Adaptive, Geometric Networks for Efficient Coarse-Grained Ab Initio Molecular Dynamics with Post-Hartree-Fock Accuracy

Journal of Chemical Theory and Computation
Timothy C RicardSrinivasan S Iyengar

Abstract

We introduce a new coarse-graining technique for ab initio molecular dynamics that is based on the adaptive generation of connected geometric networks or graphs specific to a given molecular geometry. The coarse-grained nodes depict a local chemical environment and are networked to create edges, triangles, tetrahedrons, and higher order simplexes based on (a) a Delaunay triangulation procedure and (b) a method that is based on molecular, bonded and nonbonded, local interactions. The geometric subentities thus created, that is nodes, edges, triangles, and tetrahedrons, each represent an energetic measure for a specific portion of the molecular system, capturing a specific set of interactions. The energetic measure is constructed in a manner consistent with ONIOM and allows assembling an overall molecular energy that is purely based on the geometric network derived from the molecular conformation. We use this approach to obtain accurate MP2 energies for polypeptide chains containing up to 12 amino-acid monomers (123 atoms) and DFT energies up to 26 amino-acid monomers (263 atoms). The energetic measures are obtained at much reduced computational costs; the approach currently yields MP2 energies at DFT cost and DFT energies at PM6...Continue Reading

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Citations

May 28, 2020·Physical Chemistry Chemical Physics : PCCP·Jinfeng Liu, Xiao He
Apr 24, 2021·Journal of Chemical Theory and Computation·Juncheng Harry ZhangSrinivasan S Iyengar
Sep 27, 2019·Journal of Chemical Theory and Computation·Anup Kumar, Srinivasan S Iyengar
Dec 1, 2018·Journal of Chemical Theory and Computation·Vladimir SladekYasuteru Shigeta
Oct 9, 2021·Journal of Chemical Theory and Computation·Anup KumarSrinivasan S Iyengar

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