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病毒病治疗的计算药物发现。

In Silico Drug Discovery for Treatment of Virus Diseases.

机构信息

Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan, China.

iGlobal Research and Publishing Foundation, New Delhi, India.

出版信息

Adv Exp Med Biol. 2022;1368:73-93. doi: 10.1007/978-981-16-8969-7_4.

Abstract

Viral infections have remained a serious public health burden despite significant improvements in medical and pharmaceutical research in recent years. In silico approaches for drug discovery and design are fruitful for the management of a plethora of viral diseases. Virtual screening of libraries is performed using various computational tools to search for potential antiviral compounds. For this, a rational approach is used that comprises filtration of the screened compounds using docking, ligand- or pharmacophore-based similarity searches. The selected candidates are then tested in vitro to ascertain their biological activity. This minimizes the overall cost and time incurred in conventional drug designing methods. In this book chapter, we have discussed various methods of drug discovery and design, and their applications for the development of effective antiviral compounds. A descriptive methodology for the management of some common and notorious viral diseases is also outlined.

摘要

尽管近年来医学和制药研究取得了重大进展,但病毒感染仍然是一个严重的公共卫生负担。药物发现和设计的计算方法在治疗多种病毒性疾病方面非常有效。虚拟筛选库使用各种计算工具进行,以搜索潜在的抗病毒化合物。为此,使用合理的方法,包括使用对接、配体或药效团相似性搜索筛选化合物。然后,对选定的候选物进行体外测试,以确定其生物活性。这最大限度地减少了传统药物设计方法中产生的总体成本和时间。在本章中,我们讨论了药物发现和设计的各种方法,以及它们在开发有效抗病毒化合物方面的应用。还概述了用于管理一些常见和臭名昭著的病毒性疾病的描述性方法。

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