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Proteins. 2015 Aug;83(8):1436-49. doi: 10.1002/prot.24829. Epub 2015 Jun 6.

CONFOLD: Residue-residue contact-guided ab initio protein folding.

Author information

1
Department of Computer Science, University of Missouri, Columbia, Missouri, 65211.

Abstract

Predicted protein residue-residue contacts can be used to build three-dimensional models and consequently to predict protein folds from scratch. A considerable amount of effort is currently being spent to improve contact prediction accuracy, whereas few methods are available to construct protein tertiary structures from predicted contacts. Here, we present an ab initio protein folding method to build three-dimensional models using predicted contacts and secondary structures. Our method first translates contacts and secondary structures into distance, dihedral angle, and hydrogen bond restraints according to a set of new conversion rules, and then provides these restraints as input for a distance geometry algorithm to build tertiary structure models. The initially reconstructed models are used to regenerate a set of physically realistic contact restraints and detect secondary structure patterns, which are then used to reconstruct final structural models. This unique two-stage modeling approach of integrating contacts and secondary structures improves the quality and accuracy of structural models and in particular generates better β-sheets than other algorithms. We validate our method on two standard benchmark datasets using true contacts and secondary structures. Our method improves TM-score of reconstructed protein models by 45% and 42% over the existing method on the two datasets, respectively. On the dataset for benchmarking reconstructions methods with predicted contacts and secondary structures, the average TM-score of best models reconstructed by our method is 0.59, 5.5% higher than the existing method. The CONFOLD web server is available at http://protein.rnet.missouri.edu/confold/.

KEYWORDS:

ab initio protein folding; contact assisted protein structure prediction; optimization; protein residue-residue contacts; protein structure modeling

PMID:
25974172
PMCID:
PMC4509844
DOI:
10.1002/prot.24829
[Indexed for MEDLINE]
Free PMC Article

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