Insights into in silico analysis to explore the multitarget antidepressant role of Camellia sinensis.

Abstract

Depression is the fourth leading cause of death due to suicides every year according to WHO. Various adverse effects are associated with many of the available antidepressants due to the irreversible nature of these drugs. So, it is worthwhile to explore the natural phytoconstituents as an alternative therapy for the treatment of depression-dependent symptoms. Computational chemistry provides a cost-effective method to explore or develop new therapies for various diseases through in silico studies. In this study, multitargeting antidepressant potential of Camellia sinensis is explored via docking and binding interaction studies with monoamine oxidase-A enzyme, serotonin, and dopamine receptors involved in depression as targets. All the selected phytoconstituents were evaluated for drug-likeliness properties using Swiss ADME. Among all the selected phytoconstituents, Theasinensin, and Theaflavin-3-gallate were found to have best affinities with all the selected targets under investigation and can be considered as promising lead molecules for the development of novel antidepressants. Molecular dynamics simulations assessed the binding affinity of four compounds to Human Monoamine Oxidase A. All compounds showed potential, with Theaflavin-3-gallate and Theasinesin displaying the strongest binding. This suggests their potential for modulating enzyme activity and potential relevance in depression treatment.