深入研究红霉素酯酶 C 中大环内酯类化合物的结合亲和力及相关结构调整:洞察维纳斯捕蝇草机制。

IF 5.6 2区 化学 Q1 CHEMISTRY, MEDICINAL Journal of Chemical Information and Modeling Pub Date : 2024-11-20 DOI:10.1021/acs.jcim.4c01523
Abhishek Bera, Pritish Joshi, Niladri Patra
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引用次数: 0

摘要

大环内酯类抗生素自用于抗菌治疗以来,极大地改变了病原菌的进化途径,促使它们发展出多种抗菌药耐药性(AMR)机制。其中,大环内酯酯酶(通常称为红霉素酯酶)成为一种关键的防御机制,使细菌能够通过水解细菌细胞内的大环内酯环来解毒大环内酯类药物。在本研究中,我们深入研究了红霉素酯酶家族的关键成员红霉素酯酶 C(EreC)错综复杂的相互作用和构象动力学。我们采用经典分子动力学、绝对结合自由能计算和二维阶跃元动力学模拟,重点研究了三种经美国食品药物管理局(FDA)批准并广泛使用的大环内酯类药物--红霉素、克拉霉素和阿奇霉素--来探索它们与 EreC 的相互作用。为了估算绝对结合自由能,我们使用了最近开发的强大的 "简化化学自由能扰动(SAFEP)"协议。分子动力学模拟和高级分析的结果表明,在 EreC 的大环内酯结合裂隙中,疏水相互作用起着关键作用,小叶在促进整体结构波动方面也有重要影响。硅丙氨酸扫描确定了前三个疏水残基,即 PHE248、MET333 和 PHE344,它们负责在该裂隙内与大环内酯结合。根据自由能计算,阿奇霉素和克拉霉素与 EreC 的结合亲和力高于母体大环内酯红霉素。此外,二维元动力学模拟和基于图论的特征向量中心性分析表明,在大环内酯捕获时,重要组氨酸残基 HIS289 的微妙构象变化会触发 EreC 蛋白的 "活性环闭合",在此过程中会出现 "半开放 "状态,这与著名的 "维纳斯捕蝇草 "机制有着惊人的相似之处。
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Delving into Macrolide Binding Affinities and Associated Structural Modulations in Erythromycin Esterase C: Insights into the Venus Flytrap Mechanism.

Since their inception in antibacterial therapy, macrolide-based antibiotics have significantly shaped the evolutionary pathways of pathogenic bacteria, driving them to develop diverse antimicrobial resistance (AMR) mechanisms. Among these, macrolide esterase, commonly referred to as erythromycin esterase, emerged as a critical defense mechanism, enabling bacteria to detoxify macrolides by hydrolyzing the macrolactone ring within the bacterial cell. In this study, we delve into the intricate interactions and conformational dynamics of erythromycin esterase C (EreC), a key member of the Ere enzyme family. We have focused on three FDA-approved and widely prescribed macrolides─erythromycin, clarithromycin, and azithromycin─by employing classical molecular dynamics, absolute binding free energy calculations, and 2D well-tempered metadynamics simulations to explore their interactions with EreC. To estimate the absolute binding free energies, we have used the recently developed and robust "Streamlined Alchemical Free Energy Perturbation (SAFEP)" protocol. The results from our molecular dynamics simulations and advanced analyses portrayed the crucial role of hydrophobic interactions within the macrolide binding cleft of EreC, along with the significant influence of the minor lobe in facilitating overall structural fluctuation. In silico alanine scanning identified top three hydrophobic residues, i.e., PHE248, MET333, and PHE344, responsible for macrolide binding inside that cleft. According to the free energy calculations, azithromycin and clarithromycin showed greater binding affinities toward EreC than the parent macrolide erythromycin. Moreover, 2D metadynamics simulations along with graph theory-based eigenvector centrality analyses revealed a metastable "semiopen" state during the hypothesized "active loop closure" of the EreC protein triggered by subtle conformational changes of an important histidine residue, HIS289, upon macrolide capture, drawing a fascinating parallel to the renowned "Venus flytrap" mechanism.

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来源期刊
CiteScore
9.80
自引率
10.70%
发文量
529
审稿时长
1.4 months
期刊介绍: The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.
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