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231224s2017 xx |||||o 00| ||eng c |
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|a 10.1002/jcc.24837
|2 doi
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|a eng
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|a Harada, Ryuhei
|e verfasserin
|4 aut
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|a Structural dissimilarity sampling with dynamically self-guiding selection
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|c 2017
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|a Text
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|2 rdacontent
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|a ƒaComputermedien
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|a ƒa Online-Ressource
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|a Date Revised 20.11.2019
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a © 2017 Wiley Periodicals, Inc.
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|a Structural dissimilarity sampling (SDS) has been proposed as an enhanced conformational sampling method for reproducing the structural transitions of a given protein. SDS consists of cycles of two steps: (1) Selections of initial structures with structural dissimilarities by referring to a measure. (2) Conformational resampling by restarting short-time molecular dynamics (MD) simulations from the initial structures. In the present study, an efficient measure is proposed as a dynamically self-guiding selection to accelerate the structural transitions from a reactant state to a product state as an extension to the original SDS. In the extended SDS, the inner product (IP) between the reactant and the snapshots generated by short-time MD simulations are evaluated and ranked according to the IPs at every cycle. Then, the snapshots with low IPs are selected as initial structures for the short-time MD simulations. This scheme enables one to choose dissimilar and distant initial structures from the reactant, and thus the initial structures dynamically head towards the product, promoting structural transitions from the reactant. To confirm the conformational sampling efficiency, the extended SDS was applied to maltodextrin binding protein (MBP), and we successfully reproduced the structural transition from the open to closed states with submicrosecond-order simulation times. However, a conventional long-time MD simulation failed to reproduce the same structural transition. We also compared the performance with that obtained by the ordinary SDS and other sampling techniques that have been developed by us to characterize the possible utility of the extended SDS for actual applications. © 2017 Wiley Periodicals, Inc
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|a Journal Article
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|a Research Support, Non-U.S. Gov't
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|a biologically relevant rare events
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| 650 |
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|a conformational sampling
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| 650 |
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|a molecular dynamics
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| 700 |
1 |
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|a Shigeta, Yasuteru
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t Journal of computational chemistry
|d 1984
|g 38(2017), 22 vom: 15. Aug., Seite 1921-1929
|w (DE-627)NLM098138448
|x 1096-987X
|7 nnns
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| 773 |
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|g volume:38
|g year:2017
|g number:22
|g day:15
|g month:08
|g pages:1921-1929
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|u http://dx.doi.org/10.1002/jcc.24837
|3 Volltext
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