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An empirical extrapolation scheme for efficient treatment of induced dipoles.
Simmonett, Andrew C; Pickard, Frank C; Ponder, Jay W; Brooks, Bernard R.
Afiliação
  • Simmonett AC; Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.
  • Pickard FC; Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.
  • Ponder JW; Department of Chemistry, Washington University in St. Louis, St. Louis, Missouri 63130, USA.
  • Brooks BR; Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.
J Chem Phys ; 145(16): 164101, 2016 Oct 28.
Article em En | MEDLINE | ID: mdl-27802661
ABSTRACT
Many cutting edge force fields include polarization, to enhance their accuracy and range of applicability. In this work, we develop efficient strategies for the induced dipole polarization method. By fitting various orders of perturbation theory (PT) dipoles to a diverse training set, we arrive at a family of fully analytic methods - whose nth order is referred to OPTn - that span the full spectrum of polarization methods from the fast zeroth-order approach that neglects mutual dipole coupling, approaching the fully variational approach at high order. Our training set contains many difficult cases where the PT series diverges, and we demonstrate that our OPTn methods still deliver excellent results in these cases. Our tests show that the OPTn methods exhibit rapid convergence towards the exact answer with each increasing PT order. The fourth order OPT4 method, whose costs are commensurate with three iterations of the leading conjugate gradient method, is a particularly promising candidate to be used as a drop-in replacement for existing solvers without further parameterization.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2016 Tipo de documento: Article