A new scoring function for protein-protein docking that identifies native structures with unprecedented accuracy
Research output: Contribution to journal › Journal article › Research › peer-review
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. This journal is
Original language | English |
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Journal | Physical Chemistry Chemical Physics |
Volume | 17 |
Issue number | 4 |
Pages (from-to) | 2378-2387 |
Number of pages | 10 |
ISSN | 1463-9076 |
DOIs | |
Publication status | Published - 2015 |
ID: 153377409