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首页> 外文期刊>Journal of receptor and signal transduction research >Pharmacophore modeling, 3D-QSAR, and in silico ADME prediction of N-pyridyl and pyrimidine benzamides as potent antiepileptic agents
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Pharmacophore modeling, 3D-QSAR, and in silico ADME prediction of N-pyridyl and pyrimidine benzamides as potent antiepileptic agents

机译:药镜造型,3D-QSAR,以及硅氧吡啶和嘧啶苯甲酰胺的二氧化硅和嘧啶苯甲酰胺作为有效的抗癫痫药剂

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Biological mechanism attributing mutations in KCNQ2/Q3 results in benign familial neonatal epilepsy (BFNE), a rare form of epilepsy and thus neglected. It offers a potential target for antiepileptic drug discovery. In the present work, a pharmacophore-based 3D-QSAR model was generated for a series of N-pyridyl and pyrimidine benzamides possessing KCNQ2/Q3 opening activity. The pharmacophore model generated contains one hydrogen bond donor (D), one hydrophobic (H), and two aromatic rings (R). They are the crucial molecular write-up detailing predicted binding efficacy of high affinity and low affinity ligands for KCNQ2/Q3 opening activity. Furthermore, it has been validated by using a biological correlation between pharmacophore hypothesis-based 3D-QSAR variables and functional fingerprints of openers responsible for the receptor binding and also by docking of these benzamides into the validated homology model. Excellent statistical computational tools of QSAR model such as good correlation coefficient (R-2>0.80), higher F value (F>39), and excellent predictive power (Q(2)>0.7) with low standard deviation (SD <0.3) strongly suggest that the developed model could be used for prediction of antiepileptic activity of newer analogs. A preliminary pharmacokinetic profile of these derivatives was also performed on the basis of QikProp predictions.
机译:KCNQ2/Q3突变的生物学机制导致良性家族性新生儿癫痫(BFNE),这是一种罕见的癫痫形式,因此被忽视。它为抗癫痫药物的发现提供了一个潜在的靶点。在目前的工作中,一系列具有KCNQ2/Q3开放活性的N-吡啶和嘧啶苯甲酰胺生成了基于药效团的3D-QSAR模型。生成的药效团模型包含一个氢键供体(D)、一个疏水性供体(H)和两个芳香环(R)。它们是关键的分子记录,详细说明了高亲和力和低亲和力配体对KCNQ2/Q3开放活性的预测结合效率。此外,通过使用基于药效团假设的3D-QSAR变量与负责受体结合的开放剂的功能指纹之间的生物学相关性,以及通过将这些苯甲酰胺对接到经验证的同源性模型中,对其进行了验证。QSAR模型优良的统计计算工具,如良好的相关系数(R-2>0.80),较高的F值(F>39),以及良好的预测能力(Q(2)>0.7)和较低的标准差(SD<0.3),强烈表明所开发的模型可用于预测新的类似物的抗癫痫活性。根据QikProp的预测,还对这些衍生物进行了初步的药代动力学分析。

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