Deciphering and reprogramming light induced double bond isomerization in proteins

破译和重编程蛋白质中光诱导的双键异构化

• 批准号: 1710191
• 负责人: Massimo Olivucci
• 金额: $ 35.01万
• 依托单位: Bowling Green State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2022-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1710191&HistoricalAwards=false
• 关键词: Deciphering; reprogramming; light; induced; double; Deciphering; reprogramming; light; induced; double

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.

鲍林绿色州立大学（BGSU）的Massimo Olivucci得到了化学过程中化学过程的奖励，用于开发，基准测试和应用第二代计算框架，以对光响应性蛋白质进行建模，并通过控制序列突变对其性质进行调整。只有两个生物系统能够利用光作为能源的来源：叶绿素系统和视紫红蛋白。叶绿素系统是复杂的，由数十种蛋白质和色素分子组成。另一方面，Rhodopsins由一种蛋白质和一个视网膜分子组成，该蛋白质组装在简单的结构中。尽管具有这种简单性，但视紫红蛋白仍具有各种重要的轻驱动功能，例如微生物中的离子泵，离子通道和色素感以及无脊椎动物和脊椎动物的视觉。这些可拍摄的特性对定制蛋白质的浓厚兴趣作为专门的探针，执行器和开关。这项研究使用来自蓝细菌的感觉视紫红质作为参考系统。 Olivucci教授的臂（自动视紫红质模型）方案用于构建大量计算上的“突变”视紫红蛋白，涉及蛋白质序列中的人造氨基酸取代。 ARM用于使用经典和先进的量子机械技术的组合来模拟突变的蛋白质，并预测蛋白质序列的变化与光的特定响应之间的关系。大量突变的视紫红蛋白可以平行地计算生成和模拟，从而极大地扩展了可以探索的变体的范围和多样性。该项目将扩展ARM以预测一系列新属性，其目的是开发一种系统的视紫红质光灵敏度，以应用于荧光显微镜，分子进化和光遗传学。 BGSU学生将ARM作为基于Web的在线服务器实施，以促进开放的学生和研究人员访问该协议。这将使高中生和本科生能够生成和探索精致的原子级视紫红质模型，而无需重要的理论背景。 Olivucci教授正在将ARM纳入光化学科学领域的BGSU研究生计划，以使用3D打印能力补充的分子可视化技术对结构和功能光生物学进行了新的介绍。 该项目的这个目的是了解蛋白质如何通过开发一种新颖的计算技术来控制基本光化学反应。将建立在Olivucci教授的ARM协议的基础上，以快速，自动化的QM/MM模型的轻响应蛋白模型，将开发具有自由能计算功能的更准确，第二代版本，并扩展了基准设置。目的是学习如何通过调整蛋白质参考系统的化学特性来重新编程蛋白质光谱以及热化学和光化学反应性 - 在该项目中，是蓝藻中的感觉式视紫红质。对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教授与外部合作者一起学习如何控制系统的激发状态异构化动态和寿命，除其他应用外，还将这些知识用于设计，并在实验室中表达荧光蛋白，这些荧光蛋白可以用作光学遗传学中的传感器。这项研究的具体目的包括在计算上筛选大量的Anabaena感觉视蛋白（ASR）突变体，搜索表现出更长激发态寿命的ASR突变体，并提高ARM的准确性，适用性和自动化为适合于科学社区传播和广泛使用的水平。