Deciphering and reprogramming light induced double bond isomerization in proteins

鲍灵格林州立大学（BGSU）的Massimo Olivucci获得了化学学部生命过程化学项目的奖励，他开发、测试和应用了第二代计算框架，用于模拟光响应蛋白并通过受控序列突变调整其特性。只有两种生物系统能够利用光作为能量来源：叶绿素系统和视紫红质。叶绿素系统是复杂的，由几十种蛋白质和色素分子组成。另一方面，视紫红质是由一个蛋白质和一个视网膜分子组装在一个简单的结构中组成的。尽管如此简单，视紫红质执行各种重要的光动力功能，如离子泵送，离子通道和微生物的颜色感应，以及无脊椎动物和脊椎动物的视觉。这些可光开关的特性对定制蛋白质作为专门的探针、致动器和开关具有巨大的兴趣。本研究使用来自蓝藻的一种感觉视紫红质作为参考系统。Olivucci教授的ARM（自动视紫红质模型）协议用于构建大量计算“突变”的视紫红质，包括在蛋白质序列中人工替换氨基酸。结合经典量子力学和先进量子力学技术，利用ARM模拟突变蛋白，预测蛋白质序列的变化与对光的特异性反应之间的关系。大量突变的视紫红质可以通过计算生成并并行模拟，极大地扩展了可以探索的变异的范围和多样性。该项目将扩展ARM，以预测一系列新的性质，目标是建立一个系统的视紫红质光敏理论，应用于荧光显微镜、分子进化和光遗传学。ARM是由BGSU的学生实现的，作为一个基于网络的在线服务器，以方便学生和研究人员访问协议。这将允许高中生和本科生生成和探索复杂的，原子尺度的视紫红质模型，而不需要重要的理论背景。Olivucci教授正在将ARM整合到BGSU光化学科学研究生课程中，利用分子可视化技术和3D打印功能，为结构和功能光生物学提供新颖的介绍。该项目的目的是通过开发一种新的计算技术来了解蛋白质如何控制基本光化学反应。基于Olivucci教授的ARM协议，用于快速和自动构建光响应蛋白的QM/MM模型，将开发更准确的第二代版本，具有自由能计算能力和扩展的基准集。目标是学习如何通过调整蛋白质参考系统的化学性质来重新编程蛋白质光谱，热化学和光化学反应性-在这个项目中，来自蓝藻Anabaena的感觉视紫红质。突变模型集的构建和分析及其实验验证有望揭示新的工程原理。更具体地说，Olivucci教授正在与外部合作者一起学习突变如何控制系统的激发态异构化动力学和寿命，以及在其他应用中，利用这些知识来设计和在实验室中表达可用作光遗传学传感器的荧光视紫红质。本研究的具体目标包括通过计算筛选大量的紫红藻（Anabaena sensory rhodopsin， ASR）突变体，寻找激发态寿命较长的ASR突变体，将ARM的准确性、适用性和自动化程度提高到适合科学界推广和广泛使用的水平。

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.