Controlling transcription factor networks in cell therapies at the protein-protein interaction level
How do we maximize the proportion of engineered cells that are in the desired functional or differentiation state? Transcription factor networks play an outsized role in controlling cell states. Finding and maintaining the correct balance of transcription factor expression levels, combinations, and timings is crucial to creating more effective cell therapies. We are interested in regulating the function of transcription factor networks at the level of their protein-protein interactions.
Advances in computational protein design and engineering allow us to program protein binding specificity to create new protein modules to alter transcription factor complex formation. Through engineering genetically encodable binding proteins to modulate transcription factor function, we aim to optimize cell state by controlling the function of endogenous cellular transcription factors at the post-translational level.
Dynamic regulation of transcription factors
Immune cells are constantly sensing and responding to factors in their environment. While considerable progress has been made in engineering these sense and response programs at the level of signaling receptors, fewer options exist for programming transcription factors to respond to environmental and intracellular signals. We seek to build new molecular toolsets and circuits that enable programming of transcription factors to respond to signals from the tumor microenvironment or intracellular signaling states. Creating intelligent cells that can change their behavior based on their environment is an important goal for increasing safety and efficacy of cell therapies.
Quantitative control of biological processes
Scientists need molecular control tools that allow quantitative and dynamic probing of how subcellular processes work. We have a unique multi-input/multi-output chemically regulated dimerization system that offers special capabilities of switching, graded, and proportional control in response to orthogonal drug inputs. We are interested in applying these extrinsic control capabilities in areas of basic and translational research to help scientists answer questions about their system of interest.