synthetic MS2. synthetic construct

RNA-protein interactions drive many fundamental biological processes and are targets for molecular engineering, yet quantitative and comprehensive understanding of the sequence determinants of affinity remains limited. We repurposed a high-throughput sequencing instrument to quantitatively measure binding and dissociation of a protein to >107 RNA targets generated on the flow cell surface, providing massive biophysical datasets for sequence-function analyses across diverse sequence space. Using the MS2 coat protein, we decompose the binding energy contributions from RNA primary and secondary structure, and find that differences in affinity are often driven by sequence-specific changes in association rates. Analyzing the biophysical constraints and preferences for the evolution of high-affinity RNA sequences at unprecedented scale, we observe and quantify widespread molecular epistasis, as well as long-hypothesized structure-dependent preference for G:U base pairs over C:A intermediates in evolutionary trajectories. Our results suggest quantitative variant analysis of RNA on a massively parallel array (RNA-MaP) provides generalizable insight into structure-function relationships across combinatorial sequence spac