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Better force fields start with better data: A data set of cation dipeptide interactions
We present a data set from a first-principles study of amino-methylated and acetylated (capped) dipeptides of the 20 proteinogenic amino acids – including alternative possible side chain protonation states and their interactions with selected divalent cations (Ca(2+), Mg(2+) and Ba(2+)). The data co...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9205945/ https://www.ncbi.nlm.nih.gov/pubmed/35715420 http://dx.doi.org/10.1038/s41597-022-01297-3 |
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author | Hu, Xiaojuan Lenz-Himmer, Maja-Olivia Baldauf, Carsten |
author_facet | Hu, Xiaojuan Lenz-Himmer, Maja-Olivia Baldauf, Carsten |
author_sort | Hu, Xiaojuan |
collection | PubMed |
description | We present a data set from a first-principles study of amino-methylated and acetylated (capped) dipeptides of the 20 proteinogenic amino acids – including alternative possible side chain protonation states and their interactions with selected divalent cations (Ca(2+), Mg(2+) and Ba(2+)). The data covers 21,909 stationary points on the respective potential-energy surfaces in a wide relative energy range of up to 4 eV (390 kJ/mol). Relevant properties of interest, like partial charges, were derived for the conformers. The motivation was to provide a solid data basis for force field parameterization and further applications like machine learning or benchmarking. In particular the process of creating all this data on the same first-principles footing, i.e. density-functional theory calculations employing the generalized gradient approximation with a van der Waals correction, makes this data suitable for first principles data-driven force field development. To make the data accessible across domain borders and to machines, we formalized the metadata in an ontology. |
format | Online Article Text |
id | pubmed-9205945 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-92059452022-06-19 Better force fields start with better data: A data set of cation dipeptide interactions Hu, Xiaojuan Lenz-Himmer, Maja-Olivia Baldauf, Carsten Sci Data Data Descriptor We present a data set from a first-principles study of amino-methylated and acetylated (capped) dipeptides of the 20 proteinogenic amino acids – including alternative possible side chain protonation states and their interactions with selected divalent cations (Ca(2+), Mg(2+) and Ba(2+)). The data covers 21,909 stationary points on the respective potential-energy surfaces in a wide relative energy range of up to 4 eV (390 kJ/mol). Relevant properties of interest, like partial charges, were derived for the conformers. The motivation was to provide a solid data basis for force field parameterization and further applications like machine learning or benchmarking. In particular the process of creating all this data on the same first-principles footing, i.e. density-functional theory calculations employing the generalized gradient approximation with a van der Waals correction, makes this data suitable for first principles data-driven force field development. To make the data accessible across domain borders and to machines, we formalized the metadata in an ontology. Nature Publishing Group UK 2022-06-17 /pmc/articles/PMC9205945/ /pubmed/35715420 http://dx.doi.org/10.1038/s41597-022-01297-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor Hu, Xiaojuan Lenz-Himmer, Maja-Olivia Baldauf, Carsten Better force fields start with better data: A data set of cation dipeptide interactions |
title | Better force fields start with better data: A data set of cation dipeptide interactions |
title_full | Better force fields start with better data: A data set of cation dipeptide interactions |
title_fullStr | Better force fields start with better data: A data set of cation dipeptide interactions |
title_full_unstemmed | Better force fields start with better data: A data set of cation dipeptide interactions |
title_short | Better force fields start with better data: A data set of cation dipeptide interactions |
title_sort | better force fields start with better data: a data set of cation dipeptide interactions |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9205945/ https://www.ncbi.nlm.nih.gov/pubmed/35715420 http://dx.doi.org/10.1038/s41597-022-01297-3 |
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