loading page

Improved protein docking by predicted interface residues.
  • Gabriele Pozzati,
  • Petras Kundrotas,
  • Arne Elofsson
Gabriele Pozzati
Stockholms Universitet Institutionen for biokemi och biofysik

Corresponding Author:gabriele.pozzati@scilifelab.se

Author Profile
Petras Kundrotas
Stockholms Universitet Institutionen for biokemi och biofysik
Author Profile
Arne Elofsson
Stockholms Universitet Institutionen for biokemi och biofysik
Author Profile

Abstract

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 fails for most targets. Here, we examine the possibility of utilising predicted residues on a protein-protein interface to score docking models generated during the scan stage of a docking algorithm. Many methods have been developed to infer the portions of a protein surface that interact with another protein, but most have not been benchmarked using docking algorithms. Different interface prediction methods are systematically tested for scoring >300.000 low-resolution rigid-body template free docking decoys. Overall we find that BIPSPI is the best method to identify interface amino acids and score docking solutions. Further, using BIPSPI provides better docking results than state of the art scoring functions, with >12% 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. We also discussed several limitations for the adoption of interface predictions as constraints in a docking protocol.
28 Aug 2021Submitted to PROTEINS: Structure, Function, and Bioinformatics
31 Aug 2021Submission Checks Completed
31 Aug 2021Assigned to Editor
07 Sep 2021Reviewer(s) Assigned
07 Oct 2021Review(s) Completed, Editorial Evaluation Pending
12 Oct 2021Editorial Decision: Revise Major
12 Jan 20221st Revision Received
21 Jan 2022Submission Checks Completed
21 Jan 2022Assigned to Editor
21 Jan 2022Reviewer(s) Assigned
07 Feb 2022Review(s) Completed, Editorial Evaluation Pending
16 Feb 2022Editorial Decision: Revise Minor
23 Feb 20222nd Revision Received
24 Feb 2022Submission Checks Completed
24 Feb 2022Assigned to Editor
28 Feb 2022Review(s) Completed, Editorial Evaluation Pending
01 Mar 2022Editorial Decision: Accept