# Computational Analysis of Enzyme Catalysis and Regulation

> **NIH NIH R35** · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · 2022 · $412,500

## Abstract

Project Summary: It is of great fundamental and biomedical importance to understand the physical princi-
ples that govern the coupling between the chemical step in a biomolecule and other events, such as penetration
of water molecules into the active site, recruitment of transient metal ions, or conformational rearrangements
near and afar. This is a challenging task, however, due to the intrinsic multi-scale nature of the problem. As
a result, our understanding in factors that dictate the efficiency and specificity of enzyme catalysis remains in-
complete, especially regarding contributions beyond the active site; this knowledge gap has greatly limited our
ability to design highly efficient enzymes de novo. Motivated by these considerations, the overarching theme of
our research is to develop and apply multi-scale computational methods to reveal the underlying mechanism
of enzyme catalysis at an atomic level, with a particular emphasis on establishing to what degree the chem-
ical step is coupled with other processes proximal or distal to the active site. Specifically, we aim to develop
an efficient QM/MM framework to compute free energy profiles of enzyme reactions with a good balance of
computational speed and accuracy; further integration with enhanced sampling approaches, machine learning
techniques and modern computational hardwares enables us to gain insights into the nature of coupling be-
tween the chemical step and other events during the functional cycle. Accordingly, we are in a unique position
to pursue several lines of exciting applications, which include the mechanism and impact of transient metal ion
recruiting in nucleic acid processing enzymes, the catalytic and regulatory mechanism of peripheral membrane
enzymes, and systemic analysis of allosteric coupling in a transcription factor; an emerging research direction
is to explore the interplay of stability, catalytic activity, and allostery during continuous directed evolution. Our
project integrates computational method developments with applications inspired by recent experimental ad-
vances, such as time-resolved crystallography, deep mutational scanning and continuous directed evolution.
The research efforts will lead to novel computational tools and mechanistic insights into the regulatory mech-
anisms of enzymes by processes either near or remote from the active site. Thus the project will have both
fundamental impacts and implications for better design strategies for catalysis and allostery in biomolecules.

## Key facts

- **NIH application ID:** 10376792
- **Project number:** 5R35GM141930-02
- **Recipient organization:** BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
- **Principal Investigator:** Qiang Cui
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $412,500
- **Award type:** 5
- **Project period:** 2021-04-01 → 2026-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10376792

## Citation

> US National Institutes of Health, RePORTER application 10376792, Computational Analysis of Enzyme Catalysis and Regulation (5R35GM141930-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10376792. Licensed CC0.

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