鉴定(生物学)
药物发现
严重急性呼吸综合征冠状病毒2型(SARS-CoV-2)
2019年冠状病毒病(COVID-19)
计算生物学
生物信息学
大流行
计算机科学
数据科学
2019-20冠状病毒爆发
风险分析(工程)
生化工程
疾病
传染病(医学专业)
医学
生物
生物信息学
工程类
病毒学
生物化学
植物
病理
爆发
基因
作者
Mariana Martinelli Junqueira Ribeiro
出处
期刊:Current Computer - Aided Drug Design
[Bentham Science]
日期:2023-03-30
卷期号:20 (4): 313-324
被引量:2
标识
DOI:10.2174/1573409919666230329090403
摘要
The COVID-19 pandemic is raising a worldwide search for compounds that could act against the disease, mainly due to its mortality. With this objective, many researchers invested in the discovery and development of drugs of natural origin. To assist in this search, the potential of computational tools to reduce the time and cost of the entire process is known. Thus, this review aimed to identify how these tools have helped in the identification of natural products against SARS-CoV-2. For this purpose, a literature review was carried out with scientific articles with this proposal where it was possible to observe that different classes of primary and, mainly, secondary metabolites were evaluated against different molecular targets, mostly being enzymes and spike, using computational techniques, with emphasis on the use of molecular docking. However, it is noted that in silico evaluations still have much to contribute to the identification of an anti- SARS-CoV-2 substance, due to the vast chemical diversity of natural products, identification and use of different molecular targets and computational advancement.
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