Docking prediction using biological information, ZDOCK sampling technique, and clustering guided by the DFIRE statistical energy function

Chi Zhang, Song Liu, Yaoqi Zhou

Research output: Contribution to journalArticle

35 Citations (Scopus)

Abstract

We entered the CAPRI experiment during the middle of Round 4 and have submitted predictions for all 6 targets released since then. We used the following procedures for docking prediction: (1) the identification of possible binding region (s) of a target based on known biological information, (2) rigid-body sampling around the binding region(s) by using the docking program ZDOCK, (3) ranking of the sampled complex conformations by employing the DFIRE-based statistical energy function, (4) clustering based on pairwise root-mean-square distance and the DFIRE energy, and (5) manual inspection and relaxation of the side-chain conformations of the top-ranked structures by geometric constraint. Reasonable predictions were made for 4 of the 6 targets. The best fraction of native contacts within the top 10 models are 89.1% for Target 12, 54.3% for Target 13, 29.3% for Target 14, and 94.1% for Target 18. The origin of successes and failures is discussed.

Original languageEnglish (US)
Pages (from-to)314-318
Number of pages5
JournalProteins: Structure, Function and Genetics
Volume60
Issue number2
DOIs
StatePublished - Aug 1 2005

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Cluster Analysis
Sampling
Conformations
Inspection
Experiments

Keywords

  • CAPRI
  • Docking
  • Knowledge-based potential
  • Protein-protein interaction

ASJC Scopus subject areas

  • Structural Biology
  • Biochemistry
  • Molecular Biology

Cite this

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abstract = "We entered the CAPRI experiment during the middle of Round 4 and have submitted predictions for all 6 targets released since then. We used the following procedures for docking prediction: (1) the identification of possible binding region (s) of a target based on known biological information, (2) rigid-body sampling around the binding region(s) by using the docking program ZDOCK, (3) ranking of the sampled complex conformations by employing the DFIRE-based statistical energy function, (4) clustering based on pairwise root-mean-square distance and the DFIRE energy, and (5) manual inspection and relaxation of the side-chain conformations of the top-ranked structures by geometric constraint. Reasonable predictions were made for 4 of the 6 targets. The best fraction of native contacts within the top 10 models are 89.1{\%} for Target 12, 54.3{\%} for Target 13, 29.3{\%} for Target 14, and 94.1{\%} for Target 18. The origin of successes and failures is discussed.",
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