Crystallization is a process that plays a crucial role in the production of food products, specialty chemicals, and pharmaceutical molecules but remains poorly understood. For example, many active pharmaceutical ingredients are difficult to crystallize, have poor solubility, or have multiple crystalline forms with different physical properties, yet these properties have a direct impact of the efficacy of the drug. Accordingly, computer models capable of predicting molecular crystallization behavior can be valuable in guiding drug development strategies. The first stages of crystallization involve a process called nucleation, where molecules come together into a solid-like cluster large enough to grow into a crystal. Nucleation typically involves only a few molecules and can be drastically affected by small impurities or defects in surfaces, making it challenging to study experimentally. Nucleation is also directly related to the crystallizability of a drug and to the crystalline form that emerges. With support from the Division of Chemical, Bioengineering, Environmental, and Transport Systems and from the Chemical Theory, Models, and Computational Methods program in the Division of Chemistry, this project will develop new, generally applicable computer simulation methods and software to study the nucleation of crystal molecules from a solution. These methods will be used to study the nucleation of active pharmaceutical ingredients and to understand the role of the solvent and experimental conditions on their crystallization. The software and fundamental understanding developed over the course of the project will yield direct benefits to society through the production of new drugs, advanced materials, and new high-tech jobs. The research will be integrated in outreach efforts geared toward the education and inclusion of minorities traditionally underrepresented in higher STEM education.
This project aims to develop new, generally applicable molecular simulation methods to study the nucleation of molecular crystals from solution. These methods will directly model precipitation at constant supersaturation and will explicitly include collective variables measuring the structure of the solvent, rather than just the solute. The methods will be used to study how solvents qualitatively change the nucleation mechanism and to provide a molecular-level explanation for the different precipitation behavior observed in many pairs of chemically similar molecules. Toward this goal, the project will: (1) develop a method to generate order parameters sensitive to the structure of bulk solvents, and use it to analyze data from previous studies on solvent effects on nucleation mechanisms; (2) develop a general method to generate minimum free energy paths for solute precipitation, under constant supersaturation conditions, including order parameters sensitive to solvent structure; and (3) use the new methods to obtain nucleation paths for sulfadiazine and sulfamerazine, two nearly identical molecules with very different crystallization behavior, and elucidate the causes for those differences. The proposed method is a new formulation of the String Method in Collective Variables (SMCV) that can be used in open-system ensembles such as the osmotic, grand canonical, and Gibbs ensembles. The PI (Santiso) has successfully used the SMCV to study the nucleation of pure substances from undercooled melts, and this new formulation will enable modeling solute precipitation under realistic conditions. The tools resulting from this research will enable the scientific and engineering community to simulate and study crystallization using realistic molecular models. This toolbox will accelerate innovation in the computational design of drugs and other solid products. Furthermore, methods and software enabling simulation of activated processes in open systems will enable applications in other areas such as catalysis, separations, and solution chemistry.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
