Can Coarse-Grained Molecular Dynamics Simulations Predict Pharmaceutical Crystal Growth?

To investigate the ability of coarse-grained
molecular dynamics
simulations to predict the relative growth rates of crystal facets
of pharmaceutical molecules, we apply two coarse-graining strategies
to two drug molecules, phenytoin and carbamazepine. In the first method,
we map an atomistic model to a MARTINI-level coarse-grained (CG)
force field that uses 2 or 3 heavy atoms per bead. This is followed
by applying Particle Swarm Optimization (PSO), a global optimum searching
algorithm, to the CG Lennard-Jones intermolecular potentials to fit
the radial distribution functions of both the crystalline and melt
structures. In the second, a coarser-grained method, we map 5 or more
heavy atoms into one bead with the help of the Iterative Boltzmann
Inversion (IBI) method to derive a tabulated longer-range force field
(FF). Simulations using the FF’s derived from both strategies
were able to stabilize the crystal in the correct structure and to
predict crystal growth from the melt with modest computational resources.
We evaluate the advantages and limitations of both methods and compare
the relative growth rates of various facets of both drug crystals
with those predicted by the Bravais–Friedel–Donnay–Harker
(BFDH) and attachment energy (AE) theories. While all methods, except
for the simulations conducted with the coarser-grained IBI-generated
model, produced similarly good results for phenytoin, the finer-grained
PSO-generated FF using MARTINI mapping rules outperformed the other
methods in its prediction of the facet growth rates and resulting
crystalline morphology for carbamazepine.