(6cz) From Biosynthesis to Human Health: Harnessing Biomolecules with Multiscale Quantum Mechanics–Molecular Mechanics Simulations

From Biosynthesis to Human Health: Harnessing Biomolecules
with Multiscale Quantum Mechanics–Molecular
Mechanics Simulations

Research Interests:

Computational engineering of new reactions, proteins, and enzymes
presents a holy-grail challenge in both academia and industry. The advancement
of computing hardware and algorithm has largely boosted the integration of
experiment and computation to innovate biomolecular
research. Despite significant progresses, accurate computation of mechanisms,
rates, and dynamics for biomolecules are still difficult, because of the large
size of the systems and extensive computational sampling that is required to
achieve convergence. Multiscale quantum
mechanics/molecular mechanics (QM/MM) methods have been proposed to balance
accuracy and efficiency through the division of a complex system into a portion
where a QM treatment is deemed essential and the rest where an MM treatment is
suitable. Enabled by graphics processing unit (GPU)-acceleration, a QM/MM
calculation can now incorporate a large-scale electronic structure where
500-1000 atoms can be treated quantum mechanically. This opens up the
possibilities of uncovering the quantum mechanical nature of biomolecules that
are synthetically useful and biologically important.

My research interests involve the development and utilization of
large-scale QM/MM simulation tools to investigate the mechanisms, catalytic
origins, and dynamics of enzymatic reactions, revealing how solvent molecules,
active site amino acids, and greater protein environment dictate enzyme
catalytic actions. Specifically, I will focus on 1) pericyclases that construct complex macrocycles
in biosynthesis, 2) glycyl radical enzymes that mediate
metabolism in the human gut microbiota, and 3) lasso
peptides that exhibits superior thermal stability and potential anti-microbial
activity. These studies will elucidate the biomolecular
functions from multiple temporal and spatial scales, informing new metrics and
descriptors for computational engineering of biomolecules for synthetic and
pharmaceutical uses.   

Teaching Interests:

My teaching interests lie in the general chemical engineering core classes,
including Thermodynamics, Kinetics, and Physical Chemistry. My vision is to
help students wield the weapon of thermodynamics and statistical mechanics to achieve
fundamental understandings of chemical phenomena, and to conquer cutting-edge challenges in energy, biosciences, materials, and
medicines. I majored in chemistry at college and computational chemistry in
graduate school. These programs involve a heavy load of classes that overlap
largely with the chemical engineering programs. As a graduate student at UCLA, I
served as a teaching assistant (TA) for the freshman-level general chemistry
laboratories between 2014 and 2016. I also served as a teaching assistant
for the graduate-level Computational Chemistry in 2015 and Quantum Mechanics in
2016. These experiences endowed me with valuable intuitions regarding how to
better organize hard-core class materials for students with different science
and engineer backgrounds. Collectively, my academic background and teaching experiences
will make me well positioned to take on the teaching duties in chemical
engineering departments.