# Chemical Genetic Analysis of RAS Signaling

> **NIH NIH R01** · UNIVERSITY OF WASHINGTON · 2022 · $327,812

## Abstract

Abstract
The GTPase RAS functions as a molecular “on/off” switch, existing both in GDP-bound (inactive) and GTP-
bound forms (active). Despite functioning as a simple binary switch, RAS is capable of directing complex and
diverse cellular processes, including proliferation, migration, survival, and T-cell development. Recent work
suggests that the ability of RAS to play complex, often conflicting roles in diverse processes results from
differences in cellular context and and/or subcellular localization of its signaling. We have developed a novel
chemical genetic tool–called Chemically-Inducible Activator of RAS (CIAR)–to study the dynamics of the
signaling networks that are mediated by RAS activity. CIAR allows rapid and dose-dependent activation of
RAS signaling with a cell permeable small molecule. With CIAR, we propose to use targeted, quantitative
phosphoproteomics and transcriptomics to study the fundamental dynamic behavior of RAS-driven signaling.
Subcellularly-localized versions of CIAR will also be used to determine the effects of localized RAS activation
on the dynamics of RAS-mediated signaling. Finally, we will explore positive and negative feedback within
RAS-driven signaling pathways by selectively enhancing or inhibiting downstream signaling components.

## Key facts

- **NIH application ID:** 10465689
- **Project number:** 1R01GM145011-01A1
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Dustin J Maly
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $327,812
- **Award type:** 1
- **Project period:** 2022-04-01 → 2026-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10465689

## Citation

> US National Institutes of Health, RePORTER application 10465689, Chemical Genetic Analysis of RAS Signaling (1R01GM145011-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10465689. Licensed CC0.

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