Department of Pharmacological Sciences, Icahn school of Medicine at Mount Sinai, New York, NY 10029, USA.
Nucleic Acids Res. 2019 Jan 8;47(D1):D361-D366. doi: 10.1093/nar/gky916.
Protein kinases are among the most explored protein drug targets. Visualization of kinase conformations is critical for understanding structure-function relationship in this family and for developing chemically unique, conformation-specific small molecule drugs. We have developed Kinformation, a random forest classifier that annotates the conformation of over 3500 protein kinase structures in the Protein Data Bank. Kinformation was trained on structural descriptors derived from functionally important motifs to automatically categorize kinases into five major conformations with pharmacological relevance. Here we present KinaMetrix (http://KinaMetrix.com), a web resource enabling researchers to investigate the protein kinase conformational space as well as a subset of kinase inhibitors that exhibit conformational specificity. KinaMetrix allows users to classify uploaded kinase structures, as well as to derive structural descriptors of protein kinases. Uploaded structures can then be compared to atomic structures of other kinases, enabling users to identify kinases that occupy a similar conformational space to their uploaded structure. Finally, KinaMetrix also serves as a repository for both small molecule substructures that are significantly associated with each conformation type, and for homology models of kinases in inactive conformations. We expect KinaMetrix to serve as a resource for researchers studying kinase structural biology or developing conformation-specific kinase inhibitors.
蛋白激酶是研究最多的蛋白药物靶点之一。了解该家族的结构-功能关系和开发具有化学独特性、构象特异性的小分子药物,都需要对激酶构象进行可视化。我们开发了 Kinformation,这是一种随机森林分类器,可以注释蛋白质数据库中超过 3500 种蛋白激酶结构的构象。Kinformation 是基于来自功能重要基序的结构描述符进行训练的,可自动将激酶分为具有药理学相关性的五个主要构象。这里我们介绍 KinaMetrix(http://KinaMetrix.com),这是一个网络资源,使研究人员能够研究蛋白激酶构象空间以及具有构象特异性的激酶抑制剂子集。KinaMetrix 允许用户对上传的激酶结构进行分类,并获得蛋白激酶的结构描述符。然后可以将上传的结构与其他激酶的原子结构进行比较,使用户能够识别出占据与其上传结构相似构象空间的激酶。最后,KinaMetrix 还充当与每种构象类型显著相关的小分子亚结构以及无活性构象激酶的同源模型的存储库。我们希望 KinaMetrix 能够成为研究激酶结构生物学或开发构象特异性激酶抑制剂的研究人员的资源。