Hotspot Coevolution Is a Key Identifier of Near-Native Protein Complexes

Sambit K. Mishra, Connor J. Cooper, Jerry M. Parks, Julie C. Mitchell

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Protein-protein interactions play a key role in mediating numerous biological functions, with more than half the proteins in living organisms existing as either homo- or hetero-oligomeric assemblies. Protein subunits that form oligomers minimize the free energy of the complex, but exhaustive computational search-based docking methods have not comprehensively addressed the challenge of distinguishing a natively bound complex from non-native forms. Current protein docking approaches address this problem by sampling multiple binding modes in proteins and scoring each mode, with the lowest-energy (or highest scoring) binding mode being regarded as a near-native complex. However, high-scoring modes often match poorly with the true bound form, suggesting a need for improvement of the scoring function. In this study, we propose a scoring function, KFC-E, that accounts for both conservation and coevolution of putative binding hotspot residues at protein-protein interfaces. We tested KFC-E on four benchmark sets of unbound examples and two benchmark sets of bound examples, with the results demonstrating a clear improvement over scores that examine conservation and coevolution across the entire interface.

Original languageEnglish
Pages (from-to)6058-6067
Number of pages10
JournalJournal of Physical Chemistry B
Volume125
Issue number23
DOIs
StatePublished - Jun 17 2021

Funding

C.J.C. was supported by NIH/NIGMS-IMSD Grant No. R25GM086761 and a National Science Foundation Graduate Research Fellowship under Grant No. (2017219379). J.M.P., J.C.M., and S.K.M. were supported by the Laboratory Directed Research and Development program at Oak Ridge National Laboratory, which is managed by UT-Battelle, LLC, for the DOE under Contract No. DE-AC05-00OR22725. This work used resources of the Compute and Data Environment for Science (CADES) at ORNL. The authors thank Sergey Ovchinnikov for sharing the BD1 and UD1 datasets of bound and unbound protein–protein complexes. The authors also thank Marc Lensick for helping guide the selection of CAPRI Round 30 examples in UD4.

FundersFunder number
NIGMS-IMSD
National Science Foundation2017219379
National Institutes of Health
U.S. Department of EnergyDE-AC05-00OR22725
National Institute of General Medical SciencesR25GM086761
Oak Ridge National Laboratory

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