ALLOSTERIC IMPACT OF NON-ACTIVE-SITE MUTATIONS ON ENZYMATIC FUNCTION

非活性位点突变对酶功能的变构影响

• 批准号: 9977221
• 负责人: Gregory R Bowman
• 金额: $ 29.93万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-05 至 2022-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9977221
• 关键词: Active Sites; Algorithms; American; Amino Acid Sequence; Antibiotics; Bacteria; Cefotaxime; Communication; Computing Methodologies; Coupling; Directed Molecular Evolution; Disease; Distant; Drug Binding Site; Drug Design; Drug resistance; Enzymes; Equilibrium; Evolution; Freedom; Freezing; Future; Heterogeneity; In Vitro; Kinetics; Knowledge; Measures; Methods; Modeling; Molecular Conformation; Monobactams; Mutagenesis; Mutate; Mutation; Pharmaceutical Preparations; Play; Population; Proteins; Research; Resistance; Role; Sampling; Site; Source; Specific qualifier value; Structure; System; Testing; Time; Variant; Work; X-Ray Crystallography; antibiotic resistant infections; base; beta-Lactamase; beta-Lactams; biological systems; combat; cost; design; experimental study; in vivo; insight; novel

Antibiotic-resistant infections kill tens of thousands of Americans and cost our nation billions of dollars every year. β-lactamase enzymes are one of the most common sources of resistance and are capable of quickly evolving the ability to degrade new β-lactam antibiotics as they are introduced. Surprisingly, many of the mutations that confer β-lactamases with new functions are far from the enzyme's active site and have little effect on the structure of the active site, as observed by x-ray crystallography. Such non-active site (NAS) mutations also appear frequently in other contexts, such as the evolution of other forms of drug resistance and directed evolution studies. Understanding how NAS mutations allosterically impact distant sites would provide a basis for predicting new forms of drug resistance and designing allosteric drugs to combat diseases like antibiotic-resistant infections. The objective of this proposal is to understand how NAS mutations confer β- lactamases with activity against new substrates. A predictive understanding of NAS mutations remains elusive because of the ruggedness of proteins' energy landscapes and the great diversity of mechanisms that couple distant residues, including both concerted structural changes and correlations between the dynamics of different residues. These obstacles will be overcome by integrating novel computational methods with in vitro and in vivo experiments to converge on a quantitative understanding of the full spectrum of correlated fluctuations responsible for allosteric coupling. For example, the research team will apply new methods they developed to facilitate comprehensive sampling of proteins' energy landscapes, such as their FAST algorithm for leveraging Markov State Models (MSMs) to efficiently sample conformations with pre-specified features. In Aim 1, these methods will be used to identify what features of β-lactamase's structure and dynamics give rise to new activities by comparing models for variants with different activities against the antibiotic cefotaxime. In aim 2, new methods for identifying both concerted structural changes and correlations between the dynamics of different residues will be developed. These methods will be used to predict new sites where NAS mutations can alter activities of β-lactamases. To test insights from each aim, mutations will be designed to confer β- lactamases with new activities. Then experiments will be performed to test 1) whether these mutations have the intended impact on the activities of β-lactamases and 2) whether the designed variants are capable of protecting bacteria from the target antibiotic. Completion of this work will result in a general framework for understanding allosteric communication that will serve as a basis for future efforts to predict drug resistance, design new antibiotics that allosterically inhibit their targets, and manipulate allostery in other systems.

抗生素抗性感染杀死了数以万计的美国人，每一个损失我们的国家数十亿美元 年。 β-内酰胺酶是最常见的抗性来源之一，能够快速 在引入新的β-内酰胺抗生素的降解能力。令人惊讶的是，许多 将β-内酰胺酶与新功能召集的突变远非酶的活性位点，几乎没有 对活性位点结构的影响，如X射线晶体学观察到。这种非活动地点（NAS） 突变也经常出现在其他情况下，例如其他形式的耐药性演变和 定向进化研究。了解NAS突变如何变构影响遥远的站点将提供 预测新形式的耐药性和设计变构药物以打击诸如诸如 抗生素抗性感染。该提案的目的是了解NAS突变如何会议β- 乳糖酶具有针对新底物的活性。对NAS突变的预测理解仍然难以捉摸 由于蛋白质能量景观的坚固性以及夫妇的大量机制多样性 远处残留物，包括一致的结构变化和动力学之间的相关性 不同的残留物。这些障碍将通过将新型计算方法与体外整合在一起来克服 和体内实验，以汇总对整个相关范围的定量理解 负责变构耦合的波动。例如，研究小组将采用他们的新方法 开发以促进蛋白质能量景观的全面取样，例如其快速算法 用于利用马尔可夫状态模型（MSMS），以有效地采样具有预先指定特征的组成。在 AIM 1，这些方法将用于确定β-内酰胺酶结构和动力学产生的特征 通过比较具有不同活性的变体与抗生素头孢曲霉的模型来进行新活动。 AIM 2，识别一致的结构变化和动态之间的相关性的新方法 将开发不同的残留物。这些方法将用于预测NAS突变的新站点 可以改变β-内酰胺酶的活性。为了测试每个目标的见解，突变将被设计为会议β- 具有新活动的乳糖酶。然后将进行实验进行测试1）这些突变是否具有 对β-内乳酶活性的预期影响和2）设计的变体是否能够 保护细菌免受靶抗生素的影响。这项工作的完成将导致一个一般框架 了解变构沟通，这将是未来预测耐药性的努力的基础， 设计新的抗生素，可在变构中抑制其靶标，并在其他系统中操纵变构。