In 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.

Exploiting Homology Information in Nontemplate Based Prediction of Protein Structures / Iacoangeli, Alfredo; Marcatili, Paolo; Tramontano, Anna. - In: JOURNAL OF CHEMICAL THEORY AND COMPUTATION. - ISSN 1549-9618. - STAMPA. - 11:10(2015), pp. 5045-5051. [10.1021/acs.jctc.5b00371]

Exploiting Homology Information in Nontemplate Based Prediction of Protein Structures

Iacoangeli, Alfredo;Marcatili, Paolo;Tramontano, Anna
2015

Abstract

In 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.
2015
Physical and Theoretical Chemistry; Computer Science Applications1707 Computer Vision and Pattern Recognition
01 Pubblicazione su rivista::01a Articolo in rivista
Exploiting Homology Information in Nontemplate Based Prediction of Protein Structures / Iacoangeli, Alfredo; Marcatili, Paolo; Tramontano, Anna. - In: JOURNAL OF CHEMICAL THEORY AND COMPUTATION. - ISSN 1549-9618. - STAMPA. - 11:10(2015), pp. 5045-5051. [10.1021/acs.jctc.5b00371]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/862540
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