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231226s2022 xx |||||o 00| ||eng c |
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|a 10.1002/jcc.26882
|2 doi
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|a pubmed24n1134.xml
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|a (DE-627)NLM340394323
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|a (NLM)35510789
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|a DE-627
|b ger
|c DE-627
|e rakwb
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| 041 |
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|a eng
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| 100 |
1 |
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|a Gupta, Abhinav
|e verfasserin
|4 aut
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| 245 |
1 |
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|a Exploration of high dimensional free energy landscapes by a combination of temperature-accelerated sliced sampling and parallel biasing
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|c 2022
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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|a ƒa Online-Ressource
|b cr
|2 rdacarrier
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|a Date Completed 26.05.2022
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|a Date Revised 07.09.2022
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a © 2022 Wiley Periodicals LLC.
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|a Temperature-accelerated sliced sampling (TASS) is an enhanced sampling method for achieving accelerated and controlled exploration of high-dimensional free energy landscapes in molecular dynamics simulations. With the aid of umbrella bias potentials, the TASS method realizes a controlled exploration and divide-and-conquer strategy for computing high-dimensional free energy surfaces. In TASS, diffusion of the system in the collective variable (CV) space is enhanced with the help of metadynamics bias and elevated-temperature of the auxiliary degrees of freedom (DOF) that are coupled to the CVs. Usually, a low-dimensional metadynamics bias is applied in TASS. In order to further improve the performance of TASS, we propose here to use a highdimensional metadynamics bias, in the same form as in a parallel bias metadynamics scheme. Here, a modified reweighting scheme, in combination with artificial neural network is used for computing unbiased probability distribution of CVs and projections of high-dimensional free energy surfaces. We first validate the accuracy and efficiency of our method in computing the four-dimensional free energy landscape for alanine tripeptide in vacuo. Subsequently, we employ the approach to calculate the eight-dimensional free energy landscape of alanine pentapeptide in vacuo. Finally, the method is applied to a more realistic problem wherein we compute the broad four-dimensional free energy surface corresponding to the deacylation of a drug molecule which is covalently complexed with a β-lactamase enzyme. We demonstrate that using parallel bias in TASS improves the efficiency of exploration of high-dimensional free energy landscapes
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|a Journal Article
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|a Research Support, Non-U.S. Gov't
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4 |
|a alanine pentapeptide
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| 650 |
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4 |
|a alanine tripeptide
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| 650 |
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4 |
|a artificial neural network
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| 650 |
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4 |
|a deacylation
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| 650 |
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4 |
|a free energy calculations
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| 650 |
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4 |
|a parallel bias Metadynamics
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| 650 |
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4 |
|a temperature accelerate sliced sampling
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| 650 |
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4 |
|a umbrella sampling
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| 650 |
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4 |
|a weighted histogram analysis
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| 650 |
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4 |
|a β-lactamase
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| 650 |
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7 |
|a Alanine
|2 NLM
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| 650 |
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7 |
|a OF5P57N2ZX
|2 NLM
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| 700 |
1 |
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|a Verma, Shivani
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Javed, Ramsha
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Sudhakar, Suraj
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Srivastava, Saurabh
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Nair, Nisanth N
|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 43(2022), 17 vom: 30. Juni, Seite 1186-1200
|w (DE-627)NLM098138448
|x 1096-987X
|7 nnns
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| 773 |
1 |
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|g volume:43
|g year:2022
|g number:17
|g day:30
|g month:06
|g pages:1186-1200
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| 856 |
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|u http://dx.doi.org/10.1002/jcc.26882
|3 Volltext
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