Literature DB >> 14517980

TOUCHSTONEX: protein structure prediction with sparse NMR data.

Wei Li1, Yang Zhang, Daisuke Kihara, Yuanpeng Janet Huang, Deyou Zheng, Gaetano T Montelione, Andrzej Kolinski, Jeffrey Skolnick.   

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. Copyright 2003 Wiley-Liss, Inc.

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Year:  2003        PMID: 14517980     DOI: 10.1002/prot.10499

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  21 in total

1.  TOUCHSTONE II: a new approach to ab initio protein structure prediction.

Authors:  Yang Zhang; Andrzej Kolinski; Jeffrey Skolnick
Journal:  Biophys J       Date:  2003-08       Impact factor: 4.033

2.  Application of sparse NMR restraints to large-scale protein structure prediction.

Authors:  Wei Li; Yang Zhang; Jeffrey Skolnick
Journal:  Biophys J       Date:  2004-08       Impact factor: 4.033

3.  Generation of native-like protein structures from limited NMR data, modern force fields and advanced conformational sampling.

Authors:  Jianhan Chen; Hyung-Sik Won; Wonpil Im; H Jane Dyson; Charles L Brooks
Journal:  J Biomol NMR       Date:  2005-01       Impact factor: 2.835

4.  TASSER-Lite: an automated tool for protein comparative modeling.

Authors:  Shashi Bhushan Pandit; Yang Zhang; Jeffrey Skolnick
Journal:  Biophys J       Date:  2006-09-08       Impact factor: 4.033

5.  An automated assignment-free Bayesian approach for accurately identifying proton contacts from NOESY data.

Authors:  Ling-Hong Hung; Ram Samudrala
Journal:  J Biomol NMR       Date:  2006-10-03       Impact factor: 2.835

6.  Protein structure calculation with data imputation: the use of substitute restraints.

Authors:  Carolina Cano; Konrad Brunner; Kumaran Baskaran; Ralph Elsner; Claudia E Munte; Hans Robert Kalbitzer
Journal:  J Biomol NMR       Date:  2009-10-17       Impact factor: 2.835

7.  Using NMR Chemical Shifts and Cryo-EM Density Restraints in Iterative Rosetta-MD Protein Structure Refinement.

Authors:  Sumudu P Leelananda; Steffen Lindert
Journal:  J Chem Inf Model       Date:  2019-12-24       Impact factor: 4.956

8.  BCL::Fold--protein topology determination from limited NMR restraints.

Authors:  Brian E Weiner; Nathan Alexander; Louesa R Akin; Nils Woetzel; Mert Karakas; Jens Meiler
Journal:  Proteins       Date:  2013-10-17

Review 9.  Hybrid methods for combined experimental and computational determination of protein structure.

Authors:  Justin T Seffernick; Steffen Lindert
Journal:  J Chem Phys       Date:  2020-12-28       Impact factor: 3.488

10.  Modeling helical proteins using residual dipolar couplings, sparse long-range distance constraints and a simple residue-based force field.

Authors:  Becky L Eggimann; Vitaly V Vostrikov; Gianluigi Veglia; J Ilja Siepmann
Journal:  Theor Chem Acc       Date:  2013-10-01       Impact factor: 1.702

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