Optimizing energy potential for protein fold recognition with parametric evaluation function

Junfeng Gu, Honglin Li, Hualiang Jiang, Xicheng Wang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

In this paper, a new optimization method is proposed to determine a simplified energy potential for protein fold recognition, which consists of the residue-residue contact, hydrophobicity, and pseudodihedral potentials. With a parametric evaluation function method, the Z-scores of all the proteins in a training set are optimized simultaneously to obtain the best parameter set of the potential. For this multi-objective and multi-constraint problem, the new optimization scheme is very effective. The derived potential is then tested on two high-quality decoy sets and compared with other classical fold recognition potentials. With the simplified energy potential, we achieve a high level of discrimination capability between correct and incorrect folds.

Original languageEnglish
Pages (from-to)427-441
Number of pages15
JournalJournal of Computational Biology
Volume16
Issue number3
DOIs
StatePublished - 1 Mar 2009
Externally publishedYes

Keywords

  • Parametric evaluation function method
  • Potential function
  • Protein fold recognition

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