Crystal Polymorph Search in the NPT Ensemble via a Deposition/Sublimation Alchemical Path

The formulation of active pharmaceutical ingredients involves discovering stable crystal packing arrangements, or polymorphs, each of which has distinct pharmaceutically relevant properties. Traditional experimental screening techniques utilizing various conditions are commonly supplemented with in silico crystal structure prediction (CSP) to expedite the crystallization process and mitigate risk. Most predictions are finalized using advanced classical force fields or quantum mechanical calculations that accurately depict the potential energy surface, but do not fully incorporate temperature, pressure or solution conditions during the search. This study proposes an innovative alchemical path that utilizes an advanced polarizable atomic multipole force field to predict crystal structures based on sampling from the NPT ensemble. The use of alchemical (i.e., nonphysical) intermediates, a novel Monte Carlo barostat, and an orthogonal space tempering bias combine to enhance sampling of the deposition/sublimation phase transition and promote an efficient search. The proposed algorithm was applied to 2-((4-(2-(3,4-dichlorophenyl)ethyl)phenyl)amino)benzoic acid (Cambridge Crystallography Database Centre ID: XAFPAY) as a case study to showcase the theory, features and efficiency of this algorithm. All experimentally determined polymorphs with one molecule in the asymmetric unit were successfully reproduced via 1,000 short 1 nsec simulations. Utilizing two threads from a recent Intel® CPU (a Xeon® Gold 6330 CPU at 2.00 GHz) 1 nsec of sampling using the polarizable AMOEBA force field can be acquired in 4 hours (or 336 nsec/day using all 112 threads / 56 cores of the CPU). These results demonstrate a step forward in the rigorous use of the NPT ensemble during a CSP search process and opens the door to future algorithms that incorporate solution conditions using continuum solvation methods.