Encoding and selecting coarse-grain mapping operators with hierarchical graphs

Maghesree Chakraborty; Chenliang Xu; Andrew D White

doi:10.1063/1.5040114

Encoding and selecting coarse-grain mapping operators with hierarchical graphs

J Chem Phys. 2018 Oct 7;149(13):134106. doi: 10.1063/1.5040114.

Authors

Maghesree Chakraborty¹, Chenliang Xu², Andrew D White¹

Affiliations

¹ Department of Chemical Engineering, University of Rochester, Rochester, New York 14627, USA.
² Department of Computer Science, University of Rochester, Rochester, New York 14627, USA.

PMID: 30292213
DOI: 10.1063/1.5040114

Abstract

Coarse-grained (CG) molecular dynamics (MD) can simulate systems inaccessible to fine-grained (FG) MD simulations. A CG simulation decreases the degrees of freedom by mapping atoms from an FG representation into agglomerate CG particles. The FG to CG mapping is not unique. Research into systematic selection of these mappings is challenging due to their combinatorial growth with respect to the number of atoms in a molecule. Here we present a method of reducing the total count of mappings by imposing molecular topology and symmetry constraints. The count reduction is illustrated by considering all mappings for nearly 50 000 molecules. The resulting number of mapping operators is still large, so we introduce a novel hierarchical graphical approach which encodes multiple CG mapping operators. The encoding method is demonstrated for methanol and a 14-mer peptide. With the test cases, we show how the encoding can be used for automated selection of reasonable CG mapping operators.