Computational biology and drug discovery: From single-target to network drugs
Computational biology and drug discovery: From single-target to network drugs
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DOI：
10.2174/157489306775330598
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发表时间：
2006-01-01
影响因子：
4
通讯作者：
di Bernardo, Diego
中科院分区：
文献类型：
--
作者：
Ambesi-Impiombato, Alberto;di Bernardo, Diego
药物发现过程复杂、耗时且昂贵，包括临床前和临床阶段。制药行业正从关注症状缓解转向更基于病理的方法，在这种方法中，对病理生理学的更好理解将有助于提供药物，其靶点涉及疾病的潜在致病过程。计算生物学和生物信息学不仅有可能加快药物发现过程，从而降低成本，而且还可能改变药物的设计方式。在这篇综述中，我们将重点介绍不同的计算和生物信息学方法，这些方法已被提出并应用于药物开发过程中涉及的不同步骤。“网络重建”方法的发展现在使得推断基因、蛋白质和代谢物之间调控回路的详细图谱成为可能。这些技术的发展很可能会在未来几十年从根本上改变我们今天所知道的药物发现过程。
The drug discovery process is complex, time consuming and expensive, and includes preclinical and clinical phases. The pharmaceutical industry is moving from a symptomatic relief focus towards a more pathology-based approach where a better understanding of the pathophysiology should help deliver drugs whose targets are involved in the causative processes underlying the disease. Computational biology and bioinformatics have the potential not only to speed up the drug discovery process, thus reducing the costs, but also to change the way drugs are designed. In this review we focus on the different computational and bioinformatics approaches that have been proposed and applied to the different steps involved in the drug development process. The development of 'network-reconstruction' methods is now making it possible to infer a detailed map of the regulatory circuit among genes, proteins and metabolites. It is likely that the development of these technologies will radically change, in the next decades, the drug discovery process, as we know it today.