posted on 2018-12-17, 00:00authored byMichael
A. Webb, Jean-Yves Delannoy, Juan J. de Pablo
A novel methodology is introduced
here to generate coarse-grained
(CG) representations of molecular models for simulations. The proposed
strategy relies on basic graph-theoretic principles and is referred
to as graph-based coarse-graining (GBCG). It treats a given system
as a molecular graph and derives a corresponding CG representation
by using edge contractions to combine nodes in the graph, which correspond
to atoms in the molecule, into CG sites. A key element of this methodology
is that the nodes are combined according to well-defined protocols
that rank-order nodes based on the underlying chemical connectivity.
By iteratively performing these operations, successively coarser representations
of the original atomic system can be produced to yield a systematic
set of CG mappings with hierarchical resolution in an automated fashion.
These capabilities are demonstrated in the context of several test
systems, including toluene, pentadecane, a polysaccharide dimer, and
a rhodopsin protein. In these examples, GBCG yields multiple, intuitive
structures that naturally preserve the chemical topology of the system.
Importantly, these representations are rendered from algorithmic implementation
rather than an arbitrary ansatz, which, until now, has been the conventional
approach for defining CG mapping schemes. Overall, the results presented
here indicate that GBCG is efficient, robust, and unambiguous in its
application, making it a valuable tool for future CG modeling.