Janda K D
Department of Molecular Biology, Scripps Research Institute, La Jolla, CA 92037.
Proc Natl Acad Sci U S A. 1994 Nov 8;91(23):10779-85. doi: 10.1073/pnas.91.23.10779.
Over the past two decades the pharmaceutical industry has been driven by the biological sciences. The discovery and description of the biological mechanisms that underlie disease states accompanied by an unraveling of these mechanisms has provided drug, and more recently biotechnological, companies with a barrage of new therapeutic targets. Paradoxically, as a result of such biological and biochemical advances, new sources of drug leads are in short supply. Considerable efforts in trying to create potential drug candidates has led to the parturition of combinatorial chemical libraries. In this review I will examine some of the main technologies for generating and deducing active components from combinatorial libraries that have been segregated into two schools of thought: (i) the creation and decoding of combinatorial libraries by so-called tagged methodologies, and (ii) the production and deconvolution of chemical libraries by untagged protocols.
在过去二十年中,制药行业一直由生物科学驱动。对疾病状态背后生物机制的发现与描述,以及对这些机制的深入研究,为制药公司,以及最近的生物技术公司提供了大量新的治疗靶点。矛盾的是,由于这些生物学和生物化学方面的进展,新的药物先导物来源却供不应求。为了创造潜在的药物候选物,人们付出了巨大努力,从而催生了组合化学文库。在这篇综述中,我将研究一些从组合文库中生成和推导活性成分的主要技术,这些技术已分为两种思路:(i)通过所谓的标记方法创建和解码组合文库,以及(ii)通过无标记方案生产和反卷积化学文库。