Venus: Elucidating the Impact of Amino Acid Variants on Protein Function Beyond Structure Destabilisation

被引:14
作者
Ferla, Matteo P. [1 ,2 ]
Pagnamenta, Alistair T. [1 ,2 ]
Koukouflis, Leonidas [3 ]
Taylor, Jenny C. [1 ,2 ]
Marsden, Brian D. [3 ,4 ]
机构
[1] Univ Oxford, Wellcome Ctr Human Genet, Oxford OX3 7BN, England
[2] Oxford NIHR Biomed Res Ctr, Oxford, England
[3] Univ Oxford, Ctr Med Discovery, Old Rd Campus Res Bldg, Oxford OX3 7DQ, England
[4] Univ Oxford, Kennedy Inst Rheumatol, Oxford OX3 7FY, England
基金
英国惠康基金;
关键词
WEB SERVER; STABILITY CHANGES; PREDICTION; MUTATIONS;
D O I
10.1016/j.jmb.2022.167567
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Exploring the functional effect of a non-synonymous coding variant at the protein level requires multiple pieces of information to be interpreted appropriately. This is particularly important when embarking on the study of a potentially pathogenic variant linked to a rare or monogenic disease. Whereas accurate protein stability predictions alone are generally informative, other effects, such as disruption of post translational modifications or weakened ligand binding, may also contribute to the disease phenotype. Furthermore, consideration of nearby variants that are found in the healthy population may strengthen or refute a given mechanistic hypothesis. Whilst there are several bioinformatics tools available that score a genetic variant in terms of deleteriousness, there is no single tool that assembles multiple effects of a variant on the encoded protein, beyond structural stability, and presents them on the structure for inspection. Venus is a web application which, given a protein substitution, rapidly estimates the predicted effect on protein stability of the variant, flags if the variant affects a post-translational modification site, a predicted linear motif or known annotation, and determines the effect on protein stability of variants which affect nearby residues and have been identified in healthy populations. Venus is built upon MichelaNGLO and the results can be exported to it, allowing them to be annotated and shared with other researchers. Venus is freely accessible at https://venus.cmd.ox.ac.uk and its source code is openly available at https:// github.com/CMD-Oxford/Michelanglo-and-Venus. (C) 2022 The Author(s). Published by Elsevier Ltd.
引用
收藏
页数:13
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