Open AccessAnalysis of protein missense alterations by combining sequence‐ and structure‐based methods
Author(s) -
Gyulkhandanyan Aram,
Rezaie Alireza R.,
Roumenina Lubka,
Lagarde Nathalie,
FremeauxBacchi Veronique,
Miteva Maria A.,
Villoutreix Bruno O.
Publication year - 2020
Publication title -
molecular genetics and genomic medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.765
H-Index - 29
ISSN - 2324-9269
DOI - 10.1002/mgg3.1166
Subject(s) - missense mutation , in silico , computational biology , computer science , protein structure prediction , bioinformatics , protein structure , biology , genetics , phenotype , biochemistry , gene
Background 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. Methods 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. Results 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. Conclusion 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.