Computation-based experimentation: Identification of piperazine containing antidepressants

Saman Usmani; Nousheen Mushtaq; Zaheer Ul-Haq; Laila Anwer; Ahsaan Ahmed; Saira Asghar; Rabya Munawar

doi:10.36721/PJPS.2021.34.3.SUP.1089-1096.1

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Computation-based experimentation: Identification of piperazine containing antidepressants

Author(s)

Saman Usmani Department of Pharmaceutical Chemistry, Faculty of Pharmacy & Pharmaceutical Sciences, University of Karachi, Pakistan; Institute of Pharmaceutical Sciences (IPS), Jinnah Sindh Medical University (JSMU), Pakistan

Nousheen Mushtaq Department of Pharmaceutical Chemistry, Faculty of Pharmacy & Pharmaceutical Sciences, University of Karachi,Pakistan

Zaheer Ul-Haq Dr. Panjwani Center for Molecular Medicine & Drug Research (PCMD), International Center for Chemical & Biological Sciences (ICCBS), University of Karachi,Karachi,Pakistan

Laila Anwer Department of Pharmacology, Faculty of Pharmacy, Hamdard University,Karachi,Pakistan

Ahsaan Ahmed Department of Pharmaceutical Chemistry, Faculty of Pharmacy & Pharmaceutical Sciences, University of Karachi, Pakistan; Institute of Pharmaceutical Sciences (IPS), Jinnah Sindh Medical University (JSMU), Pakistan

Saira Asghar Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Hamdard niversity,Karachi,Pakistan

Rabya Munawar Department of Pharmaceutical Chemistry, Dow College of Pharmacy, Dow University of Health Sciences,Karachi,Pakistan

Abstract

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.

Publication Details

Page(s) 1089-1096

DOI 10.36721/PJPS.2021.34.3.SUP.1089-1096.1

Published Journal: Pakistan Journal of Pharmaceutical Sciences, Volume: 34, Issue: SUP3, Year: 2021

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Keywords

MAO-A, MOE, pharmacophore screening, 2D-QSAR, molecular docking, In-silico, Antidepressants, piperazine derivatives

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