TOUCHSTONEX: protein structure prediction with sparse NMR data.

Wei Li; Yang Zhang; Daisuke Kihara; Yuanpeng Janet Huang; Deyou Zheng; Gaetano T Montelione; Andrzej Kolinski; Jeffrey Skolnick

doi:10.1002/prot.10499

PubMed · 14517980

TOUCHSTONEX: protein structure prediction with sparse NMR data.

Wei Li·Yang Zhang·Daisuke Kihara·Yuanpeng Janet Huang·Deyou Zheng·Gaetano T Montelione·Andrzej Kolinski·Jeffrey Skolnick

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Abstract

TOUCHSTONEX, a new method for folding proteins that uses a small number of long-range contact restraints derived from NMR experimental NOE (nuclear Overhauser enhancement) data, is described. The method employs a new lattice-based, reduced model of proteins that explicitly represents C(alpha), C(beta), and the sidechain centers of mass. The force field consists of knowledge-based terms to produce protein-like behavior, including various short-range interactions, hydrogen bonding, and one-body, pairwise, and multibody long-range interactions. Contact restraints were incorporated into the force field as an NOE-specific pairwise potential. We evaluated the algorithm using a set of 125 proteins of various secondary structure types and lengths up to 174 residues. Using N/8 simulated, long-range sidechain contact restraints, where N is the number of residues, 108 proteins were folded to a C(alpha)-root-mean-square deviation (RMSD) from native below 6.5 A. The average RMSD of the lowest RMSD structures for all 125 proteins (folded and unfolded) was 4.4 A. The algorithm was also applied to limited experimental NOE data generated for three proteins. Using very few experimental sidechain contact restraints, and a small number of sidechain-main chain and main chain-main chain contact restraints, we folded all three proteins to low-to-medium resolution structures. The algorithm can be applied to the NMR structure determination process or other experimental methods that can provide tertiary restraint information, especially in the early stage of structure determination, when only limited data are available.

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Algorithms Amino Acids Models, Molecular Nuclear Magnetic Resonance, Biomolecular Protein Conformation Protein Folding Protein Structure, Tertiary Proteins Staphylococcal Protein A Evaluation Study Journal Article Research Support, U.S. Gov't, P.H.S.

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Wei Li, Yang Zhang, Daisuke Kihara, Yuanpeng Janet Huang, Deyou Zheng, Gaetano T Montelione, Andrzej Kolinski, Jeffrey Skolnick. 2003-11-01. TOUCHSTONEX: protein structure prediction with sparse NMR data.. https://doi.org/10.1002/prot.10499

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