Prediction and scoring of docking poses with pyDock

Solène Grosdidier, Carles Pons, Albert Solernou, Juan Fernández-Recio

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

The two previous CAPRI experiments showed the success of our rigid-body and refinement approach. For this third edition of CAPRI, we have used a new faster protocol called pyDock, which uses electrostatics and desolvation energy to score docking poses generated with FFT-based algorithms. In target T24 (unbound/ model), our best prediction had the highest value of fraction of native contacts (40%) among all participants, although it was not considered as acceptable by the CAPRI criteria. In target T25 (unbound/bound), we submitted a model with medium quality. In target T26 (unbound/unbound), we did not submit any acceptable model (but we would have submitted acceptable predictions if we had included available mutational information about the binding site). For targets T27 (unbound/unbound) and T28 (homo-dimer using model), nobody (including us) submitted any acceptable model. Intriguingly, the crystal structure of target T27 shows an alternative interface that correlates with available biological data (we would have submitted acceptable predictions if we had included this). We aho participated in all targets of the SCORERS experiment, with at least acceptable accuracy in all valid cases. We submitted two medium and four acceptable scoring models of T25. Using additional distance restraints (from mutational data), we had two medium and two acceptable scoring models of T26. For target T27, we submitted two acceptable scoring models of the alternative interface in the crystal structure. In summary, CAPRI showed the excellent capabilities of pyDock in identifying near-native docking poses.

Original languageEnglish (US)
Pages (from-to)852-858
Number of pages7
JournalProteins: Structure, Function and Genetics
Volume69
Issue number4
DOIs
StatePublished - Dec 1 2007

Keywords

  • CAPRI
  • Desolvation energy
  • Electrostatics
  • Protein-protein docking
  • PyDock

Fingerprint Dive into the research topics of 'Prediction and scoring of docking poses with pyDock'. Together they form a unique fingerprint.

Cite this