Kandakatla Naresh, Ramakrishnan Geetha
Department of Chemistry, Sathyabama University, Jeppiaar Nagar, Chennai 600119, India.
Adv Bioinformatics. 2014;2014:812148. doi: 10.1155/2014/812148. Epub 2014 Nov 26.
Histone deacetylases 2 (HDAC2), Class I histone deacetylase (HDAC) family, emerged as an important therapeutic target for the treatment of various cancers. A total of 48 inhibitors of two different chemotypes were used to generate pharmacophore model using 3D QSAR pharmacophore generation (HypoGen algorithm) module in Discovery Studio. The best HypoGen model consists of four pharmacophore features namely, one hydrogen bond acceptor (HBA), and one hydrogen donor (HBD), one hydrophobic (HYP) and one aromatic centres, (RA). This model was validated against 20 test set compounds and this model was utilized as a 3D query for virtual screening to validate against NCI and Maybridge database and the hits further screened by Lipinski's rule of 5, and a total of 382 hit compounds from NCI and 243 hit compounds from Maybridge were found and were subjected to molecular docking in the active site of HDAC2 (PDB: 3MAX). Finally eight hit compounds, NSC108392, NSC127064, NSC110782, and NSC748337 from NCI database and MFCD01935795, MFCD00830779, MFCD00661790, and MFCD00124221 from Maybridge database, were considered as novel potential HDAC2 inhibitors.
组蛋白去乙酰化酶2(HDAC2)属于I类组蛋白去乙酰化酶(HDAC)家族,已成为治疗多种癌症的重要治疗靶点。使用Discovery Studio中的3D QSAR药效团生成(HypoGen算法)模块,共48种两种不同化学类型的抑制剂用于生成药效团模型。最佳的HypoGen模型由四个药效团特征组成,即一个氢键受体(HBA)、一个氢键供体(HBD)、一个疏水中心(HYP)和一个芳香中心(RA)。该模型针对20种测试集化合物进行了验证,并用作3D查询进行虚拟筛选,以针对NCI和Maybridge数据库进行验证,命中的化合物进一步通过Lipinski的五规则进行筛选,共从NCI中发现382种命中化合物,从Maybridge中发现243种命中化合物,并在HDAC2的活性位点(PDB:3MAX)进行分子对接。最后,来自NCI数据库的8种命中化合物NSC108392、NSC127064、NSC110782和NSC748337以及来自Maybridge数据库的MFCD01935795、MFCD00830779、MFCD00661790和MFCD00124221被视为新型潜在的HDAC2抑制剂。