Analysis of protein missense alterations by combining sequence- and structure-based methods
Gyulkhandanyan, Rezaie, Roumenina, Lagarde, Fremeaux-Bacchi, Miteva, Villoutreix (2020) Analysis of protein missense alterations by combining sequence- and structure-based methods Mol Genet Genomic Med (IF: 2) 8(4) e1166
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Abstract
Different types of in silico approaches can be used to predict the phenotypic consequence of missense variants. Such algorithms are often categorized as sequence based or structure based, when they necessitate 3D structural information. In addition, many other in silico tools, not dedicated to the analysis of variants, can be used to gain additional insights about the possible mechanisms at play.Here we applied different computational approaches to a set of 20 known missense variants present on different proteins (CYP, complement factor B, antithrombin and blood coagulation factor VIII). The tools that were used include fast computational approaches and web servers such as PolyPhen-2, PopMusic, DUET, MaestroWeb, SAAFEC, Missense3D, VarSite, FlexPred, PredyFlexy, Clustal Omega, meta-PPISP, FTMap, ClusPro, pyDock, PPM, RING, Cytoscape, and ChannelsDB.We observe some conflicting results among the methods but, most of the time, the combination of several engines helped to clarify the potential impacts of the amino acid substitutions.Combining different computational approaches including some that were not developed to investigate missense variants help to predict the possible impact of the amino acid substitutions. Yet, when the modified residues are involved in a salt-bridge, the tools tend to fail, even when the analysis is performed in 3D. Thus, interactive structural analysis with molecular graphics packages such as Chimera or PyMol or others are still needed to clarify automatic prediction.© 2020 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc.
Links
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7196459http://www.ncbi.nlm.nih.gov/pubmed/32096919
http://dx.doi.org/10.1002/mgg3.1166
