PhD Dissertation Defense: Santiago Mille Fragoso

Title: Computational and Synthetic Design of Modular Molecular Devices

Abstract: Cells use molecular mechanisms to detect environmental signals and convert them into functional responses. Engineering this capability could enable programmable cell behaviors, diagnostics, and therapies, yet these sensors remain difficult to adapt to new inputs and outputs. I propose new strategies for designing molecular devices, introducing methods to design binders to proteins of interest (POIs) and a post-transcriptional mechanism that converts the binding of a molecule into an output, thereby contributing complementary approaches to program the sensing, processing, and actuation layers of synthetic molecular sensors. First, I present LIDAR (Ligand-Induced Dimerization Activating RNA editing), a post-transcriptional receptor platform that couples ligand-dependent protein proximity to ADAR-mediated RNA editing. LIDAR functions across architectures and ligand classes to produce functional outputs. Second, I present Germinal, a computational pipeline for designing antibodies for therapeutic and synthetic biology applications. By jointly optimizing antibody structure and sequence with AlphaFold-Multimer and an antibody language model, I generated VHH and scFv binders against four proteins using tens of tested designs per target, with structural and mutational analyses confirming their binding modes. Finally, I outline how these advances could converge in LIDAR-inspired synthetic receptors that couple antibody-based recognition of intracellular proteins to RNA editing. Together, these two projects establish a path toward modular molecular devices whose inputs and outputs can be selected by design.

Please contact Sofia Rakicevic-More for the Zoom link.