Detailed Information on Publication Record
2015
Nonlinear vs. linear biasing in Trp-cage folding simulations
SPIWOK, Vojtěch, Pavel OBORSKÝ, Jana PAZÚRIKOVÁ, Aleš KŘENEK, Blanka KRÁLOVÁ et. al.Basic information
Original name
Nonlinear vs. linear biasing in Trp-cage folding simulations
Name in Czech
Vnesení lineárního a nelineárního šumu v simulacích proteinu Trp-cage
Authors
SPIWOK, Vojtěch (203 Czech Republic), Pavel OBORSKÝ (203 Czech Republic), Jana PAZÚRIKOVÁ (703 Slovakia, belonging to the institution), Aleš KŘENEK (203 Czech Republic, belonging to the institution) and Blanka KRÁLOVÁ (203 Czech Republic)
Edition
Journal of the chemical society. Faraday transactions II, Journal of chemical physics, London, Chemical society, 2015, 0021-9606
Other information
Language
English
Type of outcome
Článek v odborném periodiku
Field of Study
10600 1.6 Biological sciences
Country of publisher
United Kingdom of Great Britain and Northern Ireland
Confidentiality degree
není předmětem státního či obchodního tajemství
References:
Impact factor
Impact factor: 2.894
RIV identification code
RIV/00216224:14610/15:00080979
Organization unit
Institute of Computer Science
UT WoS
000351530100042
Keywords (in Czech)
molekularni metadynamika; foldovani proteinu
Keywords in English
molecular metadynamics; protein folding
Tags
Tags
International impact, Reviewed
Změněno: 27/4/2018 10:31, Mgr. Alena Mokrá
Abstract
V originále
Biased simulations have great potential for the study of slow processes, including protein folding. Atomic motions in molecules are nonlinear, which suggests that simulations with enhanced sampling of collective motions traced by nonlinear dimensionality reduction methods may perform better than linear ones. In this study, we compare an unbiased folding simulation of the Trp-cage miniprotein with metadynamics simulations using both linear (principle component analysis) and nonlinear (Isomap) low dimensional embeddings as collective variables. Folding of the mini-protein was successfully simulated in 200 ns simulation with linear biasing and non-linear motion biasing. The folded state was correctly predicted as the free energy minimum in both simulations. We found that the advantage of linear motion biasing is that it can sample a larger conformational space, whereas the advantage of nonlinear motion biasing lies in slightly better resolution of the resulting free energy surface. In terms of sampling efficiency, both methods are comparable.
Links
CZ.1.05/3.2.00/08.0144, interní kód MU |
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GA15-17269S, research and development project |
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