Institute for Pharmaceutical Chemistry, Philipps-University Marburg, Marbacher Weg 6, 35032 Marburg, Germany.
Helmholtz-Zentrum Berlin für Materialien und Energie, HZB, BESSY II, Abteilung Makromolekulare Kristallographie, Albert-Einstein-Straße 15, 12489 Berlin, Germany.
Structure. 2016 Aug 2;24(8):1398-1409. doi: 10.1016/j.str.2016.06.010. Epub 2016 Jul 21.
Today the identification of lead structures for drug development often starts from small fragment-like molecules raising the chances to find compounds that successfully pass clinical trials. At the heart of the screening for fragments binding to a specific target, crystallography delivers structural information essential for subsequent drug design. While it is common to search for bound ligands in electron densities calculated directly after an initial refinement cycle, we raise the important question whether this strategy is viable for fragments characterized by low affinities. Here, we describe and provide a collection of high-quality diffraction data obtained from 364 protein crystals treated with diverse fragments. Subsequent data analysis showed that ∼25% of all hits would have been missed without further refining the resulting structures. To enable fast and reliable hit identification, we have designed an automated refinement pipeline that will inspire the development of optimized tools facilitating the successful application of fragment-based methods.
如今,药物开发的先导结构的鉴定通常从小分子片段开始,从而增加了找到成功通过临床试验的化合物的机会。在筛选与特定靶标结合的片段时,晶体学提供了对于后续药物设计至关重要的结构信息。虽然在初始精修循环后直接计算电子密度中寻找结合配体是常见的做法,但我们提出了一个重要的问题,即对于亲和力较低的片段,这种策略是否可行。在这里,我们描述并提供了一组高质量的衍射数据,这些数据来自 364 个用不同片段处理的蛋白质晶体。后续数据分析表明,如果不进一步精修得到的结构,约 25%的命中结果将会丢失。为了能够快速可靠地识别命中结果,我们设计了一个自动化精修流水线,这将激发优化工具的开发,从而促进基于片段方法的成功应用。