Escaping Atom Types in Force Fields Using Direct Chemical Perception

Traditional approaches to specifying
a molecular mechanics force
field encode all the information needed to assign force field parameters
to a given molecule into a discrete set of atom types. This is equivalent
to a representation consisting of a molecular graph comprising a set
of vertices, which represent atoms labeled by atom type, and unlabeled
edges, which represent chemical bonds. Bond stretch, angle bend, and
dihedral parameters are then assigned by looking up bonded pairs,
triplets, and quartets of atom types in parameter tables to assign
valence terms and using the atom types themselves to assign nonbonded
parameters. This approach, which we call indirect chemical perception
because it operates on the intermediate graph of atom-typed nodes,
creates a number of technical problems. For example, atom types must
be sufficiently complex to encode all necessary information about
the molecular environment, making it difficult to extend force fields
encoded this way. Atom typing also results in a proliferation of redundant
parameters applied to chemically equivalent classes of valence terms,
needlessly increasing force field complexity. Here, we describe a new approach to assigning force field parameters via direct chemical perception. Rather than working through the intermediary
of the atom-typed graph, direct chemical perception operates directly
on the unmodified chemical graph of the molecule to assign parameters.
In particular, parameters are assigned to each type of force field
term (e.g., bond stretch, angle bend, torsion, and Lennard–Jones)
based on standard chemical substructure queries implemented via the
industry-standard SMARTS chemical perception language, using SMIRKS
extensions that permit labeling of specific atoms within a chemical pattern. We use this to implement a new force field format, called the SMIRKS Native Open Force Field (SMIRNOFF) format. We demonstrate the power and generality of this approach
using examples of specific molecules that pose problems for indirect
chemical perception and construct and validate a minimalist yet very
general force field, SMIRNOFF99Frosst. We find that a parameter definition
file only ∼300 lines long provides coverage of all but <0.02%
of a 5 million molecule drug-like test set. Despite its simplicity,
the accuracy of SMIRNOFF99Frosst for small molecule hydration free
energies and selected properties of pure organic liquids is similar
to that of the General Amber Force Field, whose specification requires
thousands of parameters. This force field provides a starting point
for further optimization and refitting work to follow.