CAREER: New strategy to outsmart antimicrobial resistance: Mastering evolution of beta-lactamases catalytic mechanism through reaction pathways alignment, simulation, and analysis

职业：智胜抗菌素耐药性的新策略：通过反应途径比对、模拟和分析掌握 β-内酰胺酶催化机制的演变

• 批准号: 1753167
• 负责人: Peng Tao
• 金额: $ 58.43万
• 依托单位: Southern Methodist University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-06-15 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1753167&HistoricalAwards=false
• 关键词: CAREER; New; strategy; outsmart; antimicrobial

Peng Tao of Southern Methodist University is supported by an award from the Chemical Theory, Models and Computational Methods program in the Chemistry Division to develop new computational methods to model and predict the evolution of beta-lactamase catalytic mechanisms that lead to dangerous antibiotic resistant strains. How proteins are evolved is a vital question to answer for all living systems on earth. Previous studies focusing on protein sequences and structures provided great insight into protein evolution. However, there is a lack of understanding about functional mechanisms for proteins, especially for enzymes. This prevents deeper understanding of protein evolution. To meet this challenge, Professor Tao and his research group are developing an advanced theoretical framework and computational techniques to connect the evolution of enzyme sequences and structure to the evolution of their functions, catalytic activity, and mechanisms. They focus on beta-lactamases as enzymes that hydrolyze beta-lactam antibiotics and serve as one main cause of antimicrobial resistance. This work will provide fundamental understanding about the evolution of beta-lactamases' catalytic mechanisms, and could help develop a new generation of antibiotics with low resistance. The award also supports the development of educational materials to boost basic science education and outreach on social media. These freely accessible materials will benefit and shape the next generation of interdisciplinary scientists and engineers from economically disadvantaged student populations.The project focuses on developing a theoretical framework to describe enzymatic mechanism landscapes, which are defined as the structural analysis of aligned reaction pathways of evolutionarily related enzymes using statistical and machine-learning methods. This theoretical framework is helping to predict how new mutations in enzymes could lead to changes in catalytic mechanisms and activities. New computational methods are being developed by Professor Tao and his research group to explore enzyme structure-function relations and provide the missing connection between the evolution of protein structure and the variations in enzyme mechanism that are less amenable to experiment. They are also developing online-based chemistry education channels and outreach platforms to enhance general chemistry education through collaboration with teachers from other schools.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.

南方卫理公会大学的Peng Tao得到了化学系化学理论，模型和计算方法项目的支持，以开发新的计算方法来建模和预测导致危险抗生素耐药菌株的β-内酰胺酶催化机制的演变。蛋白质是如何进化的是地球上所有生命系统都要回答的一个重要问题。以前的研究集中在蛋白质序列和结构上，为蛋白质进化提供了很好的见解。然而，人们对蛋白质，特别是酶的功能机制缺乏了解。这阻碍了对蛋白质进化的更深入理解。为了迎接这一挑战，陶教授和他的研究小组正在开发一个先进的理论框架和计算技术，将酶序列和结构的进化与其功能，催化活性和机制的进化联系起来。他们专注于β-内酰胺酶作为水解β-内酰胺抗生素的酶，并作为抗菌素耐药性的主要原因之一。这项工作将为β-内酰胺酶催化机制的演变提供基础性的理解，并有助于开发新一代低耐药性抗生素。该奖项还支持开发教育材料，以促进基础科学教育和社交媒体上的宣传。这些免费获取的材料将使来自经济困难学生群体的下一代跨学科科学家和工程师受益并塑造他们。该项目侧重于开发一个理论框架来描述酶机制景观，其定义为使用统计和机器学习方法对进化相关酶的对齐反应途径进行结构分析。这一理论框架有助于预测酶中的新突变如何导致催化机制和活性的变化。陶教授和他的研究小组正在开发新的计算方法，以探索酶的结构-功能关系，并提供蛋白质结构进化与酶机制变化之间缺少的联系，这些联系不太适合实验。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Unveiling the structural features that regulate carbapenem deacylation in KPC-2 through QM/MM and interpretable machine learning

通过 QM/MM 和可解释的机器学习揭示 KPC-2 中调节碳青霉烯脱酰化的结构特征

• DOI: 10.1039/d2cp03724f
• 发表时间: 2023
• 期刊: Physical Chemistry Chemical Physics
• 影响因子: 3.3
• 作者: Yin, Chao;Song, Zilin;Tian, Hao;Palzkill, Timothy;Tao, Peng
• 通讯作者: Tao, Peng

Dataset: 1,000 QM/MM minimum energy pathway conformations for the deacylation reactions of GES-5/imipenem

数据集：GES-5/亚胺培南脱酰反应的 1,000 个 QM/MM 最小能量途径构象

• DOI: 10.5281/zenodo.6473977
• 发表时间: 2022
• 期刊: Zenodo
• 作者: Song, Zilin;Tao, Peng
• 通讯作者: Tao, Peng

Graph-learning guided mechanistic insights into imipenem hydrolysis in GES carbapenemases

• DOI: 10.1088/2516-1075/ac7993
• 发表时间: 2022-06
• 期刊: Electronic Structure
• 影响因子: 2.6
• 作者: Zilin Song;Peng-Chu Tao

Dynamical Behavior of β-Lactamases and Penicillin- Binding Proteins in Different Functional States and Its Potential Role in Evolution

• DOI: 10.3390/e21111130
• 发表时间: 2019-11-19
• 期刊: Entropy
• 影响因子: 2.7
• 作者: Wang F;Zhou H;Wang X;Tao P
• 通讯作者: Tao P

Dataset: 800 QM/MM minimum energy pathway conformations for the acylation reactions of Toho-1/ampicillin and Toho-1/cefalexin

数据集：Toho-1/氨苄青霉素和 Toho-1/头孢氨苄酰化反应的 800 个 QM/MM 最小能量途径构象

• DOI: 10.5281/zenodo.6341803
• 发表时间: 2022
• 期刊: Zenodo
• 作者: Song, Zilin;Tao, Peng
• 通讯作者: Tao, Peng