Classification of heterodimer interfaces using docking models and construction of scoring functions for the complex structure prediction

Yuko Tsuchiya, Eiji Kanamori, Haruki Nakamura, Kengo Kinoshita

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Protein-protein docking simulations can provide the predicted complex structural models. In a docking simulation, several putative structural models are selected by scoring functions from an ensemble of many complex models. Scoring functions based on statistical analyses of heterodimers are usually designed to select the complex model with the most abundant interaction mode found among the known complexes, as the correct model. However, because the formation schemes of heterodimers are extremely diverse, a single scoring function does not seem to be sufficient to describe the fitness of the predicted models other than the most abundant interaction mode. Thus, it is necessary to classify the heterodimers in terms of their individual interaction modes, and then to construct multiple scoring functions for each heterodimer type. In this study, we constructed the classification method of heterodimers based on the discriminative characters between near-native and decoy models, which were found in the comparison of the interfaces in terms of the complementarities for the hydrophobicity, the electrostatic potential and the shape. Consequently, we found four heterodimer clusters, and then constructed the multiple scoring functions, each of which was optimized for each cluster. Our multiple scoring functions were applied to the predictions in the unbound docking.

Original languageEnglish
Pages (from-to)79-100
Number of pages22
JournalAdvances and Applications in Bioinformatics and Chemistry
Volume2
Issue number1
DOIs
Publication statusPublished - 2009
Externally publishedYes

Keywords

  • CAPRI
  • Classification of heterodimers
  • Prediction of complex structures
  • Protein-protein docking
  • Scoring functions

ASJC Scopus subject areas

  • Chemistry (miscellaneous)
  • Biochemistry
  • Biochemistry, Genetics and Molecular Biology (miscellaneous)
  • Computer Science Applications

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