Jhoti H
Astex Therapeutics Ltd., 436 Science Park, Milton Rd, CB40QA Cambridge, UK.
Ernst Schering Found Symp Proc. 2007(3):169-85. doi: 10.1007/2789_2007_064.
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.
基于片段的药物发现(FBDD)已成为一种替代高通量筛选的方法,用于生成新型小分子药物候选物。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,以检测它们与靶蛋白的结合。与高通量筛选检测到的分子量高得多的命中物相比,由于片段的尺寸和复杂性降低,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,理想情况下以三维结构数据为指导,通常相对容易将这些弱结合片段命中物优化为强效且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;检测技术和化合物文库。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,以及用于生成片段文库的一些关键原则。此外,我描述了一个FBDD如何导致生成一种药物候选物的例子,该候选物目前正在进行治疗癌症的临床试验。