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Improved protein structure selection using decoy-dependent discriminatory functions.

Kai Wang1, Boris Fain, Michael Levitt

  • 1Department of Microbiology, University of Washington School of Medicine, Seattle, WA 98195, USA. dna@u.washington.edu

BMC Structural Biology
|June 23, 2004
PubMed
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We developed new scoring functions, density score and self-RAPDF, to better select accurate protein structures from predicted models. These methods improve protein structure prediction accuracy by utilizing information within the decoy set itself.

Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Protein Structure Prediction

Background:

  • Accurate scoring functions are crucial for distinguishing native protein conformations from misfolded ones.
  • Existing scoring functions often show inadequate performance and poor correlation with prediction accuracy.
  • There is a need for improved methods to select accurate protein structures from generated decoys.

Purpose of the Study:

  • To develop and evaluate novel decoy-dependent scoring functions for enhanced protein structure selection.
  • To assess the performance of a new density score function and a self-residue-specific all-atom probability discriminatory function (self-RAPDF).

Main Methods:

  • Introduced the density score function, calculating all-against-all C-alpha Root Mean Square Deviation (RMSD) within a decoy set.

Related Experiment Videos

  • Developed self-RAPDF, a decoy-dependent function using atom-atom contact probabilities from the decoy set, weighted by density scores.
  • Tested both functions on 83 diverse decoy sets generated by various methods.

    • Main Results:

    • The density score function demonstrated high correlations (up to 0.9) with C-alpha RMSD.
    • Self-RAPDF showed higher correlation with C-alpha RMSD than the previous RAPDF for 76 out of 83 decoy sets.
    • Self-RAPDF successfully selected superior near-native conformations in 62 out of 83 decoy sets.

    Conclusions:

    • Decoy-dependent scoring functions, like density score and self-RAPDF, significantly improve protein structure selection.
    • Leveraging information from the ensemble of decoy conformations aids in identifying near-native protein structures.
    • These methods hold promise for protein structure refinement and fold simulations.