Suppr超能文献

揭示有效 HDAC8 抑制的关键结构特征:使用定量读片结构-活性关系(q-RASAR)和药效团建模的综合研究。

Unveiling critical structural features for effective HDAC8 inhibition: a comprehensive study using quantitative read-across structure-activity relationship (q-RASAR) and pharmacophore modeling.

机构信息

Laboratory of Drug Design and Discovery, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, 700032, India.

Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research (NIPER), Kolkata, West Bengal, 700054, India.

出版信息

Mol Divers. 2024 Aug;28(4):2197-2215. doi: 10.1007/s11030-024-10903-y. Epub 2024 Jun 13.

Abstract

Histone deacetylases constitute a group of enzymes that participate in several biological processes. Notably, inhibiting HDAC8 has become a therapeutic strategy for various diseases. The current inhibitors for HDAC8 lack selectivity and target multiple HDACs. Consequently, there is a growing recognition of the need for selective HDAC8 inhibitors to enhance the effectiveness of therapeutic interventions. In our current study, we have utilized a multi-faceted approach, including Quantitative Structure-Activity Relationship (QSAR) combined with Quantitative Read-Across Structure-Activity Relationship (q-RASAR) modeling, pharmacophore mapping, molecular docking, and molecular dynamics (MD) simulations. The developed q-RASAR model has a high statistical significance and predictive ability (Q:0.778, Q:0.775). The contributions of important descriptors are discussed in detail to gain insight into the crucial structural features in HDAC8 inhibition. The best pharmacophore hypothesis exhibits a high regression coefficient (0.969) and a low root mean square deviation (0.944), highlighting the importance of correctly orienting hydrogen bond acceptor (HBA), ring aromatic (RA), and zinc-binding group (ZBG) features in designing potent HDAC8 inhibitors. To confirm the results of q-RASAR and pharmacophore mapping, molecular docking analysis of the five potent compounds (44, 54, 82, 102, and 118) was performed to gain further insights into these structural features crucial for interaction with the HDAC8 enzyme. Lastly, MD simulation studies of the most active compound (54, mapped correctly with the pharmacophore hypothesis) and the least active compound (34, mapped poorly with the pharmacophore hypothesis) were carried out to validate the observations of the studies above. This study not only refines our understanding of essential structural features for HDAC8 inhibition but also provides a robust framework for the rational design of novel selective HDAC8 inhibitors which may offer insights to medicinal chemists and researchers engaged in the development of HDAC8-targeted therapeutics.

摘要

组蛋白去乙酰化酶构成了一组参与多种生物过程的酶。值得注意的是,抑制 HDAC8 已成为治疗多种疾病的一种治疗策略。目前的 HDAC8 抑制剂缺乏选择性,靶向多个 HDAC。因此,人们越来越认识到需要选择性 HDAC8 抑制剂来增强治疗干预的效果。在我们目前的研究中,我们采用了多种方法,包括定量构效关系(QSAR)与定量读交叉构效关系(q-RASAR)建模、药效团映射、分子对接和分子动力学(MD)模拟。开发的 q-RASAR 模型具有较高的统计意义和预测能力(Q:0.778,Q:0.775)。详细讨论了重要描述符的贡献,以深入了解 HDAC8 抑制中的关键结构特征。最佳药效团假说表现出较高的回归系数(0.969)和较低的均方根偏差(0.944),突出了正确定向氢键受体(HBA)、环芳香(RA)和锌结合基团(ZBG)特征在设计有效的 HDAC8 抑制剂中的重要性。为了确认 q-RASAR 和药效团映射的结果,对五个有效化合物(44、54、82、102 和 118)进行了分子对接分析,以进一步了解这些与 HDAC8 酶相互作用的关键结构特征。最后,对最活跃化合物(54,与药效团假说正确匹配)和最不活跃化合物(34,与药效团假说匹配不佳)进行了 MD 模拟研究,以验证上述研究的观察结果。这项研究不仅深化了我们对 HDAC8 抑制的基本结构特征的理解,还为新型选择性 HDAC8 抑制剂的合理设计提供了一个强大的框架,这可能为从事 HDAC8 靶向治疗开发的药物化学家提供了思路和研究人员。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验