系统性药物重新定位:药物发现的新模式

Vinod Kumar
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引用次数: 0

摘要

药物重新定位提供了更快的开发时间和降低药物发现风险的可能性。随着高通量技术的快速发展和全基因组水平数据集的不断积累,越来越多的疾病和药物可以通过其诱导的基因表达、蛋白质、代谢物和表型的变化来全面表征。在这里,我们将描述两种不同的方法,利用这些数据类型系统地评估和建议新的或现有药物的新的疾病适应症。第一种方法被称为连接图(CMap),它收集了用生物活性小分子处理过的培养人类细胞的全基因组转录表达数据,通过共同基因表达变化的短暂特征,可以发现药物、基因和疾病之间的功能联系。第二种方法利用全基因组关联研究(GWAS)的遗传关联来寻找现有药物的替代适应症。其他利用临床数据可用性的方法也将简要讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Systematic drug repositioning: A new paradigm in drug discovery
Drug repositioning offers the possibility of faster development times and reduced risks in drug discovery. With the rapid development of high-throughput technologies and ever-increasing accumulation of whole genome-level datasets, an increasing number of diseases and drugs can be comprehensively characterized by the changes they induce in gene expression, protein, metabolites and phenotypes. Here we will describe two distinct approaches that utilize these data types to systematically evaluate and suggest new disease indications for new or existing drugs. The first approach dubbed the Connectivity Map (CMap) is a collection of genome-wide transcriptional expression data from cultured human cells treated with bioactive small molecules that enable the discovery of functional connections between drugs, genes and diseases through the transitory feature of common gene-expression changes.The second approach uses genetic associations from Genome Wide Association Studies (GWAS) to find alternative indications for existing drugs. Other approaches which take advantage of the availability of clinical data will also be discussed briefly.
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