Ion-Hydroxyl Interactions: From High-Level Quantum Benchmarks to Transferable Polarizable Force Fields Article Swipe
Vered Wineman‐Fisher
,
Yasmine S. Al-Hamdani
,
Iqbal Addou
,
Alexandre Tkatchenko
,
Sameer Varma
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1021/acs.jctc.8b01198
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1021/acs.jctc.8b01198
Ion descriptors in molecular mechanics models are calibrated against reference data on ion-water interactions. It is then typically assumed that these descriptors will also satisfactorily describe interactions of ions with other functional groups, such as those present in biomolecules. However, several studies now demonstrate that this transferability assumption produces, in many different cases, large errors. Here we address this issue in a representative polarizable model and focus on transferability of cationic interactions from water to a series of alcohols. Both water and alcohols use hydroxyls for ion-coordination, and, therefore, this set of molecules constitutes the simplest possible case of transferability. We obtain gas phase reference data systematically from "gold-standard" quantum Monte Carlo and CCSD(T) methods, followed by benchmarked vdW-corrected DFT. We learn that the original polarizable model yields large gas phase water → alcohol transferability errors - the RMS and maximum errors are 2.3 and 5.1 kcal/mol, respectively. These errors are, nevertheless, systematic in that ion-alcohol interactions are overstabilized, and systematic errors typically imply that some essential physics is either missing or misrepresented. A comprehensive analysis shows that when both low- and high-field responses of ligand dipole polarization are described accurately, then transferability improves significantly - the RMS and maximum errors in the gas phase reduce, respectively, to 0.9 and 2.5 kcal/mol. Additionally, predictions of condensed phase transfer free energies also improve. Nevertheless, within the limits of the extrathermodynamic assumptions necessary to separate experimental estimates of salt dissolution into constituent cationic and anionic contributions, we note that the error in the condensed phase is systematic, which we attribute, at least, partially to the parametrization in long-range electrostatics. Overall, this work demonstrates a rational approach to boosting transferability of ionic interactions that will be applicable broadly to improving other polarizable and nonpolarizable models.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1021/acs.jctc.8b01198
- OA Status
- green
- Cited By
- 17
- References
- 81
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2918768857
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2918768857Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1021/acs.jctc.8b01198Digital Object Identifier
- Title
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Ion-Hydroxyl Interactions: From High-Level Quantum Benchmarks to Transferable Polarizable Force FieldsWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2019Year of publication
- Publication date
-
2019-03-04Full publication date if available
- Authors
-
Vered Wineman‐Fisher, Yasmine S. Al-Hamdani, Iqbal Addou, Alexandre Tkatchenko, Sameer VarmaList of authors in order
- Landing page
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https://doi.org/10.1021/acs.jctc.8b01198Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://orbilu.uni.lu/handle/10993/40823Direct OA link when available
- Concepts
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Polarizability, Transferability, Chemistry, Ion, Water model, Dipole, Force field (fiction), Molecular dynamics, Quantum, Chemical physics, Molecule, Statistical physics, Computational chemistry, Computer science, Physics, Quantum mechanics, Machine learning, Organic chemistry, LogitTop concepts (fields/topics) attached by OpenAlex
- Cited by
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17Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2024: 1, 2023: 3, 2022: 2, 2021: 3Per-year citation counts (last 5 years)
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81Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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