Literature DB >> 24206335

Dynamic neutron scattering from conformational dynamics. II. Application using molecular dynamics simulation and Markov modeling.

Zheng Yi1, Benjamin Lindner, Jan-Hendrik Prinz, Frank Noé, Jeremy C Smith.   

Abstract

Neutron scattering experiments directly probe the dynamics of complex molecules on the sub pico- to microsecond time scales. However, the assignment of the relaxations seen experimentally to specific structural rearrangements is difficult, since many of the underlying dynamical processes may exist on similar timescales. In an accompanying article, we present a theoretical approach to the analysis of molecular dynamics simulations with a Markov State Model (MSM) that permits the direct identification of structural transitions leading to each contributing relaxation process. Here, we demonstrate the use of the method by applying it to the configurational dynamics of the well-characterized alanine dipeptide. A practical procedure for deriving the MSM from an MD is introduced. The result is a 9-state MSM in the space of the backbone dihedral angles and the side-chain methyl group. The agreement between the quasielastic spectrum calculated directly from the atomic trajectories and that derived from the Markov state model is excellent. The dependence on the wavevector of the individual Markov processes is described. The procedure means that it is now practicable to interpret quasielastic scattering spectra in terms of well-defined intramolecular transitions with minimal a priori assumptions as to the nature of the dynamics taking place.

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Year:  2013        PMID: 24206335     DOI: 10.1063/1.4824071

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  2 in total

Review 1.  Markov state models of biomolecular conformational dynamics.

Authors:  John D Chodera; Frank Noé
Journal:  Curr Opin Struct Biol       Date:  2014-05-16       Impact factor: 6.809

Review 2.  Relaxation mode analysis for molecular dynamics simulations of proteins.

Authors:  Ayori Mitsutake; Hiroshi Takano
Journal:  Biophys Rev       Date:  2018-03-15
  2 in total

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