Uba Abdullahi İbrahim, Yelekçi Kemal
Center for Biotechnology Research, Bayero University Kano , Nigeria.
Department of Bioinformatics and Genetics, Faculty of Engineering and Natural Sciences, Kadir Has University , İstanbul , Turkey.
Turk J Biol. 2017 Dec 18;41(6):901-918. doi: 10.3906/biy-1701-26. eCollection 2017.
Histone deacetylases (HDACs) are enzymes that act on histone proteins to remove the acetyl group and thereby regulate the chromatin state. HDACs act not only on histone protein but also nonhistone proteins that are key players in cellular processes such as the cell cycle, signal transduction, apoptosis, and more. "Classical" HDACs have been shown to be promising targets for anticancer drug design and development. However, the selectivity of HDAC inhibitors for HDAC isoforms remains the motivation of current research in this field. Here, we explored Class I HDACs and HDAC6 by sequence alignment and structural superimposition, catalytic channel extraction, and identification of critical residues involved in HDAC catalysis. Based on the general pharmacophore features of known HDAC inhibitors, we developed a library of compounds by scaffold hopping on a fragment hit identified via structurebased virtual screening of the molecular fragment library retrieved from the Otava database. Molecular docking assay revealed five of these compounds to have increased potency and selectivity for HDACs 1 and 2. Furthermore, their predicted absorption, distribution, metabolism, elimination, and toxicity (ADMET) properties were consistent with those of drug-like compounds. With further modelingbased and experimental investigations, we believe that these findings may offer additional potential HDAC inhibitors with improved selectivity.
组蛋白去乙酰化酶(HDACs)是一类作用于组蛋白以去除乙酰基从而调节染色质状态的酶。HDACs不仅作用于组蛋白,还作用于细胞周期、信号转导、细胞凋亡等细胞过程中的关键非组蛋白。“经典”HDACs已被证明是抗癌药物设计和开发的有前景的靶点。然而,HDAC抑制剂对HDAC亚型的选择性仍然是该领域当前研究的动力。在此,我们通过序列比对和结构叠加、催化通道提取以及鉴定HDAC催化中涉及的关键残基,对I类HDACs和HDAC6进行了探索。基于已知HDAC抑制剂的一般药效团特征,我们通过对从Otava数据库检索的分子片段库进行基于结构的虚拟筛选所确定的片段命中物进行骨架跃迁,开发了一个化合物库。分子对接分析表明,这些化合物中有五种对HDACs 1和2具有增强的效力和选择性。此外,它们预测的吸收、分布、代谢、排泄和毒性(ADMET)特性与类药物化合物的特性一致。通过进一步基于模型和实验的研究,我们相信这些发现可能会提供具有更高选择性的潜在HDAC抑制剂。