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: 10387558
• 负责人: Gregory R Bowman
• 金额: $ 10.98万
• 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/10387558
• 关键词: Active Sites; Algorithms; American; Antibiotics; Bacteria; Cefotaxime; Communication; Computing Methodologies; Coupling; Directed Molecular Evolution; Disease; Distant; Drug Design; Drug resistance; Enzymes; Evolution; Future; In Vitro; Methods; Modeling; Molecular Conformation; Monobactams; Mutation; Pharmaceutical Preparations; Proteins; Research; Resistance; Sampling; Site; Source; Specific qualifier value; Structure; System; Testing; Variant; Work; X-Ray Crystallography; antibiotic resistant infections; beta-Lactamase; beta-Lactams; 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.

抗生素耐药性感染导致成千上万的美国人死亡，每年给我们国家造成数十亿美元的损失