# Regulation of the Native Protein Landscape in the Nucleus by Molecular Chaperones

> **NIH NIH R35** · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · 2021 · $376,865

## Abstract

ABSTRACT
 Homeostasis requires most, if not all, pathways to function rapidly and precisely. While
cooperative interactions between proteins and cofactors helps ensure selectivity, the events
mediating dynamic action are less well understood. Further complicating pathway performance is the
nature of the cell interior, as it is densely packed and often contains multiple binding partners for each
protein—both features increase non-productive or off-pathway interactions. These variables present
great challenges for achieving homeostasis especially in the midst of fluctuating internal and external
stimuli that must be monitored constantly to appropriately initiate, continue, or halt cellular processes.
Hence, biological complexes must be actively and persistently disassembled in order to work on a
useful time scale. We suggest that the broad binding specificity and energy-independent molecular
chaperone activities of the Hsp90 chaperone system govern the kinetic behaviors of the diverse
proteins within cells. Basically, Hsp90 and its cochaperones resolve inherently stable cooperative
complexes into a dynamic machinery capable of rapid action that enables efficient and timely
biological pathways.

## Key facts

- **NIH application ID:** 10244899
- **Project number:** 5R35GM136660-02
- **Recipient organization:** UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
- **Principal Investigator:** Brian C Freeman
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $376,865
- **Award type:** 5
- **Project period:** 2020-09-01 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10244899

## Citation

> US National Institutes of Health, RePORTER application 10244899, Regulation of the Native Protein Landscape in the Nucleus by Molecular Chaperones (5R35GM136660-02). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10244899. Licensed CC0.

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