A new scoring function for protein-protein docking that identifies native structures with unprecedented accuracy

Phys Chem Chem Phys. 2015 Jan 28;17(4):2378-87. doi: 10.1039/c4cp04688a. Epub 2014 Dec 9.


Protein-protein (P-P) 3D structures are fundamental to structural biology and drug discovery. However, most of them have never been determined. Many docking algorithms were developed for that purpose, but they have a very limited accuracy in generating native-like structures and identifying the most correct one, in particular when a single answer is asked for. With such a low success rate it is difficult to point out one docked structure as being native-like. Here we present a new, high accuracy, scoring method to identify the 3D structure of P-P complexes among a set of trial poses. It incorporates alanine scanning mutagenesis experimental data that need to be obtained a priori. The scoring scheme works by matching the computational and the experimental alanine scanning mutagenesis results. The size of the trial P-P interface area is also taken into account. We show that the method ranks the trial structures and identifies the native-like structures with unprecedented accuracy (∼94%), providing the correct P-P 3D structures that biochemists and molecular biologists need to pursue their studies. With such a success rate, the bottleneck of protein-protein docking moves from the scoring to searching algorithms.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Molecular Docking Simulation / methods*
  • Protein Binding
  • Proteins / chemistry*
  • Proteins / metabolism*
  • Software


  • Proteins