Exploiting Homology Information in Nontemplate Based Prediction of Protein Structures
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AbstractIn this paper we describe a novel strategy for exploring the conformational space of proteins and show that this leads to better models for proteins the structure of which is not amenable to template based methods. Our strategy is based on the assumption that the energy global minimum of homologous proteins must correspond to similar conformations, while the precise profiles of their energy landscape, and consequently the positions of the local minima, are likely to be different. In line with this hypothesis, we apply a replica exchange Monte Carlo simulation protocol that, rather than using different parameters for each parallel simulation, uses the sequences of homologous proteins. We show that our results are competitive with respect to alternative methods, including those producing the best model for each of the analyzed targets in the CASP10 (10th Critical Assessment of techniques for protein Structure Prediction) experiment free modeling category.
CitationIacoangeli, A., Marcatili, P., & Tramontano, A. (2015). Exploiting Homology Information in Nontemplate Based Prediction of Protein Structures. Journal of Chemical Theory and Computation, 11(10), 5045–5051. doi:10.1021/acs.jctc.5b00371
SponsorsThis work was supported by the King Abdullah University of Science and Technology (KAUST), Award Number KUK-I1-012-43 and PRIN 20108XYHJS.
PublisherAMER CHEMICAL SOC