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DrugScorePPI knowledge-based potentials used as scoring and objective function in protein-protein docking

AutorKrüger, D.M.; Garzón, José Ignacio ; Chacón, Pablo ; Gohlke, H.
Fecha de publicación2014
EditorPublic Library of Science
CitaciónPLoS ONE 9 (2014)
ResumenThe 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. © 2014 Krüger et al.
URIhttp://hdl.handle.net/10261/167568
Identificadoresdoi: 10.1371/journal.pone.0089466
issn: 1932-6203
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