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    Exploiting Homology Information in Nontemplate Based Prediction of Protein Structures

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    Type
    Article
    Authors
    Iacoangeli, Alfredo
    Marcatili, Paolo
    Tramontano, Anna
    KAUST Grant Number
    KUK-I1-012-43
    PRIN 20108XYHJS
    Date
    2015
    Permanent link to this record
    http://hdl.handle.net/10754/673082
    
    Metadata
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    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.
    Citation
    Iacoangeli, 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
    Sponsors
    This work was supported by the King Abdullah University of Science and Technology (KAUST), Award Number KUK-I1-012-43 and PRIN 20108XYHJS.
    Publisher
    AMER CHEMICAL SOC
    Journal
    JOURNAL OF CHEMICAL THEORY AND COMPUTATION
    DOI
    10.1021/acs.jctc.5b00371
    Additional Links
    https://pubs.acs.org/doi/10.1021/acs.jctc.5b00371
    ae974a485f413a2113503eed53cd6c53
    10.1021/acs.jctc.5b00371
    Scopus Count
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