†BioMed X Innovation Center, Im Neuenheimer Feld 583, 69120 Heidelberg, Germany.
‡Global Computational Chemistry, Merck KGaA, Frankfurter Strasse 250, 64293 Darmstadt, Germany.
J Chem Inf Model. 2015 Mar 23;55(3):538-49. doi: 10.1021/ci500624s. Epub 2015 Jan 20.
Protein kinases are involved in a variety of diseases including cancer, inflammation, and autoimmune disorders. Although the development of new kinase inhibitors is a major focus in pharmaceutical research, a large number of kinases remained so far unexplored in drug discovery projects. The selection and assessment of targets is an essential but challenging area. Today, a few thousands of experimentally determined kinase structures are available, covering about half of the human kinome. This large structural source allows guiding the target selection via structure-based druggability prediction approaches such as DoGSiteScorer. Here, a thorough analysis of the ATP pockets of the entire human kinome in the DFG-in state is presented in order to prioritize novel kinase structures for drug discovery projects. For this, all human kinase X-ray structures available in the PDB were collected, and homology models were generated for the missing part of the kinome. DoGSiteScorer was used to calculate geometrical and physicochemical properties of the ATP pockets and to predict the potential of each kinase to be druggable. The results indicate that about 75% of the kinome are in principle druggable. Top ranking structures comprise kinases that are primary targets of known approved drugs but additionally point to so far less explored kinases. The presented analysis provides new insights into the druggability of ATP binding pockets of the entire kinome. We anticipate this comprehensive druggability assessment of protein kinases to be helpful for the community to prioritize so far untapped kinases for drug discovery efforts.
蛋白激酶参与多种疾病,包括癌症、炎症和自身免疫性疾病。尽管开发新的激酶抑制剂是药物研发的主要关注点,但在药物发现项目中,仍有大量激酶尚未被探索。目标的选择和评估是一个必不可少但具有挑战性的领域。如今,已有数千种经实验确定的激酶结构,涵盖了人类激酶组的约一半。这个庞大的结构来源可以通过基于结构的可成药性预测方法(如 DoGSiteScorer)来指导目标选择。在这里,为了优先考虑新药发现项目中的新型激酶结构,对整个人类激酶组在 DFG-in 状态下的 ATP 口袋进行了彻底的分析。为此,收集了 PDB 中所有可用的人类激酶 X 射线结构,并为激酶组缺失的部分生成了同源模型。使用 DoGSiteScorer 计算 ATP 口袋的几何和物理化学特性,并预测每个激酶的成药性潜力。结果表明,大约 75%的激酶原则上是可成药的。排名靠前的结构包括已知批准药物的主要靶标激酶,但另外还指出了迄今研究较少的激酶。所提出的分析为整个激酶组的 ATP 结合口袋的成药性提供了新的见解。我们预计,对蛋白激酶的这种全面成药性评估将有助于社区优先考虑迄今为止尚未开发的激酶,以进行药物发现工作。