Discovery of MAO-A Inhibitors as Antidepressant Based on Virtual Screening - Xiaopeng, Wei; Zhan, Jin; Fan, Zheqi; Chen, Ying; Jing, Weikai; Zhang, Man; Gan, Chunchun; Yang, Jinrong (Letters in Drug Design & Discovery, 2024)
Aim: Major depression and anxiety have increased significantly worldwide since the 2019 outbreak of COVID-19. The development of highly effective antidepressants with low side effects is attracting researchers. Methods: Monoamine oxidase A (MAO-A) is a key enzyme that catalyzes the metabolism of norepinephrine (NE), dopamine (DA), and serotonin (5-HT), etc. Elevated level of MAO-A would lead to increased metabolism of its substrates, thereby causing a decrease in the levels of these neurotransmitter monoamines in the brain leading to depression. Consequently, inhibition of MAO-A was thought to be an effective strategy, as this would treat the root cause of depression. Results and Discussion: Based on the crystal structure of MAO-A, 4 star-hits, as potential MAO-A inhibitors was screened from the compound libraries with central nervous system (CNS) activity by using various computational techniques. Molecular dynamics simulation was used to verify the stability of the ligand- receptor complexes. Conclusion: Furthermore, the ADMET (absorption, distribution, metabolism, excretion and toxicity properties) of the virtual hits were predicted in order to evaluate their lead-like properties and safety. This work provides ideas for the drugs discovery of antidepressant.
Keywords: virtual screening