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利用化学和生物数据预测药物毒性。

Using chemical and biological data to predict drug toxicity.

机构信息

Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, CB2 1EW, Cambridge, United Kingdom; Milner Therapeutics Institute, University of Cambridge, Puddicombe Way, CB2 0AW, Cambridge, United Kingdom.

Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, CB2 1EW, Cambridge, United Kingdom.

出版信息

SLAS Discov. 2023 Apr;28(3):53-64. doi: 10.1016/j.slasd.2022.12.003. Epub 2023 Jan 11.

Abstract

Various sources of information can be used to better understand and predict compound activity and safety-related endpoints, including biological data such as gene expression and cell morphology. In this review, we first introduce types of chemical, in vitro and in vivo information that can be used to describe compounds and adverse effects. We then explore how compound descriptors based on chemical structure or biological perturbation response can be used to predict safety-related endpoints, and how especially biological data can help us to better understand adverse effects mechanistically. Overall, the described applications demonstrate how large-scale biological information presents new opportunities to anticipate and understand the biological effects of compounds, and how this can support predictive toxicology and drug discovery projects.

摘要

各种信息来源可用于更好地理解和预测化合物的活性和与安全性相关的终点,包括基因表达和细胞形态等生物学数据。在这篇综述中,我们首先介绍了可用于描述化合物和不良反应的化学、体外和体内信息的类型。然后我们探讨了如何基于化学结构或生物扰动反应的化合物描述符来预测与安全性相关的终点,以及生物数据如何帮助我们更好地从机制上理解不良反应。总的来说,所描述的应用展示了大规模生物学信息如何为预测化合物的生物学效应和理解其提供新的机会,以及如何支持预测毒理学和药物发现项目。

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