Binding Thermodynamics of Host–Guest Systems with SMIRNOFF99Frosst 1.0.5 from the Open Force Field Initiative

Designing ligands that bind their
target biomolecules with high
affinity and specificity is a key step in small-molecule drug discovery,
but accurately predicting protein–ligand binding free energies
remains challenging. Key sources of errors in the calculations include
inadequate sampling of conformational space, ambiguous protonation
states, and errors in force fields. Noncovalent complexes between
a host molecule with a binding cavity and a druglike guest molecule
have emerged as powerful model systems. As model systems, host–guest
complexes reduce many of the errors in more complex protein–ligand
binding systems, as their small size greatly facilitates conformational
sampling, and one can choose systems that avoid ambiguities in protonation
states. These features, combined with their ease of experimental characterization,
make host–guest systems ideal model systems to test and ultimately
optimize force fields in the context of binding thermodynamics calculations.
The Open Force Field Initiative aims to create a modern, open software
infrastructure for automatically generating and assessing force fields
using data sets. The first force field to arise out of this effort,
named SMIRNOFF99Frosst, has approximately one tenth the number of
parameters, in version 1.0.5, compared to typical general small molecule
force fields, such as GAFF. Here, we evaluate the accuracy of this
initial force field, using free energy calculations of 43 α
and β-cyclodextrin host–guest pairs for which experimental
thermodynamic data are available, and compare with matched calculations
using two versions of GAFF. For all three force fields, we used TIP3P
water and AM1-BCC charges. The calculations are performed using the
attach-pull-release (APR) method as implemented in the open source
package, pAPRika. For binding free energies, the root-mean-square
error of the SMIRNOFF99Frosst calculations relative to experiment
is 0.9 [0.7, 1.1] kcal/mol, while the corresponding results for GAFF
1.7 and GAFF 2.1 are 0.9 [0.7, 1.1] kcal/mol and 1.7 [1.5, 1.9] kcal/mol,
respectively, with 95% confidence ranges in brackets. These results
suggest that SMIRNOFF99Frosst performs competitively with existing
small molecule force fields and is a parsimonious starting point for
optimization.