Scoring of protein–protein docking models utilizing predicted interface residues
Autor: | Gabriele Pozzati, Petras Kundrotas, Arne Elofsson |
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Rok vydání: | 2022 |
Předmět: | |
Zdroj: | Proteins: Structure, Function, and Bioinformatics. 90:1493-1505 |
ISSN: | 1097-0134 0887-3585 |
Popis: | Scoring docking solutions is a difficult task, and many methods have been developed for this purpose. In docking, only a handful of the hundreds of thousands of models generated by docking algorithms are acceptable, causing difficulties when developing scoring functions. Today's best scoring functions can significantly increase the number of top-ranked models but still fail for most targets. Here, we examine the possibility of utilizing predicted interface residues to score docking models generated during the scan stage of a docking algorithm. Many methods have been developed to infer the regions of a protein surface that interact with another protein, but most have not been benchmarked using docking algorithms. This study systematically tests different interface prediction methods for scoring300.000 low-resolution rigid-body template free docking decoys. Overall we find that contact-based interface prediction by BIPSPI is the best method to score docking solutions, with12% of first ranked docking models being acceptable. Additional experiments indicated precision as a high-importance metric when estimating interface prediction quality, focusing on docking constraints production. Finally, we discussed several limitations for adopting interface predictions as constraints in a docking protocol. |
Databáze: | OpenAIRE |
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