Source abstract
Abstract
High Resolution Image Download MS PowerPoint Slide The green fluorescent protein (GFP) is widely used in imaging organisms at the subcellular level. However, upon exposure to UV or intense visible light, GFP undergoes irreversible reactions, altering its photocycle, which are believed to precede via photooxidation of the chromophore. The mechanism of this process is not well understood, even in the gas phase, with competing interpretations of photoelectron experiments on the isolated chromophore arguing either for nonadiabatic decay or intramolecular vibrational energy redistribution (IVR) and autoionization from an initially populated S 3 shape resonance. To address the controversy, we simulated the excited-state dynamics and time-resolved photoelectron spectroscopy (TRPES) of the GFP chromophore with ab initio multiple spawning and an on-the-fly multiconfigurational electronic structure using our dynamically weighted complete active space self-consistent field method. Our simulations show excellent agreement with experimental TRPES and reveal that S 3 -S 2 nonadiabatic transitions do occur on an ultrafast time scale that can compete with autoionization; however, the conversion between the shape and Feshbach states occurs primarily adiabatically on the S 2 state. Furthermore, the threshold energies of the shape and Feshbach resonances are very similar, with a low barrier separating these regions of the PES, leading to both states being populated and reversibly interconverting within 50 fs of the initial photoexcitation. As a result, rapid autoionization still precedes via the shape resonance. The picture that emerges thus reconciles the two competing views of the GFP chromophore’s UV response: both internal conversion and IVR from the shape resonance state are operative. Our findings of the involvement of the Feshbach state suggest new strategies to engineer FP chromophores with tailored photostabilities.
Source: openalex_inverted_index · Quality: baseline
Affiliations
NYU-ECNU Center for Computational Chemistry at NYU Shanghai, 3663 Zhongshan Road North, Shanghai 200062, China
School of Science, and Research Center for Theoretical Simulation and Applied Research in Bioscience and Sensing
Walailak University
Shanghai Frontiers Science Center of Artificial Intelligence and Deep Learning, NYU Shanghai, 567 West Yangsi Road, Shanghai 200127, China
Department of Chemistry
New York University
Division of Physical Science, Faculty of Science, Prince of Songkla University, Hat Yai, Songkhla 90112, Thailand
Center of Excellence for Trace Analysis and Biosensor
Prince of Songkla University
Funding
Walailak University · New York University Shanghai · National Natural Science Foundation of China