Search Results

Insights from genomics and high-throughput systems biology have uncovered thousands of potential gene-disease associations and putative targets for therapeutic intervention. Many of the most exciting potential targets fall into structural or functional classes that have yet to be drugged, including transcription factors and RNA-binding proteins. These proteins are often incompatible with traditional drug design due to the lack of small-molecule binding pockets or conformational plasticity. Our lab has developed screening approaches to identify binders historically recalcitrant targets, or their nearest neighbor protein partners, by screening these targets in pure form or while residing within complexes in cell lysates. Discovery stories focused on transcription factors will be discussed, including a molecule that perturbs the stability of the MYC oncoprotein, leading to attenuation of oncogenic MYC-drive transcription and reduction of tumor volume in MYC-driven tumors.

 

Machine learning of chemical information is applied to computer aided chemical synthesis - the planning of reaction paths to a given molecular target from purchasable starting materials. The use of robotics with expert user input enable execution of identified reaction paths in an automated modular continuous flow platform. Advances in automated screening and optimization of chemical reactions accelerate translation of laboratory discoveries to manufacturing. Finally, process intensification is illustrated with on-demand synthesis pharmaceuticals in plug-and-play, manually reconfigurable, refrigerator-sized manufacturing platforms.