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Predicting and Experimentally Validating Hot-spot Residues at Protein-Protein Interfaces

Research output: Contribution to journalArticle

Original languageEnglish
JournalACS Chemical Biology
Early online date16 Sep 2019
DOIs
DateAccepted/In press - 16 Sep 2019
DateE-pub ahead of print (current) - 16 Sep 2019

Abstract

Protein-protein interactions (PPIs) are vital to all biological processes. These interactions are often dynamic, sometimes transient, typically occur over large topographically shallow protein surfaces, and can exhibit a broad range of affinities. Considerable progress has been made in determining PPI structures. However, given the above properties, understanding the key determinants of their thermodynamic stability remains a challenge in chemical biology. An improved ability to identify and engineer PPIs would advance understanding of biological mechanisms and mutant phenotypes, and also, provide a firmer foundation for inhibitor design. In silico prediction of PPI hot-spot amino acids using computational alanine scanning (CAS) offers a rapid approach for predicting key residues that drive protein-protein association. This can be applied to all known PPI structures, however there is a trade-off between throughput and accuracy. Here we describe a comparative analysis of multiple CAS methods, which highlights effective approaches to improve the accuracy of predicting hot-spot residues. Alongside this, we introduce a new method, BUDE Alanine Scanning, which can be applied to single structures from crystallography, and to structural ensembles from NMR or molecular dynamics data. The comparative analyses facilitate accurate prediction of hot-spots that we validate experimentally with three diverse targets: NOXA-B/MCL-1 (an α helix-mediated PPI), SIMS/SUMO and GKAP/SHANK-PDZ (both β strand-mediated interactions). Finally, the approach is applied to the accurate prediction of hot-residues at a topographically novel Affimer/BCL-xL protein-protein interface.

Additional information

The acceptance date for this record is provisional and based upon the month of publication for the article.

    Structured keywords

  • Bristol BioDesign Institute
  • BrisSynBio

    Research areas

  • SYNTHETIC BIOLOGY

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    Rights statement: This is the final published version of the article (version of record). It first appeared online via ACS Publications at https://doi.org/10.1021/acschembio.9b00560 . Please refer to any applicable terms of use of the publisher.

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