Crisan Luminita, Avram Sorin, Pacureanu Liliana
Department of Computational Chemistry, The Institute of Chemistry Timisoara of Romanian Academy, 24 Mihai Viteazul Avenue, 300223, Timisoara, Romania.
Mol Divers. 2017 May;21(2):385-405. doi: 10.1007/s11030-016-9724-5. Epub 2017 Jan 21.
The current study was conducted to elaborate a novel pharmacophore model to accurately map selective glycogen synthase kinase-3 (GSK-3) inhibitors, and perform virtual screening and drug repurposing. Pharmacophore modeling was developed using PHASE on a data set of 203 maleimides. Two benchmarking validation data sets with focus on selectivity were assembled using ChEMBL and PubChem GSK-3 confirmatory assays. A drug repurposing experiment linking pharmacophore matching with drug information originating from multiple data sources was performed. A five-point pharmacophore model was built consisting of a hydrogen bond acceptor (A), hydrogen bond donor (D), hydrophobic (H), and two rings (RR). An atom-based 3D quantitative structure-activity relationship (QSAR) model showed good correlative and satisfactory predictive abilities (training set [Formula: see text]; test set: [Formula: see text]; whole data set: stability [Formula: see text]). Virtual screening experiments revealed that selective GSK-3 inhibitors are ranked preferentially by Hypo-1, but fail to retrieve nonselective compounds. The pharmacophore and 3D QSAR models can provide assistance to design novel, potential GSK-3 inhibitors with high potency and selectivity pattern, with potential application for the treatment of GSK-3-driven diseases. A class of purine nucleoside antileukemic drugs was identified as potential inhibitor of GSK-3, suggesting the reassessment of the target range of these drugs.
本研究旨在构建一种新型药效团模型,以精确描绘选择性糖原合酶激酶-3(GSK-3)抑制剂,并进行虚拟筛选和药物再利用研究。利用PHASE软件在203种马来酰亚胺数据集上开展药效团建模。使用ChEMBL和PubChem的GSK-3确证试验,组建了两个侧重于选择性的基准验证数据集。进行了一项药物再利用实验,将药效团匹配与来自多个数据源的药物信息相联系。构建了一个由氢键受体(A)、氢键供体(D)、疏水基团(H)和两个环(RR)组成的五点药效团模型。基于原子的三维定量构效关系(3D QSAR)模型显示出良好的相关性和令人满意的预测能力(训练集[公式:见原文];测试集:[公式:见原文];整个数据集:稳定性[公式:见原文])。虚拟筛选实验表明,选择性GSK-3抑制剂优先由Hypo-1排序,但未能检索到非选择性化合物。药效团和3D QSAR模型可为设计具有高效力和选择性模式的新型潜在GSK-3抑制剂提供帮助,在治疗由GSK-3驱动的疾病方面具有潜在应用价值。一类嘌呤核苷抗白血病药物被鉴定为GSK-3的潜在抑制剂,这表明需要重新评估这些药物的靶点范围。