Template-based protein-protein docking exploiting pairwise interfacial residue restraints

Li C. Xue, Joãao P.G.L.M. Rodrigues, Drena Dobbs, Vasant Honavar, Alexandre M.J.J. Bonvin

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


Although many advanced and sophisticated ab initio approaches for modeling protein-protein complexes have been proposed in past decades, template-based modeling (TBM) remains the most accurate and widely used approach, given a reliable template is available. However, there are many different ways to exploit template information in the modeling process. Here, we systematically evaluate and benchmark a TBM method that uses conserved interfacial residue pairs as docking distance restraints [referred to as alpha carbon-alpha carbon (CA-CA)-guided docking].We compare it with two other template- based protein-protein modeling approaches, including a conserved non-pairwise interfacial residue restrained docking approach [referred to as the ambiguous interaction restraint (AIR)-guided docking] and a simple superposition-based modeling approach. Our results show that, for most cases, the CA-CA-guided docking method outperforms both superposition with refinement and the AIR-guided docking method. We emphasize the superiority of the CA-CA-guided docking on cases with medium to large conformational changes, and interactions mediated through loops, tails or disordered regions. Our results also underscore the importance of a proper refinement of superimposition models to reduce steric clashes. In summary, we provide a benchmarked TBM protocol that uses conserved pairwise interface distance as restraints in generating realistic 3D protein-protein interaction models, when reliable templates are available. The described CA-CA-guided docking protocol is based on the HADDOCK platform, which allows users to incorporate additional prior knowledge of the target system to further improve the quality of the resulting models.

Original languageEnglish (US)
Pages (from-to)458-466
Number of pages9
JournalBriefings in bioinformatics
Issue number3
StatePublished - May 1 2017

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Molecular Biology


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