Abstract:

Biological systems are inherently asymmetric, arising from chemical isomer specificity that propagates from metabolite chirality to higher-order structure and function, with profound consequences for the development of pharmaceuticals, fragrances, and agrochemicals. Yet, modern isomer analysis relies on slow and resource-intensive chromatography, limiting the deep characterization of biochemical systems. In this seminar, I will present a biology-driven alternative in which bacterial regulatory proteins are repurposed as genetically-encoded biosensors for precise, scalable measurement of chemical isomers. Through directed evolution of malleable protein scaffolds, we generate sensors selective for diverse compounds, including terpenes, polyphenols, alkaloids, and synthetic pharmaceuticals. I will also describe computational strategies that leverage large biological datasets to systematically identify biosensors and engineer enzymes for therapeutic compounds. Finally, I will introduce growth-coupled assays combined with massively parallel sequencing that enable the simultaneous measurement of over 900,000 protein–chemical interactions, generating quantitative data to guide predictive protein engineering. Together, programmable genetic sensors provide a scalable platform for studying and engineering asymmetric biochemical systems with applications spanning diagnostics, biocatalyst development, and drug discovery.