Deciphering the principles and mechanism of RNA structure - Project Summary/Abstract: This project seeks to address the significant challenges in RNA structure, an area that remains underdeveloped despite RNA’s critical roles in various biological processes and its potential for therapeutic applications. The research is structured into three major aims, each leveraging computational and biophysical methodologies to push the boundaries of our understanding of RNA structure. Aim 1 focuses on the computational aspects of RNA structure prediction. The goal is to create an unprecedented RNA sequence database, referred to as RNAmass, which will aggregate a vast array of sequences from diverse sources, including viral and non-coding RNAs. This database will be instrumental in training a foundational RNA language model, RNA-FLM1. This model will be trained in two phases: initially on the entire RNA sequence dataset, and subsequently on sequences identified as highly conserved through rigorous conservation analysis. The final output of this aim is the development of 3DFoldRNA, a novel tool designed to predict RNA 3D structures directly from sequence data. This tool, inspired by the latest advancements in protein structure prediction, will utilize a cutting-edge architecture specifically optimized for RNA, addressing the current gaps in RNA structure prediction methodologies. Aim 2 transitions from computational predictions to in-vitro experimental validation, focusing on the structural determination of RNA elements using cryo-electron microscopy (cryoEM). The initial focus will be on highly conserved viral RNA elements, which are hypothesized to adopt stable and distinct 3D conformations. By solving the structures of these RNA elements, the project aims to gain insights into the fundamental principles of RNA folding and function. This aim will contribute new structural data to the limited repository of known RNA structures, thus enhancing the overall understanding of RNA biology. Aim 3 focuses on the in-situ study of RNA structures within their native cellular environments using cryo- electron tomography (cryoET). This aim will investigate how RNA elements, particularly those involved in programmed ribosomal frameshifting (PRF), interact with ribosomes and other cellular machinery in real-time. The study will provide a detailed view of how these RNA structures function within the crowded and dynamic environment of the cell, offering insights that cannot be captured through in vitro studies alone. By using cryoET, the project will capture the conformational dynamics of RNA structures as they perform their biological functions, thus bridging the gap between static structural data and the dynamic nature of RNA in living systems. In summary, this project combines the power of computational modeling with cutting-edge experimental techniques to tackle the RNA structure problem from multiple angles. The integration of these diverse approaches promises to make significant contributions to the field of RNA biology, with potential implications for the development of RNA-based therapeutics and the identification of new antiviral targets.
