药物发现
生物信息学
计算机科学
计算生物学
鉴定(生物学)
过程(计算)
业务流程发现
计算模型
数据科学
人工智能
风险分析(工程)
生物信息学
在制品
医学
生物
工程类
运营管理
植物
业务流程建模
操作系统
基因
业务流程
生物化学
作者
Bilal Shaker,Sajjad Ahmad,Jingyu Lee,Chanjin Jung,Dokyun Na
标识
DOI:10.1016/j.compbiomed.2021.104851
摘要
In the past, conventional drug discovery strategies have been successfully employed to develop new drugs, but the process from lead identification to clinical trials takes more than 12 years and costs approximately $1.8 billion USD on average. Recently, in silico approaches have been attracting considerable interest because of their potential to accelerate drug discovery in terms of time, labor, and costs. Many new drug compounds have been successfully developed using computational methods. In this review, we briefly introduce computational drug discovery strategies and outline up-to-date tools to perform the strategies as well as available knowledge bases for those who develop their own computational models. Finally, we introduce successful examples of anti-bacterial, anti-viral, and anti-cancer drug discoveries that were made using computational methods.
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