Computational approach for fast screening of small molecular candidates to inhibit crystallization in amorphous drugs.

The applicability of the computational docking approach was investigated to create a novel method for quick additive screening to inhibit the crystallization taking place in amorphous drugs. Surface energy and attachment energy were utilized to recognize the morphologically most important crystal faces. The surfaces (100), (001), and (010) were identified as target faces, and the estimated free energies of binding of additives on these surfaces were computationally determined. The molecule of the crystallizing compound was included in the group of the modeled additives as the reference and for the validation of the approach. Additives having a lower estimated free energy of binding than the reference molecule itself were considered as potential crystallization inhibitors. Salicylamide, salicylic acid, and sulfanilamide with computationally prescreened additives were melt-quenched, and the nucleation and crystal growth rates were subsequently monitored by polarized light microscopy. As a result, computationally screened additives decelerated the nucleation and crystal growth rates of the studied drugs while the pure drugs crystallized too fast to be measured. The use of a computational approach enabled fast and cost-effective additive selection to retard nucleation and crystal growth, thus facilitating the production of amorphous binary small molecular compounds with stabilized disordered structures.