Analysis of RNA tertiary structure and tertiary motifs: Insights into RNA prediction

Autor: Christian Laing Celestino
Christian Laing Navigate Biopharma, A Novartis Company Analysis of RNA tertiary structure and tertiary motifs: Insights into RNA prediction In recent years, many exciting discoveries have exposed the versatility of RNA. Clearly more findings are yet to come given the many novel non-protein-coding transcripts recently identified, and the structure-function relationship that exists within RNA molecules emphasizes the necessity to build more efficient computer programs to predict their structure. In this talk, I present a study on solved 3D RNA molecules, which aims to determine structural patterns and design rules that can help predict their 3D shape. Specifically, we implemented several mathematical tools to understand and predict the structural arrangements of RNAs, revealing the existence of higher-order motifs built by a combination of smaller sub-motifs. These findings have helped recognize new levels of organization in RNA structure. Furthermore, a statistical technique known as random forest was used to predict the coaxial helical stacking and junction families by using length and sequence information from known 3D junctions. The results give a reasonable prediction accuracy (~80%). These prediction scores constitute a dramatic improvement over previous attempts, and comprise an important step towards RNA 3D structure prediction.