Extended diffusion theory: Recovering dynamics from biased/accelerated molecular simulations.


Journal

Journal of computational chemistry
ISSN: 1096-987X
Titre abrégé: J Comput Chem
Pays: United States
ID NLM: 9878362

Informations de publication

Date de publication:
05 04 2021
Historique:
received: 07 09 2020
revised: 09 11 2020
accepted: 02 12 2020
pubmed: 23 12 2020
medline: 23 12 2020
entrez: 22 12 2020
Statut: ppublish

Résumé

Dynamical properties are of great importance in determining the behavior of synthetic and natural molecules, but capturing them by computational methods is a nontrivial task. Very often the time scales of the relevant phenomena are far beyond the typical time windows accessible by classical Molecular Dynamics (MD) simulations, currently limited to the order of microseconds on standard laboratory workstations. On the other hand, biased and accelerated simulations allow for fast and thorough exploration of the molecular conformational space, but they lose the dynamic information. The problem of recovering dynamics from biased/accelerated simulations is a very active field of research, but no totally robust/reliable solutions have been given yet. In this paper it is shown how the Smoluchowski equation, in the framework of Diffusion Theory (DT), can be used to bridge this gap, and dynamical properties, in the form of time correlation functions (TCFs), can be extracted also from such kind of simulations. DT is first extended (EDT) to express the mobility tensors entering the Smoluchowski operator in terms of a recently introduced unified and regularized Rotne-Prager-Yamakawa approximation, [P. J. Zuk, E. Wajnryb, K. A. Mizerski, P. Szymczak, J. Fluid. Mech. 2014, 741, R5, 1-13] also involving mixed rotation-translation contributions, and rotation-rotation terms beside the classical translation-translation ones, so far used in DT. Then, the method is applied to recover the dynamics of a nontrivial example of a peptide in explicit water from the first 200 ns of a Replica Exchange Molecular Dynamics simulation, which is a popular computational method that destroys the long time dynamics. EDT dynamics were found to favorably compare against those coming from a standard MD simulation of the same system, requiring a time window of 30 μs to converge. This result shows that EDT is a tool of practical value to recover the long time dynamics of systems in diffusive regimes from biased/accelerated simulations, to be exploited in those cases when direct evaluation by standard MD is unfeasible.

Identifiants

pubmed: 33351966
doi: 10.1002/jcc.26474
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

586-599

Informations de copyright

© 2020 Wiley Periodicals LLC.

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Auteurs

Arnaldo Rapallo (A)

CNR - Istituto di Scienze e Tecnologie Chimiche "Giulio Natta" (SCITEC), Milano, Italy.

Roberto Gaspari (R)

CNR - Istituto di Scienze e Tecnologie Chimiche "Giulio Natta" (SCITEC), Milano, Italy.

Gianvito Grasso (G)

Dalle Molle Institute for Artificial Intelligence (IDSIA), Università della Svizzera italiana (USI), Scuola Universitaria Professionale della Svizzera italiana (SUPSI), Lugano-Viganello, Switzerland.

Andrea Danani (A)

Dalle Molle Institute for Artificial Intelligence (IDSIA), Università della Svizzera italiana (USI), Scuola Universitaria Professionale della Svizzera italiana (SUPSI), Lugano-Viganello, Switzerland.

Classifications MeSH