# Understanding the Thermodynamics and Structure of RNA Secondary Structure Motifs

> **NIH NIH R15** · SAINT LOUIS UNIVERSITY · 2020 · $454,498

## Abstract

Project Summary
 While many important RNA sequences have been determined, there is little definitive secondary and
three-dimensional (3D) structure information about RNA. Several algorithms predict RNA secondary structure
from sequence. However, they are limited by a lack of experimental parameters for non-Watson-Crick regions,
the inability to incorporate non-standard nucleotides, and a lack of knowledge about how in vivo-like conditions
affect stability. NMR and X-ray crystallography are powerful tools to determine RNA 3D structure but are time
and labor intensive. Thus, there is a need for reliable, rapid methods to predict secondary and 3D structures of
RNA from sequence. Therefore, the broad, long-term objective of the PI’s laboratory is to improve RNA
secondary and tertiary structure prediction from sequence. To do so, it is essential to understand RNA
thermodynamics and structure and how these are related. Improved nearest neighbor parameters derived
from thermodynamic data and computations can improve secondary structure prediction from sequence. To
improve tertiary structure prediction, it would help to know the structural features of secondary structure motifs
in solved three-dimensional structures. Therefore, this proposal continues to investigate the thermodynamics,
energetics, and structures of common RNA secondary structure motifs.
 Specific objectives are:
 1) derive or improve nearest neighbor parameters for naturally occurring motifs;
 2) determine how in vivo-like ions, crowders, cosolvents, and cosolutes affect Watson-Crick nearest
 neighbor parameters;
 3) identify patterns of secondary structure motifs in three-dimensional structures.
 Design and methods include optical melting experiments, hydrogen bonding and base stacking
calculations, online tool development to annotate and compare 3D structures, and an in-depth analysis of the
structural features of secondary structure motifs.
 This research is relevant to the NIH mission and AREA grant program objectives. An improved method to
predict RNA secondary and tertiary structure from sequence is essential to move RNA research forward.
Further, the work should impact researchers in any field relying on RNA structure prediction, especially those
attempting to understand the structure-function relationship of RNA, understand RNA interactions with other
biological molecules, and target RNA with therapeutics. As a result, the proposed research will advance the
nation’s capacity to protect and improve health, expand knowledge in medical and associated sciences, and
benefit students through exposure to and participation in research in the biomedical sciences.

## Key facts

- **NIH application ID:** 10114514
- **Project number:** 2R15GM085699-04
- **Recipient organization:** SAINT LOUIS UNIVERSITY
- **Principal Investigator:** Brent Znosko
- **Activity code:** R15 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $454,498
- **Award type:** 2
- **Project period:** 2009-03-01 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10114514

## Citation

> US National Institutes of Health, RePORTER application 10114514, Understanding the Thermodynamics and Structure of RNA Secondary Structure Motifs (2R15GM085699-04). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10114514. Licensed CC0.

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