# Engineering the Next Generation of Safer Hsp90 Inhibitors

> **NIH NIH R01** · UNIVERSITY OF NOTRE DAME · 2024 · $423,618

## Abstract

Summary:
Hsp90 is a molecular chaperone that is responsible for the conformational maturation of
signaling proteins associated with all ten hallmarks of cancer, making it a promising
target for the treatment of cancer, as multiple signaling nodes can be simultaneously
derailed as a consequence of Hsp90 inhibition. Moreover, researchers have shown that
Hsp90 inhibitors accumulate in tumors with high differential selectivity, making Hsp90 a
highly sought after target for cancer. Unfortunately, clinical trials with 17 small molecule
inhibitors have led to multiple detriments that have significantly dampened enthusiasm
for Hsp90 inhibitors, as increased levels of Hsp90 were observed in the clinic, which led
to dose-escalating toxicities among other concerns. Consequently, Hsp90 remains a
desirable target for the development of cancer chemotherapeutics, but new approaches
to inhibit the protein machinery are needed that do not induce Hsp90 levels. Through a
number of seminal studies, it has been shown that inhibitors of the Hsp90 C-terminal
domain can segregate Hsp90 inhibition from induction of Hsp90 levels, and therefore,
we propose in this application to optimize these compounds and to perform a number of
pre-IND studies on the best molecules in an effort to move them toward clinical
evaluation.

## Key facts

- **NIH application ID:** 10798174
- **Project number:** 5R01CA270147-02
- **Recipient organization:** UNIVERSITY OF NOTRE DAME
- **Principal Investigator:** Brian S J Blagg
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $423,618
- **Award type:** 5
- **Project period:** 2023-03-01 → 2026-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10798174

## Citation

> US National Institutes of Health, RePORTER application 10798174, Engineering the Next Generation of Safer Hsp90 Inhibitors (5R01CA270147-02). Retrieved via AI Analytics 2026-06-12 from https://api.ai-analytics.org/grant/nih/10798174. Licensed CC0.

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