Multi-step virtual screening to develop selective DYRK1A inhibitors
Multi-step virtual screening to develop selective DYRK1A inhibitors
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DOI：
10.1016/j.jmgm.2017.01.014
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发表时间：
2017-03-01
影响因子：
2.9
通讯作者：
Hirono, Shuichi
中科院分区：
文献类型：
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作者：
Koyama, Tomoko;Yamaotsu, Noriyuki;Hirono, Shuichi
开发针对特定激酶的选择性抑制剂仍然是激酶靶向药物发现的主要挑战。在这里，我们进行了一个多步骤的虚拟筛选双特异性酪氨酸磷酸化调节激酶1A（DYRK 1A）抑制剂，重点对DYRK 1A的选择性超过细胞周期蛋白依赖性激酶5（CDK 5）。为了研究影响选择性的关键因素，我们构建了逻辑回归模型，分别使用基于残基的结合自由能来区分DYRK 1A和CDK 5的活性和非活性。用分子力学-广义玻恩表面积（MM-GBSA）分解方法计算了计算机配体对接模拟的激酶-配体复合物的残基参数。基于逻辑回归模型的结果，我们建立了一个三维（3D）药效团模型，并选择过滤标准的多步虚拟筛选。通过体外试验评估从筛选获得的虚拟命中化合物对DYRK 1A和CDK 5的抑制活性。我们的筛选鉴定了两种新型选择性DYRK 1A抑制剂，其对DYRK 1A的IC 50值为几μ M，对CDK 5的IC 50值>100 μ M，可以进一步优化以开发更有效的选择性DYRK 1A抑制剂。(C)2017爱思唯尔公司
Developing selective inhibitors for a particular kinase remains a major challenge in kinase-targeted drug discovery. Here we performed a multi-step virtual screening for dual-specificity tyrosine-phosphorylation-regulated kinase 1A (DYRK1A) inhibitors by focusing on the selectivity for DYRK1A over cyclin-dependent kinase 5 (CDK5). To examine the key factors contributing to the selectivity, we constructed logistic regression models to discriminate between actives and inactives for DYRK1A and CDK5, respectively, using residue-based binding free energies. The residue-based parameters were calculated by molecular mechanics-generalized Born surface area (MM-GBSA) decomposition methods for kinase-ligand complexes modeled by computer ligand docking. Based on the findings from the logistic regression models, we built a three-dimensional (3D) pharmacophore model and chose filter criteria for the multi-step virtual screening. The virtual hit compounds obtained from the screening were assessed for their inhibitory activities against DYRK1A and CDK5 by in vitro assay. Our screening identified two novel selective DYRK1A inhibitors with IC50 values of several mu M for DYRK1A and >100 mu M for CDK5, which can be further optimized to develop more potent selective DYRK1A inhibitors. (C) 2017 Elsevier Inc.