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Updated: Dec 25, 2025

Network Pharmacology and Validation of the Antidepressant Mechanisms of Qiangzhifang in a Chronic Restraint Stress-induced Depression Rat Model
Published on: June 6, 2025
Molecular docking utilising the OliveNet™ library reveals novel phenolic compounds which may potentially target key
Eleni Pitsillou1, Julia Liang2, Andrew Hung3
1Epigenomic Medicine, Department of Diabetes, Central Clinical School, Monash University, Prahran, VIC, 3004, Australia; Department of Microbiology and Immunology (Pathology), The University of Melbourne, Parkville, VIC, 3052, Australia.
Abstract:
The antidepressant medications that are currently prescribed to patients suffering from major depressive disorder (MDD) have limitations and as a result, there is an urgent need to increase the options that are available. A number of studies have found that natural polyphenols have neuroprotective properties and there is evidence to suggest that they modulate neurotransmitter systems. There are more than 200 phenolic compounds that have been identified in Olea europaea, many of which have not yet been investigated for their potential biological effects. In this study, in silico methods were used to screen the phenolic library from the OliveNet™ database and identify novel lead compounds for proteins implicated in the pathophysiology of MDD. The molecular docking results revealed that the monoamine oxidase enzyme isoforms (MAO-A/MAO-B) had binding specificities for certain phenolic subclasses. The lead ligands that were identified from these subclasses were positioned near the flavin adenine dinucleotide (FAD) cofactor, interacting in a similar manner as known inhibitors. In addition to the MAO enzymes, several phenolic compounds were docked to neurotransmitter transporters and postsynaptic receptors, as well as proteins involved in neuroinflammation, oxidative stress and the endocannabinoid system. Based on the binding affinity, position, orientation and interactions of the lead phenolic compounds identified in this study, it is predicted that they may have antidepressant properties. The results should be validated further using molecular dynamics (MD) simulations, as well as in vivo and in vitro techniques.
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