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Genomics and proteomics: the new millennium of drug discovery and development.

机译:基因组学和蛋白质组学:新世纪的药物发现和开发。

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One of the most pressing issues facing the pharmaceutical and biotechnology industry is the tremendous dropout rate of lead drug candidates. Over the last two decades, several new genomic technologies have been developed in hopes of addressing the issues of target identification and lead candidate optimization. Gene expression microarray is one of these technologies and this review describes the four main formats, which are currently available: (a) cDNA; (b) oligonucleotide; (c) electrokinetic; and (d) fiberoptic. Many of these formats have been developed with the goal of screening large numbers of genes. Recently, a high-throughput array format has been developed where a large number of samples can be assayed using arrays in parallel. In addition, focusing on gene expression may be only one avenue in preventing lead candidate failure. Proteomics or the study of protein expression may also play a role. Two-dimensional polyacrylamide gel electrophoresis (2-DE) coupled with mass spectroscopy has been the most widely accepted format to study protein expression. However, protein microarrays are now being developed and modified to a high-throughput screening format. Examples of several gene and protein expression studies as they apply to drug discovery and development are reviewed. These studies often result in large data sets. Examples of how several statistical methods (principal components analysis [PCA], clustering methods, Shannon entropy, etc.) have been applied to these data sets are also described. These newer genomic and proteomic technologies and their analysis and visualization methods have the potential to make the drug discovery and development process less costly and more efficient by aiding to select better target and lead candidates.
机译:制药和生物技术行业面临的最紧迫的问题之一是领先候选药物的巨大辍学率。在过去的二十年中,已经开发了几种新的基因组技术,以期解决目标识别和潜在候选优化的问题。基因表达微阵列是这些技术之一,本综述描述了目前可用的四种主要格式:(a)cDNA; (b)寡核苷酸; (c)电动的; (d)光纤。为了筛选大量基因,已经开发了许多这样的格式。近来,已经开发出高通量的阵列形式,其中可以使用平行的阵列来分析大量样品。此外,专注于基因表达可能只是预防先导候选者失败的一种途径。蛋白质组学或蛋白质表达研究也可能起作用。二维聚丙烯酰胺凝胶电泳(2-DE)与质谱联用已成为研究蛋白质表达的最广泛接受的格式。但是,蛋白质微阵列目前正在开发中,并已修改为高通量筛选格式。综述了一些基因和蛋白质表达研究的例子,这些研究适用于药物发现和开发。这些研究通常会产生大量数据集。还介绍了如何将几种统计方法(主要成分分析[PCA],聚类方法,香农熵等)应用于这些数据集的示例。这些较新的基因组和蛋白质组学技术及其分析和可视化方法具有潜力,可以通过帮助选择更好的靶标和潜在候选人来降低药物研发的成本和效率。

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