Computation-based experimentation: Identification of piperazine containing antidepressants.

Depression, a common mental disorder, is one of the major contributors to the overall global burden with more than 264 million individuals affected worldwide. Monoamine oxidase inhibitors (MAOIs) have well-known efficacy for treating depression and other related disorders. Herein we report the implementation of extensive in-silico calculations to predict the mono-amine inhibitory potential of an in-house library of piperazine-based compounds. In this connection, a multistep virtual screening protocol based on pharmacophore modeling, molecular docking and Quantitative Structure-Activity Relationship (QSAR) was carried out by MOE. Further, to assess its ability to cross the blood brain barrier, ADME properties of the compounds were predicted. Compounds predicted the highest enzyme inhibition by QSAR was synthesized for experimental validation. Both the synthesized compounds (I15 and I21) presented good strength against Monoamine Oxidase in in vitro enzyme inhibitory activity.