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241211s2025 xx |||||o 00| ||eng c |
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|a 10.1002/jcc.27529
|2 doi
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|a pubmed24n1630.xml
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|a DE-627
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|e rakwb
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| 041 |
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|a eng
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| 100 |
1 |
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|a Ghysbrecht, Simon
|e verfasserin
|4 aut
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| 245 |
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|a Accuracy of Reaction Coordinate Based Rate Theories for Modelling Chemical Reactions
|b Insights From the Thermal Isomerization in Retinal
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|c 2025
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
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|2 rdamedia
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|a ƒa Online-Ressource
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|a Date Revised 13.12.2024
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|a published: Print
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|a Citation Status PubMed-not-MEDLINE
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|a © 2024 The Author(s). Journal of Computational Chemistry published by Wiley Periodicals LLC.
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|a Modern potential energy surfaces have shifted attention to molecular simulations of chemical reactions. While various methods can estimate rate constants for conformational transitions in molecular dynamics simulations, their applicability to studying chemical reactions remains uncertain due to the high and sharp energy barriers and complex reaction coordinates involved. This study focuses on the thermal cis-trans isomerization in retinal, employing molecular simulations and comparing rate constant estimates based on one-dimensional rate theories with those based on sampling transitions and grid-based models for low-dimensional collective variable spaces. Even though each individual method to estimate the rate passes its quality tests, the rate constant estimates exhibit considerable disparities. Rate constant estimates based on one-dimensional reaction coordinates prove challenging to converge, even if the reaction coordinate is optimized. However, consistent estimates of the rate constant are achieved by sampling transitions and by multi-dimensional grid-based models
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|a Journal Article
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4 |
|a diffusion
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| 650 |
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4 |
|a kramers
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| 650 |
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4 |
|a metadynamics
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| 650 |
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4 |
|a path collective variable
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| 650 |
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4 |
|a rate theory
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| 650 |
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4 |
|a retinal
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| 650 |
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4 |
|a square root approximation
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| 650 |
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4 |
|a umbrella sampling
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| 700 |
1 |
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|a Donati, Luca
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Keller, Bettina G
|e verfasserin
|4 aut
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| 773 |
0 |
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|i Enthalten in
|t Journal of computational chemistry
|d 1984
|g 46(2024), 1 vom: 05. Jan., Seite e27529
|w (DE-627)NLM098138448
|x 1096-987X
|7 nnns
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| 773 |
1 |
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|g volume:46
|g year:2024
|g number:1
|g day:05
|g month:01
|g pages:e27529
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| 856 |
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|u http://dx.doi.org/10.1002/jcc.27529
|3 Volltext
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