多药理学和药物发现的系统方法。

Aislyn D W Boran, Ravi Iyengar
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引用次数: 0

摘要

系统生物学使用实验和计算方法来系统地描述大样本群体,处理大数据集,检查和分析监管网络,并模拟反应以确定组件如何连接以形成功能系统。系统生物学技术、数据和知识在理解疾病过程和药物作用方面特别有用。系统生物学和药物发现之间整合的一个重要领域是多药理学的概念:通过调节多个靶点来治疗疾病。复杂疾病的多药理学可能涉及多种药物作用于不同的靶点,这些靶点是调节生理反应网络的一部分。这篇综述讨论了目前对疾病的系统水平的理解以及药物作用的治疗和不良机制。药物靶点网络可用于识别多个靶点,并确定药物靶点或药物的合适组合。因此,发现新的药物治疗复杂的疾病可能会大大帮助系统生物学。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Systems approaches to polypharmacology and drug discovery.

Systems biology uses experimental and computational approaches to characterize large sample populations systematically, process large datasets, examine and analyze regulatory networks, and model reactions to determine how components are joined to form functional systems. Systems biology technologies, data and knowledge are particularly useful in understanding disease processes and drug actions. An important area of integration between systems biology and drug discovery is the concept of polypharmacology: the treatment of diseases by modulating more than one target. Polypharmacology for complex diseases is likely to involve multiple drugs acting on distinct targets that are part of a network regulating physiological responses. This review discusses the current state of the systems-level understanding of diseases and both the therapeutic and adverse mechanisms of drug actions. Drug-target networks can be used to identify multiple targets and to determine suitable combinations of drug targets or drugs. Thus, the discovery of new drug therapies for complex diseases may be greatly aided by systems biology.

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