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• W2801491392 abstract "Proteins are highly dynamic molecules, whose function is intrinsically linked to their molecular motions. Despite the pivotal role of protein dynamics, their computational simulation cost has led to most structure-based approaches for assessing the impact of mutations on protein structure and function relying upon static structures. Here we present DynaMut, a web server implementing two distinct, well established normal mode approaches, which can be used to analyze and visualize protein dynamics by sampling conformations and assess the impact of mutations on protein dynamics and stability resulting from vibrational entropy changes. DynaMut integrates our graph-based signatures along with normal mode dynamics to generate a consensus prediction of the impact of a mutation on protein stability. We demonstrate our approach outperforms alternative approaches to predict the effects of mutations on protein stability and flexibility (P-value < 0.001), achieving a correlation of up to 0.70 on blind tests. DynaMut also provides a comprehensive suite for protein motion and flexibility analysis and visualization via a freely available, user friendly web server at http://biosig.unimelb.edu.au/dynamut/." @default.
• W2801491392 created "2018-05-17" @default.
• W2801491392 creator A5001797627 @default.
• W2801491392 creator A5071950872 @default.
• W2801491392 creator A5091903225 @default.
• W2801491392 date "2018-04-30" @default.
• W2801491392 modified "2023-10-14" @default.
• W2801491392 title "DynaMut: predicting the impact of mutations on protein conformation, flexibility and stability" @default.
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• W2801491392 doi "https://doi.org/10.1093/nar/gky300" @default.
• W2801491392 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6031064" @default.
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• W2801491392 hasPublicationYear "2018" @default.
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