MFB: Comprehensive, Accurate Predictions of Modified RNA-protein Interactions in Biology

About This Grant

This award, under the Molecular Foundations for Biotechnology (MFB) program in the Division of Chemistry, funds Drs. Scott Aoki and Jonah Vilseck from the Indiana University School of Medicine to develop a computational strategy to accurately predict how unmodified and modified RNAs interact with proteins that control or regulate important biological functions. Chemical modifications to the bases in RNA affect their recognition by proteins and, consequently their function. With over 170 modifications identified thus far, new methods are required to elucidate how combinations of unmodified and modified RNAs interact with regulatory RNA-binding proteins. This project adapts a physics-based molecular modeling technique called λ-dynamics that, when paired with classic RNA biochemistry, determines the RNA sequence preferences of a host of RNA-binding proteins involved in gene expression. The research provides new insights into the biological function of RNA modifications in areas that impact biotechnology. In parallel, a summer program is being created that engages junior trainees in scientific literature about RNA modifications as an entrée into STEM careers. Current methods to study RNA-protein interactions are accurate but often expensive, time-consuming, and limited by available reagents. New methods are required to study how RNA and its modifications affect RNA-protein interactions and their subsequent roles in biology. λ-dynamics is an efficient computational method for simultaneously modeling the free energies of molecular interactions and modifications in biomolecular systems. The goal of this proposal is to advance the λ-dynamics method to accurately predict how chemical modifications to RNA bases will affect binding to a library of critical RNA-binding proteins. The two major contributions from these studies include presenting an effective means to predict RNA sequences that are preferred for protein binding and enabling the study of how relevant base modifications affect binding to proteins that are involved in RNA turnover. The computational predictions will be validated by classical biochemical assays for protein recognition and binding of unmodified and modified RNA oligonucleotides. These insights drive fundamental discoveries of the role of RNA modifications in biology. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.