Abstract

The current treatment of depression involves antidepressant synthetic drugs that have a variety of side effects. In searching for alternatives, natural compounds could represent a solution, as many studies reported that such compounds modulate the nervous system and exhibit antidepressant effects. We used bioinformatics methods to predict the antidepressant effect of ten natural compounds with neuroleptic activity, reported in the literature. For all compounds we computed their drug-likeness, absorption, distribution, metabolism, excretion (ADME), and toxicity profiles. Their antidepressant and neuroleptic activities were predicted by 3D-ALMOND-QSAR models built by considering three important targets, namely serotonin transporter (SERT), 5-hydroxytryptamine receptor 1A (5-HT1A), and dopamine D2 receptor. For our QSAR models we have used the following molecular descriptors: hydrophobicity, electrostatic, and hydrogen bond donor/acceptor. Our results showed that all compounds present drug-likeness features as well as promising ADME features and no toxicity. Most compounds appear to modulate SERT, and fewer appear as ligands for 5-HT1A and D2 receptors. From our prediction, linalyl acetate appears as the only ligand for all three targets, neryl acetate appears as a ligand for SERT and D2 receptors, while 1,8-cineole appears as a ligand for 5-HT1A and D2 receptors.

Highlights

  • Depression is a common mental disorder, 264 million persons being affected worldwide, according to the WHO

  • The present study looked at ten natural compounds, including resveratrol, quercetin, limonene, sabinene, 1,8-cineole, chamazulene, linalyl acetate, germacrene D, nerol, and neryl acetate, based on their potential antidepressant effects identified in the literature, as described in the Section 1

  • The types of interactions that we identified are consistent with the molecular properties relevant for target binding that we identified using our quantitative structureactivity relationship (QSAR) models

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Summary

Introduction

Depression is a common mental disorder, 264 million persons being affected worldwide, according to the WHO. A severe consequence of depression is suicide, and near. 800,000 people commit suicide every year [1]. Depression can be treated by psychotherapy and medication involving antidepressant and antipsychotic drugs. These drugs have beneficial effects in the management of depression, their usage could lead to severe side effects like hepatotoxicity, weight gain, sexual dysfunction, cardiovascular disorders, central nervous system disturbances, etc. Natural compounds may represent a viable alternative in depression treatment with possibly fewer side effects, supporting their administration even in patients with comorbidities [3,4]. We used an in silico approach to predict the antidepressant activity of Pharmaceutics 2021, 13, 1449.

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