Beyond Retinal: Machine Learning Models for Photochemical Control in Rhodopsins
Hector RCD Awardee Prof. Dr. Carolin Müller Hector Fellow Prof. Dr. Klaus Robert Müller Hector Fellow Prof. Dr. Peter Hegemann
The project is developing a machine learning framework to accurately predict the excited states of rhodopsins. To this end, a dataset of quantum chemical calculations on retinal derivatives in protein-like environments is being compiled and used for model training. The models are validated and refined through the repeated synthesis and spectroscopic analysis of specifically designed rhodopsin variants. The goal is to create a data-driven platform for the rational design of light-sensitive proteins and the accelerated development of new photoreceptors.








