Suppr超能文献

广谱抗病毒核苷——我们对未来的最大希望。

Broad spectrum antiviral nucleosides-Our best hope for the future.

作者信息

Seley-Radtke Katherine L, Thames Joy E, Waters Charles D

机构信息

Department of Chemistry & Biochemistry, University of Maryland, Baltimore County, Baltimore, MD, United States.

出版信息

Annu Rep Med Chem. 2021;57:109-132. doi: 10.1016/bs.armc.2021.09.001. Epub 2021 Oct 29.

Abstract

The current focus for many researchers has turned to the development of therapeutics that have the potential for serving as broad-spectrum inhibitors that can target numerous viruses, both within a particular family, as well as to span across multiple viral families. This will allow us to build an arsenal of therapeutics that could be used for the next outbreak. In that regard, nucleosides have served as the cornerstone for antiviral therapy for many decades. As detailed herein, many nucleosides have been shown to inhibit multiple viruses due to the conserved nature of many viral enzyme binding sites. Thus, it is somewhat surprising that up until very recently, many researchers focused more on "one bug one drug," rather than trying to target multiple viruses given those similarities. This attitude is now changing due to the realization that we need to be proactive rather than reactive when it comes to combating emerging and reemerging infectious diseases. A brief summary of prominent nucleoside analogues that previously exhibited broad-spectrum activity and are now under renewed interest, as well as new analogues, that are currently under investigation against SARS-CoV-2 and other viruses is discussed herein.

摘要

目前,许多研究人员的重点已转向开发具有作为广谱抑制剂潜力的疗法,这些抑制剂可以靶向特定病毒家族内的多种病毒,也可以跨越多个病毒家族。这将使我们能够建立一个可用于下一次疫情爆发的治疗药物库。在这方面,核苷几十年来一直是抗病毒治疗的基石。如本文所述,由于许多病毒酶结合位点的保守性质,许多核苷已被证明可抑制多种病毒。因此,直到最近,许多研究人员更多地关注“一种病毒一种药物”,而不是鉴于这些相似性尝试靶向多种病毒,这有点令人惊讶。由于意识到在对抗新出现和再次出现的传染病时我们需要积极主动而非被动应对,这种态度现在正在改变。本文讨论了以前表现出广谱活性且现在重新受到关注的著名核苷类似物,以及目前正在针对SARS-CoV-2和其他病毒进行研究的新类似物的简要概述。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ed0/8553659/7deca1c72dfe/f03-01-9780323915113_lrg.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验