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

抗生素耐药性感染导致数万美国人死亡，每年给我们国家造成数十亿美元的损失 年。β-内酰胺酶是最常见的耐药性来源之一，能够迅速 进化出在新的β-内酰胺类抗生素推出时降解它们的能力。令人惊讶的是，许多 赋予β-内酰胺酶新功能的突变远离酶的活性部位，而且几乎没有 对活性中心结构的影响，如X射线结晶学所观察到的。此类非活动站点(NAS) 突变也经常出现在其他情况下，例如其他形式的耐药性的进化和 定向进化论研究。了解NAS突变如何以变构方式影响远程站点 这是预测新的耐药性形式和设计变构药物对抗疾病的基础 抗生素耐药感染。这项建议的目的是了解NAS突变是如何赋予β- 对新底物具有活性的内酰胺酶。对NAS突变的预测性理解仍然难以捉摸 因为蛋白质的能量格局是崎岖的，其相互作用的机制也千差万别 远距离残基，包括协调的结构变化和动力学之间的相关性 不同的残留物。通过将新的计算方法与体外实验相结合，这些障碍将被克服 并在体内实验上收敛于对相关全谱的定量理解 引起变构偶联的波动。例如，研究小组将应用他们的新方法 开发以便于对蛋白质的能量景观进行全面采样，例如其快速算法 用于利用马尔可夫状态模型(MSM)有效地对具有预先指定特征的构象进行采样。在……里面 目的1.这些方法将用于鉴定β-内酰胺酶的结构和动力学特征 通过比较具有不同抗菌素活性的变异体的模型来研究新的活性。在……里面 目标2，确定协调一致的结构变化和动态之间的相关性的新方法 将开发不同残留物的种类。这些方法将用于预测NAS突变的新位点 可以改变β-内酰胺酶的活性。为了测试每个目标的洞察力，突变将被设计成授予β- 具有新活性的内酰胺酶。然后将进行实验以测试1)这些突变是否具有 对β-内酰胺酶活性的预期影响以及2)设计的变异体是否能够 保护细菌免受目标抗生素的伤害。这项工作的完成将产生一个总体框架 了解变构通讯将成为未来预测耐药性的基础， 设计新的抗生素，通过变构抑制其靶标，并在其他系统中操纵变构。

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.