DynaMut2: Assessing changes in stability and flexibility upon single and multiple point missense mutations

Predicting the effect of missense variations on protein stability and dynamics is important for understanding their role in diseases, and the link between protein structure and function. Approaches to estimate these changes have been proposed, but most only consider single‐point missense variants an...

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Bibliographic Details
Published in:	Protein science 2021-01, Vol.30 (1), p.60-69
Main Authors:	Rodrigues, Carlos H.M., Pires, Douglas E.V., Ascher, David B.
Format:	Article
Language:	eng
Subjects:	Dynamic stability dynamics Environmental effects Flexibility Free energy Gibbs free energy graph‐based signatures Internet Melt temperature Missense mutation missense mutations Mutation Mutation, Missense Point Mutation Protein Stability Protein structure Proteins Proteins - chemistry Proteins - genetics Servers Software Stability analysis stability changes Structure-function relationships Tools for Protein Science
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Summary:	Predicting the effect of missense variations on protein stability and dynamics is important for understanding their role in diseases, and the link between protein structure and function. Approaches to estimate these changes have been proposed, but most only consider single‐point missense variants and a static state of the protein, with those that incorporate dynamics are computationally expensive. Here we present DynaMut2, a web server that combines Normal Mode Analysis (NMA) methods to capture protein motion and our graph‐based signatures to represent the wildtype environment to investigate the effects of single and multiple point mutations on protein stability and dynamics. DynaMut2 was able to accurately predict the effects of missense mutations on protein stability, achieving Pearson's correlation of up to 0.72 (RMSE: 1.02 kcal/mol) on a single point and 0.64 (RMSE: 1.80 kcal/mol) on multiple‐point missense mutations across 10‐fold cross‐validation and independent blind tests. For single‐point mutations, DynaMut2 achieved comparable performance with other methods when predicting variations in Gibbs Free Energy (ΔΔG) and in melting temperature (ΔTm). We anticipate our tool to be a valuable suite for the study of protein flexibility analysis and the study of the role of variants in disease. DynaMut2 is freely available as a web server and API at http://biosig.unimelb.edu.au/dynamut2.
ISSN:	0961-8368 1469-896X