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Fold assessment for comparative protein structure modeling.

Francisco Melo1, Andrej Sali

  • 1Departamento de Genética Molecular y Microbiología, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Santiago, Chile. fmelo@bio.puc.cl

Protein Science : a Publication of the Protein Society
|October 2, 2007
PubMed
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A new composite score accurately assesses protein structure models, identifying correct folds. This method improves upon existing techniques for evaluating large-scale comparative modeling datasets.

Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Protein Modeling

Background:

  • Accurate assessment of comparative protein structure models is crucial for their reliable application.
  • Existing methods for evaluating model quality, geometrical errors, and incompleteness have limitations.

Purpose of the Study:

  • To develop a composite score for discriminating between correctly and incorrectly folded protein models.
  • To optimize this score using a genetic algorithm for improved accuracy in automated protein modeling.

Main Methods:

  • A genetic algorithm was employed to select the most informative subset from 21 input features.
  • Features included statistical potentials, stereochemistry, sequence alignment, geometry, and packing measures.
  • Nonlinear transformations were optimized to create the composite score.

Related Experiment Videos

Main Results:

  • The optimized composite score effectively combines statistical potential z-scores, model compactness, and sequence identity.
  • This composite score demonstrated superior performance over single or combined features and other common assessment methods.
  • Achieved a high correct classification rate with low false positives (3.3%) and false negatives (2.5%).

Conclusions:

  • The developed composite score provides a robust and accurate method for assessing comparative protein structure models.
  • This advancement is particularly valuable for large-scale automated modeling and database applications.
  • The score is integrated into MODELLER-8 for assessing models in the MODBASE database.