Ganai Shabir Ahmad, Abdullah Ehsaan, Rashid Romana, Altaf Mohammad
Chromatin and Epigenetics Lab, Department of Biotechnology, University of Kashmir, Srinagar, India.
Front Mol Neurosci. 2017 Nov 9;10:357. doi: 10.3389/fnmol.2017.00357. eCollection 2017.
Histone deacetylases (HDACs) regulate epigenetic gene expression programs by modulating chromatin architecture and are required for neuronal development. Dysregulation of HDACs and aberrant chromatin acetylation homeostasis have been implicated in various diseases ranging from cancer to neurodegenerative disorders. Histone deacetylase inhibitors (HDACi), the small molecules interfering HDACs have shown enhanced acetylation of the genome and are gaining great attention as potent drugs for treating cancer and neurodegeneration. HDAC2 overexpression has implications in decreasing dendrite spine density, synaptic plasticity and in triggering neurodegenerative signaling. Pharmacological intervention against HDAC2 though promising also targets neuroprotective HDAC1 due to high sequence identity (94%) with former in catalytic domain, culminating in debilitating off-target effects and creating hindrance in the defined intervention. This emphasizes the need of designing HDAC2-selective inhibitors to overcome these vicious effects and for escalating the therapeutic efficacy. Here we report a top-down combinatorial approach for identifying the structural variants that are substantial for interactions against HDAC1 and HDAC2 enzymes. We used extra-precision (XP)-molecular docking, Molecular Mechanics Generalized Born Surface Area (MMGBSA) for predicting affinity of inhibitors against the HDAC1 and HDAC2 enzymes. Importantly, we employed a novel strategy of coupling the state-of-the-art molecular dynamics simulation (MDS) to energetically-optimized structure based pharmacophores (e-Pharmacophores) method via MDS trajectory clustering for hypothesizing the e-Pharmacophore models. Further, we performed e-Pharmacophores based virtual screening against phase database containing millions of compounds. We validated the data by performing the molecular docking and MM-GBSA studies for the selected hits among the retrieved ones. Our studies attributed inhibitor potency to the ability of forming multiple interactions and infirm potency to least interactions. Moreover, our studies delineated that a single HDAC inhibitor portrays differential features against HDAC1 and HDAC2 enzymes. The high affinity and selective HDAC2 inhibitors retrieved through e-Pharmacophores based virtual screening will play a critical role in ameliorating neurodegenerative signaling without hampering the neuroprotective isoform (HDAC1).
组蛋白去乙酰化酶(HDACs)通过调节染色质结构来调控表观遗传基因表达程序,是神经元发育所必需的。HDACs的失调和异常的染色质乙酰化稳态与从癌症到神经退行性疾病等各种疾病有关。组蛋白去乙酰化酶抑制剂(HDACi),即干扰HDACs的小分子,已显示出增强的基因组乙酰化,作为治疗癌症和神经退行性疾病的有效药物正受到广泛关注。HDAC2的过表达与树突棘密度降低、突触可塑性以及触发神经退行性信号有关。尽管针对HDAC2的药物干预前景广阔,但由于其在催化结构域与神经保护型HDAC1具有高度的序列同一性(94%),也会靶向HDAC1,最终导致有害的脱靶效应,并在明确的干预中造成阻碍。这强调了设计HDAC2选择性抑制剂以克服这些不良影响并提高治疗效果的必要性。在此,我们报告一种自上而下的组合方法,用于鉴定对HDAC1和HDAC2酶相互作用至关重要的结构变体。我们使用超精确(XP)分子对接、分子力学广义玻恩表面积(MMGBSA)来预测抑制剂对HDAC1和HDAC2酶的亲和力。重要的是,我们采用了一种新颖的策略,通过分子动力学模拟(MDS)轨迹聚类,将最先进的分子动力学模拟与基于能量优化结构的药效团(e-药效团)方法相结合,以推测e-药效团模型。此外,我们针对包含数百万种化合物的相数据库进行了基于e-药效团的虚拟筛选。我们通过对检索到的选定命中物进行分子对接和MM-GBSA研究来验证数据。我们的研究将抑制剂的效力归因于形成多种相互作用的能力,而效力较弱则归因于最少的相互作用。此外,我们的研究表明,单一的HDAC抑制剂对HDAC1和HDAC2酶具有不同的特征。通过基于e-药效团的虚拟筛选获得的高亲和力和选择性HDAC2抑制剂将在改善神经退行性信号而不影响神经保护异构体(HDAC1)方面发挥关键作用。