Journal article

Assessing the performance of computational predictors for estimating protein stability changes upon missense mutations

S Iqbal, F Li, T Akutsu, DB Ascher, GI Webb, J Song

Briefings in Bioinformatics | OXFORD UNIV PRESS | Published : 2021

Abstract

Understanding how a mutation might affect protein stability is of significant importance to protein engineering and for understanding protein evolution genetic diseases. While a number of computational tools have been developed to predict the effect of missense mutations on protein stability protein stability upon mutations, they are known to exhibit large biases imparted in part by the data used to train and evaluate them. Here, we provide a comprehensive overview of predictive tools, which has provided an evolving insight into the importance and relevance of features that can discern the effects of mutations on protein stability. A diverse selection of these freely available tools was benc..

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Grants

Awarded by National Health and Medical Research Council of Australia (NHMRC)


Awarded by Collaborative Research Program of Institute for Chemical Research, Kyoto University


Awarded by National Health and Medical Research Council of Australia


Funding Acknowledgements

This work was financially supported by grants from the National Health and Medical Research Council of Australia (NHMRC) (1144652, 1127948 and 1174405), a Major Inter-Disciplinary Research (IDR) project awarded by Monash University, Dept of Data Science and AI, Faculty of IT, Monash University, and the Collaborative Research Program of Institute for Chemical Research, Kyoto University (2021-28, 201932 and 2018-28), and supported in part by the Victorian Government's OIS Program.