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采用计算方法鉴定新型 NAD(P)H 脱氢酶 [醌] 1 拮抗剂。

Identification of novel NAD(P)H dehydrogenase [quinone] 1 antagonist using computational approaches.

机构信息

CAS in Crystallography and Biophysics, University of Madras, Chennai, Tamil Nadu, India.

Department of Biotechnology, Bhupat Jyoti Mehta School of Biosciences, Indian Institute of Technology (IIT) Madras, Chennai, Tamil Nadu, India.

出版信息

J Biomol Struct Dyn. 2020 Feb;38(3):682-696. doi: 10.1080/07391102.2019.1585291. Epub 2019 Mar 22.

Abstract

NAD(P)H: quinone oxidoreductase 1 (NQO1) inhibitors are proved as promising therapeutic agents against cancer. This study is to determine potent NAD(P)H-dependent NQO1 inhibitors with new scaffold. Pharmacophore-based three-dimensional (3D) QSAR model has been built based on 45 NQO1 inhibitors reported in the literature. The structure-function correlation coefficient graph represents the relationship between phase activity and phase predicted activity for training and test sets. A QSAR model statistics shows the excellent correlation of the generated model. Pharmacophore hypothesis (AARR) yielded a statistically significant 3D QSASR model with a correlation coefficient of = 0.99 as well as an excellent predictive power. From the analysis of pharmacophore-based virtual screening using by SPEC database, 4093 hits were obtained and were further filtered using virtual screening filters (HTVS, SP, XP) through structure based molecular docking. Based on glide energy and docking score, seven lead compounds show better binding affinity compared to the co-crystal inhibitor. The results of induced fit docking and prime/MM-GBSA suggest that leads AN-153/J117103 and AT-138/KB09997 binding with the catalytic site. Further, to understanding the stability of identified lead compounds MD simulations were done. The lead AN-153/J117103 showed the strong binding stable of the protein-ligand complex. Also the computed drug likeness reveals potential of this compound to treat cancer. AbbreviationsNQO1NAD(P)H-quinine oxidoreductase 1CPHcommon pharmacophore hypothesisPLSpartial least squireHBDhydrogen bond donorSDstandard deviationXPextra precisionIFDinduced fit dockingMM-GBSAmolecular mechanics generalized born surface areaMDSmolecular dynamics simulationRMSDroot mean square deviationRMSFroot mean square fluctuationRMSEroot mean square errorADMEabsorption distribution metabolism excretionsCommunicated by Ramaswamy H. Sarma.

摘要

NAD(P)H:醌氧化还原酶 1(NQO1)抑制剂被证明是有前途的抗癌治疗药物。本研究旨在确定具有新骨架的强效依赖 NAD(P)H 的 NQO1 抑制剂。基于文献中报道的 45 种 NQO1 抑制剂,建立了基于药效团的三维(3D)QSAR 模型。构效关系相关系数图表示训练集和测试集的相活性与相预测活性之间的关系。QSAR 模型统计数据表明所生成模型具有出色的相关性。药效团假设(AARR)产生了具有统计学意义的 3D QSASR 模型,相关系数为 = 0.99,并且具有出色的预测能力。通过使用 SPEC 数据库进行基于药效团的虚拟筛选分析,得到了 4093 个命中物,并通过结构基于分子对接的虚拟筛选过滤器(HTVS、SP、XP)进一步进行过滤。基于 Glide 能量和对接得分,与共晶抑制剂相比,有 7 种先导化合物表现出更好的结合亲和力。诱导契合对接和 Prime/MM-GBSA 的结果表明,先导化合物 AN-153/J117103 和 AT-138/KB09997 与催化位点结合。此外,为了了解鉴定出的先导化合物的稳定性,进行了 MD 模拟。先导化合物 AN-153/J117103 显示出与蛋白-配体复合物的强结合稳定性。此外,计算出的药物相似性表明该化合物具有治疗癌症的潜力。缩写NQO1NAD(P)H-醌氧化还原酶 1CPH常见药效团假设PLS部分最小平方HBD氢键供体SD标准偏差XP额外精度IFD诱导契合对接MM-GBSAmolecular mechanics generalized born surface areaMDSmolecular dynamics simulationRMSD均方根偏差RMSF均方根波动RMSE均方根误差ADME吸收分布代谢排泄由 Ramaswamy H. Sarma 交流。

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