Inferring the microscopic surface energy of protein-protein interfaces from mutation data

Proteins. 2015 Apr;83(4):640-50. doi: 10.1002/prot.24761. Epub 2015 Feb 5.

Abstract

Mutations at protein-protein recognition sites alter binding strength by altering the chemical nature of the interacting surfaces. We present a simple surface energy model, parameterized with empirical ΔΔG values, yielding mean energies of -48 cal mol(-1) Å(-2) for interactions between hydrophobic surfaces, -51 to -80 cal mol(-1) Å(-2) for surfaces of complementary charge, and 66-83 cal mol(-1) Å(-2) for electrostatically repelling surfaces, relative to the aqueous phase. This places the mean energy of hydrophobic surface burial at -24 cal mol(-1) Å(-2) . Despite neglecting configurational entropy and intramolecular changes, the model correlates with empirical binding free energies of a functionally diverse set of rigid-body interactions (r = 0.66). When used to rerank docking poses, it can place near-native solutions in the top 10 for 37% of the complexes evaluated, and 82% in the top 100. The method shows that hydrophobic burial is the driving force for protein association, accounting for 50-95% of the cohesive energy. The model is available open-source from http://life.bsc.es/pid/web/surface_energy/ and via the CCharpPPI web server http://life.bsc.es/pid/ccharppi/.

Keywords: binding affinity; docking; empirical modeling; hydrophobic effect; interaction energy; mutation; protein-protein interactions.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Hydrophobic and Hydrophilic Interactions
  • Molecular Docking Simulation
  • Mutation / physiology*
  • Protein Binding*
  • Proteins / chemistry*
  • Proteins / metabolism*
  • Static Electricity
  • Thermodynamics

Substances

  • Proteins