A computational approach to find alternative drugs for managing depression

Abstract

Depression is the most prominent disorder in the field of neuropsychiatry affecting more than 300 million people worldwide, according to Global Burden of Disease report, 2020. Frequent occurrences of depressive episodes among the treated patients suggests that clinically used antidepressants have become resistant. As searching for a new drug can be time consuming and costly, an in-silico based study was conducted to repurpose approved drugs to be used in depression. Pathogenesis of depression shows that human monoamine oxidase A protein (MAOA) plays a key role in degrading notable neurotransmitters and so this protein was studied. Through molecular docking, binding affinity of around hundreds of drugs and some natural small molecules with the protein was evaluated. Furthermore, superimposition and protein-ligand interactions were visualized and assessed. It was found that Glimepiride, an anti-diabetic agent from the synthetic drugs and Curcumin from the natural small molecules have possible antidepressant properties.