# Modeling and design of complex RNA structures

> **NIH NIH R35** · STANFORD UNIVERSITY · 2024 · $250,000

## Abstract

PROJECT SUMMARY
The continuing discoveries of RNAs and their critical roles in cellular and viral machinery
are inspiring novel antibacterial, antitumor, antiviral, and genome-editing therapies
based on disabling, manipulating, and repurposing the RNAs involved. Unfortunately,
our poor biophysical understanding of `how RNAs work' is slowing the development of
these potentially life-saving efforts. A critical bottleneck has been the inapplicability of
crystallography, NMR, phylogenetic analysis, and biochemical methods to determine the
partly ordered conformations of non-coding RNAs in all their functional states. To resolve
this bottleneck, we are advancing experimental methods and complementary
computational approaches that give rich information sufficient to infer and engineer RNA
secondary and tertiary structures and their heterogeneous ensembles, evaluated
through community-wide blind trials, prospective compensatory mutation/rescue
experiments, and global RNA design challenges. Here, we continue research that will
rigorously address four biomedically significant problems that have so far seen limited
progress in molecular modeling efforts: the heterogeneity of RNA structures within their
native cellular and viral contexts; modeling and design of RNA's biological interactions
with proteins and other molecules, modulated by chemical modification; high-accuracy
calculation of RNA folding energetics; and the automated design of dynamic 3D RNA
structures for eventual medical applications. We will evaluate success through
continuing blind trials, independent tests by more than a dozen expert biological and
bioengineering collaborators, and through adoption of our methods and software tools by
the broader research community. In the same way that specialized structural biology
tools and computational design are establishing a firm understanding of protein behavior
and regulation, we propose that the technologies outlined here will transform our
understanding of structure in non-coding RNAs, providing a stronger basis for their
biomedical activation or disruption.

## Key facts

- **NIH application ID:** 11099334
- **Project number:** 3R35GM122579-08S1
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Rhiju Das
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $250,000
- **Award type:** 3
- **Project period:** 2017-09-01 → 2027-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11099334

## Citation

> US National Institutes of Health, RePORTER application 11099334, Modeling and design of complex RNA structures (3R35GM122579-08S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/11099334. Licensed CC0.

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