Deciphering and reprogramming light induced double bond isomerization in proteins

鲍林格林州立大学(BGSU)的Massimo Olivucci得到了化学部生命过程化学计划的支持，该奖项旨在开发、基准和应用第二代计算框架，以建模光响应蛋白质并通过受控的序列突变调整其性质。只有两种生物系统能够利用光作为能源：叶绿素系统和视紫红质。叶绿素系统是复杂的，由几十个蛋白质和色素分子组成。另一方面，视紫红质由一种蛋白质和一种视网膜分子组成，它们组装在一个简单的结构中。尽管这样简单，但视紫红质执行各种重要的光能功能，如微生物中的离子泵、离子通道和颜色传感，以及无脊椎动物和脊椎动物的视觉。这些光开关特性对定制用作特殊探针、致动器和开关的蛋白质具有极大的兴趣。这项研究使用蓝藻鱼腥藻的感官视紫红质作为参照系。Olivucci教授的ARM(自动视紫红质模型)方案被用来构建大量计算性的突变视紫红质，涉及蛋白质序列中的人工氨基酸替代。ARM被用来结合经典和先进的量子力学技术来模拟突变的蛋白质，并预测蛋白质序列的变化和对光的特定反应之间的关系。大量突变的视紫红质可以通过计算产生并并行模拟，极大地扩大了可以探索的变种的范围和多样性。这个项目将扩展ARM来预测一系列新的性质，目标是开发一种系统的视紫红质光敏感性理论，应用于荧光显微镜、分子进化和光遗传学。ARM正在由北卡罗来纳州立大学的学生实施，作为一个基于网络的在线服务器，以促进学生和研究人员对该协议的开放访问。这将允许高中生和本科生创建和探索复杂的原子尺度视紫红质模型，而不需要显著的理论背景。Olivucci教授正在将ARM整合到北卡罗来纳州立大学的光化学研究生项目中，利用分子可视化技术和3D打印功能提供对结构和功能光生物学的全新介绍。这个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的光化学反应。在Olivucci教授用于快速和自动构建光响应蛋白质的QM/MM模型的ARM协议的基础上，将开发具有自由能计算能力和扩展的基准集的更准确的第二代版本。我们的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以及热化学和光化学反应-在这个项目中，来自蓝藻鱼腥藻的感觉视紫红质。突变模型的构建和分析以及它们的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，利用这一知识在实验室设计和表达可用作光遗传学传感器的荧光视紫红质。这项研究的具体目标包括通过计算筛选大量鱼腥藻感觉视紫红质(ASR)突变体，寻找具有更长激发态寿命的ASR突变体，并将ARM的准确性、适用性和自动化提高到适合科学界传播和广泛使用的水平。

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.