# High Throughput Determination of RNA 3D Structures and Dynamics in Vivo

> **NIH NIH R35** · UNIVERSITY OF SOUTHERN CALIFORNIA · 2021 · $412,500

## Abstract

In addition to coding proteins, RNA plays fundamental roles in virtually every aspect of biology. The extreme
functional diversity of RNA stems from its ability to fold into complex structures and, like machines,
dynamically take input, transmit signal and force, and execute genetic instructions. RNA structures regulate
every step of gene expression in cells and control the life cycle of RNA viruses. As a result, physiological and
abnormal activities underlie a variety of human diseases. In recent years, targeting RNA has transitioned from
an interesting academic idea to a reality in the clinic, with the development of oligonucleotides and small
molecules that bind specific RNA sequences and structures, ushering in a new era in RNA medicine. Despite
decades of technology development, RNA structure analysis remains a major challenge, especially compared to
proteins. Traditional physical methods such as crystallography, NMR and cryo-EM has only been applied to
purified “well-behaving” samples in vitro, leaving the vast majority of cellular and viral RNAs beyond reach.
Recent chemical probing methods provided experimental constraints that improved de novo modeling but has
so far been limited to small and simple RNAs. This RNA structure analysis bottleneck has significantly limited
functional studies and therapeutic development. In this MIRA application, I outline a research program to
tackle the ultimate challenge in RNA structure biology: in vivo determination of structures and dynamics for
any RNA in any biological sample at high resolution. This proposal is based on the simple mathematical theory
that the 3D structure of any object is equivalent to the spatial distances among its components. Therefore, RNA
3D structure determination can be transformed into a problem of measuring spatial distances among the
nucleotides. To achieve this goal, we will develop ic3D (in vivo crosslinking of 3D structures, or “I see 3D”), a
technology that uses 3 new classes of “molecular rulers” - reversible chemical crosslinkers with defined lengths
- to precisely measure inter-nucleotide distances at the atomic level. Coupled with proximity ligation, high
throughput sequencing and Rosetta-based 3D modeling, ic3D enables in vivo global analysis of RNA structures
and ensembles of conformations. We will perform rigorous benchmarking against a wide selection of simple
and complex models that represent the full diversity of possible RNA structures in vivo. We will use ic3D to
discover and model 3D structures across the transcriptome. The completion of this project will have broad
impact in understanding the structural basis of RNA functions, mechanisms of RNA-mediated diseases, and
revealing new structure targets for therapeutic interventions.

## Key facts

- **NIH application ID:** 10276941
- **Project number:** 1R35GM143068-01
- **Recipient organization:** UNIVERSITY OF SOUTHERN CALIFORNIA
- **Principal Investigator:** Zhipeng Lu
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $412,500
- **Award type:** 1
- **Project period:** 2021-08-15 → 2026-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10276941

## Citation

> US National Institutes of Health, RePORTER application 10276941, High Throughput Determination of RNA 3D Structures and Dynamics in Vivo (1R35GM143068-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10276941. Licensed CC0.

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