Xia Jie, Hu Huabin, Xue Wenjie, Wang Xiang Simon, Wu Song
a State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Department of New Drug Research and Development , Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing , China.
b Molecular Modeling and Drug Discovery Core Laboratory for District of Columbia Center for AIDS Research (DC CFAR), Department of Pharmaceutical Sciences, College of Pharmacy , Howard University , Washington, DC , USA.
J Enzyme Inhib Med Chem. 2018 Dec;33(1):525-535. doi: 10.1080/14756366.2018.1437156.
Histone deacetylase 3 (HDAC3) is a potential target for the treatment of human diseases such as cancers, diabetes, chronic inflammation and neurodegenerative diseases. Previously, we proposed a virtual screening (VS) pipeline named "Hypo1_FRED_SAHA-3" for the discovery of HDAC3 inhibitors (HDAC3Is) and had thoroughly validated it by theoretical calculations. In this study, we attempted to explore its practical utility in a large-scale VS campaign. To this end, we used the VS pipeline to hierarchically screen the Specs chemical library. In order to facilitate compound cherry-picking, we then developed a knowledge-based pose filter (PF) by using our in-house quantitative structure activity relationship- (QSAR-) modelling approach and coupled it with FRED and Autodock Vina. Afterward, we purchased and tested 11 diverse compounds for their HDAC3 inhibitory activity in vitro. The bioassay has identified compound 2 (Specs ID: AN-979/41971160) as a HDAC3I (IC = 6.1 μM), which proved the efficacy of our workflow. As a medicinal chemistry study, we performed a follow-up substructure search and identified two more hit compounds of the same chemical type, i.e. 2-1 (AQ-390/42122119, IC = 1.3 μM) and 2-2 (AN-329/43450111, IC = 12.5 μM). Based on the chemical structures and activities, we have demonstrated the essential role of the capping group in maintaining the activity for this class of HDAC3Is. In addition, we tested the hit compounds for their in vitro activities on other HDACs, including HDAC1, HDAC2, HDAC8, HDAC4 and HDAC6. We have identified these compounds are HDAC1/2/3 selective inhibitors, of which compound 2 show the best selectivity profile. Taken together, the present study is an experimental validation and an update to our earlier VS strategy. The identified hits could be used as starting structures for the development of highly potent and selective HDAC3Is.
组蛋白去乙酰化酶3(HDAC3)是治疗癌症、糖尿病、慢性炎症和神经退行性疾病等人类疾病的潜在靶点。此前,我们提出了一种名为 “Hypo1_FRED_SAHA-3” 的虚拟筛选(VS)流程用于发现HDAC3抑制剂(HDAC3Is),并通过理论计算对其进行了全面验证。在本研究中,我们试图探索其在大规模虚拟筛选活动中的实际效用。为此,我们使用该虚拟筛选流程对Specs化学文库进行分层筛选。为了便于化合物挑选,我们随后利用内部定量构效关系(QSAR)建模方法开发了一种基于知识的构象过滤器(PF),并将其与FRED和Autodock Vina相结合。之后,我们购买并测试了11种不同化合物的体外HDAC3抑制活性。生物测定确定化合物2(Specs编号:AN-979/41971160)为HDAC3抑制剂(IC = 6.1 μM),这证明了我们工作流程的有效性。作为一项药物化学研究,我们进行了后续的子结构搜索,又鉴定出另外两种相同化学类型的活性化合物,即2-1(AQ-390/42122119,IC = 1.3 μM)和2-2(AN-329/43450111,IC = 12.5 μM)。基于化学结构和活性,我们证明了封端基团在维持这类HDAC3抑制剂活性方面的重要作用。此外,我们测试了活性化合物对其他HDACs的体外活性,包括HDAC1、HDAC2、HDAC8、HDAC4和HDAC6。我们确定这些化合物是HDAC1/2/3选择性抑制剂,其中化合物2表现出最佳的选择性特征。综上所述,本研究是对我们早期虚拟筛选策略的实验验证和更新。所鉴定出的活性化合物可作为开发高效和选择性HDAC3抑制剂的起始结构。