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  Molecular dynamics of conformational substates for a simplified protein model.

Grubmüller, H., & Tavan, P. (1994). Molecular dynamics of conformational substates for a simplified protein model. Journal of Chemical Physics, 101(6), 5047-5057. doi:10.1063/1.467427.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-000E-CA0B-F Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0027-C4B0-7
Genre: Journal Article

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Grubmüller, H.1, Author              
Tavan, P., Author
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1Department of Theoretical and Computational Biophysics, MPI for biophysical chemistry, Max Planck Society, ou_578631              

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 Abstract: Extended molecular dynamics simulations covering a total of 0.232 μs have been carried out on a simplified protein model. Despite its simplified structure, that model exhibits properties similar to those of more realistic protein models. In particular, the model was found to undergo transitions between conformational substates at a time scale of several hundred picoseconds. The computed trajectories turned out to be sufficiently long as to permit a statistical analysis of that conformational dynamics. To check whether effective descriptions neglecting memory effects can reproduce the observed conformational dynamics, two stochastic models were studied. A one‐dimensional Langevin effective potential model derived by elimination of subpicosecond dynamical processes could not describe the observed conformational transition rates. In contrast, a simple Markov model describing the transitions between but neglecting dynamical processes within conformational substates reproduced the observed distribution of first passage times. These findings suggest, that protein dynamics generally does not exhibit memory effects at time scales above a few hundred picoseconds, but confirms the existence of memory effects at a picosecond time scale.

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Language(s): eng - English
 Dates: 1994
 Publication Status: Published in print
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 Rev. Method: Peer
 Identifiers: DOI: 10.1063/1.467427
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Title: Journal of Chemical Physics
Source Genre: Journal
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Pages: - Volume / Issue: 101 (6) Sequence Number: - Start / End Page: 5047 - 5057 Identifier: -