Cutting the Gordian knot of excited-state modeling in complex environments

Autofluorescent proteins are a class of photoactive proteins widely used in biological experiments, being compatible with noninvasive imaging in living cells. The focus of this thesis is to develop a reliable and accurate modeling framework for the photophysical properties of these and other photosensitive biosystems. To this end, a multiscale approach is necessary given the size of the systems: A protein contains thousands of atoms and a quantum mechanical treatment thereof is clearly impossible. The light absorption and electronic excitation of these proteins is however typically localized on the so-called chromophore (or antenna) and a quantum description of this limited area combined with a less accurate but faster treatment of the rest of the protein is a possible solution. In this thesis, we propose a new multiscale scheme where the environment is still treated quantum mechanically but through the computationally cheaper density functional theory (DFT), and allowed to respond to the excitation of the embedded chromophore. This scheme is demonstrated on several small molecules and shown to improve on the use of a unresponsive environment. We also present its application to a prototypical autofluorescent protein and pinpoint the important ingredients for a successful modeling of the photoexcitation in this coupled chromophore-protein complex.