Awarded in 2024
Home Department: Bioengineering
Faculty Advisors: Xiaojing Gao (Chemical Engineering) and Brian Hie (Chemical Engineering)

Research Title: Machine Learning-assisted design of novel modular protein sensors

Programmable protein sensors hold promise for personalized therapies and research tools as they could allow us to sense specific cell states/types and act in response. However, fully modular protein sensors that can detect diverse inputs and produce defined outputs have been hard to design due to challenges coupling the sensing of the protein to the regulation of a defined output. Luis proposes designing single-chain intracellular sensors that couple protein binding to RNA-editing activity by using Machine Learning to design de novo protein binders and decode sequence-function relationships, enabling efficient development and screening of new functional protein sensors.