Exploiting Homology Information in Nontemplate Based Prediction of Protein Structures

Alfredo Iacoangeli, Paolo Marcatili, Anna Tramontano

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


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.
Original languageEnglish (US)
Pages (from-to)5045-5051
Number of pages7
Issue number10
StatePublished - 2015
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2021-11-04
Acknowledged KAUST grant number(s): KUK-I1-012-43, PRIN 20108XYHJS
Acknowledgements: This work was supported by the King Abdullah University of Science and Technology (KAUST), Award Number KUK-I1-012-43 and PRIN 20108XYHJS.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

ASJC Scopus subject areas

  • Physical and Theoretical Chemistry
  • Computer Science Applications


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