The Effect of Chalcogen-Chalcogen Bond Formation in the New Delhi Metallo-β-Lactamase 1 Enzyme to Counteract Antibiotic Resistance.

IF 5.7 1区 化学 Q2 CHEMISTRY, PHYSICAL Journal of Chemical Theory and Computation Pub Date : 2024-11-24 DOI:10.1021/acs.jctc.4c01266
Giada Ciardullo, Mario Prejanò, Angela Parise, Nino Russo, Tiziana Marino
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Abstract

New Delhi metallo-β-lactamase 1 (NDM-1) is an enzyme involved in the drug resistance of many bacteria against most of the widely adopted antibiotics, such as penicillins, cephalosporins, and carbapenems. Consequently, inhibiting NDM-1 swiftly has gained significant interest as a strategy to counteract this bacterial defense mechanism, thereby restoring the effectiveness of antibiotics. Among the inhibitors tested against the enzyme, ebselen (EbSe) showed particularly promising results. This molecule, renowned for its numerous benefits to the human body, targets the enzyme's active site at Cys208 with its selenium atom, facilitating the expulsion of the catalytic zinc ion from the active pocket. Since the inhibitory mechanism of EbSe remains poorly understood, gaining detailed information about it is highly desirable. In the present work, density functional theory calculations and μs-long molecular dynamics simulations are carried out to investigate the reaction mechanism of EbSe with NDM-1, unveiling the structural implications of the inhibition. A large model of the NDM-1 active site is built to investigate the different mechanistic proposals for the SeEbSe-SCys208 bond formation. Deeper insights into Lys211 are also provided to consolidate its role during the inhibition process. Furthermore, the chemical reaction with the ebsulfur (EbS) molecule is also investigated to compare its behavior with that of the periodic relative selenium. Molecular dynamics simulations, besides evidencing the role of the L3 and L10 loops in the occurrence of the inhibition, corroborate the Zn ion release from the active site as a result of the complete disruption of its coordination sphere caused by the creation of the SeEbSe-SCys208 covalent bond.

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新德里 Metallo-β-Lactamase 1 酶中 Chalcogen-Chalcogen Bond 形成对抗生素耐药性的影响。
新德里金属-β-内酰胺酶 1(NDM-1)是一种参与许多细菌对大多数广泛使用的抗生素(如青霉素类、头孢菌素类和碳青霉烯类)产生耐药性的酶。因此,迅速抑制 NDM-1 作为一种对抗这种细菌防御机制的策略,从而恢复抗生素的有效性,已经引起了人们的极大兴趣。在针对该酶测试的抑制剂中,依布硒 (EbSe) 的效果尤为显著。这种分子因其对人体的诸多益处而闻名,它以 Cys208 处的酶活性位点为目标,利用硒原子促进催化锌离子从活性袋中排出。由于人们对 EbSe 的抑制机理仍然知之甚少,因此非常有必要获得有关它的详细信息。本研究通过密度泛函理论计算和μs-长分子动力学模拟,研究了 EbSe 与 NDM-1 的反应机理,揭示了抑制作用的结构含义。建立了一个 NDM-1 活性位点的大型模型,以研究 SeEbSe-SCys208 键形成的不同机理方案。此外,还深入研究了 Lys211,以巩固其在抑制过程中的作用。此外,还研究了与乙硫(EbS)分子的化学反应,以比较其行为与周期性相对硒的行为。分子动力学模拟除了证明 L3 和 L10 环路在发生抑制作用中的作用外,还证实了由于 SeEbSe-SCys208 共价键的产生导致配位层完全破坏,锌离子从活性位点释放出来。
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来源期刊
Journal of Chemical Theory and Computation
Journal of Chemical Theory and Computation 化学-物理:原子、分子和化学物理
CiteScore
9.90
自引率
16.40%
发文量
568
审稿时长
1 months
期刊介绍: The Journal of Chemical Theory and Computation invites new and original contributions with the understanding that, if accepted, they will not be published elsewhere. Papers reporting new theories, methodology, and/or important applications in quantum electronic structure, molecular dynamics, and statistical mechanics are appropriate for submission to this Journal. Specific topics include advances in or applications of ab initio quantum mechanics, density functional theory, design and properties of new materials, surface science, Monte Carlo simulations, solvation models, QM/MM calculations, biomolecular structure prediction, and molecular dynamics in the broadest sense including gas-phase dynamics, ab initio dynamics, biomolecular dynamics, and protein folding. The Journal does not consider papers that are straightforward applications of known methods including DFT and molecular dynamics. The Journal favors submissions that include advances in theory or methodology with applications to compelling problems.
期刊最新文献
Simulating Non-Markovian Dynamics in Multidimensional Electronic Spectroscopy via Quantum Algorithm. The Effect of Chalcogen-Chalcogen Bond Formation in the New Delhi Metallo-β-Lactamase 1 Enzyme to Counteract Antibiotic Resistance. Thermodynamic Transferability in Coarse-Grained Force Fields Using Graph Neural Networks. Advancing Membrane-Associated Protein Docking with Improved Sampling and Scoring in Rosetta. Allosteric Communication Mediated by Protein Contact Clusters: A Dynamical Model.
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