Computational Analysis of Naringenin as an Antidepressant

Abstract

Objective: This works aims at analyzing the potential of Naringenin (NAR) as an antidepressant drug by computational methods.
 Methods: The database Protein Data Bank and PubChem were used to retrieve the three-dimensional structures of the protein and the compound. The software Discovery Studio was used to study the interactions between the protein and the ligand.
 Results: NAR, one of the flavanone, which has strong anti-inflammatory and antioxidant activities, is studied for its antidepressant and neuroprotective effects through in silico approach. Interaction study and pharmacophore analysis using Discovery Studio show that the molecule NAR interacts with the protein at different sites. The interaction has a maximum dock score at position B.
 Conclusion: The compound NAR shows to have antidepressant quality from the computational study. The docking studies show promising result that NAR can be explored further as a potential drug.