Ezeokonkwo Mercy A, Ogbonna Onyinyechi N, Okafor Sunday N, Godwin-Nwakwasi Evelyn U, Ibeanu Fidelia N, Okoro Uchechukwu C
Department of Pure and Industrial Chemistry, University of Nigeria, Nsukka, Nigeria.
Department of Chemistry, Evangel University, Akaeze, Nigeria.
Front Chem. 2017 Nov 28;5:107. doi: 10.3389/fchem.2017.00107. eCollection 2017.
The reaction of diaza-5H-benzo[a]phenoxazin-5-one and 5H-benzo[a]phenoxazin-5-one with various phenols catalyzed by Pd/t-BuXPhos/KPO system gave previously unknown ether derivatives ( and ) in good yields. UV-visible, FTIR, and H NMR data were used to confirm structures of the synthesized compounds. The parent compounds and the derivatives were screened for their drug-likeness and binding affinities to the microbial targets through molecular docking. Molinspiration software and AutoDock were used for the drug-likeness and docking studies, respectively. All the synthesized compounds showed strong drug-likeness. They also showed excellent binding affinities with glucosamine-6-phosphate synthase (2VF5), AmpC beta-lactamase (1KE4), and Lanosterol-14α-demethylase (3JUV), with compound 7e having the highest binding energies -9.5, -9.3, and -9.3 kcal/mol, respectively. These were found to be higher than the binding energies of the standard drugs. The binding energies of ciprofloxacin with 2VF5 and 1KE4 were -7.8 and -7.5 kcal/mol, respectively, while that of ketoconazole with 3JUV was -8.6 kcal/mol. The study showed that the synthesized compounds have multi-target inhibitory effects and can be very useful in multi-drug resistance cases. A 2D quantitative structural activity relationship (QSAR) model against target Glucosamine-6-phosphate synthase (2VF5) was developed using partial least squares regression (PLS) with good internal prediction ( = 0.7400) and external prediction (_ predicted = 0.5475) via Molecular Operating Environment (2014).
在Pd/t-BuXPhos/KPO体系催化下,二氮杂-5H-苯并[a]吩恶嗪-5-酮和5H-苯并[a]吩恶嗪-5-酮与各种酚类反应,以良好产率得到了此前未知的醚衍生物(和)。利用紫外可见光谱、傅里叶变换红外光谱和氢核磁共振数据确认了合成化合物的结构。通过分子对接对母体化合物及其衍生物进行类药性筛选以及它们与微生物靶点的结合亲和力研究。分别使用Molinspiration软件和AutoDock进行类药性和对接研究。所有合成化合物均表现出很强的类药性。它们还与6-磷酸葡糖胺合酶(2VF5)、AmpCβ-内酰胺酶(1KE4)和羊毛甾醇-14α-脱甲基酶(3JUV)表现出优异的结合亲和力,化合物7e的结合能分别为-9.5、-9.3和-9.3 kcal/mol。发现这些结合能高于标准药物的结合能。环丙沙星与2VF5和1KE4的结合能分别为-7.8和-7.5 kcal/mol,而酮康唑与3JUV的结合能为-8.6 kcal/mol。该研究表明,合成化合物具有多靶点抑制作用,在多药耐药情况下可能非常有用。使用偏最小二乘回归(PLS)通过分子操作环境(2014)建立了针对靶点6-磷酸葡糖胺合酶(2VF5)的二维定量构效关系(QSAR)模型,内部预测良好(=0.7400),外部预测(预测=0.5475)。