ClusPro: An automated docking and discrimination method for the prediction of protein complexes

Stephen R. Comeau, David W. Gatchell, Sandor Vajda, Carlos J. Camacho*

*Corresponding author for this work

Research output: Contribution to journalArticle

668 Scopus citations

Abstract

Motivation: Predicting protein interactions is one of the most challenging problems in functional genomics. Given two proteins known to interact, current docking methods evaluate billions of docked conformations by simple scoring functions, and in addition to near-native structures yield many false positives, i.e. structures with good surface complementarity but far from the native. Results: We have developed a fast algorithm for filtering docked conformations with good surface complementarity, and ranking them based on their clustering properties. The free energy filters select complexes with lowest desolvation and electrostatic energies. Clustering is then used to smooth the local minima and to select the ones with the broadest energy wells - a property associated with the free energy at the binding site. The robustness of the method was tested on sets of 2000 docked conformations generated for 48 pairs of interacting proteins. In 31 of these cases, the top 10 predictions include at least one near-native complex, with an average RMSD of 5 Å from the native structure. The docking and discrimination method also provides good results for a number of complexes that were used as targets in the Critical Assessment of PRedictions of Interactions experiment.

Original languageEnglish (US)
Pages (from-to)45-50
Number of pages6
JournalBioinformatics
Volume20
Issue number1
DOIs
StatePublished - Jan 1 2004

ASJC Scopus subject areas

  • Statistics and Probability
  • Medicine(all)
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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