An improved pair potential to recognize native protein folds.
We present a novel method to improve a simple pair potential of mean force, derived from experimentally determined protein structures, in such a way that it recognizes native protein folds with high reliability. This improvement is based on the use of mutation data matrices to overcome difficulties arising from the poor statistics of small sample sizes. A set of 167 protein chains taken from the Brookhaven Protein Structure Data Base, selected from high-resolution structures and avoiding homologous proteins, is used for generation of the potential set. The potential describes interresidue pair energies depending on distance and sequential separation, and is calculated using the Boltzmann equation. Its performance is evaluated by jackknife tests that try to identify the native fold for a given sequence among a large number of possible threadings on all structures in the set without allowing for gaps. Up to 94% of the protein chains are correctly assigned to their native folds, so that all proper single-chain domains are recognized.
Bauer
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Research Institute of Molecular Pathology, Vienna, Austria.
Beyer
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D003198:Computer Simulation; D016208:Databases, Factual; D008432:Mathematical Computing; D008956:Models, Chemical; D017510:Protein Folding; D017433:Protein Structure, Secondary; D017434:Protein Structure, Tertiary