Anticipating antimicrobial resistance: predicting the resistance-spectrum of emerging lactamase variants using atomistic simulation and experiment

预测抗菌药物耐药性：使用原子模拟和实验预测新兴内酰胺酶变体的耐药谱

• 批准号: 2767481
• 金额: --
• 依托单位: University of Bristol
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2767481
• 关键词: Anticipating; antimicrobial; resistance; predicting; spectrum

Rising antibiotic resistance is a major problem for human health. Resistance to lactams, the single most important antibiotic class, usually arises through their breakdown by lactamases (BLs). Many BL producing bacteria are multi-drug resistant and may cause untreatable infections. Worryingly, new BL variants conferring resistance are detected frequently. As bacteria usually harbour multiple BLs, it is often not clear which BLs cause resistance against which lactam antibiotics, and, importantly, how. Using multi-scale computer simulations, we have previously calculated the efficiency of lactam acyl-enzyme formation and breakdown for a number of known BLs, thereby predicting whether and how they confer resistance to specific lactams. Genomic analysis of clinical isolates as well as lab experiments can identify new BL variants and thereby provide insights into the evolution of BLs with enhanced antibiotic breakdown activity. In this atomistic simulation-led multidisciplinary project, the main aim will be to understand increased activity of newly arising BLs against key lactam antibiotics (e.g. cephalosporins, carbapenems), and then predict potential new variants. Computational assays based on multi-scale simulations will be used to assess formation and breakdown of the acyl-enzymes of 1) recently discovered, clinically relevant serine BLs; and 2) serine BLs with increased resistance obtained in the lab (e.g. by our international collaborators). This is challenging, as exact structures of these variants (in complex with antibiotics) are often not available and different reaction mechanisms will need to be explored. Notably, we will use the insights gained and protocols developed to predict new putative resistance-conferring BL variants from computational screening of mutations at key positions. Computational predictions of antibiotic breakdown by selected BLs and variants will then be validated by experimental determination of lactam hydrolysis.

抗生素耐药性的上升是人类健康的一个主要问题。内酰胺类抗生素是最重要的一类抗生素，对内酰胺类抗生素的耐药性通常是由内酰胺酶(BLS)分解引起的。许多产生BL的细菌对多种药物具有耐药性，可能导致无法治愈的感染。令人担忧的是，导致耐药的新的BL变异体被频繁检测到。由于细菌通常携带多种BLS，人们往往不清楚哪种BLS会对哪种内酰胺类抗生素产生耐药性，更重要的是，它是如何产生耐药性的。利用多尺度计算机模拟，我们先前已经计算了一些已知BL的内酰胺酰基酶的形成和分解效率，从而预测它们是否以及如何对特定的内酰胺类药物产生耐药性。临床分离株的基因组分析以及实验室实验可以识别新的BL变异，从而通过增强抗生素分解活性来深入了解BLS的进化。在这个原子模拟主导的多学科项目中，主要目的将是了解新出现的BLS对关键内酰胺类抗生素(如头孢菌素类、碳青霉烯类)的活性增加，然后预测潜在的新变种。基于多尺度模拟的计算分析将被用来评估1)新近发现的临床相关的丝氨酸BLS和2)在实验室(例如我们的国际合作者)获得的耐药性增加的丝氨酸BLS的酰基酶的形成和分解。这是具有挑战性的，因为这些变体的确切结构(与抗生素复合)通常无法获得，需要探索不同的反应机制。值得注意的是，我们将使用所获得的洞察力和开发的方案，通过对关键位置的突变进行计算筛选来预测新的假定与抗药性相关的BL变异。选定的BLS和变异体对抗生素分解的计算预测将通过内酰胺水解的实验测定来验证。