# Allosteric impact of non-active-site mutations on enzymatic function

> **NIH NIH R01** · UNIVERSITY OF PENNSYLVANIA · 2021 · $68,206

## Abstract

Antibiotic-resistant infections kill tens of thousands of Americans and cost our nation billions of
dollars every year. β-lactamase enzymes are one of the most common sources of resistance and
are capable of quickly evolving the ability to degrade new β-lactam antibiotics as they are
introduced. Surprisingly, many of the mutations that confer β-lactamases with new functions are
far from the enzyme's active site and have little effect on the structure of the active site, as
observed by x-ray crystallography. Such non-active site (NAS) mutations also appear frequently in
other contexts, such as the evolution of other forms of drug resistance and directed evolution
studies. Understanding how NAS mutations allosterically impact distant sites would provide a
basis for predicting new forms of drug resistance and designing allosteric drugs to combat
diseases like antibiotic-resistant infections. The objective of this proposal is to understand how
NAS mutations confer β- lactamases with activity against new substrates. A predictive
understanding of NAS mutations remains elusive because of the ruggedness of proteins' energy
landscapes and the great diversity of mechanisms that couple distant residues, including both
concerted structural changes and correlations between the dynamics of different residues. These
obstacles will be overcome by integrating novel computational methods with in vitro and in vivo
experiments to converge on a quantitative understanding of the full spectrum of correlated
fluctuations responsible for allosteric coupling. For example, the research team will apply new
methods they developed to facilitate comprehensive sampling of proteins' energy landscapes,
such as their FAST algorithm for leveraging Markov State Models (MSMs) to efficiently sample
conformations with pre-specified features. In Aim 1, these methods will be used to identify what
features of β-lactamase’s structure and dynamics give rise to new activities by comparing models
for variants with different activities against the antibiotic cefotaxime. In aim 2, new methods for
identifying both concerted structural changes and correlations between the dynamics of different
residues will be developed. These methods will be used to predict new sites where NAS mutations
can alter activities of β-lactamases. To test insights from each aim, mutations will be designed to
confer β- lactamases with new activities. Then experiments will be performed to test 1) whether
these mutations have the intended impact on the activities of β-lactamases and 2) whether the
designed variants are capable of protecting bacteria from the target antibiotic. Completion of this
work will result in a general framework for understanding allosteric communication that will serve
as a basis for future efforts to predict drug resistance, design new antibiotics that allosterically
inhibit their targets, and manipulate allostery in other systems.

## Key facts

- **NIH application ID:** 10692526
- **Project number:** 7R01GM124007-06
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Gregory Bowman
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $68,206
- **Award type:** 7
- **Project period:** 2017-09-05 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10692526

## Citation

> US National Institutes of Health, RePORTER application 10692526, Allosteric impact of non-active-site mutations on enzymatic function (7R01GM124007-06). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10692526. Licensed CC0.

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