Dissecting the Determinants of Domain Insertion Tolerance and Allostery in Proteins

Abstract

Domain insertion engineering is a promising approach to recombine the functions of evolutionarily unrelated proteins. Insertion of light-switchable receptor domains into a selected effector protein, for instance, can yield allosteric effectors with light-dependent activity. However, the parameters that determine domain insertion tolerance are poorly understood. Here, we used an unbiased screen to systematically assess the domain insertion permissibility of several evolutionary unrelated proteins. Training machine learning models on the resulting data allowed us to dissect features informative for domain insertion tolerance and revealed sequence conservation statistics as the strongest indicators of suitable insertion sites. Finally, extending our experimental pipeline towards the identification of switchable hybrids resulted in opto-chemogenetic derivatives of the transcription factor AraC that function as single-protein Boolean logic gates. Our study reveals determinants of domain insertion tolerance and facilitates the engineering of switchable proteins with unique mechanistic properties.