药物发现
工具箱
鉴定(生物学)
背景(考古学)
药品
计算生物学
选择(遗传算法)
制药工业
资源(消歧)
虚拟筛选
计算机科学
风险分析(工程)
药物开发
生化工程
药理学
数据科学
医学
生物技术
机器学习
工程类
生物信息学
生物
程序设计语言
古生物学
植物
计算机网络
作者
Sajda Ashraf,J. Henry Blackwell,Geoffrey A. Holdgate,Simon C. C. Lucas,Alisa Solovyeva,Richard Storer,Benjamin C. Whitehurst
标识
DOI:10.1016/j.drudis.2024.104143
摘要
Identification of high-quality hit chemical matter is of vital importance to the success of drug discovery campaigns. However, this goal is becoming ever harder to achieve as the targets entering the portfolios of pharmaceutical and biotechnology companies are increasingly trending towards novel and traditionally challenging to drug. This demand has fuelled the development and adoption of numerous new screening approaches, whereby the contemporary hit identification toolbox comprises a growing number of orthogonal and complementary technologies including high-throughput screening, fragment-based ligand design, affinity screening (affinity-selection mass spectrometry, differential scanning fluorimetry, DNA-encoded library screening), as well as increasingly sophisticated computational predictive approaches. Herein we describe how an integrated strategy for hit discovery, whereby multiple hit identification techniques are tactically applied, selected in the context of target suitability and resource priority, represents an optimal and often essential approach to maximise the likelihood of identifying quality starting points from which to develop the next generation of medicines.
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