BPS2026 – Modeling elucidates variable impact of small molecule probes on a spliceosomal U4/U6 small nuclear RNA structure in yeast

RNA sequences encode genetic information and regulatory structures controlling splicing, degradation, and other processing. Given these multiple functions, modeling the impact of small molecules on the targeted RNA is an important and challenging aspect of functional studies with potential therapeutic applications. Because of their highly flexible nature, fewer evident docking pockets, and more uniformly distributed surface charge, prediction and modeling of RNA interactions with small molecules is non-trivial. We approach these challenges by identifying hydrophobic regions as potential binding sites and by considering the available alternative NMR conformations and exploring flexibility of the RNA targets and RNA-ligand complexes with molecular dynamics simulations. Pre-mRNA splicing is controlled by a large ribonucleoprotein complex called spliceosome. Small nuclear RNAs (snRNAs) that participate in RNA-RNA and RNA-protein interactions are necessary to the assembly of spliceosome. Here, we study the assembly of yeast U4/U6 snRNAs that recruit functional proteins, such as Snu13, and Prp31. Screening with small molecule microarrays has identified two hit compounds that bind the 5’ stem-loop’s (SL) kink turn motif in a strongly asymmetric internal loop. One disrupts the target structure, while a better binding analog of the other one stabilizes the RNA SL and blocks its binding to the Snu13 protein. In agreement with the experiments, computer modeling distinguished clearly between the impact of two ligands on the targeted RNA structure’s stability and yielded insights into the mechanism of the observed interference with Snu13 binding. This presentation focuses on the modeling aspects of the study, demonstrating the benefits of a combined experimental and computational approach to targeting RNA with small molecule probes in the process of studying spliceosome assembly mechanisms and identifying potential therapeutic targets. Funded in part by 75N91019D00024.