a potential lead against SmCL1, whose pharmacophore model may be useful for future screening of potential drug molecules. To conclude, this is the first report to discuss the virtual screening of non-peptide inhibitors against SmCL1 of S. mansoni, with significant therapeutic potential. Results presented herein provide a valuable contribution to identify the significant leads and further derivatize them to suitable drug candidates for antischistosomal therapy. PMID:25933436

Camelid Ig V genes reveal significant human homology not seen in therapeutic target genes, providing for a powerful therapeutic antibody platform

PubMed Central

Klarenbeek, Alex; Mazouari, Khalil El; Desmyter, Aline; Blanchetot, Christophe; Hultberg, Anna; de Jonge, Natalie; Roovers, Rob C; Cambillau, Christian; Spinelli, Sylvia; Del-Favero, Jurgen; Verrips, Theo; de Haard, Hans J; Achour, Ikbel

2015-01-01

Camelid immunoglobulin variable (IGV) regions were found homologous to their human counterparts; however, the germline V repertoires of camelid heavy and light chains are still incomplete and their therapeutic potential is only beginning to be appreciated. We therefore leveraged the publicly available HTG and WGS databases of Lama pacos and Camelus ferus to retrieve the germline repertoire of V genes using human IGV genes as reference. In addition, we amplified IGKV and IGLV genes to uncover the V germline repertoire of Lama glama and sequenced BAC clones covering part of the Lama pacos IGK and IGL loci. Our in silico analysis showed that camelid counterparts of all human IGKV and IGLV families and most IGHV families could be identified, based on canonical structure and sequence homology. Interestingly, this sequence homology seemed largely restricted to the Ig V genes and was far less apparent in other genes: 6 therapeutically relevant target genes differed significantly from their human orthologs. This contributed to efficient immunization of llamas with the human proteins CD70, MET, interleukin (IL)-1β and IL-6, resulting in large panels of functional antibodies. The in silico predicted human-homologous canonical folds of camelid-derived antibodies were confirmed by X-ray crystallography solving the structure of 2 selected camelid anti-CD70 and anti-MET antibodies. These antibodies showed identical fold combinations as found in the corresponding human germline V families, yielding binding site structures closely similar to those occurring in human antibodies. In conclusion, our results indicate that active immunization of camelids can be a powerful therapeutic antibody platform. PMID:26018625

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

PubMed

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

2016-11-01

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

Extensive in silico analysis of Mimivirus coded Rab GTPase homolog suggests a possible role in virion membrane biogenesis.

PubMed

Zade, Amrutraj; Sengupta, Malavi; Kondabagil, Kiran

2015-01-01

Rab GTPases are the key regulators of intracellular membrane trafficking in eukaryotes. Many viruses and intracellular bacterial pathogens have evolved to hijack the host Rab GTPase functions, mainly through activators and effector proteins, for their benefit. Acanthamoeba polyphaga mimivirus (APMV) is one of the largest viruses and belongs to the monophyletic clade of nucleo-cytoplasmic large DNA viruses (NCLDV). The inner membrane lining is integral to the APMV virion structure. APMV assembly involves extensive host membrane modifications, like vesicle budding and fusion, leading to the formation of a membrane sheet that is incorporated into the virion. Intriguingly, APMV and all group I members of the Mimiviridae family code for a putative Rab GTPase protein. APMV is the first reported virus to code for a Rab GTPase (encoded by R214 gene). Our thorough in silico analysis of the subfamily specific (SF) region of Mimiviridae Rab GTPase sequences suggests that they are related to Rab5, a member of the group II Rab GTPases, of lower eukaryotes. Because of their high divergence from the existing three isoforms, A, B, and C of the Rab5-family, we suggest that Mimiviridae Rabs constitute a new isoform, Rab5D. Phylogenetic analysis indicated probable horizontal acquisition from a lower eukaryotic ancestor followed by selection and divergence. Furthermore, interaction network analysis suggests that vps34 (a Class III PI3K homolog, coded by APMV L615), Atg-8 and dynamin (host proteins) are recruited by APMV Rab GTPase during capsid assembly. Based on these observations, we hypothesize that APMV Rab plays a role in the acquisition of inner membrane during virion assembly.

Perspectives on pathway perturbation: Focused research to enhance 3R objectives

EPA Science Inventory

In vitro high-throughput screening (HTS) and in silico technologies are emerging as 21st century tools for hazard identification. Computational methods that strategically examine cross-species conservation of protein sequence/structural information for chemical molecular targets ...

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

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.

Inhibitor-induced structural change in the HCV IRES domain IIa RNA

PubMed Central

Paulsen, Ryan B.; Seth, Punit P.; Swayze, Eric E.; Griffey, Richard H.; Skalicky, Jack J.; Cheatham, Thomas E.; Davis, Darrell R.

2010-01-01

Translation of the hepatitis C virus (HCV) RNA is initiated from a highly structured internal ribosomal entry site (IRES) in the 5′ untranslated region (5′ UTR) of the RNA genome. An important structural feature of the native RNA is an approximately 90° helical bend localized to domain IIa that positions the apical loop of domain IIb of the IRES near the 40S ribosomal E-site to promote eIF2-GDP release, facilitating 80S ribosome assembly. We report here the NMR structure of a domain IIa construct in complex with a potent small-molecule inhibitor of HCV replication. Molecular dynamics refinement in explicit solvent and subsequent energetic analysis indicated that each inhibitor stereoisomer bound with comparable affinity and in an equivalent binding mode. The in silico analysis was substantiated by fluorescence-based assays showing that the relative binding free energies differed by only 0.7 kcal/mol. Binding of the inhibitor displaces key nucleotide residues within the bulge region, effecting a major conformational change that eliminates the bent RNA helical trajectory, providing a mechanism for the antiviral activity of this inhibitor class. PMID:20360559

Toward antituberculosis drugs: in silico screening of synthetic compounds against Mycobacterium tuberculosisl,d-transpeptidase 2.

PubMed

Billones, Junie B; Carrillo, Maria Constancia O; Organo, Voltaire G; Macalino, Stephani Joy Y; Sy, Jamie Bernadette A; Emnacen, Inno A; Clavio, Nina Abigail B; Concepcion, Gisela P

2016-01-01

Mycobacterium tuberculosis (Mtb) the main causative agent of tuberculosis, is the main reason why this disease continues to be a global public health threat. It is therefore imperative to find a novel antitubercular drug target that is unique to the structural machinery or is essential to the growth and survival of the bacterium. One such target is the enzyme l,d-transpeptidase 2, also known as LdtMt2, a protein primarily responsible for the catalysis of 3→3 cross-linkages that make up the mycolyl-arabinogalactan-peptidoglycan complex of Mtb. In this study, structure-based pharmacophore screening, molecular docking, and in silico toxicity evaluations were employed in screening compounds from a database of synthetic compounds. Out of the 4.5 million database compounds, 18 structures were identified as high-scoring, high-binding hits with very satisfactory absorption, distribution, metabolism, excretion, and toxicity properties. Two out of the 18 compounds were further subjected to in vitro bioactivity assays, with one exhibiting a good inhibitory activity against the Mtb H37Ra strain.

Targeting Dengue Virus NS-3 Helicase by Ligand based Pharmacophore Modeling and Structure based Virtual Screening

NASA Astrophysics Data System (ADS)

Halim, Sobia A.; Khan, Shanza; Khan, Ajmal; Wadood, Abdul; Mabood, Fazal; Hussain, Javid; Al-Harrasi, Ahmed

2017-10-01

Dengue fever is an emerging public health concern, with several million viral infections occur annually, for which no effective therapy currently exist. Non-structural protein 3 (NS-3) Helicase encoded by the dengue virus (DENV) is considered as a potential drug target to design new and effective drugs against dengue. Helicase is involved in unwinding of dengue RNA. This study was conducted to design new NS-3 Helicase inhibitor by in silico ligand- and structure based approaches. Initially ligand-based pharmacophore model was generated that was used to screen a set of 1201474 compounds collected from ZINC Database. The compounds matched with the pharmacophore model were docked into the active site of NS-3 helicase. Based on docking scores and binding interactions, twenty five compounds are suggested to be potential inhibitors of NS3 Helicase. The pharmacokinetic properties of these hits were predicted. The selected hits revealed acceptable ADMET properties. This study identified potential inhibitors of NS-3 Helicase in silico, and can be helpful in the treatment of Dengue.

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

PubMed

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

2016-01-01

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

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

PubMed Central

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

2016-01-01

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

Crysalis: an integrated server for computational analysis and design of protein crystallization.

PubMed

Wang, Huilin; Feng, Liubin; Zhang, Ziding; Webb, Geoffrey I; Lin, Donghai; Song, Jiangning

2016-02-24

The failure of multi-step experimental procedures to yield diffraction-quality crystals is a major bottleneck in protein structure determination. Accordingly, several bioinformatics methods have been successfully developed and employed to select crystallizable proteins. Unfortunately, the majority of existing in silico methods only allow the prediction of crystallization propensity, seldom enabling computational design of protein mutants that can be targeted for enhancing protein crystallizability. Here, we present Crysalis, an integrated crystallization analysis tool that builds on support-vector regression (SVR) models to facilitate computational protein crystallization prediction, analysis, and design. More specifically, the functionality of this new tool includes: (1) rapid selection of target crystallizable proteins at the proteome level, (2) identification of site non-optimality for protein crystallization and systematic analysis of all potential single-point mutations that might enhance protein crystallization propensity, and (3) annotation of target protein based on predicted structural properties. We applied the design mode of Crysalis to identify site non-optimality for protein crystallization on a proteome-scale, focusing on proteins currently classified as non-crystallizable. Our results revealed that site non-optimality is based on biases related to residues, predicted structures, physicochemical properties, and sequence loci, which provides in-depth understanding of the features influencing protein crystallization. Crysalis is freely available at http://nmrcen.xmu.edu.cn/crysalis/.

Crysalis: an integrated server for computational analysis and design of protein crystallization

PubMed Central

Wang, Huilin; Feng, Liubin; Zhang, Ziding; Webb, Geoffrey I.; Lin, Donghai; Song, Jiangning

2016-01-01

The failure of multi-step experimental procedures to yield diffraction-quality crystals is a major bottleneck in protein structure determination. Accordingly, several bioinformatics methods have been successfully developed and employed to select crystallizable proteins. Unfortunately, the majority of existing in silico methods only allow the prediction of crystallization propensity, seldom enabling computational design of protein mutants that can be targeted for enhancing protein crystallizability. Here, we present Crysalis, an integrated crystallization analysis tool that builds on support-vector regression (SVR) models to facilitate computational protein crystallization prediction, analysis, and design. More specifically, the functionality of this new tool includes: (1) rapid selection of target crystallizable proteins at the proteome level, (2) identification of site non-optimality for protein crystallization and systematic analysis of all potential single-point mutations that might enhance protein crystallization propensity, and (3) annotation of target protein based on predicted structural properties. We applied the design mode of Crysalis to identify site non-optimality for protein crystallization on a proteome-scale, focusing on proteins currently classified as non-crystallizable. Our results revealed that site non-optimality is based on biases related to residues, predicted structures, physicochemical properties, and sequence loci, which provides in-depth understanding of the features influencing protein crystallization. Crysalis is freely available at http://nmrcen.xmu.edu.cn/crysalis/. PMID:26906024

Structural characterization of a novel peptide with antimicrobial activity from the venom gland of the scorpion Tityus stigmurus: Stigmurin.

PubMed

de Melo, Edinara Targino; Estrela, Andréia Bergamo; Santos, Elizabeth Cristina Gomes; Machado, Paula Renata Lima; Farias, Kleber Juvenal Silva; Torres, Taffarel Melo; Carvalho, Enéas; Lima, João Paulo Matos Santos; Silva-Júnior, Arnóbio Antonio; Barbosa, Euzébio Guimarães; Fernandes-Pedrosa, Matheus de Freitas

2015-06-01

A new antimicrobial peptide, herein named Stigmurin, was selected based on a transcriptomic analysis of the Brazilian yellow scorpion Tityus stigmurus venom gland, an underexplored source for toxic peptides with possible biotechnological applications. Stigmurin was investigated in silico, by circular dichroism (CD) spectroscopy, and in vitro. The CD spectra suggested that this peptide interacts with membranes, changing its conformation in the presence of an amphipathic environment, with predominance of random coil and beta-sheet structures. Stigmurin exhibited antibacterial and antifungal activity, with minimal inhibitory concentrations ranging from 8.7 to 69.5μM. It was also showed that Stigmurin is toxic against SiHa and Vero E6 cell lines. The results suggest that Stigmurin can be considered a potential anti-infective drug. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

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

PubMed

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

2010-01-01

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

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

In Silico/In Vivo Insights into the Functional and Evolutionary Pathway of Pseudomonas aeruginosa Oleate-Diol Synthase. Discovery of a New Bacterial Di-Heme Cytochrome C Peroxidase Subfamily

PubMed Central

Estupiñán, Mónica; Álvarez-García, Daniel; Barril, Xavier; Diaz, Pilar; Manresa, Angeles

2015-01-01

As previously reported, P. aeruginosa genes PA2077 and PA2078 code for 10S-DOX (10S-Dioxygenase) and 7,10-DS (7,10-Diol Synthase) enzymes involved in long-chain fatty acid oxygenation through the recently described oleate-diol synthase pathway. Analysis of the amino acid sequence of both enzymes revealed the presence of two heme-binding motifs (CXXCH) on each protein. Phylogenetic analysis showed the relation of both proteins to bacterial di-heme cytochrome c peroxidases (Ccps), similar to Xanthomonas sp. 35Y rubber oxidase RoxA. Structural homology modelling of PA2077 and PA2078 was achieved using RoxA (pdb 4b2n) as a template. From the 3D model obtained, presence of significant amino acid variations in the predicted heme-environment was found. Moreover, the presence of palindromic repeats located in enzyme-coding regions, acting as protein evolution elements, is reported here for the first time in P. aeruginosa genome. These observations and the constructed phylogenetic tree of the two proteins, allow the proposal of an evolutionary pathway for P. aeruginosa oleate-diol synthase operon. Taking together the in silico and in vivo results obtained we conclude that enzymes PA2077 and PA2078 are the first described members of a new subfamily of bacterial peroxidases, designated as Fatty acid-di-heme Cytochrome c peroxidases (FadCcp). PMID:26154497

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

PubMed Central

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

2016-01-01

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

Development of Drugs for Epstein - Barr virus using High-Throughput in silico Virtual Screening

PubMed Central

Li, Ning; Thompson, Scott; Jiang, Hualiang; Lieberman, Paul M.; Luo, Cheng

2010-01-01

Importance of the field Epstein-Barr virus (EBV) is a ubiquitious human herpesvirus that is causally associated with endemic forms of Burkitt’s lymphoma (BL), nasopharyngeal carcinoma, and lymphoproliferative disease in immunosuppressed individuals. On a global scale, EBV infects over 90% of the adult population and is responsible for ~1% of all human cancers. To date, there is no efficacious drug or therapy for the treatment of EBV infection and EBV-related diseases. Areas covered in this review In this review, we discuss the existing anti-EBV inhibitors and those under development. We discuss the value of different molecular targets, including EBV lytic DNA replication enzymes, as well as proteins that are expressed exclusively during latent infection, like EBNA1 and LMP1. Since the atomic structure of the EBNA1 DNA binding domain has been described, it is an attractive target for in silico methods of drug design and small molecule screening. We discuss the use of computational methods that can greatly facilitate the development of novel inhibitors and how in silico screening methods can be applied to target proteins with known structures, like EBNA1, to treat EBV infection and disease. What the reader will gain The reader will be familiarized with the problems in targeting of EBV for inhibition by small molecules and how computational methods can greatly facilitate this process. Take home message Despite the impressive efficacy of nucleoside analogues for the treatment of herpesvirus lytic infection, there remain few effective treatments for latent infections. Since EBV-latent infection persists within and contributes to the formation of EBV-associated cancers, targeting EBV latent proteins is an unmet medical need. High throughput in silico screening can accelerate the process of drug discovery for novel and selective agents that inhibit EBV latent infection and associated disease. PMID:22822721

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

Structural Basis for the Inhibition of Gas Hydrates by α-Helical Antifreeze Proteins

PubMed Central

Sun, Tianjun; Davies, Peter L.; Walker, Virginia K.

2015-01-01

Kinetic hydrate inhibitors (KHIs) are used commercially to inhibit gas hydrate formation and growth in pipelines. However, improvement of these polymers has been constrained by the lack of verified molecular models. Since antifreeze proteins (AFPs) act as KHIs, we have used their solved x-ray crystallographic structures in molecular modeling to explore gas hydrate inhibition. The internal clathrate water network of the fish AFP Maxi, which extends to the protein’s outer surface, is remarkably similar to the {100} planes of structure type II (sII) gas hydrate. The crystal structure of this water web has facilitated the construction of in silico models for Maxi and type I AFP binding to sII hydrates. Here, we have substantiated our models with experimental evidence of Maxi binding to the tetrahydrofuran sII model hydrate. Both in silico and experimental evidence support the absorbance-inhibition mechanism proposed for KHI binding to gas hydrates. Based on the Maxi crystal structure we suggest that the inhibitor adsorbs to the gas hydrate lattice through the same anchored clathrate water mechanism used to bind ice. These results will facilitate the rational design of a next generation of effective green KHIs for the petroleum industry to ensure safe and efficient hydrocarbon flow. PMID:26488661

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.

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.

ProTox: a web server for the in silico prediction of rodent oral toxicity

PubMed Central

Drwal, Malgorzata N.; Banerjee, Priyanka; Dunkel, Mathias; Wettig, Martin R.; Preissner, Robert

2014-01-01

Animal trials are currently the major method for determining the possible toxic effects of drug candidates and cosmetics. In silico prediction methods represent an alternative approach and aim to rationalize the preclinical drug development, thus enabling the reduction of the associated time, costs and animal experiments. Here, we present ProTox, a web server for the prediction of rodent oral toxicity. The prediction method is based on the analysis of the similarity of compounds with known median lethal doses (LD50) and incorporates the identification of toxic fragments, therefore representing a novel approach in toxicity prediction. In addition, the web server includes an indication of possible toxicity targets which is based on an in-house collection of protein–ligand-based pharmacophore models (‘toxicophores’) for targets associated with adverse drug reactions. The ProTox web server is open to all users and can be accessed without registration at: http://tox.charite.de/tox. The only requirement for the prediction is the two-dimensional structure of the input compounds. All ProTox methods have been evaluated based on a diverse external validation set and displayed strong performance (sensitivity, specificity and precision of 76, 95 and 75%, respectively) and superiority over other toxicity prediction tools, indicating their possible applicability for other compound classes. PMID:24838562

In silico identification of a therapeutic target for photo-activated disinfection with indocyanine green: Modeling and virtual screening analysis of Arg-gingipain from Porphyromonas gingivalis.

PubMed

Pourhajibagher, Maryam; Bahador, Abbas

2017-06-01

Porphyromonas gingivalis is a momentous bacterial etiological agent associated with periodontitis, peri-implantitis as well as endodontic infections. The potential advantage of Photo-activated disinfection (PAD) as a promising novel approach is the choice of a suitable target site, specific photosensitizer, and wavelength of light for delivery of the light from source to target. Since Arg-gingipain is a cysteine proteinase that is involved in the virulence of P. gingivalis, it was evaluated as a target site for PAD with indocyanine green (ICG) as a photosensitizer. In this study, we used a range of in silico strategies, bioinformatics tools, biological databases, and computer simulation molecular modeling to evaluate the capacity of Arg-gingipain. The predicted structure of Arg-gingipain indicated that it is located outside the cell and has nine domains and 17 ligands, including two calcium ions and three sodium ions with positive charges which can be a site of interaction for anionic ICG. Based on the results of this study, anionic ICG desires to bind and interact with residues of Arg-gingipain during PAD as a main site to enhance the yield of treatment of endo-periodontal lesions. Copyright © 2017 Elsevier B.V. All rights reserved.

GPU.proton.DOCK: Genuine Protein Ultrafast proton equilibria consistent DOCKing.

PubMed

Kantardjiev, Alexander A

2011-07-01

GPU.proton.DOCK (Genuine Protein Ultrafast proton equilibria consistent DOCKing) is a state of the art service for in silico prediction of protein-protein interactions via rigorous and ultrafast docking code. It is unique in providing stringent account of electrostatic interactions self-consistency and proton equilibria mutual effects of docking partners. GPU.proton.DOCK is the first server offering such a crucial supplement to protein docking algorithms--a step toward more reliable and high accuracy docking results. The code (especially the Fast Fourier Transform bottleneck and electrostatic fields computation) is parallelized to run on a GPU supercomputer. The high performance will be of use for large-scale structural bioinformatics and systems biology projects, thus bridging physics of the interactions with analysis of molecular networks. We propose workflows for exploring in silico charge mutagenesis effects. Special emphasis is given to the interface-intuitive and user-friendly. The input is comprised of the atomic coordinate files in PDB format. The advanced user is provided with a special input section for addition of non-polypeptide charges, extra ionogenic groups with intrinsic pK(a) values or fixed ions. The output is comprised of docked complexes in PDB format as well as interactive visualization in a molecular viewer. GPU.proton.DOCK server can be accessed at http://gpudock.orgchm.bas.bg/.

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

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

PubMed

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

2017-01-01

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

Synthesis, structure, computational and in-silico anticancer studies of N,N-diethyl-N‧-palmitoylthiourea

NASA Astrophysics Data System (ADS)

Asegbeloyin, Jonnie Niyi; Oyeka, Ebube Evaristus; Okpareke, Obinna; Ibezim, Akachukwu

2018-02-01

A new potential ONS donor ligand N,N-diethyl-N‧-palmitoylthiourea (PACDEA) with the molecular formular C21H42N2OS has been synthesized and characterized by ESI-MS, UV, FTIR 1H and 13C NMR spectroscopy and single X-ray crystallography. The asymmetric molecules crystallized in the centrosymmetric structure of monoclinic crystal system with space group P21/c. In the crystal structure of the compound, molecules are linked in a continuous chain by intermolecular Nsbnd H⋯Odbnd C hydrogen bonds, which stabilized the crystal structure. The palmitoyl moiety and N (2)-ethyl group lie on a plane, while the thiocarbonyl moiety is twisted and lying othorgonal to the plane. Non-covalent interaction (NCI) analysis on the hydrogen bonded solid state structure of the molecule revealed the presence of a significant number of non-covalent interactions including intermolecular hydrogen bonding interactions, Csbnd Hsbnd -lone pair interactions, weak Van der Waals interactions, and steric/ring closure interactions. The NCI analysis also showed the presence of intramolecular stabilizing Csbnd H⋯Odbnd C and Csbnd H⋯Sdbnd C interactions. Docking simulation revealed that the compound interacted favourably with ten selected validated anticancer drug targets, which is an indication that the compound could possess some anticancer properties.

Structure prediction and binding sites analysis of curcin protein of Jatropha curcas using computational approaches.

PubMed

Srivastava, Mugdha; Gupta, Shishir K; Abhilash, P C; Singh, Nandita

2012-07-01

Ribosome inactivating proteins (RIPs) are defense proteins in a number of higher-plant species that are directly targeted toward herbivores. Jatropha curcas is one of the biodiesel plants having RIPs. The Jatropha seed meal, after extraction of oil, is rich in curcin, a highly toxic RIP similar to ricin, which makes it unsuitable for animal feed. Although the toxicity of curcin is well documented in the literature, the detailed toxic properties and the 3D structure of curcin has not been determined by X-ray crystallography, NMR spectroscopy or any in silico techniques to date. In this pursuit, the structure of curcin was modeled by a composite approach of 3D structure prediction using threading and ab initio modeling. Assessment of model quality was assessed by methods which include Ramachandran plot analysis and Qmean score estimation. Further, we applied the protein-ligand docking approach to identify the r-RNA binding residue of curcin. The present work provides the first structural insight into the binding mode of r-RNA adenine to the curcin protein and forms the basis for designing future inhibitors of curcin. Cloning of a future peptide inhibitor within J. curcas can produce non-toxic varieties of J. curcas, which would make the seed-cake suitable as animal feed without curcin detoxification.

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

Assessment of blood-brain barrier penetration: in silico, in vitro and in vivo.

PubMed

Feng, Meihua Rose

2002-12-01

The amount of drug achieved and maintained in the brain after systemic administration is determined by the agent's permeability at blood-brain barrier (BBB), potential involvement of transport systems, and the distribution, metabolism and elimination properties. Passive diffusion permeability may be predicted by an in silico method based on a molecule's structure property. In vitro cell culture is another useful tool for the assessment of passive permeability and BBB transports (e.g. PGP, MRP). In situ or in vivo techniques like carotid artery single injection or perfusion, brain microdialysis, autoradiography, and others are used at various stages of drug discovery and development to estimate CNS penetration and PK/PD correlation. Each technique has its own application with specific advantages and limitations.

GENIUS In Silico Screening Technology for HCV Drug Discovery.

PubMed

Patil, Vaishali M; Masand, Neeraj; Gupta, Satya P

2016-01-01

The various reported in silico screening protocols such as molecular docking are associated with various drawbacks as well as benefits. In molecular docking, on interaction with ligand, the protein or receptor molecule gets activated by adopting conformational changes. These conformational changes cannot be utilized to predict the 3D structure of a protein-ligand complex from unbound protein conformations rigid docking, which necessitates the demand for understanding protein flexibility. Therefore, efficiency and accuracy of docking should be achieved and various available/developed protocols may be adopted. One such protocol is GENIUS induced-fit docking and it is used effectively for the development of anti-HCV NS3-4A serine protease inhibitors. The present review elaborates the GENIUS docking protocol along with its benefits and drawbacks.

In silico models for the prediction of dose-dependent human hepatotoxicity

NASA Astrophysics Data System (ADS)

Cheng, Ailan; Dixon, Steven L.

2003-12-01

The liver is extremely vulnerable to the effects of xenobiotics due to its critical role in metabolism. Drug-induced hepatotoxicity may involve any number of different liver injuries, some of which lead to organ failure and, ultimately, patient death. Understandably, liver toxicity is one of the most important dose-limiting considerations in the drug development cycle, yet there remains a serious shortage of methods to predict hepatotoxicity from chemical structure. We discuss our latest findings in this area and present a new, fully general in silico model which is able to predict the occurrence of dose-dependent human hepatotoxicity with greater than 80% accuracy. Utilizing an ensemble recursive partitioning approach, the model classifies compounds as toxic or non-toxic and provides a confidence level to indicate which predictions are most likely to be correct. Only 2D structural information is required and predictions can be made quite rapidly, so this approach is entirely appropriate for data mining applications and for profiling large synthetic and/or virtual libraries.

Automatic Compound Annotation from Mass Spectrometry Data Using MAGMa

PubMed Central

Ridder, Lars; van der Hooft, Justin J. J.; Verhoeven, Stefan

2014-01-01

The MAGMa software for automatic annotation of mass spectrometry based fragmentation data was applied to 16 MS/MS datasets of the CASMI 2013 contest. Eight solutions were submitted in category 1 (molecular formula assignments) and twelve in category 2 (molecular structure assignment). The MS/MS peaks of each challenge were matched with in silico generated substructures of candidate molecules from PubChem, resulting in penalty scores that were used for candidate ranking. In 6 of the 12 submitted solutions in category 2, the correct chemical structure obtained the best score, whereas 3 molecules were ranked outside the top 5. All top ranked molecular formulas submitted in category 1 were correct. In addition, we present MAGMa results generated retrospectively for the remaining challenges. Successful application of the MAGMa algorithm required inclusion of the relevant candidate molecules, application of the appropriate mass tolerance and a sufficient degree of in silico fragmentation of the candidate molecules. Furthermore, the effect of the exhaustiveness of the candidate lists and limitations of substructure based scoring are discussed. PMID:26819876

Automatic Compound Annotation from Mass Spectrometry Data Using MAGMa.

PubMed

Ridder, Lars; van der Hooft, Justin J J; Verhoeven, Stefan

2014-01-01

The MAGMa software for automatic annotation of mass spectrometry based fragmentation data was applied to 16 MS/MS datasets of the CASMI 2013 contest. Eight solutions were submitted in category 1 (molecular formula assignments) and twelve in category 2 (molecular structure assignment). The MS/MS peaks of each challenge were matched with in silico generated substructures of candidate molecules from PubChem, resulting in penalty scores that were used for candidate ranking. In 6 of the 12 submitted solutions in category 2, the correct chemical structure obtained the best score, whereas 3 molecules were ranked outside the top 5. All top ranked molecular formulas submitted in category 1 were correct. In addition, we present MAGMa results generated retrospectively for the remaining challenges. Successful application of the MAGMa algorithm required inclusion of the relevant candidate molecules, application of the appropriate mass tolerance and a sufficient degree of in silico fragmentation of the candidate molecules. Furthermore, the effect of the exhaustiveness of the candidate lists and limitations of substructure based scoring are discussed.

Experimental and in silico investigations of organic phosphates and phosphonates sorption on polymer-ceramic monolithic materials and hydroxyapatite.

PubMed

Pietrzyńska, Monika; Zembrzuska, Joanna; Tomczak, Rafał; Mikołajczyk, Jakub; Rusińska-Roszak, Danuta; Voelkel, Adam; Buchwald, Tomasz; Jampílek, Josef; Lukáč, Miloš; Devínsky, Ferdinand

2016-10-10

A method based on experimental and in silico evaluations for investigating interactions of organic phosphates and phosphonates with hydroxyapatite was developed. This quick and easy method is used for determination of differences among organophosphorus compounds of various structures in their mineral binding affinities. Empirical sorption evaluation was carried out using liquid chromatography with tandem mass spectrometry or UV-VIS spectroscopy. Raman spectroscopy was used to confirm sorption of organic phosphates and phosphonates on hydroxyapatite. Polymer-ceramic monolithic material and bulk hydroxyapatite were applied as sorbent materials. Furthermore, a Polymer-ceramic Monolithic In-Needle Extraction device was used to investigate both sorption and desorption steps. Binding energies were computed from the fully optimised structures utilising Density Functional Theory (DFT) at B3LYP/6-31+G(d,p) level. Potential pharmacologic and toxic effects of the tested compounds were estimated by the Prediction of the Activity Spectra of Substances using GeneXplain software. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Rational design of novel TLR4 ligands by in silico screening and their functional and structural characterization in vitro.

PubMed

Honegr, Jan; Malinak, David; Dolezal, Rafael; Soukup, Ondrej; Benkova, Marketa; Hroch, Lukas; Benek, Ondrej; Janockova, Jana; Kuca, Kamil; Prymula, Roman

2018-02-25

The purpose of this study was to identify new small molecules that possess activity on human toll-like receptor 4 associated with the myeloid differentiation protein 2 (hTLR4/MD2). Following current rational drug design principles, we firstly performed a ligand and structure based virtual screening of more than 130 000 compounds to discover until now unknown class of hTLR4/MD2 modulators that could be used as novel type of immunologic adjuvants. The core of the in silico study was molecular docking of flexible ligands in a partially flexible hTLR4/MD2 receptor model using a peta-flops-scale supercomputer. The most promising substances resulting from this study, related to anthracene-succimide hybrids, were synthesized and tested. The best prepared candidate exhibited 80% of Monophosphoryl Lipid A in vitro agonistic activity in cell lines expressing hTLR4/MD2. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Computational structural analysis of an anti-l-amino acid antibody and inversion of its stereoselectivity

PubMed Central

Ranieri, Daniel I.; Hofstetter, Heike; Hofstetter, Oliver

2009-01-01

The binding site of a monoclonal anti-l-amino acid antibody was modeled using the program SWISS-MODEL. Docking experiments with the enantiomers of phenylalanine revealed that the antibody interacts with l-phenylalanine via hydrogen bonds and hydrophobic contacts, whereas the d-enantiomer is rejected due to steric hindrance. Comparison of the sequences of this antibody and an anti-d-amino acid antibody indicates that both immunoglobulins derived from the same germline progenitor. Substitution of four amino acids residues, three in the framework and one in the complementarity determining regions, allowed in silico conversion of the anti-l-amino acid antibody into an antibody that stereoselectively binds d-phenylalanine. PMID:19472280

In Silico Docking of Small-Molecule Inhibitors to the Escherichia coli Type III Secretion System EscN ATPase

DTIC Science & Technology

2014-07-01

coordinates of the EscN protein (Zarivach et al., 2007) were downloaded in pdb file format from the Research Collaboratory for Structural Biology...catalytic activity. Two structurally related compounds were observed to adopt extended conformations in the active-site cleft and essentially...adopt a very compact conformation that occupied only one side of the cleft. Our goal was to determine the three-dimensional structures of the

The Hetero-Hexameric Nature of a Chloroplast AAA+ FtsH Protease Contributes to Its Thermodynamic Stability

PubMed Central

Ziv, Tamar; Adam, Zach; Prag, Gali

2012-01-01

FtsH is an evolutionary conserved membrane-bound metalloprotease complex. While in most prokaryotes FtsH is encoded by a single gene, multiple FtsH genes are found in eukaryotes. Genetic and biochemical data suggest that the Arabidopsis chloroplast FtsH is a hetero-hexamer. This raises the question why photosynthetic organisms require a heteromeric complex, whereas in most bacteria a homomeric one is sufficient. To gain structural information of the possible complexes, the Arabidopsis FtsH2 (type B) and FtsH5 (type A) were modeled. An in silico study with mixed models of FtsH2/5 suggests that heteromeric hexamer structure with ratio of 4∶2 is more likely to exists. Specifically, calculation of the buried surface area at the interfaces between neighboring subunits revealed that a hetero-complex should be thermodynamically more stable than a homo-hexamer, due to the presence of additional hydrophobic and hydrophilic interactions. To biochemically assess this model, we generated Arabidopsis transgenic plants, expressing epitope-tagged FtsH2 and immuno-purified the protein. Mass-spectrometry analysis showed that FtsH2 is associated with FtsH1, FtsH5 and FtsH8. Interestingly, we found that ‘type B’ subunits (FtsH2 and FtsH8) were 2–3 fold more abundant than ‘type A’ (FtsH1 and FtsH5). The biochemical data corroborate the in silico model and suggest that the thylakoid FtsH hexamer is composed of two ‘type A’ and four ‘type B’ subunits. PMID:22558304

In silico design, construction and cloning of Trastuzumab humanized monoclonal antibody: A possible biosimilar for Herceptin

PubMed Central

Akbarzadeh-Sharbaf, Soudabeh; Yakhchali, Bagher; Minuchehr, Zarrin; Shokrgozar, Mohammad Ali; Zeinali, Sirous

2012-01-01

Background: There is a novel hypothesis in that antibodies may have specificity for two distinct antigens that have been named “dual specificity”. This hypothesis was evaluated for some defined therapeutic monoclonal antibodies (mAbs) such as Trastuzumab, Pertuzumab, Bevacizumab, and Cetuximab. In silico design and construction of expression vectors for trastuzumab monoclonal antibody also in this work were performed. Materials and Methods: First, in bioinformatics studies the 3D structures of concerned mAbs were obtained from the Protein Data Bank (PDB). Three-dimensional structural alignments were performed with SIM and MUSTANG softwares. AutoDock4.2 software also was used for the docking analysis. Second, the suitable genes for trastuzumab heavy and light chains were designed, synthesized, and cloned in the prokaryotic vector. These fragments individually were PCR amplified and cloned into pcDNA™ 3.3-TOPO® and pOptiVEC™ TOPO® shuttle vectors, using standard methods. Results: First, many bioinformatics tools and softwares were applied but we did not meet any new dual specificity in the selected antibodies. In the following step, the suitable expression cascade for the heavy and light chains of Trastuzumab therapeutic mAb were designed and constructed. Gene cloning was successfully performed and created constructs were confirmed using gene mapping and sequencing. Conclusions: This study was based on a recently developed technology for mAb expression in mammalian cells. The obtained constructs could be successfully used for biosimilar recombinant mAb production in CHO DG44 dihydrofolate reductase (DHFR) gene deficient cell line in the suspension culture medium. PMID:23210080

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

Jump into a New Fold—A Homology Based Model for the ABCG2/BCRP Multidrug Transporter

PubMed Central

László, Laura; Sarkadi, Balázs

2016-01-01

ABCG2/BCRP is a membrane protein, involved in xenobiotic and endobiotic transport in key pharmacological barriers and drug metabolizing organs, in the protection of stem cells, and in multidrug resistance of cancer. Pharmacogenetic studies implicated the role of ABCG2 in response to widely used medicines and anticancer agents, as well as in gout. Its Q141K variant exhibits decreased functional expression thus increased drug accumulation and decreased urate secretion. Still, there has been no reliable molecular model available for this protein, as the published structures of other ABC transporters could not be properly fitted to the ABCG2 topology and experimental data. The recently published high resolution structure of a close homologue, the ABCG5-ABCG8 heterodimer, revealed a new ABC transporter fold, unique for ABCG proteins. Here we present a structural model of the ABCG2 homodimer based on this fold and detail the experimental results supporting this model. In order to describe the effect of mutations on structure and dynamics, and characterize substrate recognition and cholesterol regulation we performed molecular dynamics simulations using full length ABCG2 protein embedded in a membrane bilayer and in silico docking simulations. Our results show that in the Q141K variant the introduced positive charge diminishes the interaction between the nucleotide binding and transmembrane domains and the R482G variation alters the orientation of transmembrane helices. Moreover, the R482 position, which plays a role the substrate specificity of the transporter, is located in one of the substrate binding pockets identified by the in silico docking calculations. In summary, the ABCG2 model and in silico simulations presented here may have significant impact on understanding drug distribution and toxicity, as well as drug development against cancer chemotherapy resistance or gout. PMID:27741279

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

PubMed

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

2016-11-16

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

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

PubMed Central

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

2016-01-01

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

In Silico Screening for Biothreat Countermeasures

DTIC Science & Technology

2006-02-03

drug candidates to each kinase structure using the well-known docking algorithm LibDock . This population of 1200 ligands includes ~400 ligands with...mentioned previously, each of the known p38 inhibitors in the population was docked to its target using the LibDock application. This method resulted

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

PubMed Central

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

2014-01-01

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

Discovery of novel DAPY-IAS hybrid derivatives as potential HIV-1 inhibitors using molecular hybridization based on crystallographic overlays.

PubMed

Huang, Boshi; Wang, Xueshun; Liu, Xinhao; Chen, Zihui; Li, Wanzhuo; Sun, Songkai; Liu, Huiqing; Daelemans, Dirk; De Clercq, Erik; Pannecouque, Christophe; Zhan, Peng; Liu, Xinyong

2017-08-15

Crystallographic overlap studies and pharmacophoric analysis indicated that diarylpyrimidine (DAPY)-based HIV-1 NNRTIs showed a similar binding mode and pharmacophoric features as indolylarylsulfones (IASs), another class of potent NNRTIs. Thus, a novel series of DAPY-IAS hybrid derivatives were identified as newer NNRTIs using structure-based molecular hybridization. Some target compounds exhibited moderate activities against HIV-1 IIIB strain, among which the two most potent inhibitors possessed EC 50 values of 1.48μM and 1.61μM, respectively. They were much potent than the reference drug ddI (EC 50 =76.0μM) and comparable to 3TC (EC 50 =2.54μM). Compound 7a also exhibited the favorable selectivity index (SI=80). Preliminary structure-activity relationships (SARs), structure-cytotoxicity relationships, molecular modeling studies, and in silico calculation of physicochemical properties of these new inhibitors were also discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Identification and preliminary structure-activity relationships of 1-Indanone derivatives as novel indoleamine-2,3-dioxygenase 1 (IDO1) inhibitors.

PubMed

Gao, Dingding; Li, Yingxia

2017-07-15

Indoleamine 2,3-dioxygenase 1 (IDO1) plays a vital role in the catabolism of tryptophan along with the kynurenine pathway which is involved in many human diseases including cancer, Alzheimer's disease, etc. In this study, compound 1 bearing a 1-Indanone scaffold was identified as a novel IDO1 inhibitor by structure-based virtual screening, with moderate to good enzymatic and cellular inhibitory activities. Also, surface plasmon resonance analysis validated the direct interaction between compound 1 and IDO1 protein. The preliminary SAR was further explored and the binding mode with IDO1 protein was predicted by experiment along with molecular docking. Subsequent ADME properties of these active compounds were analyzed in silico, and the results showed good pharmacokinetic efficiencies. We believe this study contributes a lot to the structural diversity for the future development of highly potent IDO1 inhibitors. Copyright © 2017. Published by Elsevier Ltd.

Pore Breathing of Metal-Organic Frameworks by Environmental Transmission Electron Microscopy.

PubMed

Parent, Lucas R; Pham, C Huy; Patterson, Joseph P; Denny, Michael S; Cohen, Seth M; Gianneschi, Nathan C; Paesani, Francesco

2017-10-11

Metal-organic frameworks (MOFs) have emerged as a versatile platform for the rational design of multifunctional materials, combining large specific surface areas with flexible, periodic frameworks that can undergo reversible structural transitions, or "breathing", upon temperature and pressure changes, and through gas adsorption/desorption processes. Although MOF breathing can be inferred from the analysis of adsorption isotherms, direct observation of the structural transitions has been lacking, and the underlying processes of framework reorganization in individual MOF nanocrystals is largely unknown. In this study, we describe the characterization and elucidation of these processes through the combination of in situ environmental transmission electron microscopy (ETEM) and computer simulations. This combined approach enables the direct monitoring of the breathing behavior of individual MIL-53(Cr) nanocrystals upon reversible water adsorption and temperature changes. The ability to characterize structural changes in single nanocrystals and extract lattice level information through in silico correlation provides fundamental insights into the relationship between pore size/shape and host-guest interactions.

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

PubMed

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

2015-01-01

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

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

PubMed

Jian, Xueqiu; Boerwinkle, Eric; Liu, Xiaoming

2014-12-16

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

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.

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.

In Silico Discovery of a Substituted 6-Methoxy-quinalidine with Leishmanicidal Activity in Leishmania infantum.

PubMed

Stevanović, Strahinja; Perdih, Andrej; Senćanski, Milan; Glišić, Sanja; Duarte, Margarida; Tomás, Ana M; Sena, Filipa V; Sousa, Filipe M; Pereira, Manuela M; Solmajer, Tom

2018-03-27

There is an urgent need for the discovery of new antileishmanial drugs with a new mechanism of action. Type 2 NADH dehydrogenase from Leishmania infantum ( Li NDH2) is an enzyme of the parasite's respiratory system, which catalyzes the electron transfer from NADH to ubiquinone without coupled proton pumping. In previous studies of the related NADH: ubiquinone oxidoreductase crystal structure from Saccharomyces cerevisiae , two ubiquinone-binding sites (UQ I and UQ II ) were identified and shown to play an important role in the NDH-2-catalyzed oxidoreduction reaction. Based on the available structural data, we developed a three-dimensional structural model of Li NDH2 using homology detection methods and performed an in silico virtual screening campaign to search for potential inhibitors targeting the Li NDH2 ubiquinone-binding site 1-UQ I . Selected compounds displaying favorable properties in the computational screening experiments were assayed for inhibitory activity in the structurally similar recombinant NDH-2 from S. aureus and leishmanicidal activity was determined in the wild-type axenic amastigotes and promastigotes of L. infantum . The identified compound, a substituted 6-methoxy-quinalidine, showed promising nanomolar leishmanicidal activity on wild-type axenic promastigotes and amastigotes of L. infantum and the potential for further development.

Inhibition of neuraminidase by Ganoderma triterpenoids and implications for neuraminidase inhibitor design

PubMed Central

Zhu, Qinchang; Bang, Tran Hai; Ohnuki, Koichiro; Sawai, Takashi; Sawai, Ken; Shimizu, Kuniyoshi

2015-01-01

Neuraminidase (NA) inhibitors are the dominant antiviral drugs for treating influenza in the clinic. Increasing prevalence of drug resistance makes the discovery of new NA inhibitors a high priority. Thirty-one triterpenoids from the medicinal mushroom Ganoderma lingzhi were analyzed in an in vitro NA inhibition assay, leading to the discovery of ganoderic acid T-Q and TR as two inhibitors of H5N1 and H1N1 NAs. Structure-activity relationship studies revealed that the corresponding triterpenoid structure is a potential scaffold for the design of NA inhibitors. Using these triterpenoids as probes we found, through further in silico docking and interaction analysis, that interactions with the amino-acid residues Arg292 and/or Glu119 of NA are critical for the inhibition of H5N1 and H1N1. These findings should prove valuable for the design and development of NA inhibitors. PMID:26307417

Adaptive resolution simulation of oligonucleotides

NASA Astrophysics Data System (ADS)

Netz, Paulo A.; Potestio, Raffaello; Kremer, Kurt

2016-12-01

Nucleic acids are characterized by a complex hierarchical structure and a variety of interaction mechanisms with other molecules. These features suggest the need of multiscale simulation methods in order to grasp the relevant physical properties of deoxyribonucleic acid (DNA) and RNA using in silico experiments. Here we report an implementation of a dual-resolution modeling of a DNA oligonucleotide in physiological conditions; in the presented setup only the nucleotide molecule and the solvent and ions in its proximity are described at the atomistic level; in contrast, the water molecules and ions far from the DNA are represented as computationally less expensive coarse-grained particles. Through the analysis of several structural and dynamical parameters, we show that this setup reliably reproduces the physical properties of the DNA molecule as observed in reference atomistic simulations. These results represent a first step towards a realistic multiscale modeling of nucleic acids and provide a quantitatively solid ground for their simulation using dual-resolution methods.

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.

Structure based drug discovery for designing leads for the non-toxic metabolic targets in multi drug resistant Mycobacterium tuberculosis.

PubMed

Kaur, Divneet; Mathew, Shalu; Nair, Chinchu G S; Begum, Azitha; Jainanarayan, Ashwin K; Sharma, Mukta; Brahmachari, Samir K

2017-12-21

The problem of drug resistance and bacterial persistence in tuberculosis is a cause of global alarm. Although, the UN's Sustainable Development Goals for 2030 has targeted a Tb free world, the treatment gap exists and only a few new drug candidates are in the pipeline. In spite of large information from medicinal chemistry to 'omics' data, there has been a little effort from pharmaceutical companies to generate pipelines for the development of novel drug candidates against the multi drug resistant Mycobacterium tuberculosis. In the present study, we describe an integrated methodology; utilizing systems level information to optimize ligand selection to lower the failure rates at the pre-clinical and clinical levels. In the present study, metabolic targets (Rv2763c, Rv3247c, Rv1094, Rv3607c, Rv3048c, Rv2965c, Rv2361c, Rv0865, Rv0321, Rv0098, Rv0390, Rv3588c, Rv2244, Rv2465c and Rv2607) in M. tuberculosis, identified using our previous Systems Biology and data-intensive genome level analysis, have been used to design potential lead molecules, which are likely to be non-toxic. Various in silico drug discovery tools have been utilized to generate small molecular leads for each of the 15 targets with available crystal structures. The present study resulted in identification of 20 novel lead molecules including 4 FDA approved drugs (droxidropa, tetroxoprim, domperidone and nemonapride) which can be further taken for drug repurposing. This comprehensive integrated methodology, with both experimental and in silico approaches, has the potential to not only tackle the MDR form of Mtb but also the most important persister population of the bacterium, with a potential to reduce the failures in the Tb drug discovery. We propose an integrated approach of systems and structural biology for identifying targets that address the high attrition rate issue in lead identification and drug development We expect that this system level analysis will be applicable for identification of drug candidates to other pathogenic organisms as well.

Identifying Potential Protein Targets for Toluene Using a Molecular Similarity Search, in Silico Docking and in Vitro Validation

DTIC Science & Technology

2015-01-01

the Protein Data Bank (http://www.rcsb.org/ pdb /). These structures are the most accurate and can be used for molecular docking. Target flexibility is...crystallized with the different ligands. In total, 240 files with the structures of 37 proteins were downloaded from PDB and used for docking...total, 240 files with protein structures were downloaded from the PDB and used for protein–ligand docking. It is widely accepted that ligand binding

Freely Accessible Chemical Database Resources of Compounds for in Silico Drug Discovery.

PubMed

Yang, JingFang; Wang, Di; Jia, Chenyang; Wang, Mengyao; Hao, GeFei; Yang, GuangFu

2018-05-07

In silico drug discovery has been proved to be a solidly established key component in early drug discovery. However, this task is hampered by the limitation of quantity and quality of compound databases for screening. In order to overcome these obstacles, freely accessible database resources of compounds have bloomed in recent years. Nevertheless, how to choose appropriate tools to treat these freely accessible databases are crucial. To the best of our knowledge, this is the first systematic review on this issue. The existed advantages and drawbacks of chemical databases were analyzed and summarized based on the collected six categories of freely accessible chemical databases from literature in this review. Suggestions on how and in which conditions the usage of these databases could be reasonable were provided. Tools and procedures for building 3D structure chemical libraries were also introduced. In this review, we described the freely accessible chemical database resources for in silico drug discovery. In particular, the chemical information for building chemical database appears as attractive resources for drug design to alleviate experimental pressure. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Spatio-temporal Model of Xenobiotic Distribution and Metabolism in an in Silico Mouse Liver Lobule

NASA Astrophysics Data System (ADS)

Fu, Xiao; Sluka, James; Clendenon, Sherry; Glazier, James; Ryan, Jennifer; Dunn, Kenneth; Wang, Zemin; Klaunig, James

Our study aims to construct a structurally plausible in silico model of a mouse liver lobule to simulate the transport of xenobiotics and the production of their metabolites. We use a physiologically-based model to calculate blood-flow rates in a network of mouse liver sinusoids and simulate transport, uptake and biotransformation of xenobiotics within the in silico lobule. Using our base model, we then explore the effects of variations of compound-specific (diffusion, transport and metabolism) and compound-independent (temporal alteration of blood flow pattern) parameters, and examine their influence on the distribution of xenobiotics and metabolites. Our simulations show that the transport mechanism (diffusive and transporter-mediated) of xenobiotics and blood flow both impact the regional distribution of xenobiotics in a mouse hepatic lobule. Furthermore, differential expression of metabolic enzymes along each sinusoid's portal to central axis, together with differential cellular availability of xenobiotics, induce non-uniform production of metabolites. Thus, the heterogeneity of the biochemical and biophysical properties of xenobiotics, along with the complexity of blood flow, result in different exposures to xenobiotics for hepatocytes at different lobular locations. We acknowledge support from National Institute of Health GM 077138 and GM 111243.

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

Structure prediction, expression, and antigenicity of c-terminal of GRP78.

PubMed

Aghamollaei, Hossein; Mousavi Gargari, Seyed Latif; Ghanei, Mostafa; Rasaee, Mohamad Javad; Amani, Jafar; Bakherad, Hamid; Farnoosh, Gholamreza

2017-01-01

Glucose-regulated protein 78 (GRP78) is a typical endoplasmic reticulum luminal chaperone having a main role in the activation of the unfolded protein response. Because of hypoxia and nutrient deprivation in the tumor microenvironment, expression of GRP78 in these cells becomes higher than the native cells, which makes it a suitable candidate for cancer targeting. Suppression of survival signals by antibody production against C-terminal domain of GR78 (CGRP) can induce apoptosis of cancer cells. The aim of this study was in silico analysis, recombinant production, and characterization of CGRP in Escherichia coli. Structural prediction of CGRP by bioinformatics tools was done and the construct containing optimized sequence was transferred to E. coli T7 shuffle. Expression was induced by isopropyl-β-d-thiogalactoside, and recombinant protein was purified by Ni-NTA agarose resin. The content of secondary structures was obtained by circular dichroism (CD) spectrum. CGRP immunogenicity was evaluated from the immunized mouse sera. SDS-PAGE analysis showed CGRP expression in E. coli. CD spectrum also confirmed prediction of structures by bioinformatics tools. The enzyme-linked immunosorbent assay using sera from immunized mice revealed CGRP as a good immunogen. The results obtained in this study showed that the structure of truncated CGRP is very similar to its structure in the whole protein context. This protein can be used in cancer researches. © 2015 International Union of Biochemistry and Molecular Biology, Inc.

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...

Mutagenicity in a Molecule: Identification of Core Structural Features of Mutagenicity Using a Scaffold Analysis

PubMed Central

Hsu, Kuo-Hsiang; Su, Bo-Han; Tu, Yi-Shu; Lin, Olivia A.; Tseng, Yufeng J.

2016-01-01

With advances in the development and application of Ames mutagenicity in silico prediction tools, the International Conference on Harmonisation (ICH) has amended its M7 guideline to reflect the use of such prediction models for the detection of mutagenic activity in early drug safety evaluation processes. Since current Ames mutagenicity prediction tools only focus on functional group alerts or side chain modifications of an analog series, these tools are unable to identify mutagenicity derived from core structures or specific scaffolds of a compound. In this study, a large collection of 6512 compounds are used to perform scaffold tree analysis. By relating different scaffolds on constructed scaffold trees with Ames mutagenicity, four major and one minor novel mutagenic groups of scaffold are identified. The recognized mutagenic groups of scaffold can serve as a guide for medicinal chemists to prevent the development of potentially mutagenic therapeutic agents in early drug design or development phases, by modifying the core structures of mutagenic compounds to form non-mutagenic compounds. In addition, five series of substructures are provided as recommendations, for direct modification of potentially mutagenic scaffolds to decrease associated mutagenic activities. PMID:26863515

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.

An "in Silico" DNA Cloning Experiment for the Biochemistry Laboratory

ERIC Educational Resources Information Center

Elkins, Kelly M.

2011-01-01

This laboratory exercise introduces students to concepts in recombinant DNA technology while accommodating a major semester project in protein purification, structure, and function in a biochemistry laboratory for junior- and senior-level undergraduate students. It is also suitable for forensic science courses focused in DNA biology and advanced…

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.

Phylogenetic reconstruction in the Order Nymphaeales: ITS2 secondary structure analysis and in silico testing of maturase k (matK) as a potential marker for DNA bar coding

PubMed Central

2012-01-01

Background The Nymphaeales (waterlilly and relatives) lineage has diverged as the second branch of basal angiosperms and comprises of two families: Cabombaceae and Nymphaceae. The classification of Nymphaeales and phylogeny within the flowering plants are quite intriguing as several systems (Thorne system, Dahlgren system, Cronquist system, Takhtajan system and APG III system (Angiosperm Phylogeny Group III system) have attempted to redefine the Nymphaeales taxonomy. There have been also fossil records consisting especially of seeds, pollen, stems, leaves and flowers as early as the lower Cretaceous. Here we present an in silico study of the order Nymphaeales taking maturaseK (matK) and internal transcribed spacer (ITS2) as biomarkers for phylogeny reconstruction (using character-based methods and Bayesian approach) and identification of motifs for DNA barcoding. Results The Maximum Likelihood (ML) and Bayesian approach yielded congruent fully resolved and well-supported trees using a concatenated (ITS2+ matK) supermatrix aligned dataset. The taxon sampling corroborates the monophyly of Cabombaceae. Nuphar emerges as a monophyletic clade in the family Nymphaeaceae while there are slight discrepancies in the monophyletic nature of the genera Nymphaea owing to Victoria-Euryale and Ondinea grouping in the same node of Nymphaeaceae. ITS2 secondary structures alignment corroborate the primary sequence analysis. Hydatellaceae emerged as a sister clade to Nymphaeaceae and had a basal lineage amongst the water lilly clades. Species from Cycas and Ginkgo were taken as outgroups and were rooted in the overall tree topology from various methods. Conclusions MatK genes are fast evolving highly variant regions of plant chloroplast DNA that can serve as potential biomarkers for DNA barcoding and also in generating primers for angiosperms with identification of unique motif regions. We have reported unique genus specific motif regions in the Order Nymphaeles from matK dataset which can be further validated for barcoding and designing of PCR primers. Our analysis using a novel approach of sequence-structure alignment and phylogenetic reconstruction using molecular morphometrics congrue with the current placement of Hydatellaceae within the early-divergent angiosperm order Nymphaeales. The results underscore the fact that more diverse genera, if not fully resolved to be monophyletic, should be represented by all major lineages. PMID:23282079

Structural and Phylogenetic Analysis of Laccases from Trichoderma: A Bioinformatic Approach

PubMed Central

Cázares-García, Saila Viridiana; Vázquez-Garcidueñas, Ma. Soledad; Vázquez-Marrufo, Gerardo

2013-01-01

The genus Trichoderma includes species of great biotechnological value, both for their mycoparasitic activities and for their ability to produce extracellular hydrolytic enzymes. Although activity of extracellular laccase has previously been reported in Trichoderma spp., the possible number of isoenzymes is still unknown, as are the structural and functional characteristics of both the genes and the putative proteins. In this study, the system of laccases sensu stricto in the Trichoderma species, the genomes of which are publicly available, were analyzed using bioinformatic tools. The intron/exon structure of the genes and the identification of specific motifs in the sequence of amino acids of the proteins generated in silico allow for clear differentiation between extracellular and intracellular enzymes. Phylogenetic analysis suggests that the common ancestor of the genus possessed a functional gene for each one of these enzymes, which is a characteristic preserved in T. atroviride and T. virens. This analysis also reveals that T. harzianum and T. reesei only retained the intracellular activity, whereas T. asperellum added an extracellular isoenzyme acquired through horizontal gene transfer during the mycoparasitic process. The evolutionary analysis shows that in general, extracellular laccases are subjected to purifying selection, and intracellular laccases show neutral evolution. The data provided by the present study will enable the generation of experimental approximations to better understand the physiological role of laccases in the genus Trichoderma and to increase their biotechnological potential. PMID:23383142

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.

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

PubMed

Prabhu, D Sathya; Rajeswari, V Devi

2018-06-20

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

New cycloartane-type triterpenes from Marcetia latifolia (Melastomataceae) and in silico studies on Candida parapsilosis protease.

PubMed

Leite, Tonny C C; Leite, Franco H A; Vieira, Ivo J C; Braz Filho, Raimundo; Branco, Alexsandro

2013-08-01

We have previously reported the antimicrobial activity of the ethyl acetate extract of Marcetia latifolia, particularly against Candida parapsilosis. In this work we describe the isolation of two new cycloartane-type triterpenes, 28,29-bis-norcycloartan-3beta,4alpha-diol (1) and 28,29-bis-norcycloart-24-en-3beta,4alpha-diol (2) from the same extract. These compounds were mainly characterized by one- (1H, 13C and APT) and two-dimensional (1H-1H-COSY, 1H-1H-NOESY, HMQC and HMBC) NMR spectroscopy, mass spectrometry and comparison with published structural data. In addition, the activity of triterpenes 1 and 2 on the Candida protease target was investigated by in silico methods using molecular docking.

Structural and energetic basis for the molecular recognition of dual synthetic vs. natural inhibitors of EGFR/HER2.

PubMed

Bello, Martiniano; Saldaña-Rivero, Lucia; Correa-Basurto, José; García, Benjamín; Sánchez-Espinosa, Victor Armando

2018-05-01

Activation of EGFR starts by ligand binding at the extracellular domain which results in homo and heterodimerization, leading to phosphorylation, activation of downstream signaling pathways which upregulate expression of genes, proliferation and angiogenesis. Abnormalities in the expression of EGFR play a critical role in the development of different types of cancer. HER2 is the preferred heterodimerization partner for EGFR; this biological characteristic together with the high percentage of structural homology has been exploited in the design of dual synthetic inhibitors against EGFR/HER2. Herein we combined structural data and molecular dynamics (MD) simulations coupled to an MMGBSA approach to provide insight into the binding mechanism between two dual synthetics (lapatinib and TAK-285) and one dual natural inhibitor (EGCG) which target EGFR/HER2. In addition, we proposed some EGCG derivatives which were filtered through in silico screening. Structural analysis demonstrated that the coupling of synthetic, natural or newly designed compounds impacts the conformational space of EGFR and HER2 differently. Energetic analysis points out that lapatinib and TAK-285 have better affinity for inactive EGFR than the active EGFR state or HER2, whereas some EGCG derivatives seem to form binding affinities similar to those observed for lapatinib or TAK-285. Copyright © 2018 Elsevier B.V. All rights reserved.

Phylogenetic profiles reveal structural/functional determinants of TRPC3 signal-sensing antennae

PubMed Central

Ko, Kyung Dae; Bhardwaj, Gaurav; Hong, Yoojin; Chang, Gue Su; Kiselyov, Kirill

2009-01-01

Biochemical assessment of channel structure/function is incredibly challenging. Developing computational tools that provide these data would enable translational research, accelerating mechanistic experimentation for the bench scientist studying ion channels. Starting with the premise that protein sequence encodes information about structure, function and evolution (SF&E), we developed a unified framework for inferring SF&E from sequence information using a knowledge-based approach. The Gestalt Domain Detection Algorithm-Basic Local Alignment Tool (GDDA-BLAST) provides phylogenetic profiles that can model, ab initio, SF&E relationships of biological sequences at the whole protein, single domain and single-amino acid level.1,2 In our recent paper,4 we have applied GDDA-BLAST analysis to study canonical TRP (TRPC) channels1 and empirically validated predicted lipid-binding and trafficking activities contained within the TRPC3 TRP_2 domain of unknown function. Overall, our in silico, in vitro, and in vivo experiments support a model in which TRPC3 has signal-sensing antennae which are adorned with lipid-binding, trafficking and calmodulin regulatory domains. In this Addendum, we correlate our functional domain analysis with the cryo-EM structure of TRPC3.3 In addition, we synthesize recent studies with our new findings to provide a refined model on the mechanism(s) of TRPC3 activation/deactivation. PMID:19704910

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.

Discovery of DPP IV inhibitors by pharmacophore modeling and QSAR analysis followed by in silico screening.

PubMed

Al-Masri, Ihab M; Mohammad, Mohammad K; Taha, Mutasem O

2008-11-01

Dipeptidyl peptidase IV (DPP IV) deactivates the natural hypoglycemic incretin hormones. Inhibition of this enzyme should restore glucose homeostasis in diabetic patients making it an attractive target for the development of new antidiabetic drugs. With this in mind, the pharmacophoric space of DPP IV was explored using a set of 358 known inhibitors. Thereafter, genetic algorithm and multiple linear regression analysis were employed to select an optimal combination of pharmacophoric models and physicochemical descriptors that yield selfconsistent and predictive quantitative structure-activity relationships (QSAR) (r(2) (287)=0.74, F-statistic=44.5, r(2) (BS)=0.74, r(2) (LOO)=0.69, r(2) (PRESS) against 71 external testing inhibitors=0.51). Two orthogonal pharmacophores (of cross-correlation r(2)=0.23) emerged in the QSAR equation suggesting the existence of at least two distinct binding modes accessible to ligands within the DPP IV binding pocket. Docking experiments supported the binding modes suggested by QSAR/pharmacophore analyses. The validity of the QSAR equation and the associated pharmacophore models were established by the identification of new low-micromolar anti-DPP IV leads retrieved by in silico screening. One of our interesting potent anti-DPP IV hits is the fluoroquinolone gemifloxacin (IC(50)=1.12 muM). The fact that gemifloxacin was recently reported to potently inhibit the prodiabetic target glycogen synthase kinase 3beta (GSK-3beta) suggests that gemifloxacin is an excellent lead for the development of novel dual antidiabetic inhibitors against DPP IV and GSK-3beta.

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.

Assessment of biological half life using in silico QSPkR approach: a self organizing molecular field analysis (SOMFA) on a series of antimicrobial quinolone drugs.

PubMed

Goel, Honey; Sinha, V R; Thareja, Suresh; Aggarwal, Saurabh; Kumar, Manoj

2011-08-30

The quinolones belong to a family of synthetic potent broad-spectrum antibiotics and particularly active against gram-negative organisms, especially Pseudomonas aeruginosa. A 3D-QSPkR approach has been used to obtain the quantitative structure pharmacokinetic relationship for a series of quinolone drugs using SOMFA. The series consisting of 28 molecules have been investigated for their pharmacokinetic performance using biological half life (t(1/2)). A statistically validated robust model for a diverse group of quinolone drugs having flexibility in structure and pharmacokinetic profile (t(1/2)) obtained using SOMFA having good cross-validated correlation coefficient r(cv)(2) (0.6847), non cross-validated correlation coefficient r(2) values (0.7310) and high F-test value (33.9663). Analysis of 3D-QSPkR models through electrostatic and shape grids provide useful information about the shape and electrostatic potential contributions on t(1/2). The analysis of SOMFA results provide an insight for the generation of novel molecular architecture of quinolones with optimal half life and improved biological profile. Copyright © 2011 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.

Efficient Translation of Pelargonium line pattern virus RNAs Relies on a TED-Like 3´-Translational Enhancer that Communicates with the Corresponding 5´-Region through a Long-Distance RNA-RNA Interaction

PubMed Central

Blanco-Pérez, Marta; Pérez-Cañamás, Miryam; Ruiz, Leticia; Hernández, Carmen

2016-01-01

Cap-independent translational enhancers (CITEs) have been identified at the 3´-terminal regions of distinct plant positive-strand RNA viruses belonging to families Tombusviridae and Luteoviridae. On the bases of their structural and/or functional requirements, at least six classes of CITEs have been defined whose distribution does not correlate with taxonomy. The so-called TED class has been relatively under-studied and its functionality only confirmed in the case of Satellite tobacco necrosis virus, a parasitic subviral agent. The 3´-untranslated region of the monopartite genome of Pelargonium line pattern virus (PLPV), the recommended type member of a tentative new genus (Pelarspovirus) in the family Tombusviridae, was predicted to contain a TED-like CITE. Similar CITEs can be anticipated in some other related viruses though none has been experimentally verified. Here, in the first place, we have performed a reassessment of the structure of the putative PLPV-TED through in silico predictions and in vitro SHAPE analysis with the full-length PLPV genome, which has indicated that the presumed TED element is larger than previously proposed. The extended conformation of the TED is strongly supported by the pattern of natural sequence variation, thus providing comparative structural evidence in support of the structural data obtained by in silico and in vitro approaches. Next, we have obtained experimental evidence demonstrating the in vivo activity of the PLPV-TED in the genomic (g) RNA, and also in the subgenomic (sg) RNA that the virus produces to express 3´-proximal genes. Besides other structural features, the results have highlighted the key role of long-distance kissing-loop interactions between the 3´-CITE and 5´-proximal hairpins for gRNA and sgRNA translation. Bioassays of CITE mutants have confirmed the importance of the identified 5´-3´ RNA communication for viral infectivity and, moreover, have underlined the strong evolutionary constraints that may operate on genome stretches with both regulatory and coding functions. PMID:27043436

Efficient Translation of Pelargonium line pattern virus RNAs Relies on a TED-Like 3´-Translational Enhancer that Communicates with the Corresponding 5´-Region through a Long-Distance RNA-RNA Interaction.

PubMed

Blanco-Pérez, Marta; Pérez-Cañamás, Miryam; Ruiz, Leticia; Hernández, Carmen

2016-01-01

Cap-independent translational enhancers (CITEs) have been identified at the 3´-terminal regions of distinct plant positive-strand RNA viruses belonging to families Tombusviridae and Luteoviridae. On the bases of their structural and/or functional requirements, at least six classes of CITEs have been defined whose distribution does not correlate with taxonomy. The so-called TED class has been relatively under-studied and its functionality only confirmed in the case of Satellite tobacco necrosis virus, a parasitic subviral agent. The 3´-untranslated region of the monopartite genome of Pelargonium line pattern virus (PLPV), the recommended type member of a tentative new genus (Pelarspovirus) in the family Tombusviridae, was predicted to contain a TED-like CITE. Similar CITEs can be anticipated in some other related viruses though none has been experimentally verified. Here, in the first place, we have performed a reassessment of the structure of the putative PLPV-TED through in silico predictions and in vitro SHAPE analysis with the full-length PLPV genome, which has indicated that the presumed TED element is larger than previously proposed. The extended conformation of the TED is strongly supported by the pattern of natural sequence variation, thus providing comparative structural evidence in support of the structural data obtained by in silico and in vitro approaches. Next, we have obtained experimental evidence demonstrating the in vivo activity of the PLPV-TED in the genomic (g) RNA, and also in the subgenomic (sg) RNA that the virus produces to express 3´-proximal genes. Besides other structural features, the results have highlighted the key role of long-distance kissing-loop interactions between the 3´-CITE and 5´-proximal hairpins for gRNA and sgRNA translation. Bioassays of CITE mutants have confirmed the importance of the identified 5´-3´ RNA communication for viral infectivity and, moreover, have underlined the strong evolutionary constraints that may operate on genome stretches with both regulatory and coding functions.

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.

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.

Screening of pharmacokinetic properties of fifty dihydropyrimidin(thi)one derivatives using a combo of in vitro and in silico assays.

PubMed

Matias, Mariana; Fortuna, Ana; Bicker, Joana; Silvestre, Samuel; Falcão, Amílcar; Alves, Gilberto

2017-11-15

The heterocycles dihydropyrimidin(thi)ones have been under intensive pharmacological research, but their pharmacokinetic properties remain almost unknown. Herein, fifty dihydropyrimidin(thi)ones were submitted to in vitro screening tests using parallel artificial membrane permeability assays (PAMPA) to evaluate their apparent permeability (Papp) through intestinal membrane and blood-brain barrier models, and cell-based assays to assess their interference on the efflux transporter P-glycoprotein (P-gp). Moreover, a set of kinetic and toxicological parameters was also estimated employing a new computational tool, the pkCSM. The in vitro results suggested that 82% of the test compounds have good intestinal permeability (Papp>1.1×10 -6 cm/s), and 66% of these are also expected to exhibit good permeability through blood-brain barrier (Papp>2.0×10 -6 cm/s); these findings are consistent with a high transport rate by passive transcellular pathway. In both PAMPA models, thiourea derivatives presented higher Papp values than the respective urea analogues, which were further corroborated by in silico predictions. The in vitro results also suggested a low extent of plasma protein binding for all compounds (Papp<1.0×10 -5 cm/s), and these findings were also supported by in silico data (unbound fraction ranging from 0.13 to 0.59). In addition, although approximately half of the compounds did not modulate P-gp at the tested concentrations (10 and 50μM), nine of them presented a trend to induce P-gp and particularly the chlorinated compounds exhibited a marked P-gp inhibition at 50μM. Furthermore, the in silico predictions suggested that half of the compounds have hepatotoxic potential. Overall, within this group of compounds, the thiourea derivatives containing an unsubstituted or a monosubstituted (NO 2 , CH 3 , OCH 3 ) phenyl ring attached to the position 4 of the dihydropyrimidine ring represented the most promising structures and should be considered in the subsequent studies of the development of new structurally related drug candidates. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

A Computational Approach From Gene to Structure Analysis of the Human ABCA4 Transporter Involved in Genetic Retinal Diseases.

PubMed

Trezza, Alfonso; Bernini, Andrea; Langella, Andrea; Ascher, David B; Pires, Douglas E V; Sodi, Andrea; Passerini, Ilaria; Pelo, Elisabetta; Rizzo, Stanislao; Niccolai, Neri; Spiga, Ottavia

2017-10-01

The aim of this article is to report the investigation of the structural features of ABCA4, a protein associated with a genetic retinal disease. A new database collecting knowledge of ABCA4 structure may facilitate predictions about the possible functional consequences of gene mutations observed in clinical practice. In order to correlate structural and functional effects of the observed mutations, the structure of mouse P-glycoprotein was used as a template for homology modeling. The obtained structural information and genetic data are the basis of our relational database (ABCA4Database). Sequence variability among all ABCA4-deposited entries was calculated and reported as Shannon entropy score at the residue level. The three-dimensional model of ABCA4 structure was used to locate the spatial distribution of the observed variable regions. Our predictions from structural in silico tools were able to accurately link the functional effects of mutations to phenotype. The development of the ABCA4Database gathers all the available genetic and structural information, yielding a global view of the molecular basis of some retinal diseases. ABCA4 modeled structure provides a molecular basis on which to analyze protein sequence mutations related to genetic retinal disease in order to predict the risk of retinal disease across all possible ABCA4 mutations. Additionally, our ABCA4 predicted structure is a good starting point for the creation of a new data analysis model, appropriate for precision medicine, in order to develop a deeper knowledge network of the disease and to improve the management of patients.

Bioinformatics and peptidomics approaches to the discovery and analysis of food-derived bioactive peptides.

PubMed

Agyei, Dominic; Tsopmo, Apollinaire; Udenigwe, Chibuike C

2018-06-01

There are emerging advancements in the strategies used for the discovery and development of food-derived bioactive peptides because of their multiple food and health applications. Bioinformatics and peptidomics are two computational and analytical techniques that have the potential to speed up the development of bioactive peptides from bench to market. Structure-activity relationships observed in peptides form the basis for bioinformatics and in silico prediction of bioactive sequences encrypted in food proteins. Peptidomics, on the other hand, relies on "hyphenated" (liquid chromatography-mass spectrometry-based) techniques for the detection, profiling, and quantitation of peptides. Together, bioinformatics and peptidomics approaches provide a low-cost and effective means of predicting, profiling, and screening bioactive protein hydrolysates and peptides from food. This article discuses the basis, strengths, and limitations of bioinformatics and peptidomics approaches currently used for the discovery and analysis of food-derived bioactive peptides.

LGMD2D syndrome: the importance of clinical and molecular genetics in patient and family management. Case Report.

PubMed

Al-Harbi, Khalid M; Abdallah, Atiyeh M

2016-09-01

We report the case of a seven-year-old female from a consanguineous Saudi family with autosomal recessive limb girdle muscular dystrophy type 2D (LGMD2D) most likely caused by a rare SGCA mutation. Histopathological and molecular investigations resulted in the discovery of a homozygous mutation (c.226 C>T (p.L76 F)) in exon 3 of SGCA in the patient. The parents and one sibling were heterozygous carriers, but the mutation was not otherwise detected in 80 ethnic controls from the same geographic area. In silico analysis revealed that the mutation resulted in a functional leucine to phenylalanine alteration that was deleterious to the protein structure. This is only the second reported case of the p.L76F mutation in LGMD, and highlights that molecular genetics analysis is essential to deliver the most appropriate management to the patient and offer the family genetic counseling.

α-Glucosidase inhibition by prenylated and lavandulyl compounds from Sophora flavescens roots and in silico analysis.

PubMed

Kim, Jang Hoon; Cho, Chong Woon; Kim, Hyo Young; Kim, Kyung Tae; Choi, Gug-Seoun; Kim, Hyeong-Hwang; Cho, In Sook; Kwon, Sun Jung; Choi, Seung-Kook; Yoon, Ju-Yeon; Yang, Seo Young; Kang, Jong Seong; Kim, Young Ho

2017-09-01

The enzyme α-glucosidase is a good drug target for the treatment of diabetes mellitus. Four minor flavonoids (1-4) from roots of Sophora flavescens showed the inhibitory activity, with IC 50 values ranging from 11.0±0.3 to 50.6±1.3μM, toward α-glucosidase. An enzyme kinetics analysis of them revealed that the compounds 1 and 4 were non-competitive, and compounds 2 and 3 were un-competitive inhibitors. For molecular docking, 3-dimensional structure of α-glucosidase was built by homology modeling. As the result, four compounds 1-4 were confirmed to interact into common binding site of α-glucosidase. In addition, all of the four prenylated and lavandulyl compounds (1-4) were abundant in an ethyl acetate fraction separated from a methanol extract, and the potential inhibitor (3) was extracted best using tetrahydrofuran. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Analysis of binding properties and specificity through identification of the interface forming residues (IFR) for serine proteases in silico docked to different inhibitors.

PubMed

Ribeiro, Cristina; Togawa, Roberto C; Neshich, Izabella A P; Mazoni, Ivan; Mancini, Adauto L; Minardi, Raquel C de Melo; da Silveira, Carlos H; Jardine, José G; Santoro, Marcelo M; Neshich, Goran

2010-10-20

Enzymes belonging to the same super family of proteins in general operate on variety of substrates and are inhibited by wide selection of inhibitors. In this work our main objective was to expand the scope of studies that consider only the catalytic and binding pocket amino acids while analyzing enzyme specificity and instead, include a wider category which we have named the Interface Forming Residues (IFR). We were motivated to identify those amino acids with decreased accessibility to solvent after docking of different types of inhibitors to sub classes of serine proteases and then create a table (matrix) of all amino acid positions at the interface as well as their respective occupancies. Our goal is to establish a platform for analysis of the relationship between IFR characteristics and binding properties/specificity for bi-molecular complexes. We propose a novel method for describing binding properties and delineating serine proteases specificity by compiling an exhaustive table of interface forming residues (IFR) for serine proteases and their inhibitors. Currently, the Protein Data Bank (PDB) does not contain all the data that our analysis would require. Therefore, an in silico approach was designed for building corresponding complexes. The IFRs are obtained by "rigid body docking" among 70 structurally aligned, sequence wise non-redundant, serine protease structures with 3 inhibitors: bovine pancreatic trypsin inhibitor (BPTI), ecotine and ovomucoid third domain inhibitor. The table (matrix) of all amino acid positions at the interface and their respective occupancy is created. We also developed a new computational protocol for predicting IFRs for those complexes which were not deciphered experimentally so far, achieving accuracy of at least 0.97. The serine proteases interfaces prefer polar (including glycine) residues (with some exceptions). Charged residues were found to be uniquely prevalent at the interfaces between the "miscellaneous-virus" subfamily and the three inhibitors. This prompts speculation about how important this difference in IFR characteristics is for maintaining virulence of those organisms.Our work here provides a unique tool for both structure/function relationship analysis as well as a compilation of indicators detailing how the specificity of various serine proteases may have been achieved and/or could be altered. It also indicates that the interface forming residues which also determine specificity of serine protease subfamily can not be presented in a canonical way but rather as a matrix of alternative populations of amino acids occupying variety of IFR positions.

Analysis of binding properties and specificity through identification of the interface forming residues (IFR) for serine proteases in silico docked to different inhibitors

PubMed Central

2010-01-01

Background Enzymes belonging to the same super family of proteins in general operate on variety of substrates and are inhibited by wide selection of inhibitors. In this work our main objective was to expand the scope of studies that consider only the catalytic and binding pocket amino acids while analyzing enzyme specificity and instead, include a wider category which we have named the Interface Forming Residues (IFR). We were motivated to identify those amino acids with decreased accessibility to solvent after docking of different types of inhibitors to sub classes of serine proteases and then create a table (matrix) of all amino acid positions at the interface as well as their respective occupancies. Our goal is to establish a platform for analysis of the relationship between IFR characteristics and binding properties/specificity for bi-molecular complexes. Results We propose a novel method for describing binding properties and delineating serine proteases specificity by compiling an exhaustive table of interface forming residues (IFR) for serine proteases and their inhibitors. Currently, the Protein Data Bank (PDB) does not contain all the data that our analysis would require. Therefore, an in silico approach was designed for building corresponding complexes The IFRs are obtained by "rigid body docking" among 70 structurally aligned, sequence wise non-redundant, serine protease structures with 3 inhibitors: bovine pancreatic trypsin inhibitor (BPTI), ecotine and ovomucoid third domain inhibitor. The table (matrix) of all amino acid positions at the interface and their respective occupancy is created. We also developed a new computational protocol for predicting IFRs for those complexes which were not deciphered experimentally so far, achieving accuracy of at least 0.97. Conclusions The serine proteases interfaces prefer polar (including glycine) residues (with some exceptions). Charged residues were found to be uniquely prevalent at the interfaces between the "miscellaneous-virus" subfamily and the three inhibitors. This prompts speculation about how important this difference in IFR characteristics is for maintaining virulence of those organisms. Our work here provides a unique tool for both structure/function relationship analysis as well as a compilation of indicators detailing how the specificity of various serine proteases may have been achieved and/or could be altered. It also indicates that the interface forming residues which also determine specificity of serine protease subfamily can not be presented in a canonical way but rather as a matrix of alternative populations of amino acids occupying variety of IFR positions. PMID:20961427

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.

A Tyrosine Residue Along with a Glutamic Acid of the Omega-Like Loop Governs the Beta-Lactamase Activity of MSMEG_4455 in Mycobacterium smegmatis.

PubMed

Bansal, Ankita; Kar, Debasish; Pandey, Satya Deo; Matcha, Ashok; Kumar, N Ganesh; Nathan, Soshina; Ghosh, Anindya S

2017-06-01

Mycobacterial beta-lactamases are involved in exerting beta-lactam resistance, though many of these proteins remain uncharacterized. Here, we have characterized MSMEG_4455 of Mycobacterium smegmatis as a beta-lactamase using molecular, biochemical and mutational techniques. To elucidate its nature in vivo and in vitro, and to predict its structure-function relationship in silico analysis is done. The MSMEG_4455 is cloned and expressed ectopically in a beta-lactamase deficient Escherichia coli mutant to establish the in vivo beta-lactamase like nature via minimum inhibitory concentration (MIC) determination. Likewise the in vivo results, purified soluble form of MSMEG_4455 showed beta-lactam hydrolysis pattern similar to group 2a penicillinase. In silico analyses of MSMEG_4455 reveal glutamic acid (E)193 and tyrosine (Y)194 of omega-like loop might have importance in strengthening hydrogen bond network around the active-site, though involvement of tyrosine is rare for beta-lactamase activity. Accordingly, these residues are mutated to alanine (A) and phenylalanine (F), respectively. The mutated proteins have partially lost their ability to exert beta-lactamase activity both in vivo and in vitro. The Y194F mutation had more prominent effect on the enzymatic activity. Therefore, we infer that Y194 is the key for beta-lactamase activity of MSMEG_4455.

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.

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

PubMed Central

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

2017-01-01

Mycotoxins are secondary metabolites of fungi that contaminate food and feed, and are involved in a series of foodborne illnesses and disorders in humans and animals. The mitigation of mycotoxin content via enzymatic degradation is a strategy to ensure safer food and feed, and to address the forthcoming issues in view of the global trade and sustainability. Nevertheless, the search for active enzymes is still challenging and time-consuming. The in silico analysis may strongly support the research by providing the evidence-based hierarchization of enzymes for a rational design of more effective experimental trials. The present work dealt with the degradation of aflatoxin B1 and M1 by laccase enzymes from Trametes versicolor. The enzymes–substrate interaction for various enzyme isoforms was investigated through 3D molecular modeling techniques. Structural differences among the isoforms have been pinpointed, which may cause different patterns of interaction between aflatoxin B1 and M1. The possible formation of different products of degradation can be argued accordingly. Moreover, the laccase gamma isoform was identified as the most suitable for protein engineering aimed at ameliorating the substrate specificity. Overall, 3D modeling proved to be an effective analytical tool to assess the enzyme–substrate interaction and provided a solid foothold for supporting the search of degrading enzyme at the early stage. PMID:28045427

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

ProTox: a web server for the in silico prediction of rodent oral toxicity.

PubMed

Drwal, Malgorzata N; Banerjee, Priyanka; Dunkel, Mathias; Wettig, Martin R; Preissner, Robert

2014-07-01

Animal trials are currently the major method for determining the possible toxic effects of drug candidates and cosmetics. In silico prediction methods represent an alternative approach and aim to rationalize the preclinical drug development, thus enabling the reduction of the associated time, costs and animal experiments. Here, we present ProTox, a web server for the prediction of rodent oral toxicity. The prediction method is based on the analysis of the similarity of compounds with known median lethal doses (LD50) and incorporates the identification of toxic fragments, therefore representing a novel approach in toxicity prediction. In addition, the web server includes an indication of possible toxicity targets which is based on an in-house collection of protein-ligand-based pharmacophore models ('toxicophores') for targets associated with adverse drug reactions. The ProTox web server is open to all users and can be accessed without registration at: http://tox.charite.de/tox. The only requirement for the prediction is the two-dimensional structure of the input compounds. All ProTox methods have been evaluated based on a diverse external validation set and displayed strong performance (sensitivity, specificity and precision of 76, 95 and 75%, respectively) and superiority over other toxicity prediction tools, indicating their possible applicability for other compound classes. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Binary Classification of a Large Collection of Environmental Chemicals from Estrogen Receptor Assays by Quantitative Structure-Activity Relationship and Machine Learning Methods

EPA Science Inventory

ABSTRACT: There are thousands of environmental chemicals subject to regulatory decisions for endocrine disrupting potential. A promising approach to manage this large universe of untested chemicals is to use a prioritization filter that combines in vitro assays with in silico QSA...

Too many chemicals, too little time: Rapid in silico methods to characterize and predict ADME properties for chemical toxicity and exposure potential

EPA Science Inventory

Evaluating proposed alternative chemical structures to support the design of safer chemicals and products is an important component of EPA's Green Chemistry and Design for the Environment (DfE) Programs. As such, science-based alternatives assessment is essential to support EPA's...

In-silico structure activity relationship study of toxicity endpoints by QSAR modeling (SOT)

EPA Science Inventory

Several thousand chemicals were tested in 700 toxicity-related in-vitro HTS bioassays through the EPA’s ToxCast and Tox21 projects. This chemical set only covers a portion of the chemical space of interest for environmental exposure, leading to a need to fill data gaps with alter...

Identification of potential glutaminyl cyclase inhibitors from lead-like libraries by in silico and in vitro fragment-based screening.

PubMed

Szaszkó, Mária; Hajdú, István; Flachner, Beáta; Dobi, Krisztina; Magyar, Csaba; Simon, István; Lőrincz, Zsolt; Kapui, Zoltán; Pázmány, Tamás; Cseh, Sándor; Dormán, György

2017-02-01

A glutaminyl cyclase (QC) fragment library was in silico selected by disconnection of the structure of known QC inhibitors and by lead-like 2D virtual screening of the same set. The resulting fragment library (204 compounds) was acquired from commercial suppliers and pre-screened by differential scanning fluorimetry followed by functional in vitro assays. In this way, 10 fragment hits were identified ([Formula: see text]5 % hit rate, best inhibitory activity: 16 [Formula: see text]). The in vitro hits were then docked to the active site of QC, and the best scoring compounds were analyzed for binding interactions. Two fragments bound to different regions in a complementary manner, and thus, linking those fragments offered a rational strategy to generate novel QC inhibitors. Based on the structure of the virtual linked fragment, a 77-membered QC target focused library was selected from vendor databases and docked to the active site of QC. A PubChem search confirmed that the best scoring analogues are novel, potential QC inhibitors.

Sound transmission in porcine thorax through airway insonification.

PubMed

Peng, Ying; Dai, Zoujun; Mansy, Hansen A; Henry, Brian M; Sandler, Richard H; Balk, Robert A; Royston, Thomas J

2016-04-01

Many pulmonary injuries and pathologies may lead to structural and functional changes in the lungs resulting in measurable sound transmission changes on the chest surface. Additionally, noninvasive imaging of externally driven mechanical wave motion in the chest (e.g., using magnetic resonance elastography) can provide information about lung structural property changes and, hence, may be of diagnostic value. In the present study, a comprehensive computational simulation (in silico) model was developed to simulate sound wave propagation in the airways, lung, and chest wall under normal and pneumothorax conditions. Experiments were carried out to validate the model. Here, sound waves with frequency content from 50 to 700 Hz were introduced into airways of five porcine subjects via an endotracheal tube, and transmitted waves were measured by scanning laser Doppler vibrometry at the chest wall surface. The computational model predictions of decreased sound transmission with pneumothorax were consistent with experimental measurements. The in silico model can also be used to visualize wave propagation inside and on the chest wall surface for other pulmonary pathologies, which may help in developing and interpreting diagnostic procedures that utilize sound and vibration.

In Vivo, In Vitro, and In Silico Characterization of Peptoids as Antimicrobial Agents.

PubMed

Czyzewski, Ann M; Jenssen, Håvard; Fjell, Christopher D; Waldbrook, Matt; Chongsiriwatana, Nathaniel P; Yuen, Eddie; Hancock, Robert E W; Barron, Annelise E

2016-01-01

Bacterial resistance to conventional antibiotics is a global threat that has spurred the development of antimicrobial peptides (AMPs) and their mimetics as novel anti-infective agents. While the bioavailability of AMPs is often reduced due to protease activity, the non-natural structure of AMP mimetics renders them robust to proteolytic degradation, thus offering a distinct advantage for their clinical application. We explore the therapeutic potential of N-substituted glycines, or peptoids, as AMP mimics using a multi-faceted approach that includes in silico, in vitro, and in vivo techniques. We report a new QSAR model that we developed based on 27 diverse peptoid sequences, which accurately correlates antimicrobial peptoid structure with antimicrobial activity. We have identified a number of peptoids that have potent, broad-spectrum in vitro activity against multi-drug resistant bacterial strains. Lastly, using a murine model of invasive S. aureus infection, we demonstrate that one of the best candidate peptoids at 4 mg/kg significantly reduces with a two-log order the bacterial counts compared with saline-treated controls. Taken together, our results demonstrate the promising therapeutic potential of peptoids as antimicrobial agents.

Sound transmission in porcine thorax through airway insonification

PubMed Central

Dai, Zoujun; Mansy, Hansen A.; Henry, Brian M.; Sandler, Richard H.; Balk, Robert A.; Royston, Thomas J.

2015-01-01

Many pulmonary injuries and pathologies may lead to structural and functional changes in the lungs resulting in measurable sound transmission changes on the chest surface. Additionally, noninvasive imaging of externally driven mechanical wave motion in the chest (e.g., using magnetic resonance elastography) can provide information about lung structural property changes and, hence, may be of diagnostic value. In the present study, a comprehensive computational simulation (in silico) model was developed to simulate sound wave propagation in the airways, lung, and chest wall under normal and pneumothorax conditions. Experiments were carried out to validate the model. Here, sound waves with frequency content from 50 to 700 Hz were introduced into airways of five porcine subjects via an endotracheal tube, and transmitted waves were measured by scanning laser Doppler vibrometry at the chest wall surface. The computational model predictions of decreased sound transmission with pneumothorax were consistent with experimental measurements. The in silico model can also be used to visualize wave propagation inside and on the chest wall surface for other pulmonary pathologies, which may help in developing and interpreting diagnostic procedures that utilize sound and vibration. PMID:26280512

Life's attractors : understanding developmental systems through reverse engineering and in silico evolution.

PubMed

Jaeger, Johannes; Crombach, Anton

2012-01-01

We propose an approach to evolutionary systems biology which is based on reverse engineering of gene regulatory networks and in silico evolutionary simulations. We infer regulatory parameters for gene networks by fitting computational models to quantitative expression data. This allows us to characterize the regulatory structure and dynamical repertoire of evolving gene regulatory networks with a reasonable amount of experimental and computational effort. We use the resulting network models to identify those regulatory interactions that are conserved, and those that have diverged between different species. Moreover, we use the models obtained by data fitting as starting points for simulations of evolutionary transitions between species. These simulations enable us to investigate whether such transitions are random, or whether they show stereotypical series of regulatory changes which depend on the structure and dynamical repertoire of an evolving network. Finally, we present a case study-the gap gene network in dipterans (flies, midges, and mosquitoes)-to illustrate the practical application of the proposed methodology, and to highlight the kind of biological insights that can be gained by this approach.

IspE Inhibitors Identified by a Combination of In Silico and In Vitro High-Throughput Screening

PubMed Central

Tidten-Luksch, Naomi; Grimaldi, Raffaella; Torrie, Leah S.; Frearson, Julie A.; Hunter, William N.; Brenk, Ruth

2012-01-01

CDP-ME kinase (IspE) contributes to the non-mevalonate or deoxy-xylulose phosphate (DOXP) pathway for isoprenoid precursor biosynthesis found in many species of bacteria and apicomplexan parasites. IspE has been shown to be essential by genetic methods and since it is absent from humans it constitutes a promising target for antimicrobial drug development. Using in silico screening directed against the substrate binding site and in vitro high-throughput screening directed against both, the substrate and co-factor binding sites, non-substrate-like IspE inhibitors have been discovered and structure-activity relationships were derived. The best inhibitors in each series have high ligand efficiencies and favourable physico-chemical properties rendering them promising starting points for drug discovery. Putative binding modes of the ligands were suggested which are consistent with established structure-activity relationships. The applied screening methods were complementary in discovering hit compounds, and a comparison of both approaches highlights their strengths and weaknesses. It is noteworthy that compounds identified by virtual screening methods provided the controls for the biochemical screens. PMID:22563402

Secondary metabolites of Cynodon dactylon as an antagonist to angiotensin II type1 receptor: Novel in silico drug targeting approach for diabetic retinopathy

PubMed Central

Jananie, R. K.; Priya, V.; Vijayalakshmi, K.

2012-01-01

Objectives: To study the ability of the secondary metabolites of Cynodon dactylon to serve as an antagonist to angiotensin II type 1 receptor (AT1); activation of this receptor plays a vital role in diabetic retinopathy (DR). Materials and Methods: In silico methods are mainly harnessed to reduce time, cost and risk associated with drug discovery. Twenty-four compounds were identified as the secondary metabolites of hydroalcoholic extract of C. dactylon using the GCMS technique. These were considered as the ligands or inhibitors that would serve as an antagonist to the AT1. The ACD/Chemsketch tool was used to generate 3D structures of the ligands. A molecular file format converter tool was used to convert the generated data to the PDB format (Protein Data Bank) and was used for docking studies. The AT1 structure was retrieved from the Swissprot data base and PDB and visualized using the Rasmol tool. Domain analysis was carried from the Pfam data base; following this, the active site of the target protein was identified using a Q-site finder tool. The ability of the ligands to bind with the active site of AT1 was studied using the Autodocking tool. The docking results were analyzed using the WebLab viewer tool. Results: Sixteen ligands showed effective binding with the target protein; diazoprogesteron, didodecyl phthalate, and 9,12-octadecadienoyl chloride (z,z) may be considered as compounds that could be used to bind with the active site sequence of AT1. Conclusions: The present study shows that the metabolites of C. dactylon could serve as a natural antagonist to AT1 that could be used to treat diabetic retinopathy. PMID:22368412

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

Synthesis, structure characterization, in vitro and in silico biological evaluation of a new series of thiazole nucleus integrated with pyrazoline scaffolds

NASA Astrophysics Data System (ADS)

Sadashiva, Rajitha; Naral, Damodara; Kudva, Jyothi; Madan Kumar, S.; Byrappa, K.; Mohammed Shafeeulla, R.; Kumsi, Manjunatha

2017-10-01

In the current study, a series of 2,4-disubstituted-1,3-thiazoles linked with pyrazoline scaffolds 3a-o were rationally designed and synthesized. The structures of the title compounds were elucidated by spectroscopic data (UV-Vis, IR, NMR and Mass spectra) and elemental analysis. Single crystal X-Ray diffraction studies revealed that, the compounds 3i and 3k crystallized in monoclinic crystal system with P21/n space group and Z = 4. The molecules 3i and 3k were connected with intermolecular hydrogen bonds N2-H2 … O1, N3sbnd H3 … Cl1 and short contacts (Csbnd H … π and Csbnd Cl … π). Intramolecular hydrogen bonds, N3sbnd H3 … N5 and C5sbnd H5 ….N1 were also existed. The compounds were evaluated for their anticancer activity against A549 and MCF-7 human cancer cell lines and in vitro antimicrobial activity against pathogenic microbial strains. The compounds bearing chloro atom at the para position of phenyl ring A like 3f, 3j and 3k with the IC50: 7.5, 5.0 and 5.0 μM respectively, exhibited better activity than standard drug Cisplatin (IC50: 10.0 μM). In addition, the compounds 3a, 3f, 3j and 3l have exhibited the similar antimicrobial activity as that of standard drug Ciprofloxacin and Fluconazole. Furthermore, to support the biological potency of the compounds, in silico molecular docking studies were carried out against the E. coli MurB (PDB code: pdb:2MBR)

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.

RapA2 Is a Calcium-binding Lectin Composed of Two Highly Conserved Cadherin-like Domains That Specifically Recognize Rhizobium leguminosarum Acidic Exopolysaccharides*

PubMed Central

Abdian, Patricia L.; Caramelo, Julio J.; Ausmees, Nora; Zorreguieta, Angeles

2013-01-01

In silico analyses have revealed a conserved protein domain (CHDL) widely present in bacteria that has significant structural similarity to eukaryotic cadherins. A CHDL domain was shown to be present in RapA, a protein that is involved in autoaggregation of Rhizobium cells, biofilm formation, and adhesion to plant roots as shown by us and others. Structural similarity to cadherins suggested calcium-dependent oligomerization of CHDL domains as a mechanistic basis for RapA action. Here we show by circular dichroism spectroscopy, light scattering, isothermal titration calorimetry, and other methods that RapA2 from Rhizobium leguminosarum indeed exhibits a cadherin-like β-sheet conformation and that its proper folding and stability are dependent on the binding of one calcium ion per protein molecule. By further in silico analysis we also reveal that RapA2 consists of two CHDL domains and expand the range of CHDL-containing proteins in bacteria and archaea. However, light scattering assays at various concentrations of added calcium revealed that RapA2 formed neither homo-oligomers nor hetero-oligomers with RapB (a distinct CHDL protein), indicating that RapA2 does not mediate cellular interactions through a cadherin-like mechanism. Instead, we demonstrate that RapA2 interacts specifically with the acidic exopolysaccharides (EPSs) produced by R. leguminosarum in a calcium-dependent manner, sustaining a role of these proteins in the development of the biofilm matrix made of EPS. Because EPS binding by RapA2 can only be attributed to its two CHDL domains, we propose that RapA2 is a calcium-dependent lectin and that CHDL domains in various bacterial and archaeal proteins confer carbohydrate binding activity to these proteins. PMID:23235153

High-Throughput and Rapid Screening of Novel ACE Inhibitory Peptides from Sericin Source and Inhibition Mechanism by Using in Silico and in Vitro Prescriptions.

PubMed

Sun, Huaju; Chang, Qing; Liu, Long; Chai, Kungang; Lin, Guangyan; Huo, Qingling; Zhao, Zhenxia; Zhao, Zhongxing

2017-11-22

Several novel peptides with high ACE-I inhibitory activity were successfully screened from sericin hydrolysate (SH) by coupling in silico and in vitro approaches for the first time. Most screening processes for ACE-I inhibitory peptides were achieved through high-throughput in silico simulation followed by in vitro verification. QSAR model based predicted results indicated that the ACE-I inhibitory activity of these SH peptides and six chosen peptides exhibited moderate high ACE-I inhibitory activities (log IC 50 values: 1.63-2.34). Moreover, two tripeptides among the chosen six peptides were selected for ACE-I inhibition mechanism analysis which based on Lineweaver-Burk plots indicated that they behave as competitive ACE-I inhibitors. The C-terminal residues of short-chain peptides that contain more H-bond acceptor groups could easily form hydrogen bonds with ACE-I and have higher ACE-I inhibitory activity. Overall, sericin protein as a strong ACE-I inhibition source could be deemed a promising agent for antihypertension applications.

Bond efficacy of recycled orthodontic brackets: A comparative in vitro evaluation of two methods.

PubMed

Shetty, Vikram; Shekatkar, Yash; Kumbhat, Neesu; Gautam, G; Karbelkar, Shalan; Vandekar, Meghna

2015-01-01

Recycling of orthodontic brackets in developing orthodontic economies is an extremely common procedure. Bonding protocols and reliability of these brackets is, however, questionable, and still the subject of research. The aim was to evaluate and compare the shear bond strength of brackets recycled with sandblasting and silicoating. Ninety extracted human premolars were bonded with 0.022" SS brackets (American Orthodontics, Sheboygan USA) and then debonded. The debonded brackets were divided into three groups of 30 each. Group I: Sandblasting with 50-μm aluminum oxide (control group) Group II: Sandblasting with 50-μm aluminum oxide followed by metal primer application Group III: Silicoating with 30-μm Cojet sand followed by silane application and rebonded with Transbond XT. The sandblasted brackets and silicoated brackets were viewed under the scanning electron microscope, immediately after surface conditioning before rebonding. The shear bond strength with each group was tested. One-way analysis of variance, post-hoc Scheffe multiple comparison tests. The results showed that sandblasting created more irregularities and deeper erosions while silica coating created superficial irregularities and shallow erosions.

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.

In Silico Identification of Protein Disulfide Isomerase Gene Families in the De Novo Assembled Transcriptomes of Four Different Species of the Genus Conus.

PubMed

Figueroa-Montiel, Andrea; Ramos, Marco A; Mares, Rosa E; Dueñas, Salvador; Pimienta, Genaro; Ortiz, Ernesto; Possani, Lourival D; Licea-Navarro, Alexei F

2016-01-01

Small peptides isolated from the venom of the marine snails belonging to the genus Conus have been largely studied because of their therapeutic value. These peptides can be classified in two groups. The largest one is composed by peptides rich in disulfide bonds, and referred to as conotoxins. Despite the importance of conotoxins given their pharmacology value, little is known about the protein disulfide isomerase (PDI) enzymes that are required to catalyze their correct folding. To discover the PDIs that may participate in the folding and structural maturation of conotoxins, the transcriptomes of the venom duct of four different species of Conus from the peninsula of Baja California (Mexico) were assembled. Complementary DNA (cDNA) libraries were constructed for each species and sequenced using a Genome Analyzer Illumina platform. The raw RNA-seq data was converted into transcript sequences using Trinity, a de novo assembler that allows the grouping of reads into contigs without a reference genome. An N50 value of 605 was established as a reference for future assemblies of Conus transcriptomes using this software. Transdecoder was used to extract likely coding sequences from Trinity transcripts, and PDI-specific sequence motif "APWCGHCK" was used to capture potential PDIs. An in silico analysis was performed to characterize the group of PDI protein sequences encoded by the duct-transcriptome of each species. The computational approach entailed a structural homology characterization, based on the presence of functional Thioredoxin-like domains. Four different PDI families were characterized, which are constituted by a total of 41 different gene sequences. The sequences had an average of 65% identity with other PDIs. Using MODELLER 9.14, the homology-based three-dimensional structure prediction of a subset of the sequences reported, showed the expected thioredoxin fold which was confirmed by a "simulated annealing" method.

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

PubMed

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

2016-03-17

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

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

Integrative, multimodal analysis of glioblastoma using TCGA molecular data, pathology images, and clinical outcomes.

PubMed

Kong, Jun; Cooper, Lee A D; Wang, Fusheng; Gutman, David A; Gao, Jingjing; Chisolm, Candace; Sharma, Ashish; Pan, Tony; Van Meir, Erwin G; Kurc, Tahsin M; Moreno, Carlos S; Saltz, Joel H; Brat, Daniel J

2011-12-01

Multimodal, multiscale data synthesis is becoming increasingly critical for successful translational biomedical research. In this letter, we present a large-scale investigative initiative on glioblastoma, a high-grade brain tumor, with complementary data types using in silico approaches. We integrate and analyze data from The Cancer Genome Atlas Project on glioblastoma that includes novel nuclear phenotypic data derived from microscopic slides, genotypic signatures described by transcriptional class and genetic alterations, and clinical outcomes defined by response to therapy and patient survival. Our preliminary results demonstrate numerous clinically and biologically significant correlations across multiple data types, revealing the power of in silico multimodal data integration for cancer research.

In silico and in vitro prediction of gastrointestinal absorption from potential drug eremantholide C.

PubMed

Caldeira, Tamires G; Saúde-Guimarães, Dênia A; Dezani, André B; Serra, Cristina Helena Dos Reis; de Souza, Jacqueline

2017-11-01

Analysis of the biopharmaceutical properties of eremantholide C, sesquiterpene lactone with proven pharmacological activity and low toxicity, is required to evaluate its potential to become a drug. Preliminary analysis of the physicochemical characteristics of eremantholide C was performed in silico. Equilibrium solubility was evaluated using the shake-flask method, at 37.0 °C, 100 rpm during 72 h in biorelevant media. The permeability was analysed using parallel artificial membrane permeability assay, at 37.0 °C, 50 rpm for 5 h. The donor compartment was composed of an eremantholide C solution in intestinal fluid simulated without enzymes, while the acceptor compartment consisted of phosphate buffer. Physicochemical characteristics predicted in silico indicated that eremantholide C has a low solubility and high permeability. In-vitro data of eremantholide C showed low solubility, with values for the dose/solubility ratio (ml): 9448.82, 10 389.61 e 15 000.00 for buffers acetate (pH 4.5), intestinal fluid simulated without enzymes (pH 6.8) and phosphate (pH 7.4), respectively. Also, it showed high permeability, with effective permeability of 30.4 × 10 -6 cm/s, a higher result compared with propranolol hydrochloride (9.23 × 10 -6 cm/s). The high permeability combined with its solubility, pharmacological activity and low toxicity demonstrate the importance of eremantholide C as a potential drug candidate. © 2017 Royal Pharmaceutical Society.

Genererating a core cluster of Fasciola hepatica virulence and immunomodulation-related genes using a comparative in silico approach.

PubMed

Haçarız, Orçun; Sayers, Gearóid P

2018-04-01

A total of 71 virulence and immunomodulation-related transcripts (VIRs) of Fasciola hepatica have been previously proposed (Haçarız et al., 2015). In an attempt to further refine this cohort, an in silico meta analysis approach was carried out using publicly available sequence data of related liver flukes, Clonorchis sinensis and Opisthorchis viverrini. Data of both liver flukes were investigated in terms of sequential homology with data of non-parasitic organisms, pathogens and VIRs of F. hepatica, directional selection (Ka/Ks), and cytokine signaling relation (protein motif based). Some VIRs of F. hepatica [showing homology with immune receptors (for toll/interleukin-1, TGF-β or TNF-α), TGF-β, TNF-α, CD147, or relation with suppressors of cytokine signaling/IKBKE 1 or stimulation of TGF-β (through thrombospondin similarity)] were found to be orthologous with those of both C. sinensis and O. viverrini. The in silico analysis indicates that on the basis of genetic commonality, a total of 30 VIRs of F. hepatica are highlighted as of foremost importance in the parasite evasion strategy, through controlling of host immune system. Findings in this study could be important to further enhance our understanding of the parasitic mechanisms and develop effective control strategies against F. hepatica and other related parasites. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0

PubMed Central

Schellenberger, Jan; Que, Richard; Fleming, Ronan M. T.; Thiele, Ines; Orth, Jeffrey D.; Feist, Adam M.; Zielinski, Daniel C.; Bordbar, Aarash; Lewis, Nathan E.; Rahmanian, Sorena; Kang, Joseph; Hyduke, Daniel R.; Palsson, Bernhard Ø.

2012-01-01

Over the past decade, a growing community of researchers has emerged around the use of COnstraint-Based Reconstruction and Analysis (COBRA) methods to simulate, analyze and predict a variety of metabolic phenotypes using genome-scale models. The COBRA Toolbox, a MATLAB package for implementing COBRA methods, was presented earlier. Here we present a significant update of this in silico ToolBox. Version 2.0 of the COBRA Toolbox expands the scope of computations by including in silico analysis methods developed since its original release. New functions include: (1) network gap filling, (2) 13C analysis, (3) metabolic engineering, (4) omics-guided analysis, and (5) visualization. As with the first version, the COBRA Toolbox reads and writes Systems Biology Markup Language formatted models. In version 2.0, we improved performance, usability, and the level of documentation. A suite of test scripts can now be used to learn the core functionality of the Toolbox and validate results. This Toolbox lowers the barrier of entry to use powerful COBRA methods. PMID:21886097

Characterization and validation of an in silico toxicology model to predict the mutagenic potential of drug impurities*

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

Valerio, Luis G., E-mail: luis.valerio@fda.hhs.gov; Cross, Kevin P.

Control and minimization of human exposure to potential genotoxic impurities found in drug substances and products is an important part of preclinical safety assessments of new drug products. The FDA's 2008 draft guidance on genotoxic and carcinogenic impurities in drug substances and products allows use of computational quantitative structure–activity relationships (QSAR) to identify structural alerts for known and expected impurities present at levels below qualified thresholds. This study provides the information necessary to establish the practical use of a new in silico toxicology model for predicting Salmonella t. mutagenicity (Ames assay outcome) of drug impurities and other chemicals. We describemore » the model's chemical content and toxicity fingerprint in terms of compound space, molecular and structural toxicophores, and have rigorously tested its predictive power using both cross-validation and external validation experiments, as well as case studies. Consistent with desired regulatory use, the model performs with high sensitivity (81%) and high negative predictivity (81%) based on external validation with 2368 compounds foreign to the model and having known mutagenicity. A database of drug impurities was created from proprietary FDA submissions and the public literature which found significant overlap between the structural features of drug impurities and training set chemicals in the QSAR model. Overall, the model's predictive performance was found to be acceptable for screening drug impurities for Salmonella mutagenicity. -- Highlights: ► We characterize a new in silico model to predict mutagenicity of drug impurities. ► The model predicts Salmonella mutagenicity and will be useful for safety assessment. ► We examine toxicity fingerprints and toxicophores of this Ames assay model. ► We compare these attributes to those found in drug impurities known to FDA/CDER. ► We validate the model and find it has a desired predictive performance.« less

Novel 16S rDNA primers revealed the diversity and habitats-related community structure of sphingomonads in 10 different niches.

PubMed

Huang, Yili; Feng, Hao; Lu, Hang; Zeng, Yanhua

2017-07-01

It is believed that sphingomonads are ubiquitously distributed in environments. However detailed information about their community structure and their co-relationship with environmental parameters remain unclear. In this study, novel sphingomonads-specific primers based on the 16S rRNA gene were designed to investigate the distribution of sphingomonads in 10 different niches. Both in silico and in-practice tests on pure cultures and environmental samples showed that Sph384f/Sph701r was an efficient primer set. Illumina MiSeq sequencing revealed that community structures of sphingomonads were significantly different among the 10 samples, although 12 sphingomonad genera were present in all samples. Based on RDA analysis and Monte Carlo permutation test, sphingomonad community structure was significantly correlated with limnetic and marine habitat types. Among these niches, the genus Sphingomicrobium showed strong positive correlation with marine habitats, whereas genera Sphingobium, Novosphingobium, Sphingopyxis, and Sphingorhabdus showed strong positive correlation with limnetic habitats. Our study provided direct evidence that sphingomonads are ubiquitously distributed in environments, and revealed for the first time that their community structure can be correlated with habitats.

Small molecule correctors of F508del-CFTR discovered by structure-based virtual screening

NASA Astrophysics Data System (ADS)

Kalid, Ori; Mense, Martin; Fischman, Sharon; Shitrit, Alina; Bihler, Hermann; Ben-Zeev, Efrat; Schutz, Nili; Pedemonte, Nicoletta; Thomas, Philip J.; Bridges, Robert J.; Wetmore, Diana R.; Marantz, Yael; Senderowitz, Hanoch

2010-12-01

Folding correctors of F508del-CFTR were discovered by in silico structure-based screening utilizing homology models of CFTR. The intracellular segment of CFTR was modeled and three cavities were identified at inter-domain interfaces: (1) Interface between the two Nucleotide Binding Domains (NBDs); (2) Interface between NBD1 and Intracellular Loop (ICL) 4, in the region of the F508 deletion; (3) multi-domain interface between NBD1:2:ICL1:2:4. We hypothesized that compounds binding at these interfaces may improve the stability of the protein, potentially affecting the folding yield or surface stability. In silico structure-based screening was performed at the putative binding-sites and a total of 496 candidate compounds from all three sites were tested in functional assays. A total of 15 compounds, representing diverse chemotypes, were identified as F508del folding correctors. This corresponds to a 3% hit rate, tenfold higher than hit rates obtained in corresponding high-throughput screening campaigns. The same binding sites also yielded potentiators and, most notably, compounds with a dual corrector-potentiator activity (dual-acting). Compounds harboring both activity types may prove to be better leads for the development of CF therapeutics than either pure correctors or pure potentiators. To the best of our knowledge this is the first report of structure-based discovery of CFTR modulators.

Large Dataset of Acute Oral Toxicity Data Created for Testing ...

EPA Pesticide Factsheets

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 being developed due to animal welfare and resource considerations. We compiled a large dataset of oral rat LD50 values to assess the predictive performance currently available in silico models. Our dataset combines LD50 values from five different sources: literature data provided by The Dow Chemical Company, REACH data from eChemportal, HSDB (Hazardous Substances Data Bank), RTECS data from Leadscope, and the training set underpinning TEST (Toxicity Estimation Software Tool). Combined these data sources yield 33848 chemical-LD50 pairs (data points), with 23475 unique data points covering 16439 compounds. The entire dataset was loaded into a chemical properties database. All of the compounds were registered in DSSTox and 59.5% have publically available structures. Compounds without a structure in DSSTox are currently having their structures registered. The structural data will be used to evaluate the predictive performance and applicable chemical domains of three QSAR models (TIMES, PROTOX, and TEST). Future work will combine the dataset with information from ToxCast assays, and using random forest modeling, assess whether ToxCast assays are useful in predicting acute oral toxicity. Pre

Xanthine oxidase inhibitors beyond allopurinol and febuxostat; an overview and selection of potential leads based on in silico calculated physico-chemical properties, predicted pharmacokinetics and toxicity.

PubMed

Šmelcerović, Andrija; Tomović, Katarina; Šmelcerović, Žaklina; Petronijević, Živomir; Kocić, Gordana; Tomašič, Tihomir; Jakopin, Žiga; Anderluh, Marko

2017-07-28

Xanthine oxidase (XO), a versatile metalloflavoprotein enzyme, catalyzes the oxidative hydroxylation of hypoxanthine and xanthine to uric acid in purine catabolism while simultaneously producing reactive oxygen species. Both lead to the gout-causing hyperuricemia and oxidative damage of the tissues where overactivity of XO is present. Over the past years, significant progress and efforts towards the discovery and development of new XO inhibitors have been made and we believe that not only experts in the field, but also general readership would benefit from a review that addresses this topic. Accordingly, the aim of this article was to overview and select the most potent recently reported XO inhibitors and to compare their structures, mechanisms of action, potency and effectiveness of their inhibitory activity, in silico calculated physico-chemical properties as well as predicted pharmacokinetics and toxicity. Derivatives of imidazole, 1,3-thiazole and pyrimidine proved to be more potent than febuxostat while also displaying/possessing favorable predicted physico-chemical, pharmacokinetic and toxicological properties. Although being structurally similar to febuxostat, these optimized inhibitors bear some structural freshness and could be adopted as hits for hit-to-lead development and further evaluation by in vivo studies towards novel drug candidates, and represent valuable model structures for design of novel XO inhibitors. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Molecular characterization of HIV-1 Nef and ACOT8 interaction: insights from in silico structural predictions and in vitro functional assays

NASA Astrophysics Data System (ADS)

Serena, Michela; Giorgetti, Alejandro; Busato, Mirko; Gasparini, Francesca; Diani, Erica; Romanelli, Maria Grazia; Zipeto, Donato

2016-03-01

HIV-1 Nef interacts with several cellular proteins, among which the human peroxisomal thioesterase 8 (ACOT8). This interaction may be involved in the endocytosis regulation of membrane proteins and might modulate lipid composition in membrane rafts. Nef regions involved in the interaction have been experimentally characterized, whereas structural details of the ACOT8 protein are unknown. The lack of structural information hampers the comprehension of the functional consequences of the complex formation during HIV-1 infection. We modelled, through in silico predictions, the ACOT8 structure and we observed a high charge complementarity between Nef and ACOT8 surfaces, which allowed the identification of the ACOT8 putative contact points involved in the interaction. The predictions were validated by in vitro assays through the development of ACOT8 deletion mutants. Coimmunoprecipitation and immunofluorescence analyses showed that ACOT8 Arg45-Phe55 and Arg86-Pro93 regions are involved in Nef association. In addition, K91S mutation abrogated the interaction with Nef, indicating that Lys91 plays a key role in the interaction. Finally, when associated with ACOT8, Nef may be preserved from degradation. These findings improve the comprehension of the association between HIV-1 Nef and ACOT8, helping elucidating the biological effect of their interaction.

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.

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

PubMed

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

2004-01-01

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

Unravelling the effects of mechanical physiological conditioning on cardiac adipose tissue-derived progenitor cells in vitro and in silico.

PubMed

Llucià-Valldeperas, Aida; Bragós, Ramon; Soler-Botija, Carolina; Roura, Santiago; Gálvez-Montón, Carolina; Prat-Vidal, Cristina; Perea-Gil, Isaac; Bayes-Genis, Antoni

2018-01-11

Mechanical conditioning is incompletely characterized for stimulating therapeutic cells within the physiological range. We sought to unravel the mechanism of action underlying mechanical conditioning of adipose tissue-derived progenitor cells (ATDPCs), both in vitro and in silico. Cardiac ATDPCs, grown on 3 different patterned surfaces, were mechanically stretched for 7 days at 1 Hz. A custom-designed, magnet-based, mechanical stimulator device was developed to apply ~10% mechanical stretching to monolayer cell cultures. Gene and protein analyses were performed for each cell type and condition. Cell supernatants were also collected to analyze secreted proteins and construct an artificial neural network. Gene and protein modulations were different for each surface pattern. After mechanostimulation, cardiac ATDPCs increased the expression of structural genes and there was a rising trend on cardiac transcription factors. Finally, secretome analyses revealed upregulation of proteins associated with both myocardial infarction and cardiac regeneration, such as regulators of the immune response, angiogenesis or cell adhesion. To conclude, mechanical conditioning of cardiac ATDPCs enhanced the expression of early and late cardiac genes in vitro. Additionally, in silico analyses of secreted proteins showed that mechanical stimulation of cardiac ATDPCs was highly associated with myocardial infarction and repair.

The Development of CK2 Inhibitors: From Traditional Pharmacology to in Silico Rational Drug Design

PubMed Central

Cozza, Giorgio

2017-01-01

Casein kinase II (CK2) is an ubiquitous and pleiotropic serine/threonine protein kinase able to phosphorylate hundreds of substrates. Being implicated in several human diseases, from neurodegeneration to cancer, the biological roles of CK2 have been intensively studied. Upregulation of CK2 has been shown to be critical to tumor progression, making this kinase an attractive target for cancer therapy. Several CK2 inhibitors have been developed so far, the first being discovered by “trial and error testing”. In the last decade, the development of in silico rational drug design has prompted the discovery, de novo design and optimization of several CK2 inhibitors, active in the low nanomolar range. The screening of big chemical libraries and the optimization of hit compounds by Structure Based Drug Design (SBDD) provide telling examples of a fruitful application of rational drug design to the development of CK2 inhibitors. Ligand Based Drug Design (LBDD) models have been also applied to CK2 drug discovery, however they were mainly focused on methodology improvements rather than being critical for de novo design and optimization. This manuscript provides detailed description of in silico methodologies whose applications to the design and development of CK2 inhibitors proved successful and promising. PMID:28230762

Isoquinoline Alkaloids from Erythrinapoeppigiana (Leguminosae) and Cytotoxic Activity Against Breast Cancer Cells Line MCF-7 In Silico

NASA Astrophysics Data System (ADS)

Herlina, T.; Mardianingrum, R.; Gaffar, S.; Supratman, U.

2017-02-01

Erythrinapoeppigiana(Leguminosae) is a higher plant that has been used as a folk for the treatment of infection, fever, and inflammation. In the course of our continuing search for novel cytotoxic compounds from genus Erythrina, the methanol extract of E. poeppigiana showed a significant cytotoxic activity against breast cancer cells line MCF-7 in silico. The compounds in methanol extract of the E. poeppigiana was separated using a bioassay-guided fractionation. By using a cytotoxic activity to follow separation, the methylene chloride was separated by several column chromatography techniques on silica gel and ODS to yield three active compounds (1-3). The chemical structures of active compounds were determined on the basis of spectroscopic evidence and comparison with those identical compounds that previously reported and identified as a 10,11-dihydroxyerysodine (1) 6,7-dihydro-17-hydroxyerysotrine (2) 6,7-dihydro-11-methoxyerysotrine (3). Compounds (1-3) showed cytotoxic activity inhibits EGFR 2 against breast cancer cell line MCF-7 in silico molecular docking method with bond Gibbs free energy (ΔG) (kcal/mol) and inhibition constants (Ki) (nM) of value (-8.61121, 4.84×10-7) (-8.1145, 1.12×10-6) and (-7.3394, 4.14×10-6), respectively.

In silico design of context-responsive mammalian promoters with user-defined functionality

PubMed Central

Gibson, Suzanne J.; Hatton, Diane

2017-01-01

Abstract Comprehensive de novo-design of complex mammalian promoters is restricted by unpredictable combinatorial interactions between constituent transcription factor regulatory elements (TFREs). In this study, we show that modular binding sites that do not function cooperatively can be identified by analyzing host cell transcription factor expression profiles, and subsequently testing cognate TFRE activities in varying homotypic and heterotypic promoter architectures. TFREs that displayed position-insensitive, additive function within a specific expression context could be rationally combined together in silico to create promoters with highly predictable activities. As TFRE order and spacing did not affect the performance of these TFRE-combinations, compositions could be specifically arranged to preclude the formation of undesirable sequence features. This facilitated simple in silico-design of promoters with context-required, user-defined functionalities. To demonstrate this, we de novo-created promoters for biopharmaceutical production in CHO cells that exhibited precisely designed activity dynamics and long-term expression-stability, without causing observable retroactive effects on cellular performance. The design process described can be utilized for applications requiring context-responsive, customizable promoter function, particularly where co-expression of synthetic TFs is not suitable. Although the synthetic promoter structure utilized does not closely resemble native mammalian architectures, our findings also provide additional support for a flexible billboard model of promoter regulation. PMID:28977454

Structural insight into the binding interactions of modeled structure of Arabidopsis thaliana urease with urea: an in silico study.

PubMed

Yata, Vinod Kumar; Thapa, Arun; Mattaparthi, Venkata Satish Kumar

2015-01-01

Urease (EC 3.5.1.5., urea amidohydrolase) catalyzes the hydrolysis of urea to ammonia and carbon dioxide. Urease is present to a greater abundance in plants and plays significant role related to nitrogen recycling from urea. But little is known about the structure and function of the urease derived from the Arabidopsis thaliana, the model system of choice for research in plant biology. In this study, a three-dimensional structural model of A. thaliana urease was constructed using computer-aided molecular modeling technique. The characteristic structural features of the modeled structure were then studied using atomistic molecular dynamics simulation. It was observed that the modeled structure was stable and regions between residues index (50-80, 500-700) to be significantly flexible. From the docking studies, we detected the possible binding interactions of modeled urease with urea. Ala399, Ile675, Thr398, and Thr679 residues of A. thaliana urease were observed to be significantly involved in binding with the substrate urea. We also compared the docking studies of ureases from other sources such as Canavalia ensiformis, Helicobacter pylori, and Bacillus pasteurii. In addition, we carried out mutation analysis to find the highly mutable amino acid residues of modeled A. thaliana urease. In this particular study, we observed Met485, Tyr510, Ser786, Val426, and Lys765 to be highly mutable amino acids. These results are significant for the mutagenesis analysis. As a whole, this study expounds the salient structural features as well the binding interactions of the modeled structure of A. thaliana urease.

Structural insight into the antagonistic action of diarylheptanoid on human estrogen receptor alpha.

PubMed

Geetha Rani, Yuvaraj; Lakshmi, Baddireddi Subhadra

2018-03-30

Estrogen receptor α (ER α) is an important therapeutic target in the regulation of ligand dependent signaling in breast cancer. The current study investigates the anti-estrogenic potential of the Diarylheptanoid, 5-hydroxy-7-(4-hydroxy-3 methoxyphenyl)-1-phenyl-3-heptanone (DAH) in silico. Rigid Docking analysis of DAH at the ligand binding domain (LBD) of ER α showed hydrogen bond interactions with Arg394 and Glu353 at the active site, similar to the positive controls 4-Hydroxy Tamoxifen (4-OHT) and Fulvestrant (FUL). The protein and the protein-DAH complexes were further analyzed using molecular dynamics simulations for a time scale of 50 ns using GROMACS. Root mean square fluctuation (RMSF) analysis showed large fluctuations at the N-terminal region of Helices (H) 3, 9 and at the C-terminal region of H11, which could be involved in the antagonistic conformational change. Interestingly, H12 appeared to move away from the ligand binding pocket and occupy the co-activator binding groove at the LBD of ER α. Secondary structure analysis of the protein upon binding of DAH and CUR showed structural change from α-helix to Turn conformation at H4. We hypothesize that this structural change at H4, similar to the positive control, could hinder the activity of AF-2 by blocking the binding of co-activator. These conformational changes in ER α indicate an anti-estrogenic and therapeutic potential of the DAH.

Genomic analysis of Staphylococcus phage Stau2 isolated from medical specimen.

PubMed

Hsieh, Sue-Er; Tseng, Yi-Hsiung; Lo, Hsueh-Hsia; Chen, Shui-Tu; Wu, Cheng-Nan

2016-02-01

Stau2 is a lytic myophage of Staphylococcus aureus isolated from medical specimen. Exhibiting a broad host range against S. aureus clinical isolates, Stau2 is potentially useful for topical phage therapy or as an additive in food preservation. In this study, Stau2 was firstly revealed to possess a circularly permuted linear genome of 133,798 bp, with low G + C content, containing 146 open reading frames, but encoding no tRNA. The genome is organized into several modules containing genes for packaging, structural proteins, replication/transcription and host-cell-lysis, with the structural proteins and DNA polymerase modules being organized similarly to that in Twort-like phages of Staphylococcus. With the encoded DNA replication genes, Stau2 can possibly use its own system for replication. In addition, analysis in silico found several introns in seven genes, including those involved in DNA metabolism, packaging, and structure, while one of them (helicase gene) is experimentally confirmed to undergo splicing. Furthermore, phylogenetic analysis suggested Stau2 to be most closely related to Staphylococcus phages SA11 and Remus, members of Twort-like phages. The results of sodium dodecyl sulfate polyacrylamide gel electrophoresis showed 14 structural proteins of Stau2 and N-terminal sequencing identified three of them. Importantly, this phage does not encode any proteins which are known or suspected to be involved in toxicity, pathogenicity, or antibiotic resistance. Therefore, further investigations of feasible therapeutic application of Stau2 are needed.

"Vibrational spectroscopic analysis and molecular docking studies of (E)-4-methoxy-N‧-(4-methylbenzylidene) benzohydrazide by DFT"

NASA Astrophysics Data System (ADS)

Maheswari, R.; Manjula, J.

2016-07-01

(E)-4-methoxy-N‧-(4-methylbenzylidene)benzohydrazide (4MN'MBH) a novel, organic, hydrazone Schiff base compound was synthesized and its structure was characterized by Fourier Transform Infrared (4000-400 cm-1), Fourier Transform Raman (3500-50 cm-1), Ultraviolet-Visible (200-800 nm) and 1H and 13C NMR spectroscopic analysis. Optimized molecular structure, vibrational frequencies and corresponding vibrational assignments regarding 4MN'MBH has become screened tentatively as well as hypothetically utilizing Gaussian09Wprogram package. Potential energy distributions of the normal modes of vibrations connected with vibrations are generally accomplished by applying VEDA program. Natural Bonding Orbital (NBO) assessment was completed with a reason to clarify charge transfer or conjugative interaction, the intra-molecular-hybridization and delocalization of electron density within the molecule. Electronic transitions were studied employing UV-Visible spectrum and the observed values were compared with theoretical values. 1H and13C NMR spectral assessment had been made with choosing structure property relationship by chemical shifts along with magnetic shielding effects of title compound. The first order hyperpolarizability (β0) and related properties (β, α0 and Δα) of 4MN'MBH were calculated. The computed first order hyperpolarizability commensurate with the documented worth of very similar structure and could be an interesting thing for more experiments on non linear optics. Molecular docking study has been performed by in silico method to analysis their antituberculosis aspects against Enoyl acyl carrier protein reductase (Mycobacterium tuberculosis InhA) protein.

GP0.4 from bacteriophage T7: in silico characterisation of its structure and interaction with E. coli FtsZ.

PubMed

Simpkin, Adam J; Rigden, Daniel J

2016-07-13

Proteins produced by bacteriophages can have potent antimicrobial activity. The study of phage-host interactions can therefore inform small molecule drug discovery by revealing and characterising new drug targets. Here we characterise in silico the predicted interaction of gene protein 0.4 (GP0.4) from the Escherichia coli (E. coli) phage T7 with E. coli filamenting temperature-sensitive mutant Z division protein (FtsZ). FtsZ is a tubulin homolog which plays a key role in bacterial cell division and that has been proposed as a drug target. Using ab initio, fragment assembly structure modelling, we predicted the structure of GP0.4 with two programs. A structure similarity-based network was used to identify a U-shaped helix-turn-helix candidate fold as being favoured. ClusPro was used to dock this structure prediction to a homology model of E. coli FtsZ resulting in a favourable predicted interaction mode. Alternative docking methods supported the proposed mode which offered an immediate explanation for the anti-filamenting activity of GP0.4. Importantly, further strong support derived from a previously characterised insertion mutation, known to abolish GP0.4 activity, that is positioned in close proximity to the proposed GP0.4/FtsZ interface. The mode of interaction predicted by bioinformatics techniques strongly suggests a mechanism through which GP0.4 inhibits FtsZ and further establishes the latter's druggable intrafilament interface as a potential drug target.

Multi-Layer Identification of Highly-Potent ABCA1 Up-Regulators Targeting LXRβ Using Multiple QSAR Modeling, Structural Similarity Analysis, and Molecular Docking.

PubMed

Chen, Meimei; Yang, Fafu; Kang, Jie; Yang, Xuemei; Lai, Xinmei; Gao, Yuxing

2016-11-29

In this study, in silico approaches, including multiple QSAR modeling, structural similarity analysis, and molecular docking, were applied to develop QSAR classification models as a fast screening tool for identifying highly-potent ABCA1 up-regulators targeting LXRβ based on a series of new flavonoids. Initially, four modeling approaches, including linear discriminant analysis, support vector machine, radial basis function neural network, and classification and regression trees, were applied to construct different QSAR classification models. The statistics results indicated that these four kinds of QSAR models were powerful tools for screening highly potent ABCA1 up-regulators. Then, a consensus QSAR model was developed by combining the predictions from these four models. To discover new ABCA1 up-regulators at maximum accuracy, the compounds in the ZINC database that fulfilled the requirement of structural similarity of 0.7 compared to known potent ABCA1 up-regulator were subjected to the consensus QSAR model, which led to the discovery of 50 compounds. Finally, they were docked into the LXRβ binding site to understand their role in up-regulating ABCA1 expression. The excellent binding modes and docking scores of 10 hit compounds suggested they were highly-potent ABCA1 up-regulators targeting LXRβ. Overall, this study provided an effective strategy to discover highly potent ABCA1 up-regulators.

UV-vis degradation of α-tocopherol in a model system and in a cosmetic emulsion-Structural elucidation of photoproducts and toxicological consequences.

PubMed

De Vaugelade, Ségolène; Nicol, Edith; Vujovic, Svetlana; Bourcier, Sophie; Pirnay, Stéphane; Bouchonnet, Stéphane

2017-09-29

The UV-vis photodegradation of α-tocopherol was investigated in a model system and in a cosmetic emulsion. Both gas chromatography coupled with tandem mass spectrometry (GC-MS/MS) and high performance liquid chromatography coupled with ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry (LC-UHR-MS) were used for photoproducts structural identification. Nine photoproduct families were detected and identified based on their mass spectra and additional experiments with α-tocopherol-d 9 ; phototransformation mechanisms were postulated to rationalize their formation under irradiation. In silico QSAR (Quantitative Structure Activity Relationship) toxicity predictions were conducted with the Toxicity Estimation Software Tool (T.E.S.T.). Low oral rat LD50 values of 466.78mgkg -1 and 467.9mgkg -1 were predicted for some photoproducts, indicating a potential toxicity more than 10 times greater that of α-tocopherol (5742.54mgkg -1 ). In vitro assays on Vibrio fischeri bacteria showed that the global ecotoxicity of the α-tocopherol solution significantly increases with irradiation time. One identified product should contribute to this ecotoxicity enhancement since in silico estimations for D. magna provide a LC50 value 4 times lower than that of the parent molecule. Copyright © 2017. Published by Elsevier B.V.

Bio-AIMS Collection of Chemoinformatics Web Tools based on Molecular Graph Information and Artificial Intelligence Models.

PubMed

Munteanu, Cristian R; Gonzalez-Diaz, Humberto; Garcia, Rafael; Loza, Mabel; Pazos, Alejandro

2015-01-01

The molecular information encoding into molecular descriptors is the first step into in silico Chemoinformatics methods in Drug Design. The Machine Learning methods are a complex solution to find prediction models for specific biological properties of molecules. These models connect the molecular structure information such as atom connectivity (molecular graphs) or physical-chemical properties of an atom/group of atoms to the molecular activity (Quantitative Structure - Activity Relationship, QSAR). Due to the complexity of the proteins, the prediction of their activity is a complicated task and the interpretation of the models is more difficult. The current review presents a series of 11 prediction models for proteins, implemented as free Web tools on an Artificial Intelligence Model Server in Biosciences, Bio-AIMS (http://bio-aims.udc.es/TargetPred.php). Six tools predict protein activity, two models evaluate drug - protein target interactions and the other three calculate protein - protein interactions. The input information is based on the protein 3D structure for nine models, 1D peptide amino acid sequence for three tools and drug SMILES formulas for two servers. The molecular graph descriptor-based Machine Learning models could be useful tools for in silico screening of new peptides/proteins as future drug targets for specific treatments.

Discovery of Dual ETA/ETB Receptor Antagonists from Traditional Chinese Herbs through in Silico and in Vitro Screening

PubMed Central

Wang, Xing; Zhang, Yuxin; Liu, Qing; Ai, Zhixin; Zhang, Yanling; Xiang, Yuhong; Qiao, Yanjiang

2016-01-01

Endothelin-1 receptors (ETAR and ETBR) act as a pivotal regulator in the biological effects of ET-1 and represent a potential drug target for the treatment of multiple cardiovascular diseases. The purpose of the study is to discover dual ETA/ETB receptor antagonists from traditional Chinese herbs. Ligand- and structure-based virtual screening was performed to screen an in-house database of traditional Chinese herbs, followed by a series of in vitro bioassay evaluation. Aristolochic acid A (AAA) was first confirmed to be a dual ETA/ETB receptor antagonist based intracellular calcium influx assay and impedance-based assay. Dose-response curves showed that AAA can block both ETAR and ETBR with IC50 of 7.91 and 7.40 μM, respectively. Target specificity and cytotoxicity bioassay proved that AAA is a selective dual ETA/ETB receptor antagonist and has no significant cytotoxicity on HEK293/ETAR and HEK293/ETBR cells within 24 h. It is a feasible and effective approach to discover bioactive compounds from traditional Chinese herbs using in silico screening combined with in vitro bioassay evaluation. The structural characteristic of AAA for its activity was especially interpreted, which could provide valuable reference for the further structural modification of AAA. PMID:26999111

Modeling of Fibrin Gels Based on Confocal Microscopy and Light-Scattering Data

PubMed Central

Magatti, Davide; Molteni, Matteo; Cardinali, Barbara; Rocco, Mattia; Ferri, Fabio

2013-01-01

Fibrin gels are biological networks that play a fundamental role in blood coagulation and other patho/physiological processes, such as thrombosis and cancer. Electron and confocal microscopies show a collection of fibers that are relatively monodisperse in diameter, not uniformly distributed, and connected at nodal points with a branching order of ∼3–4. Although in the confocal images the hydrated fibers appear to be quite straight (mass fractal dimension Dm = 1), for the overall system 1

Enhancing bioactive peptide release and identification using targeted enzymatic hydrolysis of milk proteins.

PubMed

Nongonierma, Alice B; FitzGerald, Richard J

2018-06-01

Milk proteins have been extensively studied for their ability to yield a range of bioactive peptides following enzymatic hydrolysis/digestion. However, many hurdles still exist regarding the widespread utilization of milk protein-derived bioactive peptides as health enhancing agents for humans. These mostly arise from the fact that most milk protein-derived bioactive peptides are not highly potent. In addition, they may be degraded during gastrointestinal digestion and/or have a low intestinal permeability. The targeted release of bioactive peptides during the enzymatic hydrolysis of milk proteins may allow the generation of particularly potent bioactive hydrolysates and peptides. Therefore, the development of milk protein hydrolysates capable of improving human health requires, in the first instance, optimized targeted release of specific bioactive peptides. The targeted hydrolysis of milk proteins has been aided by a range of in silico tools. These include peptide cutters and predictive modeling linking bioactivity to peptide structure [i.e., molecular docking, quantitative structure activity relationship (QSAR)], or hydrolysis parameters [design of experiments (DOE)]. Different targeted enzymatic release strategies employed during the generation of milk protein hydrolysates are reviewed herein and their limitations are outlined. In addition, specific examples are provided to demonstrate how in silico tools may help in the identification and discovery of potent milk protein-derived peptides. It is anticipated that the development of novel strategies employing a range of in silico tools may help in the generation of milk protein hydrolysates containing potent and bioavailable peptides, which in turn may be used to validate their health promoting effects in humans. Graphical abstract The targeted enzymatic hydrolysis of milk proteins may allow the generation of highly potent and bioavailable bioactive peptides.

Computer Simulation of Embryonic Systems: What can a virtual embryo teach us about developmental toxicity? (LA Conference on Computational Biology & Bioinformatics)

EPA Science Inventory

This presentation will cover work at EPA under the CSS program for: (1) Virtual Tissue Models built from the known biology of an embryological system and structured to recapitulate key cell signals and responses; (2) running the models with real (in vitro) or synthetic (in silico...

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

Structural and biophysical properties of h-FANCI ARM repeat protein.

PubMed

Siddiqui, Mohd Quadir; Choudhary, Rajan Kumar; Thapa, Pankaj; Kulkarni, Neha; Rajpurohit, Yogendra S; Misra, Hari S; Gadewal, Nikhil; Kumar, Satish; Hasan, Syed K; Varma, Ashok K

2017-11-01

Fanconi anemia complementation groups - I (FANCI) protein facilitates DNA ICL (Inter-Cross-link) repair and plays a crucial role in genomic integrity. FANCI is a 1328 amino acids protein which contains armadillo (ARM) repeats and EDGE motif at the C-terminus. ARM repeats are functionally diverse and evolutionarily conserved domain that plays a pivotal role in protein-protein and protein-DNA interactions. Considering the importance of ARM repeats, we have explored comprehensive in silico and in vitro approach to examine folding pattern. Size exclusion chromatography, dynamic light scattering (DLS) and glutaraldehyde crosslinking studies suggest that FANCI ARM repeat exist as monomer as well as in oligomeric forms. Circular dichroism (CD) and fluorescence spectroscopy results demonstrate that protein has predominantly α- helices and well-folded tertiary structure. DNA binding was analysed using electrophoretic mobility shift assay by autoradiography. Temperature-dependent CD, Fluorescence spectroscopy and DLS studies concluded that protein unfolds and start forming oligomer from 30°C. The existence of stable portion within FANCI ARM repeat was examined using limited proteolysis and mass spectrometry. The normal mode analysis, molecular dynamics and principal component analysis demonstrated that helix-turn-helix (HTH) motif present in ARM repeat is highly dynamic and has anti-correlated motion. Furthermore, FANCI ARM repeat has HTH structural motif which binds to double-stranded DNA.

In Silico Analysis of Usher Encoding Genes in Klebsiella pneumoniae and Characterization of Their Role in Adhesion and Colonization

PubMed Central

Khater, Fida; Balestrino, Damien; Charbonnel, Nicolas; Dufayard, Jean François; Brisse, Sylvain; Forestier, Christiane

2015-01-01

Chaperone/usher (CU) assembly pathway is used by a wide range of Enterobacteriaceae to assemble adhesive surface structures called pili or fimbriae that play a role in bacteria-host cell interactions. In silico analysis revealed that the genome of Klebsiella pneumoniae LM21 harbors eight chromosomal CU loci belonging to γκп and ϭ clusters. Of these, only two correspond to previously described operons, namely type 1 and type 3-encoding operons. Isogenic usher deletion mutants of K. pneumoniae LM21 were constructed for each locus and their role in adhesion to animal (Intestine 407) and plant (Arabidopsis thaliana) cells, biofilm formation and murine intestinal colonization was investigated. Type 3 pili usher deleted mutant was impaired in all assays, whereas type 1 pili usher deleted mutant only showed attenuation in adhesion to plant cells and in intestinal colonization. The LM21ΔkpjC mutant was impaired in its capacity to adhere to Arabidopsis cells and to colonize the murine intestine, either alone or in co-inoculation experiments. Deletion of LM21kpgC induced a significant decrease in biofilm formation, in adhesion to animal cells and in colonization of the mice intestine. The LM21∆kpaC and LM21∆kpeC mutants were only attenuated in biofilm formation and the adhesion abilities to Arabidopsis cells, respectively. No clear in vitro or in vivo effect was observed for LM21∆kpbC and LM21∆kpdC mutants. The multiplicity of CU loci in K. pneumoniae genome and their specific adhesion pattern probably reflect the ability of the bacteria to adhere to different substrates in its diverse ecological niches. PMID:25751658

In silico analysis of the polygalacturonase inhibiting protein 1 from apple, Malus domestica.

PubMed

Matsaunyane, Lerato Bt; Oelofse, Dean; Dubery, Ian A

2015-03-11

The Malus domestica polygalacturonase inhibiting protein 1 (MdPGIP1) gene, encoding the M. domestica polygalacturonase inhibiting protein 1 (MdPGIP1), was isolated from the Granny Smith apple cultivar (GenBank accession no. DQ185063). The gene was used to transform tobacco and potato for enhanced resistance against fungal diseases. Analysis of the MdPGIP1 nucleotide sequence revealed that the gene comprises 993 nucleotides that encode a 330 amino acid polypeptide. In silico characterization of the MdPGIP1 polypeptide revealed domains typical of PGIP proteins, which include a 24 amino acid putative signal peptide, a potential cleavage site [Alanine-Leucine-Serine (ALS)] for the signal peptide, a 238 amino acid leucine-rich repeat (LRR) domain, a 46 amino acid N-terminal domain and a 22 amino acid C-terminal domain. The hydropathic evaluation of MdPGIP1 indicated a repetitive hydrophobic motif in the LRR domain and a hydrophilic surface area consistent with a globular protein. The typical consensus glycosylation sequence of Asn-X-Ser/Thr was identified in MdPGIP1, indicating potential N-linked glycosylation of MdPGIP1. The molecular mass of non-glycosylated MdPGIP1 was calculated as 36.615 kDa and the theoretical isoelectric point as 6.98. Furthermore, the secondary and tertiary structure of MdPGIP1 was modelled, and revealed that MdPGIP1 is a curved and elongated molecule that contains sheet B1, sheet B2 and 310-helices on its LRR domain. The overall properties of the MdPGIP1 protein is similar to that of the prototypical Phaseolus vulgaris PGIP 2 (PvPGIP2), and the detected differences supported its use in biotechnological applications as an inhibitor of targeted fungal polygalacturonases (PGs).

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

PubMed Central

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

2012-01-01

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

The effects of plant extracts on microbial community structure in a rumen-simulating continuous-culture system as revealed by molecular profiling.

PubMed

Ferme, D; Banjac, M; Calsamiglia, S; Busquet, M; Kamel, C; Avgustin, G

2004-01-01

An in vitro study in dual-flow continuous-culture fermentors was conducted with two different concentrations of monensin, cinnamaldehyde or garlic extract added to 1:1 forage-to-concentrate diet in order to determine their effects on selected rumen bacterial populations. Samples were subjected to total DNA extraction, restriction analysis of PCR amplified parts of 16S rRNA genes (ARDRA) and subsequent analysis of the restriction profiles by lab-on-chip technology with the Agilent's Bioanalyser 2100. Eub338-BacPre primer pair was used to select for the bacteria from the genera Bacteroides, Porphyromonas and Prevotella, especially the latter representing the dominant Gram-negative bacterial population in the rumen. Preliminary results of HaeIII restriction analysis show that the effects of monensin, cinnamaldehyde and garlic extract on the BacPre targeted ruminal bacteria are somewhat different in regard to targeted populations and to the nature of the effect. Garlic extract was found to trigger the most intensive changes in the structure of the BacPre targeted population. Comparison of the in silico restriction analysis of BacPre sequences deposited in different DNA databanks and of the results of performed amplified ribosomal DNA restriction analysis showed differences between the predicted and obtained HaeIII restriction profiles, and suggested the presence of novel, still unknown Prevotella populations in studied samples.

Structural impact analysis of missense SNPs present in the uroguanylin gene by long-term molecular dynamics simulations.

PubMed

Marcolino, Antonio C S; Porto, William F; Pires, Állan S; Franco, Octavio L; Alencar, Sérgio A

2016-12-07

The guanylate cyclase activator 2B, also known as uroguanylin, is part of the guanylin peptide family, which includes peptides such as guanylin and lymphoguanylin. The guanylin peptides could be related to sodium absorption inhibition and water secretion induction and their dysfunction may be related to various pathologies such as chronic renal failure, congestive heart failure and nephrotic syndrome. Besides, uroguanylin point mutations have been associated with essential hypertension. However, currently there are no studies on the impact of missense SNPs on uroguanylin structure. This study applied in silico SNP impact prediction tools to evaluate the impact of uroguanylin missense SNPs and to filter those considered as convergent deleterious, which were then further analyzed through long-term molecular dynamics simulations of 1μs of duration. The simulations suggested that all missense SNPs considered as convergent deleterious caused some kind of structural change to the uroguanylin peptide. Additionally, four of these SNPs were also shown to cause modifications in peptide flexibility, possibly resulting in functional changes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Thermophysical and structural studies on some glass-ceramics and role of nano size crystallites

NASA Astrophysics Data System (ADS)

Kothiyal, G. P.; Arvind, A.; Kumar, Rakesh; Dixit, Anupam; Sharma, Kuldeep; Goswami, Madhumita

2009-07-01

In this paper, we present some studies on structure and thermophysical properties of glass and glass-ceramics with possible bio-medical and sealing applications. The glass-ceramics prepared for bio-medical applications include phosphate as well as silico-phosphate compositions. In vitro bio-compatibility/activity of these materials is discussed. The glass-ceramics used for the sealing application are lithium aluminium silicate (LAS) and lithium zinc silicate (LZS). The phase formation and some aspects of thermophysical properties and sealing are discussed.

Structural and mechanistic analysis of engineered trichodiene synthase enzymes from Trichoderma harzianum: towards higher catalytic activities empowering sustainable agriculture.

PubMed

Kumari, Indu; Chaudhary, Nitika; Sandhu, Padmani; Ahmed, Mushtaq; Akhter, Yusuf

2016-06-01

Trichoderma spp. are well-known bioagents for the plant growth promotion and pathogen suppression. The beneficial activities of the fungus Trichoderma spp. are attributed to their ability to produce and secrete certain secondary metabolites such as trichodermin that belongs to trichothecene family of molecules. The initial steps of trichodermin biosynthetic pathway in Trichoderma are similar to the trichothecenes from Fusarium sporotrichioides. Trichodiene synthase (TS) encoded by tri5 gene in Trichoderma catalyses the conversion of farnesyl pyrophosphate to trichodiene as reported earlier. In this study, we have carried out a comprehensive comparative sequence and structural analysis of the TS, which revealed the conserved residues involved in catalytic activity of the protein. In silico, modelled tertiary structure of TS protein showed stable structural behaviour during simulations. Two single-substitution mutants, i.e. D109E, D248Y and one double-substitution mutant (D109E and D248Y) of TS with potentially higher activities are screened out. The mutant proteins showed more stability than the wild type, an increased number of electrostatic interactions and better binding energies with the ligand, which further elucidates the amino acid residues involved in the reaction mechanism. These results will lead to devise strategies for higher TS activity to ultimately enhance the trichodermin production by Trichoderma spp. for its better exploitation in the sustainable agricultural practices.

Exploring the science of thinking independently together: Faraday Discussion Volume 204 - Complex Molecular Surfaces and Interfaces, Sheffield, UK, July 2017.

PubMed

Samperi, M; Hirsch, B E; Diaz Fernandez, Y A

2017-11-23

The 2017 Faraday Discussion on Complex Molecular Surfaces and Interfaces brought together theoreticians and experimentalists from both physical and chemical backgrounds to discuss the relevant applied and fundamental research topics within the broader field of chemical surface analysis and characterization. Main discussion topics from the meeting included the importance of "disordered" two-dimensional (2D) molecular structures and the utility of kinetically trapped states. An emerging need for new experimental tools to address dynamics and kinetic pathways involved in self-assembled systems, as well as the future prospects and current limitations of in silico studies were also discussed. The following article provides a brief overview of the work presented and the challenges discussed during the meeting.

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.

Novel α-L-arabinofuranosidase from Cellulomonas fimi ATCC 484 and its substrate-specificity analysis with the aid of computer.

PubMed

Yang, Ying; Zhang, Lujia; Guo, Mingrong; Sun, Jiaqi; Matsukawa, Shingo; Xie, Jingli; Wei, Dongzhi

2015-04-15

In the process of gene mining for novel α-L-arabinofuranosidases (AFs), the gene Celf_3321 from Cellulomonas fimi ATCC 484 encodes an AF, termed as AbfCelf, with potent activity, 19.4 U/mg under the optimum condition, pH 6.0 and 40 °C. AbfCelf can hydrolyze α-1,5-linked oligosaccharides, sugar beet arabinan, linear 1,5-α-arabinan, and wheat flour arabinoxylan, which is partly different from some previously well-characterized GH 51 AFs. The traditional substrate-specificity analysis for AFs is labor-consuming and money costing, because the substrates include over 30 kinds of various 4-nitrophenol (PNP)-glycosides, oligosaccharides, and polysaccharides. Hence, a preliminary structure and mechanism based method was applied for substrate-specificity analysis. The binding energy (ΔG, kcal/mol) obtained by docking suggested the reaction possibility and coincided with the experimental results. AbfA crystal 1QW9 was used to test the rationality of docking method in simulating the interaction between enzyme and substrate, as well the credibility of the substrate-specificity analysis method in silico.

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.

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.

Bitterness prediction in-silico: A step towards better drugs.

PubMed

Bahia, Malkeet Singh; Nissim, Ido; Niv, Masha Y

2018-02-05

Bitter taste is innately aversive and thought to protect against consuming poisons. Bitter taste receptors (Tas2Rs) are G-protein coupled receptors, expressed both orally and extra-orally and proposed as novel targets for several indications, including asthma. Many clinical drugs elicit bitter taste, suggesting the possibility of drugs re-purposing. On the other hand, the bitter taste of medicine presents a major compliance problem for pediatric drugs. Thus, efficient tools for predicting, measuring and masking bitterness of active pharmaceutical ingredients (APIs) are required by the pharmaceutical industry. Here we highlight the BitterDB database of bitter compounds and survey the main computational approaches to prediction of bitter taste based on compound's chemical structure. Current in silico bitterness prediction methods provide encouraging results, can be constantly improved using growing experimental data, and present a reliable and efficient addition to the APIs development toolbox. Copyright © 2017 Elsevier B.V. All rights reserved.

Molecular evolution of gas cavity in [NiFeSe] hydrogenases resurrected in silico

NASA Astrophysics Data System (ADS)

Tamura, Takashi; Tsunekawa, Naoki; Nemoto, Michiko; Inagaki, Kenji; Hirano, Toshiyuki; Sato, Fumitoshi

2016-01-01

Oxygen tolerance of selenium-containing [NiFeSe] hydrogenases (Hases) is attributable to the high reducing power of the selenocysteine residue, which sustains the bimetallic Ni-Fe catalytic center in the large subunit. Genes encoding [NiFeSe] Hases are inherited by few sulphate-reducing δ-proteobacteria globally distributed under various anoxic conditions. Ancestral sequences of [NiFeSe] Hases were elucidated and their three-dimensional structures were recreated in silico using homology modelling and molecular dynamic simulation, which suggested that deep gas channels gradually developed in [NiFeSe] Hases under absolute anaerobic conditions, whereas the enzyme remained as a sealed edifice under environmental conditions of a higher oxygen exposure risk. The development of a gas cavity appears to be driven by non-synonymous mutations, which cause subtle conformational changes locally and distantly, even including highly conserved sequence regions.

Virtual Interactomics of Proteins from Biochemical Standpoint

PubMed Central

Kubrycht, Jaroslav; Sigler, Karel; Souček, Pavel

2012-01-01

Virtual interactomics represents a rapidly developing scientific area on the boundary line of bioinformatics and interactomics. Protein-related virtual interactomics then comprises instrumental tools for prediction, simulation, and networking of the majority of interactions important for structural and individual reproduction, differentiation, recognition, signaling, regulation, and metabolic pathways of cells and organisms. Here, we describe the main areas of virtual protein interactomics, that is, structurally based comparative analysis and prediction of functionally important interacting sites, mimotope-assisted and combined epitope prediction, molecular (protein) docking studies, and investigation of protein interaction networks. Detailed information about some interesting methodological approaches and online accessible programs or databases is displayed in our tables. Considerable part of the text deals with the searches for common conserved or functionally convergent protein regions and subgraphs of conserved interaction networks, new outstanding trends and clinically interesting results. In agreement with the presented data and relationships, virtual interactomic tools improve our scientific knowledge, help us to formulate working hypotheses, and they frequently also mediate variously important in silico simulations. PMID:22928109

Hairpin structures with conserved sequence motifs determine the 3' ends of non-polyadenylated invertebrate iridovirus transcripts.

PubMed

İnce, İkbal Agah; Pijlman, Gorben P; Vlak, Just M; van Oers, Monique M

2017-11-01

Previously, we observed that the transcripts of Invertebrate iridescent virus 6 (IIV6) are not polyadenylated, in line with the absence of canonical poly(A) motifs (AATAAA) downstream of the open reading frames (ORFs) in the genome. Here, we determined the 3' ends of the transcripts of fifty-four IIV6 virion protein genes in infected Drosophila Schneider 2 (S2) cells. By using ligation-based amplification of cDNA ends (LACE) it was shown that the IIV6 mRNAs often ended with a CAUUA motif. In silico analysis showed that the 3'-untranslated regions of IIV6 genes have the ability to form hairpin structures (22-56 nt in length) and that for about half of all IIV6 genes these 3' sequences contained complementary TAATG and CATTA motifs. We also show that a hairpin in the 3' flanking region with conserved sequence motifs is a conserved feature in invertebrate-infecting iridoviruses (genus Iridovirus and Chloriridovirus). Copyright © 2017 Elsevier Inc. All rights reserved.

In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design.

PubMed

Porto, William F; Irazazabal, Luz; Alves, Eliane S F; Ribeiro, Suzana M; Matos, Carolina O; Pires, Állan S; Fensterseifer, Isabel C M; Miranda, Vivian J; Haney, Evan F; Humblot, Vincent; Torres, Marcelo D T; Hancock, Robert E W; Liao, Luciano M; Ladram, Ali; Lu, Timothy K; de la Fuente-Nunez, Cesar; Franco, Octavio L

2018-04-16

Plants are extensively used in traditional medicine, and several plant antimicrobial peptides have been described as potential alternatives to conventional antibiotics. However, after more than four decades of research no plant antimicrobial peptide is currently used for treating bacterial infections, due to their length, post-translational modifications or  high dose requirement for a therapeutic effect . Here we report the design of antimicrobial peptides derived from a guava glycine-rich peptide using a genetic algorithm. This approach yields guavanin peptides, arginine-rich α-helical peptides that possess an unusual hydrophobic counterpart mainly composed of tyrosine residues. Guavanin 2 is characterized as a prototype peptide in terms of structure and activity. Nuclear magnetic resonance analysis indicates that the peptide adopts an α-helical structure in hydrophobic environments. Guavanin 2 is bactericidal at low concentrations, causing membrane disruption and triggering hyperpolarization. This computational approach for the exploration of natural products could be used to design effective peptide antibiotics.

G12V Kras mutations in cervical cancer under virtual microscope of molecular dynamics simulations.

PubMed

Chen, X P; Xu, W H; Xu, D F; Fu, S M; Ma, Z C

2016-01-01

Kras mutations and cancers are common and their role in the progression of cancer is well known and elucidated. The present work is searching for the most deleterious mutation of the four found at codon 12 and 13 of Kras in cervical cancers using prediction servers; different servers were used to look into different factors that govern the protein function. The in silico results predicted G12V to be the most devastating; this particular mutation was then subjected to molecular dynamics simulation (MDS) for further analysis. The authors' approach of MDSs helped them to place the native and mutant structure under virtual microscope and observe their dynamics over time. The results generated are enlightening the effect of G12V variation on the dynamics of Kras. The structural variation between the native and mutant Kras over 50 nanoseconds (ns) run varied at every parameter checked and the results are in excellent agreement with the available experimental data.

Comprehensive Analysis of a Vibrio parahaemolyticus Strain Extracellular Serine Protease VpSP37

PubMed Central

Bennici, Carmelo; Quatrini, Paola; Catania, Valentina; Mazzola, Salvatore; Ghersi, Giulio; Cuttitta, Angela

2015-01-01

Proteases play an important role in the field of tissue dissociation combined with regenerative medicine. During the years new sources of proteolytic enzymes have been studied including proteases from different marine organisms both eukaryotic and prokaryotic. Herein we have purified a secreted component of an isolate of Vibrio parahaemolyticus, with electrophoretic mobilities corresponding to 36 kDa, belonging to the serine proteases family. Sequencing of the N-terminus enabled the in silico identification of the whole primary structure consisting of 345 amino acid residues with a calculated molecular mass of 37.4 KDa. The purified enzyme, named VpSP37, contains a Serine protease domain between residues 35 and 276 and a canonical Trypsin/Chimotrypsin 3D structure. Functional assays were performed to evaluate protease activity of purified enzyme. Additionally the performance of VpSP37 was evaluated in tissue dissociations experiments and the use of such enzyme as a component of enzyme blend for tissue dissociation procedures is strongly recommended. PMID:26162075

A novel piperazine linked β-amino alcohols bearing a benzosuberone scaffolds as anti-proliferative agents.

PubMed

Vanguru, Sowmya; Jilla, Lavanya; Sajja, Yasodakrishna; Bantu, Rajashaker; Nagarapu, Lingaiah; Nanubolu, Jagadeesh Babu; Bhaskar, Bala; Jain, Nishant; Sivan, Sreekanth; Manga, Vijjulatha

2017-02-15

A new series of 1-((9-chloro-2,3-dimethyl-6,7-dihydro-5H-benzo[7]annulen-8-yl)methoxy)-3-(4-phenylpiperzin-1-yl) propan-2-ols (6a-k) have been designed, synthesized and their structures were established by spectroscopic data (FT-IR, 1 H NMR, 13 C NMR, HRMS) and further confirmed by X-ray analysis. The newly synthesized compounds 6a-k were evaluated for their in vitro anti-proliferative activity against four cancer cell lines such as HeLa (cervical), MDA-MB-231 (breast), A549 (lung) and MIAPACA (pancreatic). Among the compounds tested, the compound 6e displayed most potent activity against four cancer cell lines with GI 50 values ranging from 0.010 to 0.097μM. The structure and anti-proliferative activity relationship was further supported by in silico molecular docking study of the active compounds against Colchicine binding site of β-tubulin. Copyright © 2017 Elsevier Ltd. All rights reserved.

The role of protein plasticity in computational rationalization studies on regioselectivity in testosterone hydroxylation by cytochrome P450 BM3 mutants.

PubMed

de Beer, Stephanie B A; van Bergen, Laura A H; Keijzer, Karlijn; Rea, Vanina; Venkataraman, Harini; Guerra, Celia Fonseca; Bickelhaupt, F Matthias; Vermeulen, Nico P E; Commandeur, Jan N M; Geerke, Daan P

2012-02-01

Recently, it was found that mutations in the binding cavity of drug-metabolizing Cytochrome P450 BM3 mutants can result in major changes in regioselectivity in testosterone (TES) hydroxylation. In the current work, we report the intrinsic reactivity of TES' C-H bonds and our attempts to rationalize experimentally observed changes in TES hydroxylation using a protein structure-based in silico approach, by setting up and employing a combined Molecular Dynamics (MD) and ligand docking approach to account for the flexibility and plasticity of BM3 mutants. Using this approach, about 100,000 TES binding poses were obtained per mutant. The predicted regioselectivity in TES hydroxylation by the mutants was found to be in disagreement with experiment. As revealed in a detailed structural analysis of the obtained docking poses, this disagreement is due to limitations in correctly scoring hydrogen-bonding and steric interactions with specific active-site residues, which could explain the experimentally observed trends in regioselectivity in TES hydroxylation.

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

Knowledge representation in metabolic pathway databases.

PubMed

Stobbe, Miranda D; Jansen, Gerbert A; Moerland, Perry D; van Kampen, Antoine H C

2014-05-01

The accurate representation of all aspects of a metabolic network in a structured format, such that it can be used for a wide variety of computational analyses, is a challenge faced by a growing number of researchers. Analysis of five major metabolic pathway databases reveals that each database has made widely different choices to address this challenge, including how to deal with knowledge that is uncertain or missing. In concise overviews, we show how concepts such as compartments, enzymatic complexes and the direction of reactions are represented in each database. Importantly, also concepts which a database does not represent are described. Which aspects of the metabolic network need to be available in a structured format and to what detail differs per application. For example, for in silico phenotype prediction, a detailed representation of gene-protein-reaction relations and the compartmentalization of the network is essential. Our analysis also shows that current databases are still limited in capturing all details of the biology of the metabolic network, further illustrated with a detailed analysis of three metabolic processes. Finally, we conclude that the conceptual differences between the databases, which make knowledge exchange and integration a challenge, have not been resolved, so far, by the exchange formats in which knowledge representation is standardized.

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.

In silico analyses of structural and allergenicity features of sapodilla (Manilkara zapota) acidic thaumatin-like protein in comparison with allergenic plant TLPs.

PubMed

Ashok Kumar, Hassan G; Venkatesh, Yeldur P

2014-02-01

Thaumatin-like proteins (TLPs) belong to the pathogenesis-related family (PR-5) of plant defense proteins. TLPs from only 32 plant genera have been identified as pollen or food allergens. IgE epitopes on allergens play a central role in food allergy by initiating cross-linking of specific IgE on basophils/mast cells. A comparative analysis of pollen- and food-allergenic TLPs is lacking. The main objective of this investigation was to study the structural and allergenicity features of sapodilla (Manilkara zapota) acidic TLP (TLP 1) by in silico methods. The allergenicity prediction of composite sequence of sapodilla TLP 1 (NCBI B3EWX8.1, G5DC91.1) was performed using FARRP, Allermatch and Evaller web tools. A homology model of the protein was generated using banana TLP template (1Z3Q) by HHPRED-MODELLER. B-cell linear epitope prediction was performed using BCpreds and BepiPred. Sapodilla TLP 1 matched significantly with allergenic TLPs from olive, kiwi, bell pepper and banana. IgE epitope prediction as performed using AlgPred indicated the presence of 2 epitopes (epitope 1: residues 36-48; epitope 2: residues 51-63), and a comprehensive analysis of all allergenic TLPs displayed up to 3 additional epitopes on other TLPs. It can be inferred from these analyses that plant allergenic TLPs generally carry 2-3 IgE epitopes. ClustalX alignments of allergenic TLPs indicate that IgE epitopes 1 and 2 are common in food allergenic TLPs, and IgE epitopes 2 and 3 are common in pollen allergenic TLPs; IgE epitope 2 overlaps with a portion of the thaumatin family signature. The secondary structural elements of TLPs vary markedly in regions 1 and 2 which harbor all the predicted IgE epitopes in all food and pollen TLPs in either of the region. Further, based on the number of IgE epitopes, food TLPs are grouped into rosid and non-rosid clades. The number and distribution of the predicted IgE epitopes among the allergenic TLPs may explain the specificity of food or pollen allergy as well as the varied degree of cross-reactivity among plant foods and/or pollens. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

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

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

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.

Promiscuous histone mis-assembly is actively prevented by chaperones | Center for Cancer Research

Cancer.gov

About the Cover Chaperone HJURP drives the proper loading of protein CENP-A to the centromere of a chromosome. The effect of HJURP on CENP-A's structural dynamics are observed and explained using dual-resolution in silico simulations, while in vivo experiments demonstrate how CENP-A mutations influence its specific localization in human cells. Abstract

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

PubMed

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

2018-05-29

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

Medium-sized tandem repeats represent an abundant component of the Drosophila virilis genome.

PubMed

Abdurashitov, Murat A; Gonchar, Danila A; Chernukhin, Valery A; Tomilov, Victor N; Tomilova, Julia E; Schostak, Natalia G; Zatsepina, Olga G; Zelentsova, Elena S; Evgen'ev, Michael B; Degtyarev, Sergey K H

2013-11-09

Previously, we developed a simple method for carrying out a restriction enzyme analysis of eukaryotic DNA in silico, based on the known DNA sequences of the genomes. This method allows the user to calculate lengths of all DNA fragments that are formed after a whole genome is digested at the theoretical recognition sites of a given restriction enzyme. A comparison of the observed peaks in distribution diagrams with the results from DNA cleavage using several restriction enzymes performed in vitro have shown good correspondence between the theoretical and experimental data in several cases. Here, we applied this approach to the annotated genome of Drosophila virilis which is extremely rich in various repeats. Here we explored the combined approach to perform the restriction analysis of D. virilis DNA. This approach enabled to reveal three abundant medium-sized tandem repeats within the D. virilis genome. While the 225 bp repeats were revealed previously in intergenic non-transcribed spacers between ribosomal genes of D. virilis, two other families comprised of 154 bp and 172 bp repeats were not described. Tandem Repeats Finder search demonstrated that 154 bp and 172 bp units are organized in multiple clusters in the genome of D. virilis. Characteristically, only 154 bp repeats derived from Helitron transposon are transcribed. Using in silico digestion in combination with conventional restriction analysis and sequencing of repeated DNA fragments enabled us to isolate and characterize three highly abundant families of medium-sized repeats present in the D. virilis genome. These repeats comprise a significant portion of the genome and may have important roles in genome function and structural integrity. Therefore, we demonstrated an approach which makes possible to investigate in detail the gross arrangement and expression of medium-sized repeats basing on sequencing data even in the case of incompletely assembled and/or annotated genomes.

Validation and Application of a PCR Primer Set to Quantify Fungal Communities in the Soil Environment by Real-Time Quantitative PCR

PubMed Central

Chemidlin Prévost-Bouré, Nicolas; Christen, Richard; Dequiedt, Samuel; Mougel, Christophe; Lelièvre, Mélanie; Jolivet, Claudy; Shahbazkia, Hamid Reza; Guillou, Laure; Arrouays, Dominique; Ranjard, Lionel

2011-01-01

Fungi constitute an important group in soil biological diversity and functioning. However, characterization and knowledge of fungal communities is hampered because few primer sets are available to quantify fungal abundance by real-time quantitative PCR (real-time Q-PCR). The aim in this study was to quantify fungal abundance in soils by incorporating, into a real-time Q-PCR using the SYBRGreen® method, a primer set already used to study the genetic structure of soil fungal communities. To satisfy the real-time Q-PCR requirements to enhance the accuracy and reproducibility of the detection technique, this study focused on the 18S rRNA gene conserved regions. These regions are little affected by length polymorphism and may provide sufficiently small targets, a crucial criterion for enhancing accuracy and reproducibility of the detection technique. An in silico analysis of 33 primer sets targeting the 18S rRNA gene was performed to select the primer set with the best potential for real-time Q-PCR: short amplicon length; good fungal specificity and coverage. The best consensus between specificity, coverage and amplicon length among the 33 sets tested was the primer set FR1 / FF390. This in silico analysis of the specificity of FR1 / FF390 also provided additional information to the previously published analysis on this primer set. The specificity of the primer set FR1 / FF390 for Fungi was validated in vitro by cloning - sequencing the amplicons obtained from a real time Q-PCR assay performed on five independent soil samples. This assay was also used to evaluate the sensitivity and reproducibility of the method. Finally, fungal abundance in samples from 24 soils with contrasting physico-chemical and environmental characteristics was examined and ranked to determine the importance of soil texture, organic carbon content, C∶N ratio and land use in determining fungal abundance in soils. PMID:21931659

The secrets of Oriental panacea: Panax ginseng.

PubMed

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

2016-01-01

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

Toward a theory of multilevel evolution: long-term information integration shapes the mutational landscape and enhances evolvability.

PubMed

Hogeweg, Paulien

2012-01-01

Most of evolutionary theory has abstracted away from how information is coded in the genome and how this information is transformed into traits on which selection takes place. While in the earliest stages of biological evolution, in the RNA world, the mapping from the genotype into function was largely predefined by the physical-chemical properties of the evolving entities (RNA replicators, e.g. from sequence to folded structure and catalytic sites), in present-day organisms, the mapping itself is the result of evolution. I will review results of several in silico evolutionary studies which examine the consequences of evolving the genetic coding, and the ways this information is transformed, while adapting to prevailing environments. Such multilevel evolution leads to long-term information integration. Through genome, network, and dynamical structuring, the occurrence and/or effect of random mutations becomes nonrandom, and facilitates rapid adaptation. This is what does happen in the in silico experiments. Is it also what did happen in biological evolution? I will discuss some data that suggest that it did. In any case, these results provide us with novel search images to tackle the wealth of biological data.

Exploring astrobiology using in silico molecular structure generation.

PubMed

Meringer, Markus; Cleaves, H James

2017-12-28

The origin of life is typically understood as a transition from inanimate or disorganized matter to self-organized, 'animate' matter. This transition probably took place largely in the context of organic compounds, and most approaches, to date, have focused on using the organic chemical composition of modern organisms as the main guide for understanding this process. However, it has gradually come to be appreciated that biochemistry, as we know it, occupies a minute volume of the possible organic 'chemical space'. As the majority of abiotic syntheses appear to make a large set of compounds not found in biochemistry, as well as an incomplete subset of those that are, it is possible that life began with a significantly different set of components. Chemical graph-based structure generation methods allow for exhaustive in silico enumeration of different compound types and different types of 'chemical spaces' beyond those used by biochemistry, which can be explored to help understand the types of compounds biology uses, as well as to understand the nature of abiotic synthesis, and potentially design novel types of living systems.This article is part of the themed issue 'Reconceptualizing the origins of life'. © 2017 The Authors.

Exploring astrobiology using in silico molecular structure generation

NASA Astrophysics Data System (ADS)

Meringer, Markus; Cleaves, H. James

2017-11-01

The origin of life is typically understood as a transition from inanimate or disorganized matter to self-organized, `animate' matter. This transition probably took place largely in the context of organic compounds, and most approaches, to date, have focused on using the organic chemical composition of modern organisms as the main guide for understanding this process. However, it has gradually come to be appreciated that biochemistry, as we know it, occupies a minute volume of the possible organic `chemical space'. As the majority of abiotic syntheses appear to make a large set of compounds not found in biochemistry, as well as an incomplete subset of those that are, it is possible that life began with a significantly different set of components. Chemical graph-based structure generation methods allow for exhaustive in silico enumeration of different compound types and different types of `chemical spaces' beyond those used by biochemistry, which can be explored to help understand the types of compounds biology uses, as well as to understand the nature of abiotic synthesis, and potentially design novel types of living systems. This article is part of the themed issue 'Reconceptualizing the origins of life'.

In Vivo, In Vitro, and In Silico Characterization of Peptoids as Antimicrobial Agents

PubMed Central

Fjell, Christopher D.; Waldbrook, Matt; Chongsiriwatana, Nathaniel P.; Yuen, Eddie; Hancock, Robert E. W.; Barron, Annelise E.

2016-01-01

Bacterial resistance to conventional antibiotics is a global threat that has spurred the development of antimicrobial peptides (AMPs) and their mimetics as novel anti-infective agents. While the bioavailability of AMPs is often reduced due to protease activity, the non-natural structure of AMP mimetics renders them robust to proteolytic degradation, thus offering a distinct advantage for their clinical application. We explore the therapeutic potential of N-substituted glycines, or peptoids, as AMP mimics using a multi-faceted approach that includes in silico, in vitro, and in vivo techniques. We report a new QSAR model that we developed based on 27 diverse peptoid sequences, which accurately correlates antimicrobial peptoid structure with antimicrobial activity. We have identified a number of peptoids that have potent, broad-spectrum in vitro activity against multi-drug resistant bacterial strains. Lastly, using a murine model of invasive S. aureus infection, we demonstrate that one of the best candidate peptoids at 4 mg/kg significantly reduces with a two-log order the bacterial counts compared with saline-treated controls. Taken together, our results demonstrate the promising therapeutic potential of peptoids as antimicrobial agents. PMID:26849681

Mechanical Network in Titin Immunoglobulin from Force Distribution Analysis

PubMed Central

Wilmanns, Matthias; Gräter, Frauke

2009-01-01

The role of mechanical force in cellular processes is increasingly revealed by single molecule experiments and simulations of force-induced transitions in proteins. How the applied force propagates within proteins determines their mechanical behavior yet remains largely unknown. We present a new method based on molecular dynamics simulations to disclose the distribution of strain in protein structures, here for the newly determined high-resolution crystal structure of I27, a titin immunoglobulin (IG) domain. We obtain a sparse, spatially connected, and highly anisotropic mechanical network. This allows us to detect load-bearing motifs composed of interstrand hydrogen bonds and hydrophobic core interactions, including parts distal to the site to which force was applied. The role of the force distribution pattern for mechanical stability is tested by in silico unfolding of I27 mutants. We then compare the observed force pattern to the sparse network of coevolved residues found in this family. We find a remarkable overlap, suggesting the force distribution to reflect constraints for the evolutionary design of mechanical resistance in the IG family. The force distribution analysis provides a molecular interpretation of coevolution and opens the road to the study of the mechanism of signal propagation in proteins in general. PMID:19282960

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 ...

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

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

PubMed

Gopal, J Vinay; Kannabiran, K

2013-12-01

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

First Pass Annotation of Promoters on Human Chromosome 22

PubMed Central

Scherf, Matthias; Klingenhoff, Andreas; Frech, Kornelie; Quandt, Kerstin; Schneider, Ralf; Grote, Korbinian; Frisch, Matthias; Gailus-Durner, Valérie; Seidel, Alexander; Brack-Werner, Ruth; Werner, Thomas

2001-01-01

The publication of the first almost complete sequence of a human chromosome (chromosome 22) is a major milestone in human genomics. Together with the sequence, an excellent annotation of genes was published which certainly will serve as an information resource for numerous future projects. We noted that the annotation did not cover regulatory regions; in particular, no promoter annotation has been provided. Here we present an analysis of the complete published chromosome 22 sequence for promoters. A recent breakthrough in specific in silico prediction of promoter regions enabled us to attempt large-scale prediction of promoter regions on chromosome 22. Scanning of sequence databases revealed only 20 experimentally verified promoters, of which 10 were correctly predicted by our approach. Nearly 40% of our 465 predicted promoter regions are supported by the currently available gene annotation. Promoter finding also provides a biologically meaningful method for “chromosomal scaffolding”, by which long genomic sequences can be divided into segments starting with a gene. As one example, the combination of promoter region prediction with exon/intron structure predictions greatly enhances the specificity of de novo gene finding. The present study demonstrates that it is possible to identify promoters in silico on the chromosomal level with sufficient reliability for experimental planning and indicates that a wealth of information about regulatory regions can be extracted from current large-scale (megabase) sequencing projects. Results are available on-line at http://genomatix.gsf.de/chr22/. PMID:11230158

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

PubMed

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

2017-12-01

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

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.

Genome mining reveals the genus Xanthomonas to be a promising reservoir for new bioactive non-ribosomally synthesized peptides

PubMed Central

2013-01-01

Background Various bacteria can use non-ribosomal peptide synthesis (NRPS) to produce peptides or other small molecules. Conserved features within the NRPS machinery allow the type, and sometimes even the structure, of the synthesized polypeptide to be predicted. Thus, bacterial genome mining via in silico analyses of NRPS genes offers an attractive opportunity to uncover new bioactive non-ribosomally synthesized peptides. Xanthomonas is a large genus of Gram-negative bacteria that cause disease in hundreds of plant species. To date, the only known small molecule synthesized by NRPS in this genus is albicidin produced by Xanthomonas albilineans. This study aims to estimate the biosynthetic potential of Xanthomonas spp. by in silico analyses of NRPS genes with unknown function recently identified in the sequenced genomes of X. albilineans and related species of Xanthomonas. Results We performed in silico analyses of NRPS genes present in all published genome sequences of Xanthomonas spp., as well as in unpublished draft genome sequences of Xanthomonas oryzae pv. oryzae strain BAI3 and Xanthomonas spp. strain XaS3. These two latter strains, together with X. albilineans strain GPE PC73 and X. oryzae pv. oryzae strains X8-1A and X11-5A, possess novel NRPS gene clusters and share related NRPS-associated genes such as those required for the biosynthesis of non-proteinogenic amino acids or the secretion of peptides. In silico prediction of peptide structures according to NRPS architecture suggests eight different peptides, each specific to its producing strain. Interestingly, these eight peptides cannot be assigned to any known gene cluster or related to known compounds from natural product databases. PCR screening of a collection of 94 plant pathogenic bacteria indicates that these novel NRPS gene clusters are specific to the genus Xanthomonas and are also present in Xanthomonas translucens and X. oryzae pv. oryzicola. Further genome mining revealed other novel NRPS genes specific to X. oryzae pv. oryzicola or Xanthomonas sacchari. Conclusions This study revealed the significant potential of the genus Xanthomonas to produce new non-ribosomally synthesized peptides. Interestingly, this biosynthetic potential seems to be specific to strains of Xanthomonas associated with monocotyledonous plants, suggesting a putative involvement of non-ribosomally synthesized peptides in plant-bacteria interactions. PMID:24069909

Insights from spectroscopic and in-silico techniques for the exploitation of biomolecular interactions between Human serum albumin and Paromomycin.

PubMed

Raza, Muslim; Jiang, Yang; Wei, Yun; Ahmad, Aftab; Khan, Ajmal; Qipeng, Yuan

2017-09-01

The study of molecular interactions of drug-protein are extremely important from the biological aspect in all living organisms, and therefore such type of investigation hold a tremendous significance in rational drug design and discovery. In the present study, the molecular interactions between paromomycin (PAR) and human serum albumin (HSA) have been studied by different biophysical techniques and validated by in-silico approaches. The results obtained from Ultraviolet-visible spectroscopy (UV) and Fourier transform infrared spectroscopy (FT-IR) demonstrated a remarkable change upon the complexation of PAR with HSA. Circular Dichroism (CD), Dynamic Light Scattering (DLS) and Resonance Rayleigh scattering (RRS) results revealed a significant secondary structure alteration and reduction of hydrodynamic radii upon the conjugation of PAR with HSA. The fluorescence spectroscopy results also apparently revealed the static quenching mechanism. The number of binding sites, binding constants, and Gibbs free energy values were calculated to illustrate the nature of intermolecular interactions. Similarly, the in-silico docking and molecular dynamics simulation clearly explain the theoretical basis of the binding mechanism of PAR with HSA. The experimental and docking approaches suggested that PAR binds to the hydrophobic cavity site I of HSA. The finding of present investigation will provide binding insight of PAR and associated alterations in the stability and conformation of HSA. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Anticancer activity of cow, sheep, goat, mare, donkey and camel milks and their caseins and whey proteins and in silico comparison of the caseins.

PubMed

Shariatikia, Malihe; Behbahani, Mandana; Mohabatkar, Hassan

2017-06-01

The present investigation was carried out to evaluate anticancer activity of cow, goat, sheep, mare, donkey and camel milks and their casein and whey proteins against MCF7 cell line. The structure-based properties of the casein proteins were also investigated, using bioinformatics tools to find explanation for their antitumor activities. The effect of different milks and their casein and whey proteins on MCF7 proliferation was measured using MTT assay at different concentrations (0.5, 1 and 2 mg/ml). The results showed that mare, donkey, cow and camel milks and their casein and whey proteins have potent cytotoxic activity against MCF7 cells in a dose dependent manner while sheep and goat milks and their proteins did not reveal any cytotoxic activity. The in silico results demonstrated that mare, donkey and camel caseins had highest positive and negative charges. The secondary structure prediction indicated that mare and donkey caseins had the maximum percentage of α helix and camel casein had the highest percentage of extended strand. This study suggests that there is a striking correlation between anti-cancer activity of milk caseins and their physicochemical properties such as alpha helix structure and positive and negative charges. In conclusion, the results indicated that mare, camel and donkey milks might be good candidates against breast cancer cells.

In silico modeling of the Moniliophthora perniciosa Atg8 protein.

PubMed

Pereira, A C F; Cardoso, T H S; Brendel, M; Pungartnik, C

2013-12-11

Autophagy is defined as an intracellular system of lysosomal degradation in eukaryotic cells, and the genes involved in this process are conserved from yeast to humans. Among these genes, ATG8 encodes a ubiquitin-like protein that is conjugated to a phosphatidylethanolamine (PE) membrane by the ubiquitination system. The Atg8p-PE complex is important in initiating the formation of the autophagosome and thus plays a critical role in autophagy. In silico modeling of Atg8p of Moniliophthora perniciosa revealed its three-dimensional structure and enabled comparison with its Saccharomyces cerevisiae homologue ScAtg8p. Some common and distinct features were observed between these two proteins, including the conservation of residues required to allow the interaction of α-helix1 with the ubiquitin core. However, the electrostatic potential surfaces of these helices differ, implying particular roles in selecting specific binding partners. The proposed structure was validated by the programs PROCHECK 3.4, ANOLEA, and QMEAN, which demonstrated 100% of amino acids located in favorable regions with low total energy. Our results showed that MpAtg8p contains the same functional domains (3 α-helices and 4 β-sheets) and is similar in structure as the ScAtg8p yeast. Both proteins have many conserved sequences in common, and therefore, their proposed three-dimensional models show similar configuration.

In silico study of in vitro GPCR assays by QSAR modeling ...

EPA Pesticide Factsheets

The U.S. EPA is screening thousands of chemicals of environmental interest in hundreds of in vitro high-throughput screening (HTS) assays (the ToxCast program). One goal is to prioritize chemicals for more detailed analyses based on activity in molecular initiating events (MIE) of adverse outcome pathways (AOPs). However, the chemical space of interest for environmental exposure is much wider than this set of chemicals. Thus, there is a need to fill data gaps with in silico methods, and quantitative structure-activity relationships (QSARs) are a proven and cost effective approach to predict biological activity. ToxCast in turn provides relatively large datasets that are ideal for training and testing QSAR models. The overall goal of the study described here was to develop QSAR models to fill the data gaps in a larger environmental database of ~32k structures. The specific aim of the current work was to build QSAR models for 18 G-Protein Coupled Receptor (GPCR) assays, part of the aminergic category. Two QSAR modeling strategies were adopted: classification models were developed to separate chemicals into active/non-active classes, and then regression models were built to predict the potency values of the bioassays for the active chemicals. Multiple software programs were used to calculate constitutional, topological and substructural molecular descriptors from two-dimensional (2D) chemical structures. Model-fitting methods included PLSDA (partial least squares d

Identification of phototransformation products of thalidomide and mixture toxicity assessment: an experimental and quantitative structural activity relationships (QSAR) approach.

PubMed

Mahmoud, Waleed M M; Toolaram, Anju P; Menz, Jakob; Leder, Christoph; Schneider, Mandy; Kümmerer, Klaus

2014-02-01

The fate of thalidomide (TD) was investigated after irradiation with a medium-pressure Hg-lamp. The primary elimination of TD was monitored and structures of phototransformation products (PTPs) were assessed by LC-UV-FL-MS/MS. Environmentally relevant properties of TD and its PTPs as well as hydrolysis products (HTPs) were predicted using in silico QSAR models. Mutagenicity of TD and its PTPs was investigated in the Ames microplate format (MPF) aqua assay (Xenometrix, AG). Furthermore, a modified luminescent bacteria test (kinetic luminescent bacteria test (kinetic LBT)), using the luminescent bacteria species Vibrio fischeri, was applied for the initial screening of environmental toxicity. Additionally, toxicity of phthalimide, one of the identified PTPs, was investigated separately in the kinetic LBT. The UV irradiation eliminated TD itself without complete mineralization and led to the formation of several PTPs. TD and its PTPs did not exhibit mutagenic response in the Salmonella typhimurium strains TA 98, and TA 100 with and without metabolic activation. In contrast, QSAR analysis of PTPs and HTPs provided evidence for mutagenicity, genotoxicity and carcinogenicity using additional endpoints in silico software. QSAR analysis of different ecotoxicological endpoints, such as acute toxicity towards V. fischeri, provided positive alerts for several identified PTPs and HTPs. This was partially confirmed by the results of the kinetic LBT, in which a steady increase of acute and chronic toxicity during the UV-treatment procedure was observed for the photolytic mixtures at the highest tested concentration. Moreover, the number of PTPs within the reaction mixture that might be responsible for the toxification of TD during UV-treatment was successfully narrowed down by correlating the formation kinetics of PTPs with QSAR predictions and experimental toxicity data. Beyond that, further analysis of the commercially available PTP phthalimide indicated that transformation of TD into phthalimide was not the cause for the toxification of TD during UV-treatment. These results provide a path for toxicological assessment of complex chemical mixtures and in detail show the toxic potential of TD and its PTPs as well as its HTPs. This deserves further attention as UV irradiation might not always be a green technology, because it might pose a toxicological risk for the environment in general and specifically for water compartments. Copyright © 2013 Elsevier Ltd. All rights reserved.

Stearoyl-Acyl Carrier Protein Desaturase Mutations Uncover an Impact of Stearic Acid in Leaf and Nodule Structure.

PubMed

Lakhssassi, Naoufal; Colantonio, Vincent; Flowers, Nicholas D; Zhou, Zhou; Henry, Jason; Liu, Shiming; Meksem, Khalid

2017-07-01

Stearoyl-acyl carrier protein desaturase (SACPD-C) has been reported to control the accumulation of seed stearic acid; however, no study has previously reported its involvement in leaf stearic acid content and impact on leaf structure and morphology. A subset of an ethyl methanesulfonate mutagenized population of soybean ( Glycine max ) 'Forrest' was screened to identify mutants within the GmSACPD-C gene. Using a forward genetics approach, one nonsense and four missense Gmsacpd-c mutants were identified to have high levels of seed, nodule, and leaf stearic acid content. Homology modeling and in silico analysis of the GmSACPD-C enzyme revealed that most of these mutations were localized near or at conserved residues essential for diiron ion coordination. Soybeans carrying Gmsacpd-c mutations at conserved residues showed the highest stearic acid content, and these mutations were found to have deleterious effects on nodule development and function. Interestingly, mutations at nonconserved residues show an increase in stearic acid content yet retain healthy nodules. Thus, random mutagenesis and mutational analysis allows for the achievement of high seed stearic acid content with no associated negative agronomic characteristics. Additionally, expression analysis demonstrates that nodule leghemoglobin transcripts were significantly more abundant in soybeans with deleterious mutations at conserved residues of GmSACPD-C. Finally, we report that Gmsacpd-c mutations cause an increase in leaf stearic acid content and an alteration of leaf structure and morphology in addition to differences in nitrogen-fixing nodule structure. © 2017 American Society of Plant Biologists. All Rights Reserved.

A Mechanism-based 3D-QSAR Approach for Classification ...

EPA Pesticide Factsheets

Organophosphate (OP) and carbamate esters can inhibit acetylcholinesterase (AChE) by binding covalently to a serine residue in the enzyme active site, and their inhibitory potency depends largely on affinity for the enzyme and the reactivity of the ester. Despite this understanding, there has been no mechanism-based in silico approach for classification and prediction of the inhibitory potency of ether OPs or carbamates. This prompted us to develop a three dimensional prediction framework for OPs, carbamates, and their analogs. Inhibitory structures of a compound that can form the covalent bond were identified through analysis of docked conformations of the compound and its metabolites. Inhibitory potencies of the selected structures were then predicted using a previously developed three dimensional quantitative structure-active relationship. This approach was validated with a large number of structurally diverse OP and carbamate compounds encompassing widely used insecticides and structural analogs including OP flame retardants and thio- and dithiocarbamate pesticides. The modeling revealed that: (1) in addition to classical OP metabolic activation, the toxicity of carbamate compounds can be dependent on biotransformation, (2) OP and carbamate analogs such as OP flame retardants and thiocarbamate herbicides can act as AChEI, (3) hydrogen bonds at the oxyanion hole is critical for AChE inhibition through the covalent bond, and (4) π–π interaction with Trp86

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.

A novel QSAR model of Salmonella mutagenicity and its application in the safety assessment of drug impurities

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

Valencia, Antoni; Prous, Josep; Mora, Oscar

As indicated in ICH M7 draft guidance, in silico predictive tools including statistically-based QSARs and expert analysis may be used as a computational assessment for bacterial mutagenicity for the qualification of impurities in pharmaceuticals. To address this need, we developed and validated a QSAR model to predict Salmonella t. mutagenicity (Ames assay outcome) of pharmaceutical impurities using Prous Institute's Symmetry℠, a new in silico solution for drug discovery and toxicity screening, and the Mold2 molecular descriptor package (FDA/NCTR). Data was sourced from public benchmark databases with known Ames assay mutagenicity outcomes for 7300 chemicals (57% mutagens). Of these data, 90%more » was used to train the model and the remaining 10% was set aside as a holdout set for validation. The model's applicability to drug impurities was tested using a FDA/CDER database of 951 structures, of which 94% were found within the model's applicability domain. The predictive performance of the model is acceptable for supporting regulatory decision-making with 84 ± 1% sensitivity, 81 ± 1% specificity, 83 ± 1% concordance and 79 ± 1% negative predictivity based on internal cross-validation, while the holdout dataset yielded 83% sensitivity, 77% specificity, 80% concordance and 78% negative predictivity. Given the importance of having confidence in negative predictions, an additional external validation of the model was also carried out, using marketed drugs known to be Ames-negative, and obtained 98% coverage and 81% specificity. Additionally, Ames mutagenicity data from FDA/CFSAN was used to create another data set of 1535 chemicals for external validation of the model, yielding 98% coverage, 73% sensitivity, 86% specificity, 81% concordance and 84% negative predictivity. - Highlights: • A new in silico QSAR model to predict Ames mutagenicity is described. • The model is extensively validated with chemicals from the FDA and the public domain. • Validation tests show desirable high sensitivity and high negative predictivity. • The model predicted 14 reportedly difficult to predict drug impurities with accuracy. • The model is suitable to support risk evaluation of potentially mutagenic compounds.« less

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.

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.

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.

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

Arc is a flexible modular protein capable of reversible self-oligomerization

PubMed Central

Myrum, Craig; Baumann, Anne; Bustad, Helene J.; Flydal, Marte Innselset; Mariaule, Vincent; Alvira, Sara; Cuéllar, Jorge; Haavik, Jan; Soulé, Jonathan; Valpuesta, José Maria; Márquez, José Antonio; Martinez, Aurora; Bramham, Clive R.

2015-01-01

The immediate early gene product Arc (activity-regulated cytoskeleton-associated protein) is posited as a master regulator of long-term synaptic plasticity and memory. However, the physicochemical and structural properties of Arc have not been elucidated. In the present study, we expressed and purified recombinant human Arc (hArc) and performed the first biochemical and biophysical analysis of hArc's structure and stability. Limited proteolysis assays and MS analysis indicate that hArc has two major domains on either side of a central more disordered linker region, consistent with in silico structure predictions. hArc's secondary structure was estimated using CD, and stability was analysed by CD-monitored thermal denaturation and differential scanning fluorimetry (DSF). Oligomerization states under different conditions were studied by dynamic light scattering (DLS) and visualized by AFM and EM. Biophysical analyses show that hArc is a modular protein with defined secondary structure and loose tertiary structure. hArc appears to be pyramid-shaped as a monomer and is capable of reversible self-association, forming large soluble oligomers. The N-terminal domain of hArc is highly basic, which may promote interaction with cytoskeletal structures or other polyanionic surfaces, whereas the C-terminal domain is acidic and stabilized by ionic conditions that promote oligomerization. Upon binding of presenilin-1 (PS1) peptide, hArc undergoes a large structural change. A non-synonymous genetic variant of hArc (V231G) showed properties similar to the wild-type (WT) protein. We conclude that hArc is a flexible multi-domain protein that exists in monomeric and oligomeric forms, compatible with a diverse, hub-like role in plasticity-related processes. PMID:25748042

Proposed structural basis of interaction of piperine and related compounds with monoamine oxidases.

PubMed

Rahman, Taufiq; Rahmatullah, Mohammed

2010-01-15

Several studies have revealed piperine and a few related compounds as potent inhibitors of monoamine oxidases without delineating the underlying mechanism. Using in silico modelling, we propose a structural basis of such activity by showing that these compounds can successfully dock into the inhibitor binding pockets of human monoamine oxidase isoforms with predicted affinities comparable to some known inhibitors. The results therefore suggest that piperine can be a promising lead for developing novel monoamine oxidase inhibitors. Copyright 2009 Elsevier Ltd. All rights reserved.

Pyridine-substituted thiazolylphenol derivatives: Synthesis, modeling studies, aromatase inhibition, and antiproliferative activity evaluation.

PubMed

Ertas, Merve; Sahin, Zafer; Berk, Barkin; Yurttas, Leyla; Biltekin, Sevde N; Demirayak, Seref

2018-04-01

Drugs used in breast cancer treatments target the suppression of estrogen biosynthesis. During this suppression, the main goal is to inhibit the aromatase enzyme that is responsible for the cyclization and structuring of estrogens either with steroid or non-steroidal-type inhibitors. Non-steroidal derivatives generally have a planar aromatic structure attached to the triazole ring system in their structures, which inhibits hydroxylation reactions during aromatization by coordinating the heme group. Bioisosteric replacement of the triazole ring system and development of aromatic/cyclic structures of the side chain can increase the selectivity for aromatase enzyme inhibition. In this study, pyridine-substituted thiazolylphenol derivatives, which are non-steroidal triazole bioisosteres, were synthesized using the Hantzsch method, and physical analysis and structural determination studies were performed. The IC 50 values of the compounds were determined by a fluorescence-based aromatase inhibition assay. Then, their antiproliferative activities on the MCF7 and HEK 293 cell lines were evaluated with the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Furthermore, the crystal structure of human placental aromatase was subjected to a series of docking experiments to identify the possible interactions between the most active structure and the active site. Lastly, an in silico technique was performed to analyze and predict the drug-likeness, molecular and ADME properties of the synthesized molecules. © 2018 Deutsche Pharmazeutische Gesellschaft.

Oral LD50 toxicity modeling and prediction of per- and polyfluorinated chemicals on rat and mouse.

PubMed

Bhhatarai, Barun; Gramatica, Paola

2011-05-01

Quantitative structure-activity relationship (QSAR) analyses were performed using the LD(50) oral toxicity data of per- and polyfluorinated chemicals (PFCs) on rodents: rat and mouse. PFCs are studied under the EU project CADASTER which uses the available experimental data for prediction and prioritization of toxic chemicals for risk assessment by using the in silico tools. The methodology presented here applies chemometrical analysis on the existing experimental data and predicts the toxicity of new compounds. QSAR analyses were performed on the available 58 mouse and 50 rat LD(50) oral data using multiple linear regression (MLR) based on theoretical molecular descriptors selected by genetic algorithm (GA). Training and prediction sets were prepared a priori from available experimental datasets in terms of structure and response. These sets were used to derive statistically robust and predictive (both internally and externally) models. The structural applicability domain (AD) of the models were verified on 376 per- and polyfluorinated chemicals including those in REACH preregistration list. The rat and mouse endpoints were predicted by each model for the studied compounds, and finally 30 compounds, all perfluorinated, were prioritized as most important for experimental toxicity analysis under the project. In addition, cumulative study on compounds within the AD of all four models, including two earlier published models on LC(50) rodent analysis was studied and the cumulative toxicity trend was observed using principal component analysis (PCA). The similarities and the differences observed in terms of descriptors and chemical/mechanistic meaning encoded by descriptors to prioritize the most toxic compounds are highlighted.

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.

Virtual screening and optimization of Type II inhibitors of JAK2 from a natural product library.

PubMed

Ma, Dik-Lung; Chan, Daniel Shiu-Hin; Wei, Guo; Zhong, Hai-Jing; Yang, Hui; Leung, Lai To; Gullen, Elizabeth A; Chiu, Pauline; Cheng, Yung-Chi; Leung, Chung-Hang

2014-11-21

Amentoflavone has been identified as a JAK2 inhibitor by structure-based virtual screening of a natural product library. In silico optimization using the DOLPHIN model yielded analogues with enhanced potency against JAK2 activity and HCV activity in cellulo. Molecular modeling and kinetic experiments suggested that the analogues may function as Type II inhibitors of JAK2.

Combinatorial In Silico Strategy towards Identifying Potential Hotspots during Inhibition of Structurally Identical HDAC1 and HDAC2 Enzymes for Effective Chemotherapy against Neurological Disorders

PubMed Central

Ganai, Shabir Ahmad; Abdullah, Ehsaan; Rashid, Romana; Altaf, Mohammad

2017-01-01

Histone deacetylases (HDACs) regulate epigenetic gene expression programs by modulating chromatin architecture and are required for neuronal development. Dysregulation of HDACs and aberrant chromatin acetylation homeostasis have been implicated in various diseases ranging from cancer to neurodegenerative disorders. Histone deacetylase inhibitors (HDACi), the small molecules interfering HDACs have shown enhanced acetylation of the genome and are gaining great attention as potent drugs for treating cancer and neurodegeneration. HDAC2 overexpression has implications in decreasing dendrite spine density, synaptic plasticity and in triggering neurodegenerative signaling. Pharmacological intervention against HDAC2 though promising also targets neuroprotective HDAC1 due to high sequence identity (94%) with former in catalytic domain, culminating in debilitating off-target effects and creating hindrance in the defined intervention. This emphasizes the need of designing HDAC2-selective inhibitors to overcome these vicious effects and for escalating the therapeutic efficacy. Here we report a top-down combinatorial in silico approach for identifying the structural variants that are substantial for interactions against HDAC1 and HDAC2 enzymes. We used extra-precision (XP)-molecular docking, Molecular Mechanics Generalized Born Surface Area (MMGBSA) for predicting affinity of inhibitors against the HDAC1 and HDAC2 enzymes. Importantly, we employed a novel in silico strategy of coupling the state-of-the-art molecular dynamics simulation (MDS) to energetically-optimized structure based pharmacophores (e-Pharmacophores) method via MDS trajectory clustering for hypothesizing the e-Pharmacophore models. Further, we performed e-Pharmacophores based virtual screening against phase database containing millions of compounds. We validated the data by performing the molecular docking and MM-GBSA studies for the selected hits among the retrieved ones. Our studies attributed inhibitor potency to the ability of forming multiple interactions and infirm potency to least interactions. Moreover, our studies delineated that a single HDAC inhibitor portrays differential features against HDAC1 and HDAC2 enzymes. The high affinity and selective HDAC2 inhibitors retrieved through e-Pharmacophores based virtual screening will play a critical role in ameliorating neurodegenerative signaling without hampering the neuroprotective isoform (HDAC1). PMID:29170627

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.

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 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.

Ab Initio Molecular-Dynamics Simulation of Neuromorphic Computing in Phase-Change Memory Materials.

PubMed

Skelton, Jonathan M; Loke, Desmond; Lee, Taehoon; Elliott, Stephen R

2015-07-08

We present an in silico study of the neuromorphic-computing behavior of the prototypical phase-change material, Ge2Sb2Te5, using ab initio molecular-dynamics simulations. Stepwise changes in structural order in response to temperature pulses of varying length and duration are observed, and a good reproduction of the spike-timing-dependent plasticity observed in nanoelectronic synapses is demonstrated. Short above-melting pulses lead to instantaneous loss of structural and chemical order, followed by delayed partial recovery upon structural relaxation. We also investigate the link between structural order and electrical and optical properties. These results pave the way toward a first-principles understanding of phase-change physics beyond binary switching.

In silico local structure approach: a case study on outer membrane proteins.

PubMed

Martin, Juliette; de Brevern, Alexandre G; Camproux, Anne-Claude

2008-04-01

The detection of Outer Membrane Proteins (OMP) in whole genomes is an actual question, their sequence characteristics have thus been intensively studied. This class of protein displays a common beta-barrel architecture, formed by adjacent antiparallel strands. However, due to the lack of available structures, few structural studies have been made on this class of proteins. Here we propose a novel OMP local structure investigation, based on a structural alphabet approach, i.e., the decomposition of 3D structures using a library of four-residue protein fragments. The optimal decomposition of structures using hidden Markov model results in a specific structural alphabet of 20 fragments, six of them dedicated to the decomposition of beta-strands. This optimal alphabet, called SA20-OMP, is analyzed in details, in terms of local structures and transitions between fragments. It highlights a particular and strong organization of beta-strands as series of regular canonical structural fragments. The comparison with alphabets learned on globular structures indicates that the internal organization of OMP structures is more constrained than in globular structures. The analysis of OMP structures using SA20-OMP reveals some recurrent structural patterns. The preferred location of fragments in the distinct regions of the membrane is investigated. The study of pairwise specificity of fragments reveals that some contacts between structural fragments in beta-sheets are clearly favored whereas others are avoided. This contact specificity is stronger in OMP than in globular structures. Moreover, SA20-OMP also captured sequential information. This can be integrated in a scoring function for structural model ranking with very promising results. (c) 2007 Wiley-Liss, Inc.

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