Fragment-based drug discovery using rational design.

H Jhoti
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引用次数: 20

Abstract

Fragment-based drug discovery (FBDD) is established as an alternative approach to high-throughput screening for generating novel small molecule drug candidates. In FBDD, relatively small libraries of low molecular weight compounds (or fragments) are screened using sensitive biophysical techniques to detect their binding to the target protein. A lower absolute affinity of binding is expected from fragments, compared to much higher molecular weight hits detected by high-throughput screening, due to their reduced size and complexity. Through the use of iterative cycles of medicinal chemistry, ideally guided by three-dimensional structural data, it is often then relatively straightforward to optimize these weak binding fragment hits into potent and selective lead compounds. As with most other lead discovery methods there are two key components of FBDD; the detection technology and the compound library. In this review I outline the two main approaches used for detecting the binding of low affinity fragments and also some of the key principles that are used to generate a fragment library. In addition, I describe an example of how FBDD has led to the generation of a drug candidate that is now being tested in clinical trials for the treatment of cancer.

使用合理设计的基于片段的药物发现。
基于片段的药物发现(FBDD)是一种高通量筛选的替代方法,用于生成新的小分子候选药物。在FBDD中,使用灵敏的生物物理技术筛选相对较小的低分子量化合物(或片段)文库,以检测它们与目标蛋白的结合。与高通量筛选检测到的高分子量命中相比,由于碎片的尺寸和复杂性减小,预计其结合的绝对亲和力较低。通过使用药物化学的迭代循环,在三维结构数据的理想指导下,通常可以相对直接地将这些弱结合片段优化为有效和选择性的先导化合物。与大多数其他先导发现方法一样,FBDD有两个关键组成部分:检测技术及化合物库。在这篇综述中,我概述了用于检测低亲和力片段结合的两种主要方法,以及用于生成片段库的一些关键原则。此外,我还描述了一个例子,说明FBDD如何导致了一种候选药物的产生,这种候选药物目前正在进行癌症治疗的临床试验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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