McGaughey Georgia B, Culberson J Chris, Feuston Bradley P, Kreatsoulas Constantine, Maiorov Vladimir, Shpungin Joseph
Molecular Systems, West Point, PA 19486, USA.
Mol Divers. 2006 Aug;10(3):341-7. doi: 10.1007/s11030-006-9037-1. Epub 2006 Sep 27.
Within a congeneric series of ATP-competitive KDR kinase inhibitors, we determined that the IC(50) values, which span four orders of magnitude, correlated best with the calculated ligand-protein interaction energy using the Merck Molecular Force Field (MMFFs(94)). Using the ligand-protein interaction energy as a guide, we outline a workflow to rank order virtual KDR kinase inhibitors prior to synthesis. When structural information of the target is available, the ability to score molecules a priori can be used to rationally select reagents. Our implementation allows one to select thousands of readily available reagents, enumerate compounds in multiple poses and score molecules in the active site of a protein within a few hours. In our experience, virtual library enumeration is best used when a correlation between computed descriptors/properties and IC(50) or K (i) values has been established.
在一系列同类的ATP竞争性KDR激酶抑制剂中,我们确定,跨度达四个数量级的IC50值与使用默克分子力场(MMFFs(94))计算出的配体-蛋白质相互作用能相关性最佳。以配体-蛋白质相互作用能为指导,我们概述了一个在合成前对虚拟KDR激酶抑制剂进行排序的工作流程。当有靶点的结构信息时,先验地对分子进行评分的能力可用于合理选择试剂。我们的方法允许在几小时内从数千种现成的试剂中进行选择,列举出处于多种构象的化合物,并对蛋白质活性位点中的分子进行评分。根据我们的经验,当已建立计算描述符/性质与IC50或Ki值之间的相关性时,虚拟库列举法最为适用。