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An in silico argument for mitochondrial microRNA as a determinant of primary non function in liver transplantation. Sci Rep 2018; 8:3105. [PMID: 29449571 PMCID: PMC5814406 DOI: 10.1038/s41598-018-21091-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2017] [Accepted: 01/29/2018] [Indexed: 02/07/2023] Open
Abstract
Mitochondria have their own genomic, transcriptomic and proteomic machinery but are unable to be autonomous, needing both nuclear and mitochondrial genomes. The aim of this work was to use computational biology to explore the involvement of Mitochondrial microRNAs (MitomiRs) and their interactions with the mitochondrial proteome in a clinical model of primary non function (PNF) of the donor after cardiac death (DCD) liver. Archival array data on the differential expression of miRNA in DCD PNF was re-analyzed using a number of publically available computational algorithms. 10 MitomiRs were identified of importance in DCD PNF, 7 with predicted interaction of their seed sequence with the mitochondrial transcriptome that included both coding, and non coding areas of the hypervariability region 1 (HVR1) and control region. Considering miRNA regulation of the nuclear encoded mitochondrial proteome, 7 hypothetical small proteins were identified with homolog function that ranged from co-factor for formation of ATP Synthase, REDOX balance and an importin/exportin protein. In silico, unconventional seed interactions, both non canonical and alternative seed sites, appear to be of greater importance in MitomiR regulation of the mitochondrial genome. Additionally, a number of novel small proteins of relevance in transplantation have been identified which need further characterization.
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Chartier M, Morency LP, Zylber MI, Najmanovich RJ. Large-scale detection of drug off-targets: hypotheses for drug repurposing and understanding side-effects. BMC Pharmacol Toxicol 2017; 18:18. [PMID: 28449705 PMCID: PMC5408384 DOI: 10.1186/s40360-017-0128-7] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2016] [Accepted: 02/28/2017] [Indexed: 01/21/2023] Open
Abstract
Background Promiscuity in molecular interactions between small-molecules, including drugs, and proteins is widespread. Such unintended interactions can be exploited to suggest drug repurposing possibilities as well as to identify potential molecular mechanisms responsible for observed side-effects. Methods We perform a large-scale analysis to detect binding-site molecular interaction field similarities between the binding-sites of the primary target of 400 drugs against a dataset of 14082 cavities within 7895 different proteins representing a non-redundant dataset of all proteins with known structure. Statistically-significant cases with high levels of similarities represent potential cases where the drugs that bind the original target may in principle bind the suggested off-target. Such cases are further analysed with docking simulations to verify if indeed the drug could, in principle, bind the off-target. Diverse sources of data are integrated to associated potential cross-reactivity targets with side-effects. Results We observe that promiscuous binding-sites tend to display higher levels of hydrophobic and aromatic similarities. Focusing on the most statistically significant similarities (Z-score ≥ 3.0) and corroborating docking results (RMSD < 2.0 Å), we find 2923 cases involving 140 unique drugs and 1216 unique potential cross-reactivity protein targets. We highlight a few cases with a potential for drug repurposing (acetazolamide as a chorismate pyruvate lyase inhibitor, raloxifene as a bacterial quorum sensing inhibitor) as well as to explain the side-effects of zanamivir and captopril. A web-interface permits to explore the detected similarities for each of the 400 binding-sites of the primary drug targets and visualise them for the most statistically significant cases. Conclusions The detection of molecular interaction field similarities provide the opportunity to suggest drug repurposing opportunities as well as to identify potential molecular mechanisms responsible for side-effects. All methods utilized are freely available and can be readily applied to new query binding-sites. All data is freely available and represents an invaluable source to identify further candidates for repurposing and suggest potential mechanisms responsible for side-effects. Electronic supplementary material The online version of this article (doi:10.1186/s40360-017-0128-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Matthieu Chartier
- Department of Biochemistry, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Québec, Canada
| | - Louis-Philippe Morency
- Department of Biochemistry, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Québec, Canada
| | - María Inés Zylber
- Department of Biochemistry, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Québec, Canada.,Department of Pharmacology and Physiology, Faculty of Medicine, Université de Montréal, Québec, Canada
| | - Rafael J Najmanovich
- Department of Biochemistry, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Québec, Canada. .,Department of Pharmacology and Physiology, Faculty of Medicine, Université de Montréal, Québec, Canada.
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Systematic Analysis of the 4-Coumarate:Coenzyme A Ligase (4CL) Related Genes and Expression Profiling during Fruit Development in the Chinese Pear. Genes (Basel) 2016; 7:genes7100089. [PMID: 27775579 PMCID: PMC5083928 DOI: 10.3390/genes7100089] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2016] [Revised: 09/24/2016] [Accepted: 10/07/2016] [Indexed: 12/31/2022] Open
Abstract
In plants, 4-coumarate:coenzyme A ligases (4CLs), comprising some of the adenylate-forming enzymes, are key enzymes involved in regulating lignin metabolism and the biosynthesis of flavonoids and other secondary metabolites. Although several 4CL-related proteins were shown to play roles in secondary metabolism, no comprehensive study on 4CL-related genes in the pear and other Rosaceae species has been reported. In this study, we identified 4CL-related genes in the apple, peach, yangmei, and pear genomes using DNATOOLS software and inferred their evolutionary relationships using phylogenetic analysis, collinearity analysis, conserved motif analysis, and structure analysis. A total of 149 4CL-related genes in four Rosaceous species (pear, apple, peach, and yangmei) were identified, with 30 members in the pear. We explored the functions of several 4CL and acyl-coenzyme A synthetase (ACS) genes during the development of pear fruit by quantitative real-time PCR (qRT-PCR). We found that duplication events had occurred in the 30 4CL-related genes in the pear. These duplicated 4CL-related genes are distributed unevenly across all pear chromosomes except chromosomes 4, 8, 11, and 12. The results of this study provide a basis for further investigation of both the functions and evolutionary history of 4CL-related genes.
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Chartier M, Najmanovich R. Detection of Binding Site Molecular Interaction Field Similarities. J Chem Inf Model 2015; 55:1600-15. [PMID: 26158641 DOI: 10.1021/acs.jcim.5b00333] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
Protein binding-site similarity detection methods can be used to predict protein function and understand molecular recognition, as a tool in drug design for drug repurposing and polypharmacology, and for the prediction of the molecular determinants of drug toxicity. Here, we present IsoMIF, a method able to identify binding site molecular interaction field similarities across protein families. IsoMIF utilizes six chemical probes and the detection of subgraph isomorphisms to identify geometrically and chemically equivalent sections of protein cavity pairs. The method is validated using six distinct data sets, four of those previously used in the validation of other methods. The mean area under the receiver operator curve (AUC) obtained across data sets for IsoMIF is higher than those of other methods. Furthermore, while IsoMIF obtains consistently high AUC values across data sets, other methods perform more erratically across data sets. IsoMIF can be used to predict function from structure, to detect potential cross-reactivity or polypharmacology targets, and to help suggest bioisosteric replacements to known binding molecules. Given that IsoMIF detects spatial patterns of molecular interaction field similarities, its predictions are directly related to pharmacophores and may be readily translated into modeling decisions in structure-based drug design. IsoMIF may in principle detect similar binding sites with distinct amino acid arrangements that lead to equivalent interactions within the cavity. The source code to calculate and visualize MIFs and MIF similarities are freely available.
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Affiliation(s)
- Matthieu Chartier
- Department of Biochemistry, Faculty of Medicine and Health Sciences, University of Sherbrooke , 12e Avenue Nord, Sherbrooke, J1H 5N4 Québec, Canada
| | - Rafael Najmanovich
- Department of Biochemistry, Faculty of Medicine and Health Sciences, University of Sherbrooke , 12e Avenue Nord, Sherbrooke, J1H 5N4 Québec, Canada
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Pradeepkiran JA, Sainath SB, Kumar KK, Bhaskar M. Complete genome-wide screening and subtractive genomic approach revealed new virulence factors, potential drug targets against bio-war pathogen Brucella melitensis 16M. DRUG DESIGN DEVELOPMENT AND THERAPY 2015; 9:1691-706. [PMID: 25834405 PMCID: PMC4371898 DOI: 10.2147/dddt.s76948] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
Brucella melitensis 16M is a Gram-negative coccobacillus that infects both animals and humans. It causes a disease known as brucellosis, which is characterized by acute febrile illness in humans and causes abortions in livestock. To prevent and control brucellosis, identification of putative drug targets is crucial. The present study aimed to identify drug targets in B. melitensis 16M by using a subtractive genomic approach. We used available database repositories (Database of Essential Genes, Kyoto Encyclopedia of Genes and Genomes Automatic Annotation Server, and Kyoto Encyclopedia of Genes and Genomes) to identify putative genes that are nonhomologous to humans and essential for pathogen B. melitensis 16M. The results revealed that among 3 Mb genome size of pathogen, 53 putative characterized and 13 uncharacterized hypothetical genes were identified; further, from Basic Local Alignment Search Tool protein analysis, one hypothetical protein showed a close resemblance (50%) to Silicibacter pomeroyi DUF1285 family protein (2RE3). A further homology model of the target was constructed using MODELLER 9.12 and optimized through variable target function method by molecular dynamics optimization with simulating annealing. The stereochemical quality of the restrained model was evaluated by PROCHECK, VERIFY-3D, ERRAT, and WHATIF servers. Furthermore, structure-based virtual screening was carried out against the predicted active site of the respective protein using the glycerol structural analogs from the PubChem database. We identified five best inhibitors with strong affinities, stable interactions, and also with reliable drug-like properties. Hence, these leads might be used as the most effective inhibitors of modeled protein. The outcome of the present work of virtual screening of putative gene targets might facilitate design of potential drugs for better treatment against brucellosis.
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Affiliation(s)
| | - Sri Bhashyam Sainath
- CIMAR/CIIMAR, Centro Interdisciplinar de Investigação Marinha e Ambiental, Universidade do Porto, Rua dos Bragas, Porto, Portugal ; Department of Biotechnology, Vikrama Simhapuri University, Nellore, Andhra Pradesh, India
| | - Konidala Kranthi Kumar
- Division of Animal Biotechnology, Department of Zoology, Sri Venkateswara University, Tirupati, India
| | - Matcha Bhaskar
- Division of Animal Biotechnology, Department of Zoology, Sri Venkateswara University, Tirupati, India
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Kurbatova N, Chartier M, Zylber MI, Najmanovich R. IsoCleft Finder - a web-based tool for the detection and analysis of protein binding-site geometric and chemical similarities. F1000Res 2014; 2:117. [PMID: 24555058 DOI: 10.12688/f1000research.2-117.v1] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/30/2013] [Indexed: 11/20/2022] Open
Abstract
IsoCleft Finder is a web-based tool for the detection of local geometric and chemical similarities between potential small-molecule binding cavities and a non-redundant dataset of ligand-bound known small-molecule binding-sites. The non-redundant dataset developed as part of this study is composed of 7339 entries representing unique Pfam/PDB-ligand (hetero group code) combinations with known levels of cognate ligand similarity. The query cavity can be uploaded by the user or detected automatically by the system using existing PDB entries as well as user-provided structures in PDB format. In all cases, the user can refine the definition of the cavity interactively via a browser-based Jmol 3D molecular visualization interface. Furthermore, users can restrict the search to a subset of the dataset using a cognate-similarity threshold. Local structural similarities are detected using the IsoCleft software and ranked according to two criteria (number of atoms in common and Tanimoto score of local structural similarity) and the associated Z-score and p-value measures of statistical significance. The results, including predicted ligands, target proteins, similarity scores, number of atoms in common, etc., are shown in a powerful interactive graphical interface. This interface permits the visualization of target ligands superimposed on the query cavity and additionally provides a table of pairwise ligand topological similarities. Similarities between top scoring ligands serve as an additional tool to judge the quality of the results obtained. We present several examples where IsoCleft Finder provides useful functional information. IsoCleft Finder results are complementary to existing approaches for the prediction of protein function from structure, rational drug design and x-ray crystallography. IsoCleft Finder can be found at: http://bcb.med.usherbrooke.ca/isocleftfinder.
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Affiliation(s)
- Natalja Kurbatova
- European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SD, UK
| | - Matthieu Chartier
- Department of Biochemistry, Université de Sherbrooke, Sherbrooke, J1H 5N4, Canada
| | - María Inés Zylber
- Department of Biochemistry, Université de Sherbrooke, Sherbrooke, J1H 5N4, Canada
| | - Rafael Najmanovich
- Department of Biochemistry, Université de Sherbrooke, Sherbrooke, J1H 5N4, Canada
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Kurbatova N, Chartier M, Zylber MI, Najmanovich R. IsoCleft Finder - a web-based tool for the detection and analysis of protein binding-site geometric and chemical similarities. F1000Res 2013; 2:117. [PMID: 24555058 PMCID: PMC3892921 DOI: 10.12688/f1000research.2-117.v2] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/30/2013] [Indexed: 11/23/2022] Open
Abstract
IsoCleft Finder is a web-based tool for the detection of local geometric and chemical similarities between potential small-molecule binding cavities and a non-redundant dataset of ligand-bound known small-molecule binding-sites. The non-redundant dataset developed as part of this study is composed of 7339 entries representing unique Pfam/PDB-ligand (hetero group code) combinations with known levels of cognate ligand similarity. The query cavity can be uploaded by the user or detected automatically by the system using existing PDB entries as well as user-provided structures in PDB format. In all cases, the user can refine the definition of the cavity interactively via a browser-based Jmol 3D molecular visualization interface. Furthermore, users can restrict the search to a subset of the dataset using a cognate-similarity threshold. Local structural similarities are detected using the IsoCleft software and ranked according to two criteria (number of atoms in common and Tanimoto score of local structural similarity) and the associated Z-score and p-value measures of statistical significance. The results, including predicted ligands, target proteins, similarity scores, number of atoms in common, etc., are shown in a powerful interactive graphical interface. This interface permits the visualization of target ligands superimposed on the query cavity and additionally provides a table of pairwise ligand topological similarities. Similarities between top scoring ligands serve as an additional tool to judge the quality of the results obtained. We present several examples where IsoCleft Finder provides useful functional information. IsoCleft Finder results are complementary to existing approaches for the prediction of protein function from structure, rational drug design and x-ray crystallography. IsoCleft Finder can be found at:
http://bcb.med.usherbrooke.ca/isocleftfinder.
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Affiliation(s)
- Natalja Kurbatova
- European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SD, UK
| | - Matthieu Chartier
- Department of Biochemistry, Université de Sherbrooke, Sherbrooke, J1H 5N4, Canada
| | - María Inés Zylber
- Department of Biochemistry, Université de Sherbrooke, Sherbrooke, J1H 5N4, Canada
| | - Rafael Najmanovich
- Department of Biochemistry, Université de Sherbrooke, Sherbrooke, J1H 5N4, Canada
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Andreeva A, Murzin AG. Structural classification of proteins and structural genomics: new insights into protein folding and evolution. Acta Crystallogr Sect F Struct Biol Cryst Commun 2010; 66:1190-7. [PMID: 20944210 PMCID: PMC2954204 DOI: 10.1107/s1744309110007177] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2010] [Accepted: 02/24/2010] [Indexed: 11/10/2022]
Abstract
During the past decade, the Protein Structure Initiative (PSI) centres have become major contributors of new families, superfamilies and folds to the Structural Classification of Proteins (SCOP) database. The PSI results have increased the diversity of protein structural space and accelerated our understanding of it. This review article surveys a selection of protein structures determined by the Joint Center for Structural Genomics (JCSG). It presents previously undescribed β-sheet architectures such as the double barrel and spiral β-roll and discusses new examples of unusual topologies and peculiar structural features observed in proteins characterized by the JCSG and other Structural Genomics centres.
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Affiliation(s)
- Antonina Andreeva
- MRC Laboratory of Molecular Biology, Hills Road, Cambridge CB2 0QH, England
| | - Alexey G. Murzin
- MRC Laboratory of Molecular Biology, Hills Road, Cambridge CB2 0QH, England
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