# Data-Rich Strategies for Programming Ligand-Responsive RNA Regulatory Systems

> **NIH NIH R01** · STANFORD UNIVERSITY · 2023 · $332,984

## Abstract

PROJECT SUMMARY
 Genetically-encoded technologies that enable the design of systems that receive, process, and
transmit molecular information are essential to advancing basic biological research, applied
biomedical research, and biotechnology. RNA switches are a class of ligand-responsive genetic
controllers that are being implemented in diverse biological systems to transform our ability to
monitor, interface with, and program the dynamic cellular state. While the application of synthetic
regulatory RNAs has grown remarkably over the past decade, current approaches to the design of
new RNA regulatory elements are inefficient, laborious, and typically do not yield insight into the
sequence-structure-function relationships underlying the activities of these molecules in complex
biological systems.
 The goal of the proposed project is to develop new strategies for approaching the design,
measurement, and analysis of an important class of RNA switches that incorporate ribozymes as the
gene-control element. The goal of the project will be achieved through three specific aims. The first
specific aim will focus on developing and validating a multiplexed, automated evolution pipeline to
enable the scalable discovery and characterization of new RNA switches. The second specific aim
will focus on developing new quantitative methods to examine the secondary structures and tertiary
interactions that are key to the activity of RNA switches. The third specific aim will apply the new
evolution pipeline and analysis methods to generate new RNA switches and probe the diversity of
mechanisms underlying the function of engineered switches.
 The successful execution of the project will transform our capacity to rapidly and reliably build
these genetic tools for diverse biological systems. In addition, the rich datasets generated through the
newly developed methods will be leveraged to uncover new insight into the sequence-activity
landscapes underlying this important class of functional RNA molecules and answer long-standing
questions in the field. These insights will more broadly advance our understanding of RNA sequence-
structure-function relationships and ultimately dramatically improve our capacities to design functional
RNA molecules tailored to biomedical applications. The pipelines and approaches developed through
this project will change the paradigm by which the research community approaches functional RNA
design, thereby having a substantially broader impact on the field.

## Key facts

- **NIH application ID:** 10588123
- **Project number:** 5R01GM086663-11
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** DREW ENDY
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $332,984
- **Award type:** 5
- **Project period:** 2009-01-02 → 2025-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10588123

## Citation

> US National Institutes of Health, RePORTER application 10588123, Data-Rich Strategies for Programming Ligand-Responsive RNA Regulatory Systems (5R01GM086663-11). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10588123. Licensed CC0.

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