Sampling-based methods for a full characterization of energy landscapes of small peptides

Devaurs, Didier and Shehu, Amarda and Siméon, Thierry and Cortés, Juan; Zheng, Huiru and Dubitzky, Werner and Hu, Xiaohua and Hao, Jin-Kao and Berrar, Daniel and Cho, Kwang-Hyun and Wang, Yadong and Gilbert, David, eds. (2015) Sampling-based methods for a full characterization of energy landscapes of small peptides. In: 2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, GBR, pp. 37-44. ISBN 9781479956692 (https://doi.org/10.1109/BIBM.2014.6999124)

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Abstract

Obtaining accurate representations of energy landscapes of biomolecules such as proteins and peptides is central to structure-function studies. Peptides are particularly interesting, as they exploit structural flexibility to modulate their biological function. Despite their small size, peptide modeling remains challenging due to the complexity of the energy landscape of such highly-flexible dynamic systems. Currently, only sampling-based methods can efficiently explore the conformational space of a peptide. In this paper, we suggest to combine two such methods to obtain a full characterization of energy landscapes of small yet flexible peptides. First, we propose a simplified version of the classical Basin Hopping algorithm to quickly reveal the meta-stable structural states of a peptide and the corresponding low-energy basins in the landscape. Then, we present several variants of a robotics-inspired algorithm, the Transition-based Rapidly-exploring Random Tree, to quickly determine transition state and transition path ensembles, as well as transition probabilities between meta-stable states. We demonstrate this combined approach on the terminally-blocked alanine.

ORCID iDs

Devaurs, Didier ORCID logoORCID: https://orcid.org/0000-0002-3415-9816, Shehu, Amarda, Siméon, Thierry and Cortés, Juan; Zheng, Huiru, Dubitzky, Werner, Hu, Xiaohua, Hao, Jin-Kao, Berrar, Daniel, Cho, Kwang-Hyun, Wang, Yadong and Gilbert, David
CORE (COnnecting REpositories)