Acceleration of Molecular Simulations by Parametric Time-Lagged tSNE Metadynamics
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14610%2F24%3A00135420" target="_blank" >RIV/00216224:14610/24:00135420 - isvavai.cz</a>
Alternative codes found
RIV/60461373:22330/24:43928908
Result on the web
<a href="https://pubs.acs.org/doi/full/10.1021/acs.jpcb.3c05669" target="_blank" >https://pubs.acs.org/doi/full/10.1021/acs.jpcb.3c05669</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1021/acs.jpcb.3c05669" target="_blank" >10.1021/acs.jpcb.3c05669</a>
Alternative languages
Result language
angličtina
Original language name
Acceleration of Molecular Simulations by Parametric Time-Lagged tSNE Metadynamics
Original language description
The potential of molecular simulations is limited by their computational costs. There is often a need to accelerate simulations using some of the enhanced sampling methods. Metadynamics applies a history-dependent bias potential that disfavors previously visited states. To apply metadynamics, it is necessary to select a few properties of the system─collective variables (CVs) that can be used to define the bias potential. Over the past few years, there have been emerging opportunities for machine learning and, in particular, artificial neural networks within this domain. In this broad context, a specific unsupervised machine learning method was utilized, namely, parametric time-lagged t-distributed stochastic neighbor embedding (ptltSNE) to design CVs. The approach was tested on a Trp-cage trajectory (tryptophan cage) from the literature. The trajectory was used to generate a map of conformations, distinguish fast conformational changes from slow ones, and design CVs. Then, metadynamic simulations were performed. To accelerate the formation of the α-helix, we added the α-RMSD collective variable. This simulation led to one folding event in a 350 ns metadynamics simulation. To accelerate degrees of freedom not addressed by CVs, we performed parallel tempering metadynamics. This simulation led to 10 folding events in a 200 ns simulation with 32 replicas.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10403 - Physical chemistry
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
The Journal of Physical Chemistry B
ISSN
1520-6106
e-ISSN
1520-5207
Volume of the periodical
128
Issue of the periodical within the volume
4
Country of publishing house
US - UNITED STATES
Number of pages
11
Pages from-to
903-913
UT code for WoS article
001156065400001
EID of the result in the Scopus database
2-s2.0-85183515639