4.3 Article

Community-wide evaluation of methods for predicting the effect of mutations on protein-protein interactions

期刊

PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
卷 81, 期 11, 页码 1980-1987

出版社

WILEY
DOI: 10.1002/prot.24356

关键词

CAPRI; hemagglutinin; binding; deep mutational scanning; yeast display

资金

  1. National Science Foundation [DBI-0845196, IOS-1126992]
  2. Spanish Ministry of Science [BIO2010-22324]
  3. Defense Threat Reduction Agency [HDTRA1-10-0040]
  4. Direct For Biological Sciences
  5. Division Of Integrative Organismal Systems [1126992] Funding Source: National Science Foundation
  6. Div Of Biological Infrastructure
  7. Direct For Biological Sciences [1147082] Funding Source: National Science Foundation
  8. Div Of Biological Infrastructure
  9. Direct For Biological Sciences [0845196] Funding Source: National Science Foundation
  10. Grants-in-Aid for Scientific Research [23370071] Funding Source: KAKEN
  11. Cancer Research UK [10748] Funding Source: researchfish

向作者/读者索取更多资源

Community-wide blind prediction experiments such as CAPRI and CASP provide an objective measure of the current state of predictive methodology. Here we describe a community-wide assessment of methods to predict the effects of mutations on protein-protein interactions. Twenty-two groups predicted the effects of comprehensive saturation mutagenesis for two designed influenza hemagglutinin binders and the results were compared with experimental yeast display enrichment data obtained using deep sequencing. The most successful methods explicitly considered the effects of mutation on monomer stability in addition to binding affinity, carried out explicit side-chain sampling and backbone relaxation, evaluated packing, electrostatic, and solvation effects, and correctly identified around a third of the beneficial mutations. Much room for improvement remains for even the best techniques, and large-scale fitness landscapes should continue to provide an excellent test bed for continued evaluation of both existing and new prediction methodologies. Proteins 2013; 81:1980-1987. (c) 2013 Wiley Periodicals, Inc.

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