摘要
金黄色葡萄球菌(Staphylococcus aureus)是一种臭名昭着的致病菌,引起多种疾病,从软组织污染到更严重和深层感染。该物种的特点是能够表达几种毒力因子并获得与抗药性相关的基因。针对这一系列因素设计任何药物都不是一件容易的事。在这篇综述中,我们讨论了计算方法对推动针对金黄色葡萄球菌的新药开发的重要性。展示了对接方法在筛选天然或合成化合物的大型文库中的应用以及对作用机制的见解。特别强调了用生物化学和微生物学分析验证计算机结果的研究。我们还评论了使用一些已知抑制剂的新分子的计算机辅助设计。通过生物化学和微生物学测定确认计算机结果,可以鉴定可用于药物设计的先导分子,如罗多霉素,奎宁环,小檗碱(及其衍生化合物)。计算方法的快速发展对于提高我们发现新药物的能力以及扩大对药物 - 靶标相互作用的理解至关重要。
关键词: 计算方法,药物发现,抗微生物剂,抗毒剂,外排泵,DNA复制抑制剂。
Current Medicinal Chemistry
Title:Virtual Screening for the Development of New Effective Compounds Against Staphylococcus aureus
Volume: 25 Issue: 42
关键词: 计算方法,药物发现,抗微生物剂,抗毒剂,外排泵,DNA复制抑制剂。
摘要: Staphylococcus aureus is a notorious pathogenic bacterium causing a wide range of diseases from soft-tissue contamination, to more serious and deep-seated infections. This species is highlighted by its ability to express several kinds of virulence factors and to acquire genes related to drug resistance. Target this number of factors to design any drug is not an easy task. In this review, we discuss the importance of computational methods to impulse the development of new drugs against S. aureus. The application of docking methods to screen large libraries of natural or synthetic compounds and to provide insights into action mechanisms is demonstrated. Particularly, the studies that validated in silico results with biochemical and microbiological assays are highlighted. We also comment on the computer-aided design of new molecules using some known inhibitors. The confirmation of in silico results with biochemical and microbiological assays allowed the identification of lead molecules that could be used for drug design such as rhodomyrtone, quinuclidine, berberine (and their derivative compounds). The fast development of the computational methods is essential to improve our ability to discover new drugs, as well as to expand understanding about drug-target interactions.
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Virtual Screening for the Development of New Effective Compounds Against Staphylococcus aureus, Current Medicinal Chemistry 2018; 25 (42) . https://dx.doi.org/10.2174/0929867325666180327105842
DOI https://dx.doi.org/10.2174/0929867325666180327105842 |
Print ISSN 0929-8673 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-533X |
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