Patel Preeti, Singh Avineesh, Patel Vijay K, Jain Deepak K, Veerasamy Ravichandran, Rajak Harish
SLT Institute of Pharmaceutical Sciences, Guru Ghasidas University, Bilaspur 495009, India.
Comb Chem High Throughput Screen. 2016;19(9):735-751. doi: 10.2174/1386207319666160801154415.
Histone deacetylase (HDAC) inhibitors can reactivate gene expression and inhibit the growth and survival of cancer cells.
To identify the important pharmacophoric features and correlate 3Dchemical structure with biological activity using 3D-QSAR and Pharmacophore modeling studies.
The pharmacophore hypotheses were developed using e-pharmacophore script and phase module. Pharmacophore hypothesis represents the 3D arrangement of molecular features necessary for activity. A series of 55 compounds with wellassigned HDAC inhibitory activity were used for 3D-QSAR model development.
Best 3D-QSAR model, which is a five partial least square (PLS) factor model with good statistics and predictive ability, acquired Q2 (0.7293), R2 (0.9811), cross-validated coefficient rcv 2=0.9807 and R2 pred=0.7147 with low standard deviation (0.0952). Additionally, the selected pharmacophore model DDRRR.419 was used as a 3D query for virtual screening against the ZINC database. In the virtual screening workflow, docking studies (HTVS, SP and XP) were carried out by selecting multiple receptors (PDB ID: 1T69, 1T64, 4LXZ, 4LY1, 3MAX, 2VQQ, 3C10, 1W22). Finally, six compounds were obtained based on high scoring function (dock score -11.2278-10.2222 kcal/mol) and diverse structures.
The structure activity correlation was established using virtual screening, docking, energetic based pharmacophore modelling, pharmacophore, atom based 3D QSAR models and their validation. The outcomes of these studies could be further employed for the design of novel HDAC inhibitors for anticancer activity.
组蛋白去乙酰化酶（HDAC）抑制剂可重新激活基因表达并抑制癌细胞的生长和存活。
利用三维定量构效关系（3D-QSAR）和药效团建模研究，确定重要的药效基团特征，并将三维化学结构与生物活性相关联。
使用电子药效团脚本和相模块开发药效团假设。药效团假设代表了活性所需分子特征的三维排列。一系列具有明确HDAC抑制活性的55种化合物用于三维定量构效关系模型开发。
最佳的三维定量构效关系模型是一个具有良好统计学和预测能力的五偏最小二乘（PLS）因子模型，其Q2为0.7293，R2为0.9811，交叉验证系数rcv2 = 0.9807，R2 pred = 0.7147，标准差较低（0.0952）。此外，所选的药效团模型DDRRR.419用作针对ZINC数据库进行虚拟筛选的三维查询。在虚拟筛选工作流程中，通过选择多个受体（PDB ID：1T69、1T64、4LXZ、4LY1、3MAX、2VQQ、3C10、1W22）进行对接研究（高通量虚拟筛选、标准精度和精确精度）。最后，基于高评分函数（对接分数-11.2278 - 10.2222千卡/摩尔）和不同结构获得了六种化合物。
利用虚拟筛选、对接、基于能量的药效团建模、药效团、基于原子的三维定量构效关系模型及其验证建立了构效关系。这些研究结果可进一步用于设计具有抗癌活性的新型HDAC抑制剂。
