Combatting Antibiotic-Resistant Staphylococcus aureus: Discovery of TST1N-224, a Potent Inhibitor Targeting Response Regulator VraRC, through Pharmacophore-Based Screening and Molecular Characterizations.

IF 5.6 2区 化学 Q1 CHEMISTRY, MEDICINAL Journal of Chemical Information and Modeling Pub Date : 2024-08-12 Epub Date: 2024-07-30 DOI:10.1021/acs.jcim.4c01046
Ying-Chu Hsu, Ching-Hui Liu, Yi-Chen Wu, Shu-Jung Lai, Chi-Jan Lin, Tien-Sheng Tseng
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Abstract

Staphylococcus aureus (S. aureus) is a major global health concern, causing various infections and presenting challenges due to antibiotic resistance. In particular, methicillin-resistant S. aureus, vancomycin-intermediate S. aureus (VISA), and vancomycin-resistant S. aureus pose significant obstacles in treating S. aureus infections. Therefore, the critical need for novel drugs to counter these resistant forms is pressing. Two-component systems (TCSs), integral to bacterial regulation, offer promising targets for disruption. In this study, a comprehensive approach, involving pharmacophore-based inhibitor screening, along with biochemical and biophysical analyses were conducted to identify, characterize, and validate potential inhibitors targeting the response regulator VraRC of S. aureus. The constructed pharmacophore model, Phar-VRPR-N3, demonstrated effectiveness in identifying a potent inhibitor, TST1N-224 (IC50 = 60.2 ± 4.0 μM), against the formation of the VraRC-DNA complex. Notably, TST1N-224 exhibited strong binding to VraRC (KD = 23.4 ± 1.2 μM) using a fast-on-fast-off binding mechanism. Additionally, NMR-based molecular modeling revealed that TST1N-224 predominantly interacts with the α9- and α10-helixes of the DNA-binding domain of VraR, where the interactive and functionally essential residues (N165, K180, S184, and R195) act as hotspots for structure-based inhibitor optimization. Furthermore, TST1N-224 evidently enhanced the susceptibility of VISA to both vancomycin and methicillin. Importantly, TST1N-224 distinguished by 1,2,5,6-tetrathiocane with the 3 and 8 positions modified with ethanesulfonates holds significant potential as a lead compound for the development of new antimicrobial agents.

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抗击耐抗生素金黄色葡萄球菌:通过基于药理的筛选和分子表征发现靶向反应调节器 VraRC 的强效抑制剂 TST1N-224。
金黄色葡萄球菌(S. aureus)是全球主要的健康问题,可引起各种感染,并因抗生素耐药性而带来挑战。特别是耐甲氧西林金黄色葡萄球菌、万古霉素中间型金黄色葡萄球菌(VISA)和耐万古霉素金黄色葡萄球菌给治疗金黄色葡萄球菌感染带来了巨大障碍。因此,迫切需要新型药物来应对这些耐药形式。双组分系统(TCS)是细菌调控不可或缺的组成部分,它为破坏提供了有希望的目标。本研究采用了一种综合方法,包括基于药理的抑制剂筛选,以及生化和生物物理分析,以鉴定、表征和验证针对金黄色葡萄球菌反应调节器 VraRC 的潜在抑制剂。所构建的药理模型 Phar-VRPR-N3 能有效鉴定出一种强效抑制剂 TST1N-224(IC50 = 60.2 ± 4.0 μM),它能抑制 VraRC-DNA 复合物的形成。值得注意的是,TST1N-224 与 VraRC 的结合力很强(KD = 23.4 ± 1.2 μM),采用的是快上快下结合机制。此外,基于核磁共振的分子建模显示,TST1N-224 主要与 VraR DNA 结合结构域的 α9- 和 α10- 螺旋相互作用,其中相互作用和功能必需残基(N165、K180、S184 和 R195)是基于结构优化抑制剂的热点。此外,TST1N-224 明显增强了 VISA 对万古霉素和甲氧西林的敏感性。重要的是,TST1N-224 的 1,2,5,6-四硫代烷的 3 位和 8 位被乙烷磺酸盐修饰,具有开发新型抗菌剂先导化合物的巨大潜力。
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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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