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Computational Biology and Drug Discovery: From Single-Target to Network Drugs

机译:计算生物学和药物发现:从单一目标药物到网络药物

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摘要

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.
机译:药物发现过程复杂,耗时且昂贵,并且包括临床前和临床阶段。制药行业正在从以症状缓解为重的方法转变为以病理学为基础的方法,在这种方法中,对病理生理学的更好理解应有助于提供目标靶点涉及疾病潜在病因的药物。计算生物学和生物信息学不仅有可能加速药物发现过程,从而降低成本,而且有可能改变药物的设计方式。在这篇综述中,我们关注于已提出并应用于药物开发过程中不同步骤的不同计算和生物信息学方法。现在,“网络重构”方法的发展使得可以推断出基因,蛋白质和代谢物之间的调控回路的详细图谱。正如我们今天所知,在未来几十年中,这些技术的发展可能会从根本上改变药物开发过程。

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