Lanka Goverdhan, Banerjee Suvankar, Regula Sanjeev, Adhikari Nilanjan, Ghosh Balaram
Epigenetic Research Laboratory, Department of Pharmacy, Birla Institute of Technology and Science-Pilani Hyderabad Campus, Shamirpet, Hyderabad, India.
Computer Aided Drug Design Laboratory, Department of Pharmacy, Birla Institute of Technology and Science-Pilani Hyderabad Campus, Shamirpet, Hyderabad, India.
J Biomol Struct Dyn. 2024 Nov 25:1-24. doi: 10.1080/07391102.2024.2429020.
Histone deacetylases (HDACs) are important epigenetic regulators that modulate the activity of histone and non-histone proteins leading to various cancers. Histone deacetylase 1 (HDAC1) is a member of class 1 HDAC family related to different cancers. However, the nonselective profile of existing HDAC1 inhibitors restricted their clinical utility. Therefore, the identification of new HDAC1 selective inhibitors may be fruitful against cancer therapy. In this present work, a pharmacophore model was built using 60 benzamide-based known HDAC1 selective inhibitors and it was used further to filter the large epigenetic molecular database of small molecules. Further, the 3D-QSAR model was built using the best common pharmacophore hypothesis consisting of higher PLS statistics of of 0.89, of 0.83, variance ratio () of 65.7 and Pearson- value of 0.94 revealing the model reliability and its high predictive power. The screened hits of the pharmacophore model were then subjected to molecular docking against HDAC1 to identify high-affinity lead molecules. The top 10 hits were ranked from the docking studies using docking scores for lead optimization. The potential hit molecules M1 and M2 identified from the study showed promising interaction during HDAC1 docking and MD simulation studies with acceptable ADME properties. Also, the newly designed lead compounds M11 and M12 may be considered highly potential inhibitors against HDAC1. The 3D-QSAR analysis, conformational requirements, and observations noticed in the MD simulations study will enable the optimization of lead molecules and to design of novel effective, and selective HDAC1 inhibitors in the future.
组蛋白去乙酰化酶（HDACs）是重要的表观遗传调节因子，可调节组蛋白和非组蛋白的活性，进而引发各种癌症。组蛋白去乙酰化酶1（HDAC1）是1类HDAC家族的成员，与多种癌症相关。然而，现有HDAC1抑制剂的非选择性特征限制了它们的临床应用。因此，鉴定新型HDAC1选择性抑制剂可能对癌症治疗具有重要意义。在本研究中，利用60种基于苯甲酰胺的已知HDAC1选择性抑制剂构建了一个药效团模型，并进一步用于筛选大型小分子表观遗传分子数据库。此外，使用最佳通用药效团假设构建了3D-QSAR模型，其偏最小二乘法（PLS）统计值较高，Q²为0.89，R²为0.83，方差比（F）为65.7，Pearson相关系数（r）为0.94，表明该模型具有可靠性和较高的预测能力。然后，将药效团模型筛选出的命中化合物与HDAC1进行分子对接，以鉴定高亲和力先导分子。根据对接分数对对接研究中的前10个命中化合物进行排名，以优化先导化合物。从该研究中鉴定出的潜在命中分子M1和M2在HDAC1对接和分子动力学（MD）模拟研究中显示出有前景的相互作用，且具有可接受的药物代谢动力学性质。此外，新设计的先导化合物M11和M12可能被认为是针对HDAC1的极具潜力的抑制剂。MD模拟研究中的3D-QSAR分析、构象要求和观察结果将有助于未来优化先导分子并设计新型有效的选择性HDAC1抑制剂。
