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Better force fields start with better data: A data set of cation dipeptide interactions

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Hu,  Xiaojuan
Theory, Fritz Haber Institute, Max Planck Society;

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Lenz,  Maja-Olivia       
Theory, Fritz Haber Institute, Max Planck Society;

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Baldauf,  Carsten       
Theory, Fritz Haber Institute, Max Planck Society;

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Citation

Hu, X., Lenz, M.-O., & Baldauf, C. (2022). Better force fields start with better data: A data set of cation dipeptide interactions. Scientific Data, 9: 327. doi:10.1038/s41597-022-01297-3.


Cite as: https://hdl.handle.net/21.11116/0000-000A-AFF8-A
Abstract
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 (Ca2+, Mg2+ and Ba2+). 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.