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。内酰胺是最重要的一类抗生素，对内酰胺的耐药性通常是通过内酰胺酶 (BL) 的分解而产生的。许多产生 BL 的细菌具有多重耐药性，可能会导致无法治疗的感染。令人担忧的是，经常检测到赋予耐药性的新 BL 变体。由于细菌通常含有多种 BL，因此通常不清楚哪些 BL 会导致对哪种内酰胺抗生素产生耐药性，更重要的是，不清楚如何产生耐药性。使用多尺度计算机模拟，我们之前计算了许多已知 BL 的内酰胺酰基酶形成和分解的效率，从而预测它们是否以及如何赋予特定内酰胺抗性。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 变体，从而深入了解具有增强抗生素分解活性的 BL 的进化。在这个以原子模拟为主导的多学科项目中，主要目标是了解新出现的 BL 对关键内酰胺抗生素（例如头孢菌素、碳青霉烯类）的活性增加，然后预测潜在的新变体。基于多尺度模拟的计算测定将用于评估 1) 最近发现的临床相关丝氨酸 BL 的酰基酶的形成和分解； 2) 在实验室中获得的抗性增强的丝氨酸 BL（例如由我们的国际合作者获得）。这是具有挑战性的，因为这些变体（与抗生素复合）的确切结构通常无法获得，并且需要探索不同的反应机制。值得注意的是，我们将利用获得的见解和开发的协议，通过关键位置突变的计算筛选来预测新的假定的赋予抗性的 BL 变体。然后，通过内酰胺水解的实验测定来验证所选 BL 和变体对抗生素分解的计算预测。