Autor: |
Linda Martini, Adam Kells, Roberto Covino, Gerhard Hummer, Nicolae-Viorel Buchete, Edina Rosta |
Jazyk: |
angličtina |
Rok vydání: |
2017 |
Předmět: |
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Zdroj: |
Physical Review X, Vol 7, Iss 3, p 031060 (2017) |
Druh dokumentu: |
article |
ISSN: |
2160-3308 |
DOI: |
10.1103/PhysRevX.7.031060 |
Popis: |
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. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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