title: Accurate prediction of polarised high order electrostatic interactions for hydrogen bonded complexes using the machine learning method kriging.
abstract: As intermolecular interactions such as the hydrogen bond are electrostatic in origin, rigorous treatment of this term within force field methodologies should be mandatory. We present a method able of accurately reproducing such interactions for seven van der Waals complexes. It uses atomic multipole moments up to hexadecupole moment mapped to the positions of the nuclear coordinates by the machine learning method kriging. Models were built at three levels of theory: HF/6-31G(**), B3LYP/aug-cc-pVDZ and M06-2X/aug-cc-pVDZ. The quality of the kriging models was measured by their ability to predict the electrostatic interaction energy between atoms in external test examples for which the true energies are known. At all levels of theory, >90% of test cases for small van der Waals complexes were predicted within 1 kJ mol(-1), decreasing to 60-70% of test cases for larger base pair complexes. Models built on moments obtained at B3LYP and M06-2X level generally outperformed those at HF level. For all systems the individual interactions were predicted with a mean unsigned error of less than 1 kJ mol(-1).
authors.affiliation: Manchester Institute of Biotechnology (MIB), 131 Princess Street, Manchester M1 7DN, United Kingdom; School of Chemistry, University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom.
authors.forename: Timothy J
authors.initials: TJ
authors.lastname: Hughes
authors.affiliation: Manchester Institute of Biotechnology (MIB), 131 Princess Street, Manchester M1 7DN, United Kingdom; School of Chemistry, University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom.
authors.forename: Shaun M
authors.initials: SM
authors.lastname: Kandathil
authors.affiliation: Manchester Institute of Biotechnology (MIB), 131 Princess Street, Manchester M1 7DN, United Kingdom; School of Chemistry, University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom. Electronic address: pla@manchester.ac.uk.
authors.forename: Paul L A
authors.initials: PL
authors.lastname: Popelier
mesh_terms: D000641:Ammonia / Q000737:chemistry; D001185:Artificial Intelligence; D006860:Hydrogen Bonding; D008956:Models, Chemical; D008958:Models, Molecular; D055672:Static Electricity; D014867:Water / Q000737:chemistry
chemical_list: D014867:Water; D000641:Ammonia
keywords: Force fields; Hydrogen bonding; Kriging; Multipole moments; QCT; QTAIM