Rhodopsin Engineering through Structure-Guided Recombination

Abstract

Membrane proteins assume key roles in environmental sensing, metabolite uptake, and product efflux. Given the vital connections they facilitate between a cell and its environment, there is great potential to engineer these proteins to modulate cellular activity and productivity. For this project, we focus our efforts on rhodopsins, light-sensing transporters and channels that have applications in optical biosensors, neuronal monitoring and control, and bioenergy. Using structure-guided recombination we have built a library of chimeric rhodopsins. We used a novel assay for membrane protein localization to pre-screen a fraction of the library. A diverse selection of well-expressing variants has been further characterized via electrophysiology. Through machine learning we can associate rhodopsin expression, localization, and functional properties to blocks of structure and make predictions on the properties of untested chimeras.

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