Per|Mut : Spatially Resolved Hydration Entropies from Atomistic Simulations
The hydrophobic effect is essential for many biophysical phenomena and processes. It is governed by a fine-tuned balance between enthalpy and entropy contributions from the hydration shell. Whereas enthalpies can in principle be calculated from an atomistic simulation trajectory, calculating solvation entropies by sampling the extremely large configuration space is challenging and often impossible. Furthermore, to qualitatively understand how the balance is affected by individual side chains, chemical groups, or the protein topology, a local description of the hydration entropy is required. In this study, we present and assess the new method "Per|Mut", which uses a permutation reduction to alleviate the sampling problem by a factor of N! and employs a mutual information expansion to the third order to obtain spatially resolved hydration entropies. We tested the method on an argon system, a series of solvated n-alkanes, and solvated octanol.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:17 |
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| Enthalten in: |
Journal of chemical theory and computation - 17(2021), 4 vom: 13. Apr., Seite 2090-2098 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Heinz, Leonard P [VerfasserIn] |
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| Links: |
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| Themen: |
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| Anmerkungen: |
Date Completed 13.04.2021 Date Revised 17.04.2021 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1021/acs.jctc.0c00961 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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NLM322677351 |
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| 520 | |a The hydrophobic effect is essential for many biophysical phenomena and processes. It is governed by a fine-tuned balance between enthalpy and entropy contributions from the hydration shell. Whereas enthalpies can in principle be calculated from an atomistic simulation trajectory, calculating solvation entropies by sampling the extremely large configuration space is challenging and often impossible. Furthermore, to qualitatively understand how the balance is affected by individual side chains, chemical groups, or the protein topology, a local description of the hydration entropy is required. In this study, we present and assess the new method "Per|Mut", which uses a permutation reduction to alleviate the sampling problem by a factor of N! and employs a mutual information expansion to the third order to obtain spatially resolved hydration entropies. We tested the method on an argon system, a series of solvated n-alkanes, and solvated octanol | ||
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