Martini, L;
Kells, A;
Covino, R;
Hummer, G;
Buchete, N-V;
Rosta, E;
(2017)
Variational Identification of Markovian Transition States.
Physical Review X
, 7
(3)
, Article 031060. 10.1103/PhysRevX.7.031060.
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Abstract
We present a method that enables the identification and analysis of conformational Markovian transition states from atomistic or coarse-grained molecular dynamics (MD) trajectories. Our algorithm is presented by using both analytical models and examples from MD simulations of the benchmark system helix-forming peptide Ala 5 , and of larger, biomedically important systems: the 15-lipoxygenase-2 enzyme (15-LOX-2), the epidermal growth factor receptor (EGFR) protein, and the Mga2 fungal transcription factor. The analysis of 15-LOX-2 uses data generated exclusively from biased umbrella sampling simulations carried out at the hybrid ab initio density functional theory (DFT) quantum mechanics/molecular mechanics (QM/MM) level of theory. In all cases, our method automatically identifies the corresponding transition states and metastable conformations in a variationally optimal way, with the input of a set of relevant coordinates, by accurately reproducing the intrinsic slowest relaxation rate of each system. Our approach offers a general yet easy-to-implement analysis method that provides unique insight into the molecular mechanism and the rare but crucial (i.e., rate-limiting) transition states occurring along conformational transition paths in complex dynamical systems such as molecular trajectories.
| Type: | Article |
|---|---|
| Title: | Variational Identification of Markovian Transition States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1103/PhysRevX.7.031060 |
| Publisher version: | https://doi.org/10.1103/PhysRevX.7.031060 |
| Language: | English |
| Additional information: | Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/). Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Physics and Astronomy |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10119927 |
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