# Determinants of the Hsp90-client interaction

> **NIH NIH R01** · UNIVERSITY OF IDAHO · 2022 · $61,038

## Abstract

!Project Abstract
The highly conserved abundant molecular chaperone Hsp90 is a global cellular regulator
that interacts with client proteins in a dynamic ATP-dependent cycle to ensure client
protein folding, transport and/or assembly into multiprotein complexes. Hsp90-
dependent proteins have critical roles in many forms of cancer and neurodegenerative
disease as well as cystic fibrosis and other diseases. Our long-term goal is to
understand how Hsp90 and cochaperones cooperate in the folding of hundreds of
proteins with diverse sequences and structures sufficiently to develop small compounds
that only affect subsets of Hsp90 clients. In the first Aim, we will use a novel set of
Hsp90 mutants to understand how three cochaperones that bind the closed, ATP and
client-bound conformation of Hsp90 fine-tune client folding. The technically innovative
second Aim will identify and characterize Hsp90 mutants that affect different subsets of
client proteins. Together these studies will enable a better mechanistic understanding of
the function of cochaperones in regulating client selection, conformation and activity.
Identification of clusters of Hsp90 mutants with similar effects will pave a path towards
rational design of compounds with selective effects on Hsp90 clients in vivo.
!

## Key facts

- **NIH application ID:** 10670003
- **Project number:** 3R01GM127675-04S1
- **Recipient organization:** UNIVERSITY OF IDAHO
- **Principal Investigator:** JILL L JOHNSON
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $61,038
- **Award type:** 3
- **Project period:** 2019-09-16 → 2025-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10670003

## Citation

> US National Institutes of Health, RePORTER application 10670003, Determinants of the Hsp90-client interaction (3R01GM127675-04S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10670003. Licensed CC0.

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