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Refining intra-protein contact prediction by graph analysis.

Milana Frenkel-Morgenstern1, Rachel Magid, Eran Eyal

  • 1Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel. milana.frenkel@weizmann.ac.il

BMC Bioinformatics
|July 13, 2007
PubMed
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We developed a graph analysis refinement (GARP) method to improve intra-protein residue contact prediction. GARP enhances basic prediction accuracy by 1.5 times, aiding in protein structure prediction.

Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Protein Science

Background:

  • Accurate prediction of intra-protein residue contacts is crucial for protein structure prediction.
  • Existing methods can be refined by analyzing predicted contacts and their sequence positions.

Purpose of the Study:

  • To introduce and evaluate the Graph Analysis Refinement of intra-protein contacts (GARP) method.
  • To enhance the accuracy of basic intra-protein contact prediction methods.

Main Methods:

  • Developed GARP, a graph-based refinement method for intra-protein contacts.
  • Utilized a previously developed pair-to-pair substitution matrix (P2PConPred) method for initial contact prediction.
  • Constructed a weighted graph using top contact predictions as edges, scored by mutual clustering coefficient and edge density.

Related Experiment Videos

Main Results:

  • GARP improved the accuracy of the P2PConPred method from 12% to 18% on a test set of 57 proteins.
  • The graph analysis refinement significantly enhanced the prediction of intra-protein residue contacts.

Conclusions:

  • The GARP method offers a simple yet effective approach to increase contact prediction accuracy.
  • GARP is compatible with various basic prediction methods and can support downstream analyses.