PROJECT SUMMARY: Most small molecule drugs elicit their effects by modulating protein function, despite the fact that only a small portion of the genome is translated (~1-2%). Further, only ~15% of the human proteome is considered to be druggable, severely limiting therapeutic pipelines. The scientific challenge is to develop generalizable methods to drug the other ~85% of coding genes. The purpose of this proposal is to advance a radically new paradigm to expand the druggability of the (protein coding) genome by targeting disease-causing genes at the level of their RNA. To do so, we will computationally and biochemically determine RNA secondary structures in the transcriptome, with a focus on disease associated genes, to aid in the design of drug-like small molecules to treat diseases at the RNA level. This innovative approach for targeting the transcriptome could massively expand our ability to treat a wide array of diseases, spanning from genetic disorders to cancer and pathogenic infections, and expanding the repertoire of drug action. The proposed studies synergize the expertise of two laboratories. Dr. Walter Moss’ Lab (sponsor) has developed and implemented robust approaches to precisely define conserved and functional RNA structures throughout the human genome. Dr. Matthew Disney’s lab (co-sponsor) has established a comprehensive program for the design of small molecules that selectively target RNA and modulate disease biology, including those that selectively recruit endogenous nucleases to a desired transcript. Collectively, our synergistic areas of expertise will allow us to define the druggable human genome, drug undruggable protein targets at the level of their mRNAs, and push forward a bench-to-bedside, precision medicine paradigm. In Aim 1, we will define conserved RNA structures throughout the genome, with a focus on validating and targeting conserved structures in mRNAs that encode proteins that are considered undruggable. These studies will define evolutionary conservation across vertebrate genomes to provide key insights into both biology and druggability. We will evaluate and improve model structures using in cellulis RNA structure probing to test predictions and, where needed, provide constraints that can be used to create experimentally informed revised models. In Aim 2 we will generate a list of high value motifs with the highest probability of being druggable, perform functional analyses to determine their effects on gene expression, and deduce interactions.