# Discovering and Manipulating Macromolecular Conformational Ensembles

> **NIH NIH R35** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2024 · $597,550

## Abstract

PROJECT SUMMARY
Macromolecules fluctuate between different structural states of a conformational ensemble. One of the major
effects of ligands and mutations is to change the relative stability of these different states. However, most of
our structural biology modeling revolves around a paradigm of distinct and singular structures. Our major goal
is to move beyond static images of biological macromolecules, while retaining the ability to interrogate the
resulting models to improve ligand design and mutational engineering. We are also interested in creating
experimental methods to perturb the relative populations of these conformations, using temperature or
chemical perturbation to bring them into the window where they can be observed and modeled. In two previous
grants supported by NIGMS, we have focused three primary technologies: 1) ensemble modeling, where
alternative conformations present in X-ray (and now, increasingly, cryoEM) density maps are explicitly
identified and refined as a conformational ensemble or multiconformer model; 2) multitemperature
crystallography, where the temperature of X-ray data collection is shifted, while avoiding radiation damage, to
change the relative balance of different populations; 3) model validation, where the density at specific points is
quantified to support or falsify modelling. We have applied these paradigms broadly and collaboratively, with a
commitment to open methods and software. Two major foci have been: 1) ligand discovery using combinations
of multitemperature crystallography and empirical X-ray fragment screening (most notably to identify new ways
to allosterically inhibit the phosphatase PTP1B); 2) protein mutational engineering (most notably in the context
of protein design and in understanding the relationship between conformation dynamics and catalysis). With
MIRA support, we will continue our computational developments to further improve cryoEM modeling of
alternative conformations, to perform large scale test of the effects of ligand binding on protein conformational
heterogeneity, to improve validation and comparison of distinct ensemble model types, and to quantify density
signals for alternative conformations, hydrogens, and modifications. In parallel, our experimental work will
focus on the structural basis of new ligands to counter antibiotic resistance and on defining the conformational
landscape of the oligomeric enzyme glutamine synthetase. Our experimental work provides an important
testbed for new computational innovations and ways to validate the importance of newly modeled alternative
conformations. MIRA support will also enable us to conduct our research in a transparent and open manner,
dedicating ourselves further into early data disclosure (e.g. preprints and posts on our website) and data reuse
(e.g. deposition of primary diffraction and EM data), which are already paying dividends by enabling other
researchers. In summary, our research will create robust experimental and ...

## Key facts

- **NIH application ID:** 10895358
- **Project number:** 5R35GM145238-03
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** James Solomon Fraser
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $597,550
- **Award type:** 5
- **Project period:** 2022-09-26 → 2027-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10895358

## Citation

> US National Institutes of Health, RePORTER application 10895358, Discovering and Manipulating Macromolecular Conformational Ensembles (5R35GM145238-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10895358. Licensed CC0.

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