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

J Mol Biol. 2022 Jun 15;434(11):167567. doi: 10.1016/j.jmb.2022.167567. Epub 2022 Mar 29.


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 and its source code is openly available at

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Amino Acid Substitution* / genetics
  • Computational Biology / methods
  • Disease* / genetics
  • Genetic Code
  • Humans
  • Internet Use*
  • Protein Conformation*
  • Proteins* / chemistry
  • Proteins* / genetics
  • Software*


  • Proteins