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### 预反应态模型浅析：催化活性和近过渡态分子模拟

SIM Byuri, 赵一雷

1. 上海交通大学生命科学技术学院，微生物代谢国家重点实验室，上海 　200240
• 收稿日期:2021-01-27 修回日期:2021-02-03 出版日期:2022-06-30 发布日期:2022-07-13
• 通讯作者: 赵一雷
• 作者简介:SIM Byuri（1990—），男，硕士研究生。研究方向为醇脱氢酶CpRCR的共进化突变效应。E-mail：byurisim@sjtu.edu.cn|赵一雷（1972—），男，教授，博士生导师。研究方向为酶催化反应分子机制、蛋白质与核酸化学修饰，计算化学与分子生物信息学在蛋白质工程和生物医学中应用。E-mail：yileizhao@sjtu.edu.cn
• 基金资助:
国家自然科学基金(31970041);国家重点研发计划(2020YFA0907700)

### Assessment on the pre-reaction state of enzyme: could we understand catalytic activity with near transition-state molecular dynamic simulation?-a review

Byuri SIM, Yilei ZHAO

1. State Key Laboratory of Microbial Metabolism，School of Life Sciences and Biotechnology，Shanghai Jiao Tong University，Shanghai 200240，China
• Received:2021-01-27 Revised:2021-02-03 Online:2022-06-30 Published:2022-07-13
• Contact: Yilei ZHAO

Abstract:

The bottleneck of enzyme design for biosynthetic elements lies in the incompetence of the limited computing resources with demanding for an in-depth computation on complicated potential energy surfaces of catalytic reactions. However, two unprecedented achievements are expected to expand artificial intelligence machine learning in protein engineering-one is a variety of high-efficient mutants brought by high-throughput directed evolution experiments, and the other is the high-quality molecular simulation of all-atom with femtosecond precision revealed by ab initio quantum mechanics calculation and three-dimensional structural information. This work briefly describes the basic concept and application of the pre-reaction state (PRS) model from the perspectives of the fundamental enzyme theories, the near-attack conformation of Michealis complex, and the control points of the catalytic cycle efficiency. The pre-reaction state model tries to use the intrinsic features of biochemical reactions with low activation energy in which transition state and pre-reaction states share similar physiochemical stability, flexibly selects the rate-determining transition states related to the evolutional goal of the catalytic element, and employs classical molecular dynamics simulations to understand the relationship of active conformation population with distal mutations, substrate spectrum, and experimental conditions. The general pre-reaction state protocol is: first, the near-transition state structural features are extracted from the high-level quantum-mechanical calculation on the rate-determining transition structures; then the PRS molecular dynamic simulations are collected from the restrained to the free state, which is used to study the adaptability between mutants and substrates. The population in the PRS trajectory is used as a semi-quantitative correlation coefficient of “pre-reaction state-enzyme activity” （PRS-EA）, and the adaptation map of enzyme and substrate is mined from the pre-reaction state stability. Although the mechanism-based pre-reaction state analysis provides an insightful rationale at atom levels as a post-NAC approach, the quantitative relationship between the PRS structure and enzymatic reaction cannot be fully illustrated owing to the ambiguity of the PRS constraint, the repeatability of molecular dynamics simulation, and the arbitrariness of reactive population. The high throughput quantum calculation for transition state samplings and machine learning and artificial intelligence could be integrated to unveil the quantitative structure-activity relationship, paving a way for the practical applications of pre-reaction state in protein engineering.