Systems biology in drug discovery
Systems biology in drug discovery
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DOI：
10.1038/nbt1017
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发表时间：
2004-10-01
影响因子：
46.9
通讯作者：
Kunkel, EJ
中科院分区：
文献类型：
--
作者：
Butcher, EC;Berg, EL;Kunkel, EJ
将“基因快速转化为药物”的希望已经破灭，因为疾病生物学是复杂的，药物开发必须由对生物反应的洞察来驱动。系统生物学旨在描述和理解复杂生物系统的运作，并最终开发人类疾病的预测模型。虽然有意义的人类细胞和组织功能的分子水平模型是一个遥远的目标，系统生物学的努力已经影响药物的发现。大规模的基因、蛋白质和代谢物测量（“组学”）大大加快了疾病模型中假设的生成和检验。计算机模拟整合了器官和系统水平反应的知识，有助于确定目标的优先顺序和设计临床试验。旨在捕获紧急特性的复杂原代人类细胞检测系统的自动化现在可以将广泛的疾病相关人类生物学整合到药物发现过程中，为靶标和化合物验证、先导物优化和临床适应症选择提供信息。这些系统生物学方法有望改善药物开发中的决策。
The hope of the rapid translation of 'genes to drugs' has foundered on the reality that disease biology is complex, and that drug development must be driven by insights into biological responses. Systems biology aims to describe and to understand the operation of complex biological systems and ultimately to develop predictive models of human disease. Although meaningful molecular level models of human cell and tissue function are a distant goal, systems biology efforts are already influencing drug discovery. Large-scale gene, protein and metabolite measurements ('omics') dramatically accelerate hypothesis generation and testing in disease models. Computer simulations integrating knowledge of organ and system-level responses help prioritize targets and design clinical trials. Automation of complex primary human cell-based assay systems designed to capture emergent properties can now integrate a broad range of disease-relevant human biology into the drug discovery process, informing target and compound validation, lead optimization, and clinical indication selection. These systems biology approaches promise to improve decision making in pharmaceutical development.