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Identifying native-like protein structures using physics-based potentials.

Brian N Dominy1, Charles L Brooks

  • 1Department of Molecular Biology, The Scripps Research Institute, La Jolla, California 92037, USA.

Journal of Computational Chemistry
|March 27, 2002
PubMed
Summary
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A new physics-based method accurately distinguishes native protein structures from misfolded ones using CHARMM force fields and generalized Born solvation. This approach improves protein structure prediction reliability and identifies misfolded proteins based on energetic and dynamic criteria.

Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Protein Folding

Background:

  • The field of structural genomics requires accurate methods to differentiate reliable protein structure predictions from unreliable ones.
  • Distinguishing native protein conformations from misfolded states is crucial for understanding protein function and disease mechanisms.

Purpose of the Study:

  • To develop and validate a physics-based computational method for discriminating native protein structures from misfolded conformations.
  • To assess the accuracy of the method across various structural databases and protein types.

Main Methods:

  • Utilized the CHARMM gas phase implicit hydrogen force field combined with a generalized Born implicit solvation model.
  • Analyzed pre-constructed databases of protein structures, including threaded structures from EMBL and misfolded proteins from 'Decoys 'R' Us'.

Related Experiment Videos

  • Evaluated energetic properties, specifically solvation energy and intramolecular ionic contacts, and dynamic behavior of protein conformations.

    • Main Results:

    • Achieved over 90% accuracy in identifying misfolded structures across multiple databases (EMBL, globin, Park and Levitt's models).
    • Misfolded states were consistently favored by the solvation term due to mispaired intramolecular ionic contacts.
    • The generalized Born solvation term improved the correlation between energy and structural similarity to native conformations, enhancing prediction reliability.
    • Z-scores computed using the method were comparable to trained and knowledge-based scoring functions.
    • Properly folded proteins exhibited greater stability and diverged less dynamically compared to misfolded counterparts.

    Conclusions:

    • Physics-based force fields, incorporating implicit solvation, are effective tools for identifying native-like protein conformations.
    • The method provides reliable energetic and dynamic criteria for distinguishing between folded and misfolded protein states.
    • The accuracy of discrimination is influenced by the specific characteristics of the structural databases used.