(160n) Computational RNA Design in the Ribosomal Active Site

The ribosome, a complex biological machine capable of synthesizing proteins by rapidly polymerizing α-amino acids, has attracted much interest for repurposing it to program and build polymers from novel substrates. Previous work from our lab has shown that the rRNA in the ribosome’s active site, despite high sequence conservation, demonstrates significant flexibility at the scale of single-nucleotide mutations. However, making larger-scale changes to the active site, as will likely be required to expand the ribosomal substrate pool, has remained a challenge, as the design rules of how to redesign the rRNA sequence without breaking activity remain unknown. To address this challenge, we leverage a computational RNA design approach in combination with in vivo and in vitro ribosome testing platforms to explore whether a modeling approach can provide us with guiding principles to create functional rRNA designs. By testing the activity of the computationally designed ribosomes, we can identify patterns in rRNA design that either enable or preclude ribosome activity, as well as how these results differ in an in vivo versus in vitro environment. The results from this analysis can be leveraged to explore the design space in a high-throughput manner and ultimately to design ribosomal mutants capable of novel activities.