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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...

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Detalles Bibliográficos
Autores principales: Hu, Xiaojuan, Lenz-Himmer, Maja-Olivia, Baldauf, Carsten
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
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
Descripción
Sumario: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.