Suppr超能文献

通过基于结构的虚拟筛选和体外测定鉴定和评价潜在的 c-Jun N-末端激酶 3 抑制剂及其神经保护作用。

Identification and neuroprotective evaluation of a potential c-Jun N-terminal kinase 3 inhibitor through structure-based virtual screening and in-vitro assay.

机构信息

Department of Pharmacology, PSG College of Pharmacy, Coimbatore, Tamilnadu, India.

出版信息

J Comput Aided Mol Des. 2020 Jun;34(6):671-682. doi: 10.1007/s10822-020-00297-y. Epub 2020 Feb 10.

Abstract

The c-Jun N-terminal kinase 3 (JNK3) signaling cascade is activated during cerebral ischemia leading to neuronal damage. The present study was carried out to identify and evaluate novel JNK3 inhibitors using in-silico and in-vitro approach. A total of 380 JNK3 inhibitors belonging to different organic groups was collected from the previously reported literature. These molecules were used to generate a pharmacophore model. This model was used to screen a chemical database (SPECS) to identify newer molecules with similar chemical features. The top 1000 hits molecules were then docked against the JNK3 enzyme coordinate following GLIDE rigid receptor docking (RRD) protocol. Best posed molecules of RRD were used during induced-fit docking (IFD), allowing receptor flexibility. Other computational predictions such as binding free energy, electronic configuration and ADME/tox were also calculated. Inferences from the best pharmacophore model suggested that, in order to have specific JNK3 inhibitory activity, the molecules must possess one H-bond donor, two hydrophobic and two ring features. Docking studies suggested that the main interaction between lead molecules and JNK3 enzyme consisted of hydrogen bond interaction with methionine 149 of the hinge region. It was also observed that the molecule with better MM-GBSA dG binding free energy, had greater correlation with JNK3 inhibition. Lead molecule (AJ-292-42151532) with the highest binding free energy (dG = 106.8 Kcal/mol) showed better efficacy than the SP600125 (reference JNK3 inhibitor) during cell-free JNK3 kinase assay (IC50 = 58.17 nM) and cell-based neuroprotective assay (EC50 = 7.5 µM).

摘要

c-Jun N-末端激酶 3(JNK3)信号级联在脑缺血期间被激活,导致神经元损伤。本研究旨在使用计算机和体外方法鉴定和评估新型 JNK3 抑制剂。从以前的文献中收集了总共 380 种属于不同有机基团的 JNK3 抑制剂。这些分子被用于生成药效团模型。该模型用于筛选化学数据库(SPECS),以识别具有相似化学特征的新型分子。然后,根据 GLIDE 刚性受体对接(RRD)方案,对前 1000 个命中分子与 JNK3 酶坐标进行对接。RRD 的最佳构象分子用于诱导拟合对接(IFD),允许受体灵活性。还计算了其他计算预测,如结合自由能、电子构型和 ADME/tox。最佳药效团模型的推论表明,为了具有特定的 JNK3 抑制活性,分子必须具有一个氢键供体、两个疏水性和两个环特征。对接研究表明,先导分子与 JNK3 酶之间的主要相互作用包括与铰链区域的蛋氨酸 149 的氢键相互作用。还观察到,具有更好 MM-GBSA dG 结合自由能的分子与 JNK3 抑制的相关性更大。具有最高结合自由能(dG = 106.8 Kcal/mol)的先导分子(AJ-292-42151532)在无细胞 JNK3 激酶测定(IC50 = 58.17 nM)和基于细胞的神经保护测定(EC50 = 7.5 µM)中显示出比 SP600125(参考 JNK3 抑制剂)更好的疗效。

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