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理解蛋白激酶信号网络的药理学方法。

Pharmacological approaches to understanding protein kinase signaling networks.

作者信息

Stephenson Elloise H, Higgins Jonathan M G

机构信息

Faculty of Medical Sciences, Biosciences Institute, Newcastle University, Newcastle uponTyne, United Kingdom.

出版信息

Front Pharmacol. 2023 Dec 14;14:1310135. doi: 10.3389/fphar.2023.1310135. eCollection 2023.

Abstract

Protein kinases play vital roles in controlling cell behavior, and an array of kinase inhibitors are used successfully for treatment of disease. Typical drug development pipelines involve biological studies to validate a protein kinase target, followed by the identification of small molecules that effectively inhibit this target in cells, animal models, and patients. However, it is clear that protein kinases operate within complex signaling networks. These networks increase the resilience of signaling pathways, which can render cells relatively insensitive to inhibition of a single kinase, and provide the potential for pathway rewiring, which can result in resistance to therapy. It is therefore vital to understand the properties of kinase signaling networks in health and disease so that we can design effective multi-targeted drugs or combinations of drugs. Here, we outline how pharmacological and chemo-genetic approaches can contribute to such knowledge, despite the known low selectivity of many kinase inhibitors. We discuss how detailed profiling of target engagement by kinase inhibitors can underpin these studies; how chemical probes can be used to uncover kinase-substrate relationships, and how these tools can be used to gain insight into the configuration and function of kinase signaling networks.

摘要

蛋白激酶在控制细胞行为方面发挥着至关重要的作用,一系列激酶抑制剂已成功用于疾病治疗。典型的药物研发流程包括进行生物学研究以验证蛋白激酶靶点,随后在细胞、动物模型和患者中鉴定能有效抑制该靶点的小分子。然而,很明显蛋白激酶在复杂的信号网络中发挥作用。这些网络增强了信号通路的弹性,这可能使细胞对单一激酶的抑制相对不敏感,并提供了通路重新布线的可能性,进而导致治疗抵抗。因此,了解健康和疾病状态下激酶信号网络的特性至关重要,这样我们才能设计出有效的多靶点药物或药物组合。在此,我们概述了药理学和化学遗传学方法如何能为这类知识做出贡献,尽管许多激酶抑制剂的选择性已知较低。我们讨论了激酶抑制剂对靶点作用的详细分析如何能为这些研究提供支持;化学探针如何用于揭示激酶 - 底物关系,以及这些工具如何用于深入了解激酶信号网络的结构和功能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89ad/10757940/2cc811d6890e/fphar-14-1310135-g001.jpg

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