bioRxivNeurosciencePreprint
Exploring the Antidepressant Effects of Saffron Constituents: Targeting Dopamine and Serotonin Transport Proteins, and Monoamine Oxidase-B: An in Silico Evidence-Based Study
Brijendra Bahadur SinghiD, Deepak sharma, Vyas Shingatgeri, Vinay Lomash
Abstract
Globally, about 264 million individuals across all age groups are impacted by depression, a prevalent central nervous system (CNS) condition. Chronic and enduring depression might result in significant health consequences. Numerous pharmaceutical antidepressants exist for the management of mild to severe depression, largely functioning by modifying neurotransmitter levels in the brain. Nevertheless, these drugs frequently induce a variety of side effects, such as insomnia, constipation, exhaustion, drowsiness, and anxiety. Saffron (Crocus sativus L.) is widely acknowledged as a natural antidepressant with little adverse effects. This study investigated the potential antidepressant mechanisms of saffrons principal bioactive compounds safranal, crocin, and picrocrocin via molecular docking against critical target proteins associated with depression, namely the dopamine transporter (DAT), serotonin transporter (SERT), and monoamine oxidase B (MAO-B). Molecular docking was conducted with AutoDock 4.2 to assess the binding affinity and interaction energy of these drugs with the target proteins. Furthermore, Discovery Studio facilitated the viewing and study of both interacting and non-interacting residues at the docking sites, juxtaposing these interactions with those of established inhibitors in crystal structures. The permeability of the blood-brain barrier (BBB), pharmacokinetic characteristics, and toxicity profiles of saffron components were evaluated using SWISS ADME, DataWarrior, and Osiris Molecular Property Explorer. Among the evaluated elements, safranal had the greatest potential as a competitive inhibitor of the dopamine transporter, according to its notable blood-brain barrier permeability, robust binding affinity, and analogous interaction residues in comparison to nortriptyline, a recognized inhibitor. Our findings indicate that safranal may be a viable natural alternative to traditional antidepressants, with minimized adverse effects.
- research focus: drug response / drug discovery
- approach: statistical model
- approach: machine learning (classical)
- Citations
- 0
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Uncovering the Elusive Structures and Mechanisms of Prevalent Antidepressants
J. Lin, G. Bu, … T. Gonen·Advanced TherapeuticsPeer-reviewed·Sep 1, 2024
- In silico analysis of Bacopa monnieri (L.) Wettst. compounds for drug development against Neurodegenerative Disorders
S. Sangeet, A. Khan, … P. K. Hui·bioRxiv·Mar 30, 2022
- Structure-based Discovery of Conformationally Selective Inhibitors of the Serotonin Transporter
I. Singh, A. Seth, … G. Rudnick·bioRxiv·Jun 13, 2022
- Exploring the Therapeutic Potential of Cannabis Constituents in Parkinson's Disease: Insights from Molecular Docking Studies
Moawaz Aziz, Hafsa Rehman, … Muhammad Arsalan Ali Sajid·bioRxiv·Nov 11, 2023
- Pharmacodynamic profiles inform systematization, efficacy and whole-brain drug distribution profiles in 18 antidepressants
Benjamin Hänisch, Sofie Louise Valk·bioRxiv·Apr 29, 2026
- Identifying potential dopamine receptor D2 antagonist from Rauwolfia serpentina An in-silico virtual screening approach
Souvik Chakraborty, Sushmita Bhowmick, Tarasankar Maiti·bioRxiv·Oct 10, 2024