# Computational Analysis of Enzyme Catalysis and Regulation

> **NIH NIH R35** · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · 2024 · $248,418

## Abstract

Project Summary
It is of great fundamental and biomedical importance to understand the physical principles 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 incomplete, 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 chemical 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 hardware enables us to gain insights into the nature of coupling between 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 advances, 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
mechanisms 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:** 11100229
- **Project number:** 3R35GM141930-04S1
- **Recipient organization:** BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
- **Principal Investigator:** Qiang Cui
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $248,418
- **Award type:** 3
- **Project period:** 2021-04-01 → 2026-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11100229

## Citation

> US National Institutes of Health, RePORTER application 11100229, Computational Analysis of Enzyme Catalysis and Regulation (3R35GM141930-04S1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/11100229. Licensed CC0.

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