Suppr超能文献

针对黏质沙雷氏菌中氨基糖苷 N(6')-乙酰转移酶的潜在先导化合物设计:一种药物发现策略。

Designing potential lead compounds targeting aminoglycoside N (6')-acetyltransferase in Serratia marcescens: A drug discovery strategy.

机构信息

Centre for Bioinformatics, Karpagam Academy of Higher Education, Coimbatore 641021, India; Department of Biotechnology, Karpagam Academy of Higher Education, Coimbatore 641021, India.

Centre for Bioinformatics, Karpagam Academy of Higher Education, Coimbatore 641021, India; Department of Biochemistry, Karpagam Academy of Higher Education, Coimbatore 641021, India.

出版信息

Int J Biol Macromol. 2024 Nov;281(Pt 1):136976. doi: 10.1016/j.ijbiomac.2024.136976. Epub 2024 Oct 28.

Abstract

Serratia marcescens is an opportunistic human pathogen that causes urinary tract infections, ocular lens infections, and respiratory tract infections. S. marcescens employs various defense mechanisms to evade antibiotics, one of which is mediated by aminoglycoside N-acetyltransferase (AAC). In this mechanism, the enzyme AAC facilitates the transfer and linkage of the acetyl moiety from the donor substrate acetyl-coenzyme A to specific positions on antibiotics. This modification alters the antibiotic's structure, leading to the inactivation of aminoglycoside antibiotics. In the current scenario, antibiotic resistance has become a global threat, and targeting the enzymes that mediate resistance is considered crucial to combat this issue. The study aimed to address the increasing global threat of antibiotic resistance in Serratia marcescens by targeting the aminoglycoside N-acetyltransferase (AAC (6')) enzyme, which inactivates aminoglycoside antibiotics through acetylation. Due to the absence of experimental structure, we constructed a homology model of aminoglycoside N (6')-acetyltransferase (AAC (6')) of S. marcescens using the atomic structure of aminoglycoside N-acetyltransferase AAC (6')-Ib (PDB ID: 1V0C) as a template. The stable architecture and integrity of the modelled AAC (6') structure were analyzed through a 100 ns simulation. Structure-guided high-throughput screening of four small molecule databases (Binding, Life Chemicals, Zinc, and Toslab) resulted in the identification of potent inhibitors against AAC (6'). The hits obtained from screening were manually clustered, and the five hit molecules were shortlisted based on the docking score, which are observed in the range of -17.09 kcal/mol to -11.95 kcal/mol. These selected five molecules displayed acceptable pharmacological properties in ADME predictions. The binding free energy calculations, and molecular dynamics simulations of ligand bound AAC (6') complexes represented higher affinity and stable binding. The selected molecules demonstrated stable binding with AAC (6'), indicating their strong potential to hamper the binding of aminoglycoside in the respective site. and thereby inhibit. This process mitigates enzyme mediated AAC (6') activity on aminoglycosides and reverse the bactericidal function of aminoglycosides, and also this method could serve as a platform for the development of potential antimicrobials.

摘要

粘质沙雷氏菌是一种机会性人类病原体,可引起尿路感染、眼部晶状体感染和呼吸道感染。粘质沙雷氏菌采用各种防御机制来逃避抗生素的作用,其中一种机制是由氨基糖苷类 N-乙酰转移酶 (AAC) 介导的。在这种机制中,酶 AAC 促进乙酰基从供体底物乙酰辅酶 A 转移并连接到抗生素的特定位置。这种修饰改变了抗生素的结构,导致氨基糖苷类抗生素失活。在当前情况下,抗生素耐药性已成为全球性威胁,针对介导耐药性的酶已被认为是解决这一问题的关键。本研究旨在通过靶向粘质沙雷氏菌中的氨基糖苷类 N-乙酰转移酶 (AAC (6')) 酶来解决粘质沙雷氏菌中日益严重的全球抗生素耐药性威胁,该酶通过乙酰化使氨基糖苷类抗生素失活。由于缺乏实验结构,我们使用氨基糖苷类 N-乙酰转移酶 AAC (6')-Ib (PDB ID: 1V0C) 的原子结构作为模板,构建了粘质沙雷氏菌氨基糖苷类 N (6')-乙酰转移酶 (AAC (6')) 的同源模型。通过 100ns 模拟分析了建模的 AAC (6') 结构的稳定架构和完整性。对四个小分子数据库(Binding、Life Chemicals、Zinc 和 Toslab)进行结构导向的高通量筛选,鉴定出针对 AAC (6') 的有效抑制剂。从筛选中获得的命中物进行手动聚类,根据对接得分从五个命中物中筛选出五个命中物,观察到范围为-17.09 kcal/mol 至-11.95 kcal/mol。这些选定的五个分子在 ADME 预测中表现出可接受的药理学特性。配体结合 AAC (6') 复合物的结合自由能计算和分子动力学模拟显示出更高的亲和力和稳定的结合。所选分子与 AAC (6') 表现出稳定的结合,表明它们具有很强的潜力来阻止氨基糖苷类药物在相应部位的结合,从而抑制其活性。该过程减轻了酶介导的 AAC (6') 对氨基糖苷类药物的活性,并逆转了氨基糖苷类药物的杀菌功能,并且该方法可以作为开发潜在抗菌药物的平台。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验