UKRI/BBSRC-NSF/BIO: Evolving quantum mechanical tunnelling in enzymes

UKRI/BBSRC-NSF/BIO：酶中量子力学隧道效应的演变

• 批准号: 2244981
• 负责人: Steven Schwartz
• 金额: $ 64.71万
• 依托单位: University of Arizona
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-12-01 至 2025-11-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2244981&HistoricalAwards=false
• 关键词: UKRI; BBSRC; NSF; BIO; Evolving

Enzymes are the most effective catalysts on the planet. They have the capability of speeding chemical reactions by a factor of up to 1015 over uncatalyzed reactions. Amazingly, after decades of research, the way this occurs is still in many instances a mystery to chemists and biologists. In addition, while chemistry is governed by the laws of Quantum Mechanics, there is still controversy over the importance of quantum mechanical effects in enzymatic reactions. The use of quantum principles would potentially allow many technological advances such as creating bio-inspired catalysts that were immune to low temperatures and have broader reactivities. This project explores the way such quantum effects may be built into enzyme function using the technology known as directed evolution. A Nobel prize winning technology that allows scientists to create enzyme functions in the laboratory using evolutionary principles in months rather than millennia. This project will train pre-and post-doctoral students in interdisciplinary research and broaden their experience by exposing them to international research collaboration.The functions of enzymes remain a topic of hot debate in the scientific community. Two of the most important areas of controversy are the importance of the coupling of dynamics to enzyme function, and what that has to do with the importance of quantum effects such as tunneling on enzyme rate. This project explores such question through the application of rare event sampling for enzymatic chemistry. The PI has pioneered such studies in particular the use of Transition Path Sampling coupled with committor distribution analysis to identify rigorous reaction coordinates. The PI has also developed methods to include quantum dynamics via path integral simulations. These will be coupled with directed evolution experiments of with UK collaborators who in their projects will craft artificial enzymes optimized for example to transfer deuterons rather than protons. These experiments coupled with the project described will show if quantum capabilities can be built into artificial enzymes, and just what those capabilities will allow. This collaborative US/UK project is supported by the US National Science Foundation and the UK Biotechnology and Biological Sciences Research Council where NSF funds the US investigator and BBSRC funds the UK partner.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

酶是地球上最有效的催化剂。它们具有加速化学反应的能力，比非催化反应快1015倍。令人惊讶的是，经过几十年的研究，这种情况发生的方式在许多情况下仍然是化学家和生物学家的一个谜。此外，虽然化学受量子力学定律的支配，但在酶反应中量子力学效应的重要性仍然存在争议。量子原理的使用可能会使许多技术进步成为可能，例如创造出不受低温影响并具有更广泛反应性的生物启发催化剂。该项目探索了这种量子效应如何使用被称为定向进化的技术构建酶功能。一项获得诺贝尔奖的技术，使科学家能够在实验室中使用进化原理在几个月而不是几千年内创造酶功能。本项目将培养跨学科研究的博士生和博士后学生，并通过国际研究合作扩大他们的经验。酶的功能仍然是科学界争论的热点。两个最重要的争议领域是动力学与酶功能耦合的重要性，以及这与量子效应（如隧道效应）对酶速率的重要性有什么关系。本计画借由稀有事件取样于酵素化学之应用，探讨此一问题。PI开创了这种研究，特别是使用过渡路径采样与提交者分布分析相结合，以确定严格的反应坐标。PI还开发了通过路径积分模拟包含量子动力学的方法。这些将与英国合作者的定向进化实验相结合，这些合作者将在他们的项目中制作人工酶，例如优化转移氘而不是质子。这些实验与所描述的项目相结合，将展示量子能力是否可以构建到人工酶中，以及这些能力将允许什么。这个美国/英国的合作项目得到了美国国家科学基金会和英国生物技术和生物科学研究理事会的支持，NSF资助美国研究者，BBSRC资助英国合作伙伴。这个奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。