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  • 标题:MutaBind2: Predicting the Impacts of Single and Multiple Mutations on Protein-Protein Interactions
  • 本地全文:下载
  • 作者:Ning Zhang ; Yuting Chen ; Haoyu Lu
  • 期刊名称:iScience
  • 印刷版ISSN:2589-0042
  • 出版年度:2020
  • 卷号:23
  • 期号:3
  • 页码:1-38
  • DOI:10.1016/j.isci.2020.100939
  • 语种:English
  • 出版社:Elsevier
  • 摘要:SummaryMissense mutations may affect proteostasis by destabilizing or over-stabilizing protein complexes and changing the pathway flux. Predicting the effects of stabilizing mutations on protein-protein interactions is notoriously difficult because existing experimental sets are skewed toward mutations reducing protein-protein binding affinity and many computational methods fail to correctly evaluate their effects. To address this issue, we developed a method MutaBind2, which estimates the impacts of single as well as multiple mutations on protein-protein interactions. MutaBind2 employs only seven features, and the most important of them describe interactions of proteins with the solvent, evolutionary conservation of the site, and thermodynamic stability of the complex and each monomer. This approach shows a distinct improvement especially in evaluating the effects of mutations increasing binding affinity. MutaBind2 can be used for finding disease driver mutations, designing stable protein complexes, and discovering new protein-protein interaction inhibitors.Graphical AbstractDisplay OmittedHighlights•A new method to predict binding affinity changes upon single and multiple mutations•Improved performance in evaluating the effects of mutations increasing binding affinity•Generation of the structural model of a mutant complexProtein Folding; Bioinformatics; 3D Reconstruction of Protein
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