3D-QSAR, molecular docking and ADME studies on indole analogues reveal antidepressant activity through monoamine oxidase-A inhibition.

Monoamine oxidase (MAO) enzymes over see 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 have been developed by applying the partial least squares regression algorithm that exhibit 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 are used to generate library of 1853 indole derivatives. Library is evaluated and has resulted in the identification of 30 indole derivatives with high docking scores (−9.978 to −7.136) in comparison to the antidepressant standard drug Isocarboxazid (−7.125). Further, these compounds have been 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. [ABSTRACT FROM AUTHOR]