Proteins play a key role as therapeutics in a number of diseases and protein crystallization is a central activity in the pharmaceutical industry. Specifically, the production of highly-ordered, high-quality protein crystals through batch crystallization processes is vital in devising proteins for therapeutic purposes. However, despite extensive experimental and computational work on understanding protein structure and function, there is a lack of a systematic framework that relies on a fundamental understanding of the nucleation and growth mechanisms of protein crystals at the microscopic level and utilizes such information to model and operate protein batch crystallization processes at the macroscopic level.
Intellectual Merit:
Motivated by the above considerations, a hierarchical and computationally tractable approach is planned to: (a) elucidate the phase diagrams and understand the physics of crystallization of globular proteins at the microscopic level, (b) deduce microscopically consistent crystal nucleation and growth rate laws, and (c) utilize the previous knowledge to model and control batch protein crystallization processes at the macroscopic level. The previous objectives will be achieved by the following specific projects: (1) The equilibrium protein phase diagrams will be determined via coarse-graining techniques, Monte Carlo simulations, and finite-size scaling theory. The simulations will be implemented according to the methodology of spatial updating. Crystal nucleation will be studied by a combination of Monte Carlo and molecular dynamics simulations. (2) The results of part (1) will be used to: (i) study the growth of protein crystals via molecular dynamics and kinetic Monte Carlo simulations, and (ii) derive microscopically consistent rate laws. (3) The nucleation and growth rates of parts (1) and (2) will be used to model batch protein crystallizers through population and mass and energy balances. These models will be used in conjunction with stochastic model predictive control methodologies that account for model uncertainty to achieve a desired crystal size distribution at the end of the batch protein crystallization process. This modeling effort will be tested and validated against available experimental data. The PI plans to pursue interaction and collaboration with industry to actively share the research results. The integration of the research into education will be achieved through: (a) The development of elective courses on: (i) molecular/multiscale modeling and simulation, and (ii) applied mathematics and numerical analysis. The algorithmic advances of the work will also be incorporated into these courses. (b) The involvement of undergraduate students in research and the recruitment of qualified college students (including students from minority and under-represented groups) into the graduate chemical engineering program at UCLA via internships.
Broader Impact:
This work will provide a basic understanding of the factors that affect protein phase separation and crystallization and will benefit a wide range of pharmaceutical companies and products. In addition, it will provide a practical framework to simulate, model, and control globular protein crystallization processes. The research program will be integrated into the chemical engineering curriculum and is well-suited for the training of both graduate and undergraduate students in the area of molecular and multiscale modeling and simulation.
