Toward Prediction of Electrostatic Parameters for Force Fields That Explicitly Treat Electronic Polarization.

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TitleToward Prediction of Electrostatic Parameters for Force Fields That Explicitly Treat Electronic Polarization.
Publication TypeJournal Article
Year of Publication2019
AuthorsHeid, E, Fleck, M, Chatterjee, P, Schröder, C, Mackerell, AD
JournalJ Chem Theory Comput
Date Published2019 Mar 12
ISSN1549-9626
Abstract

The derivation of atomic polarizabilities for polarizable force field development has been a long-standing problem. Atomic polarizabilities were often refined manually starting from tabulated values, rendering an automated assignment of parameters difficult and hampering reproducibility and transferability of the obtained values. To overcome this, we trained both a linear increment scheme and a multilayer perceptron neural network on a large number of high-quality quantum mechanical atomic polarizabilities and partial atomic charges, where only the type of each atom and its connectivity were used as input. The predicted atomic polarizabilities and charges had average errors of 0.023 Å and 0.019 e using the neural net and 0.063 Å and 0.069 e using the simple increment scheme. As the algorithm relies only on the connectivities of the atoms within a molecule, thus omitting dependencies on the three-dimensional conformation, the approach naturally assigns like charges and polarizabilities to symmetrical groups. Accordingly, a convenient utility is presented for generating the partial atomic charges and atomic polarizabilities for organic molecules as needed in polarizable force field development.

DOI10.1021/acs.jctc.8b01289
Alternate JournalJ Chem Theory Comput
PubMed ID30811193
Grant ListR01 GM051501 / GM / NIGMS NIH HHS / United States
R01 GM070855 / GM / NIGMS NIH HHS / United States
R01 GM072558 / GM / NIGMS NIH HHS / United States