%0 Journal Article
%T DrugScorePPI Knowledge-Based Potentials Used as Scoring and Objective Function in Protein-Protein Docking
%A Dennis M. Kr¨¹ger
%A Jos¨¦ Ignacio Garz¨®n
%A Pablo Chac¨®n
%A Holger Gohlke
%J PLOS ONE
%D 2014
%I Public Library of Science (PLoS)
%R 10.1371/journal.pone.0089466
%X The distance-dependent knowledge-based DrugScorePPI potentials, previously developed for in silico alanine scanning and hot spot prediction on given structures of protein-protein complexes, are evaluated as a scoring and objective function for the structure prediction of protein-protein complexes. When applied for ranking ¡°unbound perturbation¡± (¡°unbound docking¡±) decoys generated by Baker and coworkers a 4-fold (1.5-fold) enrichment of acceptable docking solutions in the top ranks compared to a random selection is found. When applied as an objective function in FRODOCK for bound protein-protein docking on 97 complexes of the ZDOCK benchmark 3.0, DrugScorePPI/FRODOCK finds up to 10% (15%) more high accuracy solutions in the top 1 (top 10) predictions than the original FRODOCK implementation. When used as an objective function for global unbound protein-protein docking, fair docking success rates are obtained, which improve by ~2-fold to 18% (58%) for an at least acceptable solution in the top 10 (top 100) predictions when performing knowledge-driven unbound docking. This suggests that DrugScorePPI balances well several different types of interactions important for protein-protein recognition. The results are discussed in view of the influence of crystal packing and the type of protein-protein complex docked. Finally, a simple criterion is provided with which to estimate a priori if unbound docking with DrugScorePPI/FRODOCK will be successful.
%U http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0089466