Journal
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
Volume 78, Issue 14, Pages 2950-2960Publisher
WILEY
DOI: 10.1002/prot.22817
Keywords
knowledge-based potentials; protein aggregation; coarse grained; models; protein force field
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Funding
- National Institutes of Health, USA [GM56766, EB006006]
- National Creative Research Initiatives (Center for Proteome Biophysics) of National Research Foundation/Ministry of Education, Science and Technology, Korea [2008-0061984]
- National Research Foundation of Korea [2008-0061984] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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We extend PRIME, an intermediate-resolution protein model previously used in simulations of the aggregation of polyalanine and polyglutamine, to the description of the geometry and energetics of peptides containing all 20 amino acid residues. The 20 amino acid side chains are classified into 14 groups according to their hydrophobicity, polarity, size, charge, and potential for side chain hydrogen bonding. The parameters for extended PRIME, called PRIME 20, include hydrogen-bonding energies, side chain interaction range and energy, and excluded volume. The parameters are obtained by applying a perceptron-learning algorithm and a modified stochastic learning algorithm that optimizes the energy gap between 711 known native states from the PDB and decoy structures generated by gapless threading. The number of independent pair interaction parameters is chosen to be small enough to be physically meaningful yet large enough to give reasonably accurate results in discriminating decoys from native structures. The most physically meaningful results are obtained with 19 energy parameters.
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