{"title":"针对金黄色葡萄球菌的天然化合物的计算探索:抑制 AgrA 启动子结合以进行抗菌干预。","authors":"Subhadip Saha, Monidipa Ghosh","doi":"10.1080/07391102.2023.2246566","DOIUrl":null,"url":null,"abstract":"<p><p><i>Staphylococcus aureus</i> is a highly virulent nosocomial pathogen that poses a significant threat to individuals exposed to healthcare settings. Due to its sophisticated machinery for producing virulence factors, <i>S. aureus</i> can cause severe and potentially fatal infections in humans. This study focuses on the response regulator AgrA, which plays a crucial role in regulating the production of virulence factors in <i>S. aureus</i>. The objective is to identify natural compounds that can inhibit the binding of AgrA to its promoter site, thus inhibiting the expression of virulence genes. To achieve this, a pharmacophore model was generated using known drugs and applied to screen the ZINC natural product database. The resulting compounds were subjected to molecular docking-based virtual screening against the C-terminal DNA binding domain of AgrA. Three compounds, namely ZINC000077269178, ZINC000051012304, and ZINC000004266026, were shortlisted based on their strong affinity for key residues involved in DNA binding and transcription initiation. Subsequently, the unbound and ligand-bound complexes were subjected to a 200 ns molecular dynamics simulation to assess their conformational stability. Various analyses, including RMSD, RMSF, Rg, SASA, Principal Component Analysis, and Gibbs free energy landscape, were conducted on the simulation trajectory. The RMSD profile indicated similar fluctuations in both bound and unbound structures, while the Rg profile demonstrated the compactness of the protein without any unfolding during the simulation. Furthermore, Principal component analysis revealed that ligand binding reduced the overall atomic motion of the protein whereas free energy landscape suggested the energy variations obtained in complexes.Communicated by Ramaswamy H. Sarma.</p>","PeriodicalId":15272,"journal":{"name":"Journal of Biomolecular Structure & Dynamics","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Computational exploration of natural compounds targeting <i>Staphylococcus aureus</i>: inhibiting AgrA promoter binding for antimicrobial intervention.\",\"authors\":\"Subhadip Saha, Monidipa Ghosh\",\"doi\":\"10.1080/07391102.2023.2246566\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p><i>Staphylococcus aureus</i> is a highly virulent nosocomial pathogen that poses a significant threat to individuals exposed to healthcare settings. 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Subsequently, the unbound and ligand-bound complexes were subjected to a 200 ns molecular dynamics simulation to assess their conformational stability. Various analyses, including RMSD, RMSF, Rg, SASA, Principal Component Analysis, and Gibbs free energy landscape, were conducted on the simulation trajectory. The RMSD profile indicated similar fluctuations in both bound and unbound structures, while the Rg profile demonstrated the compactness of the protein without any unfolding during the simulation. Furthermore, Principal component analysis revealed that ligand binding reduced the overall atomic motion of the protein whereas free energy landscape suggested the energy variations obtained in complexes.Communicated by Ramaswamy H. 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引用次数: 0
摘要
金黄色葡萄球菌是一种毒性极强的医院内病原体,对暴露在医疗环境中的人构成严重威胁。由于金黄色葡萄球菌具有生产毒力因子的复杂机制,因此可对人类造成严重和潜在的致命感染。本研究的重点是反应调节器 AgrA,它在调节金黄色葡萄球菌毒力因子的产生方面起着至关重要的作用。研究的目的是找出能够抑制 AgrA 与其启动子位点结合的天然化合物,从而抑制毒力基因的表达。为此,我们利用已知药物生成了一个药理模型,并将其应用于筛选 ZINC 天然产品数据库。筛选出的化合物针对 AgrA 的 C 端 DNA 结合域进行了基于分子对接的虚拟筛选。根据与参与 DNA 结合和转录启动的关键残基的强亲和力,最终筛选出三个化合物,即 ZINC000077269178、ZINC000051012304 和 ZINC000004266026。随后,对未结合和配体结合的复合物进行了 200 ns 分子动力学模拟,以评估它们的构象稳定性。对模拟轨迹进行了各种分析,包括 RMSD、RMSF、Rg、SASA、主成分分析和吉布斯自由能景观。RMSD 分析表明,结合和非结合结构的波动相似,而 Rg 分析表明,在模拟过程中,蛋白质结构紧凑,没有发生任何折叠。此外,主成分分析表明,配体的结合减少了蛋白质的整体原子运动,而自由能图谱则表明了在复合物中获得的能量变化。
Computational exploration of natural compounds targeting Staphylococcus aureus: inhibiting AgrA promoter binding for antimicrobial intervention.
Staphylococcus aureus is a highly virulent nosocomial pathogen that poses a significant threat to individuals exposed to healthcare settings. Due to its sophisticated machinery for producing virulence factors, S. aureus can cause severe and potentially fatal infections in humans. This study focuses on the response regulator AgrA, which plays a crucial role in regulating the production of virulence factors in S. aureus. The objective is to identify natural compounds that can inhibit the binding of AgrA to its promoter site, thus inhibiting the expression of virulence genes. To achieve this, a pharmacophore model was generated using known drugs and applied to screen the ZINC natural product database. The resulting compounds were subjected to molecular docking-based virtual screening against the C-terminal DNA binding domain of AgrA. Three compounds, namely ZINC000077269178, ZINC000051012304, and ZINC000004266026, were shortlisted based on their strong affinity for key residues involved in DNA binding and transcription initiation. Subsequently, the unbound and ligand-bound complexes were subjected to a 200 ns molecular dynamics simulation to assess their conformational stability. Various analyses, including RMSD, RMSF, Rg, SASA, Principal Component Analysis, and Gibbs free energy landscape, were conducted on the simulation trajectory. The RMSD profile indicated similar fluctuations in both bound and unbound structures, while the Rg profile demonstrated the compactness of the protein without any unfolding during the simulation. Furthermore, Principal component analysis revealed that ligand binding reduced the overall atomic motion of the protein whereas free energy landscape suggested the energy variations obtained in complexes.Communicated by Ramaswamy H. Sarma.
期刊介绍:
The Journal of Biomolecular Structure and Dynamics welcomes manuscripts on biological structure, dynamics, interactions and expression. The Journal is one of the leading publications in high end computational science, atomic structural biology, bioinformatics, virtual drug design, genomics and biological networks.