Venus: Elucidating the Impact of Amino Acid Variants on Protein Function Beyond Structure Destabilisation. Issue 11 (15th June 2022) - Ferla, Matteo P.; Pagnamenta, Alistair T.; Koukouflis, Leonidas; Taylor, Jenny C.; Marsden, Brian D.
Graphical abstract: Highlights: Understanding how a genomic variant relates to pathogenicity is critical. Protein destabilisation, alone, is often not a plausible explanation. Nearby gnomAD variants and Uniprot annotations are often crucial for the hypothesis. We have developed the Venus webapp to help formulate potential hypotheses. Venus incorporates different pieces of information mapped onto structure. Abstract: 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 .