3D-QSAR, Molecular Docking and ADME Studies on Indole Analogues Reveal Antidepressant Activity Through Monoamine Oxidase-A Inhibition

IF 0.4 4区 化学 Q4 CHEMISTRY, ORGANIC INDIAN JOURNAL OF CHEMISTRY Pub Date : 2023-10-18 DOI:10.56042/ijc.v62i10.3779
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Abstract

Monoamine oxidase (MAO) enzymes oversee the concentration of neurotransmitters and intracellular amines in the brain and peripheral tissues by catalysing their oxidative deamination and represents a crucial target in drug designing for the management of neurological and psychiatric disorders. Present study is an effort to present an economical fast high throughput screening easy method to identify indole analogues as potent MAO inhibitors, using different computational techniques. CoMSIA field-based 3D-QSAR models were developed by applying the partial least squares regression algorithm that exhibited satisfactory predictive and descriptive capability with statistical parameters R² (0.9557) and Q² (0.8529). Generated model (s) helped in explaining the key descriptors firmly related with MAO inhibitory activity and were used to generate library of 1853 indole derivatives.  Library was evaluated and resulted in the dentification of 30indole derivatives with high docking scores (-9.978 to -7.136) in comparison to the antidepressant standard drug Isocarboxazid (-7.125). Further, these compounds were scrutinized through drug-likeliness profiles and Desmond's molecular dynamics simulations studies for 100 ns.  Further in vitro and in vivo studies on these molecules might provide us with new drug candidate for the treatment of depression with high therapeutic index.
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吲哚类似物的3D-QSAR、分子对接和ADME研究通过单胺氧化酶a抑制揭示抗抑郁活性
单胺氧化酶通过催化神经递质和细胞内胺在大脑和外周组织中的氧化脱胺作用来监督神经递质和细胞内胺的浓度,是神经和精神疾病治疗药物设计中的一个重要靶点。采用偏最小二乘回归算法建立CoMSIA现场3D-QSAR模型,统计参数R²(0.9557)和Q²(0.8529)具有较好的预测和描述能力。对文库进行评估,鉴定出30个吲哚衍生物,与抗抑郁标准药异羧肼(-7.125)相比,对接评分较高(-9.978至-7.136)。此外,这些化合物通过药物可能性谱和Desmond的100 ns分子动力学模拟研究进行了仔细检查。对这些分子的进一步体外和体内研究可能为我们提供治疗指数高的治疗抑郁症的新候选药物。
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