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CoCo-MD: A Simple and Effective Method for the Enhanced Sampling of Conformational Space

Shkurti, Ardita; Styliari, Ioanna Danai; Balasubramanian, Vivek; Bethune, Iain; Pedebos, Conrado; Jha, Shantenu; Laughton, Charles A.

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Authors

Ardita Shkurti

Ioanna Danai Styliari

Vivek Balasubramanian

Iain Bethune

Conrado Pedebos

Shantenu Jha

CHARLES LAUGHTON CHARLES.LAUGHTON@NOTTINGHAM.AC.UK
Professor of Computational Pharmaceutical Science



Abstract

© 2019 American Chemical Society. CoCo ("complementary coordinates") is a method for ensemble enrichment based on principal component analysis (PCA) that was developed originally for the investigation of NMR data. Here we investigate the potential of the CoCo method, in combination with molecular dynamics simulations (CoCo-MD), to be used more generally for the enhanced sampling of conformational space. Using the alanine penta-peptide as a model system, we find that an iterative workflow, interleaving short multiple-walker MD simulations with long-range jumps through conformational space informed by CoCo analysis, can increase the rate of sampling of conformational space up to 10 times for the same computational effort (total number of MD timesteps). Combined with the reservoir-REMD method, free energies can be readily calculated. An alternative, approximate but fast and practically useful, alternative approach to unbiasing CoCo-MD generated data is also described. Applied to cyclosporine A, we can achieve far greater conformational sampling than has been reported previously, using a fraction of the computational resource. Simulations of the maltose binding protein, begun from the "open" state, effectively sample the "closed" conformation associated with ligand binding. The PCA-based approach means that optimal collective variables to enhance sampling need not be defined in advance by the user but are identified automatically and are adaptive, responding to the characteristics of the developing ensemble. In addition, the approach does not require any adaptations to the associated MD code and is compatible with any conventional MD package.

Citation

Shkurti, A., Styliari, I. D., Balasubramanian, V., Bethune, I., Pedebos, C., Jha, S., & Laughton, C. A. (2019). CoCo-MD: A Simple and Effective Method for the Enhanced Sampling of Conformational Space. Journal of Chemical Theory and Computation, 15(4), 2587-2596. https://doi.org/10.1021/acs.jctc.8b00657

Journal Article Type Article
Acceptance Date Jan 8, 2019
Online Publication Date Jan 8, 2019
Publication Date Apr 9, 2019
Deposit Date May 8, 2019
Publicly Available Date May 8, 2019
Journal Journal of Chemical Theory and Computation
Print ISSN 1549-9618
Electronic ISSN 1549-9626
Publisher American Chemical Society
Peer Reviewed Peer Reviewed
Volume 15
Issue 4
Pages 2587-2596
DOI https://doi.org/10.1021/acs.jctc.8b00657
Keywords Physical and Theoretical Chemistry; Computer Science Applications
Public URL https://nottingham-repository.worktribe.com/output/1879490
Publisher URL https://pubs.acs.org/doi/10.1021/acs.jctc.8b00657
Additional Information This document is the Accepted Manuscript version of a Published Work that appeared in final form in Journal of Chemical Theory and Computation, copyright © 2019 American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://pubs.acs.org/doi/10.1021/acs.jctc.8b00657.
Contract Date May 8, 2019

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