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Application of genomics, proteomics and metabolomics in drug discovery, development and clinic

机译:基因组学,蛋白质组学和代谢组学在药物发现,开发和临床中的应用

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摘要

Genomics, proteomics and metabolomics are three areas that are routinely applied throughout the drug-development process as well as after a product enters the market. This review discusses all three 'omics, reporting on the key applications, techniques, recent advances and expectations of each. Genomics, mainly through the use of novel and next-generation sequencing techniques, has advanced areas of drug discovery and development through the comparative assessment of normal and diseased-state tissues, transcription and/or expression profiling, side-effect profiling, pharmacogenomics and the identification of biomarkers. Proteomics, through techniques including isotope coded affinity tags, stable isotopic labeling by amino acids in cell culture, isobaric tags for relative and absolute quantification, multidirectional protein identification technology, activity-based probes, protein/peptide arrays, phage displays and two-hybrid systems is utilized in multiple areas through the drug development pipeline including target and lead identification, compound optimization, throughout the clinical trials process and after market analysis. Metabolomics, although the most recent and least developed of the three 'omics considered in this review, provides a significant contribution to drug development through systems biology approaches. Already implemented to some degree in the drug-discovery industry and used in applications spanning target identification through to toxicological analysis, metabolic network understanding is essential in generating future discoveries.
机译:基因组学,蛋白质组学和代谢组学是在药物开发过程中以及产品进入市场后通常应用的三个领域。这篇综述讨论了所有三种“组学”,报告了它们的关键应用,技术,最新进展和期望。基因组学主要通过使用新型和下一代测序技术,通过对正常和患病状态组织,转录和/或表达谱,副作用谱,药物基因组学和生物标志物的鉴定。蛋白质组学,包括同位素编码的亲和标签,细胞培养中氨基酸的稳定同位素标记,相对和绝对定量的同量异位标签,多方向蛋白质鉴定技术,基于活性的探针,蛋白质/肽阵列,噬菌体展示和两杂交系统通过药物开发管道可在多个领域使用它,包括靶标和先导识别,化合物优化,整个临床试验过程以及市场分析之后。代谢组学虽然是本综述中考虑的三个“组学”中最新,最不发达的,但它通过系统生物学方法为药物开发做出了重大贡献。代谢网络的理解已经在药物发现行业中得到了一定程度的实施,并已用于从靶标识别到毒理学分析的各种应用中,对于产生未来发现至关重要。

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