Moses Chung
Program: Physics
Current advisor: Jay W. Ponder, PhD
Undergraduate university: State University of New York-Buffalo
Research summary
The development of computationally efficient and accurate methods to predict biophysical properties is a central goal of molecular modeling and computational chemistry. For example, accurate predictions of binding free energy between proteins and small molecules enables computer-aided drug design. To achieve this goal, we develop and apply physics-based force fields to accurately model intermolecular interactions. This thesis is divided into an application and a theory sections. First, we apply the Atomic Multipole Optimized Energetics for Biomolecular Applications (AMOEBA) force field to accurately predict the binding free energy of small molecules to host systems. We also compute the binding free energy of ions to an RNA G-quadruplex system and present new mechanisms of ion binding. Second, we delve into the physics of next-generation force fields by incorporating the principles of quantum mechanics into classical models. We explore how the Pauli exclusion principle can be recapitulated in classical terms. In summary, we show that our “physics first” approach enables accurate biochemical predictions and development of next-generation force fields.
Graduate publications
Chung MKJ, Ponder JW. 2024 Beyond isotropic repulsion: Classical anisotropic repulsion by inclusion of p orbitals. J Chem Phys, 160(17):174118.
Chung MKJ, Miller RJ, Novak B, Wang Z, Ponder JW. 2023 Accurate Host-Guest Binding Free Energies Using the AMOEBA Polarizable Force Field. J Chem Inf Model, 63(9):2769-2782.
Chung MKJ, Wang Z, Rackers JA, Ponder JW. 2022 Classical Exchange Polarization: An Anisotropic Variable Polarizability Model. J Phys Chem B, 126(39):7570-94.
Ward MD, Zimmerman MI, Meller A, Chung M, Swamidass SJ, Bowman GR. 2021 Deep learning the structural determinants of protein biochemical properties by comparing structural ensembles with DiffNets. Nat Commun, 12(1):3023.