Vrontaki Eleni, Melagraki Georgia, Mavromoustakos Thomas, Afantitis Antreas
Department of Chemoinformatics, NovaMechanics Ltd., Nicosia, Cyprus; Laboratory of Organic Chemistry, Department of Chemistry, University of Athens, Athens 15771, Greece.
Department of Chemoinformatics, NovaMechanics Ltd., Nicosia, Cyprus.
Methods. 2015 Jan;71:4-13. doi: 10.1016/j.ymeth.2014.03.021. Epub 2014 Mar 27.
Molecular docking, 3D-QSAR CoMSIA and similarity search were combined in a multi-step framework with the ultimate goal to identify potent indole analogs, in the ChEMBL database, as inhibitors of HCV replication. The crystal structure of HCV RNA-dependent RNA polymerase (NS5B GT1b) was utilized and 41 known inhibitors were docked into the enzyme "Palm II" active site. In a second step, the docking pose of each compound was used in a receptor-based alignment for the generation of the CoMSIA fields. A validated 3D-QSAR CoMSIA model was subsequently built to accurately estimate the activity values. The proposed framework gives insight into the structural characteristics that affect the binding and the inhibitory activity of these analogs on HCV polymerase. The obtained in silico model was used to predict the activity of novel compounds prior to their synthesis and biological testing, within a Virtual Screening framework. The ChEMBL database was mined to afford compounds containing the indole scaffold that are predicted to possess high activity and thus can be prioritized for biological screening.
分子对接、3D-QSAR CoMSIA和相似性搜索在一个多步骤框架中相结合，其最终目标是在ChEMBL数据库中识别出作为丙型肝炎病毒（HCV）复制抑制剂的强效吲哚类似物。利用HCV RNA依赖性RNA聚合酶（NS5B GT1b）的晶体结构，并将41种已知抑制剂对接至该酶的“Palm II”活性位点。在第二步中，每种化合物的对接姿势用于基于受体的比对，以生成CoMSIA场。随后构建了经过验证的3D-QSAR CoMSIA模型，以准确估计活性值。所提出的框架深入了解了影响这些类似物对HCV聚合酶的结合和抑制活性的结构特征。在虚拟筛选框架内，所获得的计算机模拟模型用于在新型化合物合成和生物学测试之前预测其活性。挖掘ChEMBL数据库以提供含有吲哚支架的化合物，这些化合物预计具有高活性，因此可优先进行生物学筛选。
