Advancing Structural Analysis with Computational Methods Development

Author: Mai, Huanghao

Year: 2025

Degree: Dissertation (Ph.D.)

Advisor: Nelson, Hosea M.

Committee Members: Clemons, William M.; Mayo, Stephen L.; Rees, Douglas C.; Nelson, Hosea M.

Option: Biochemistry and Molecular Biophysics

DOI: 10.7907/4p95-d385

Abstract

In this thesis, a set of computational methods is developed to extend structural techniques beyond their conventional practice. First, we build in silico simulations and image processing protocols to design a new data acquisition workflow in cryo-electron tomography. This enables in situ visualization of macromolecular complexes at sub-nanometer resolution in a micron-scale field of view. Then, we demonstrate the applicability of a novel machine-learning algorithm in processing small molecule electron diffraction data for the first time. For most molecules tested, the correct ab initio structures can be obtained without the common practice of manual dataset curation. Finally, molecular dynamics simulations using crystallographic structures of protein and drug molecule complexes are performed to investigate the fundamental principles of a ternary binding property. A minimal forcefield with multi-scale coarse-graining enables alchemical free energy calculations at an unconventional size of perturbation while providing physical insight into the role of the drug linker and protein shapes.

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