Deciphering and reprogramming light induced double bond isomerization in proteins

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Massimo Olivucci of Bowling Green State University (BGSU) is supported by an award from the Chemistry of Life Processes Program in the Chemistry Division to develop, benchmark, and apply a second-generation computational framework for modeling light-responsive proteins and tuning their properties via controlled sequence mutations. Only two biological systems are capable of exploiting light as a source of energy: chlorophyll systems and rhodopsins. Chlorophyll systems are complex, composed of dozens of protein and pigment molecules. Rhodopsins, on the other hand, consist of one protein and one retinal molecule assembled in a simple architecture. In spite of such simplicity, rhodopsins carry out a variety of important light-powered functions such as ion-pumping, ion-channeling and color-sensing in microorganisms, and vision in invertebrates and vertebrates. These photoswitchable properties are of enormous interest in tailoring proteins for use as specialized probes, actuators, and switches. This research uses a sensory rhodopsin from the cyanobacterium Anabaena as a reference system. Professor Olivucci's ARM (Automatic Rhodopsin Model) protocol is used to construct a large number of computationally "mutated" rhodopsins, involving an artificial amino acid substitution in the protein sequence. ARM is used to simulate the mutated protein using a combination of classical and advanced quantum mechanical techniques, and predict the relationship between the changes in protein sequence and specific responses to light. Large numbers of mutated rhodopsins can be computationally generated and simulated in parallel, enormously extending the range and diversity of variants that can be explored. This project will extend ARM to predict a range of new properties, with the goal of developing a systematic theory of rhodopsin light sensitivity for application to fluorescence microscopy, molecular evolution, and optogenetics. ARM is being implemented by BGSU students as an online web-based server to facilitate open student and researcher access to the protocol. This will allow high school students and undergraduates to generate and explore sophisticated, atomic-scale rhodopsin models without requiring significant theoretical background. Professor Olivucci is integrating ARM into the BGSU graduate program in photochemical science, to provide a novel introduction to structural and functional photobiology using molecular visualization techniques complemented by 3D printing capabilities. This aim of this project is to understand how proteins control elementary photochemical reactions by developing a novel computational technology. Building on Professor Olivucci's ARM protocol for the fast and automated construction of QM/MM models of light-responsive proteins, a more accurate, second-generation version will be developed featuring free energy calculation capabilities and an expanded benchmark set. The goal is to learn how to reprogram protein spectroscopy and thermochemical and photochemical reactivity by tailoring the chemical properties of a protein reference system---in this project, a sensory rhodopsin from the cyanobacterium Anabaena. The construction and analysis of sets of mutated models and their experimental verification are expected to reveal novel engineering principles. More specifically, and together with external collaborators, Professor Olivucci is learning how mutations may control the excited state isomerization dynamics and lifetime of the system and, among other applications, to use this knowledge to design, and express in the laboratory, fluorescent rhodopsins that could be employed as sensors in optogenetics. Specific aims of the research include computationally screening large numbers of Anabaena sensory rhodopsin (ASR) mutants, searching for ASR mutants exhibiting longer excited state lifetimes, and improving the accuracy, applicability and automation of ARM to a level suitable for dissemination and broad use by the scientific community.