Abstract

The purpose of the current study was to explore the virtual library for the screening against Monoamine oxidase (MAO) isoforms. An in-house library of natural based ligands was docked within the active sites of MAO isoforms and their in vitro study was also conducted. The prime objective of the current study was to screen and validate the natural-based derivatives for MAO inhibitory action with the least adverse effects and get molecular aspects about further structural modifications on the most active leads. The importance of MAOs in controlling the activity of the central nervous system has been extensively studied. Our goal in this work is to identify a prospective natural lead molecule that has a stronger affinity for the MAO enzyme in order to produce a more effective natural candidate for a neurological agent. In order to get insight into how different categories of natural compounds interact with the targeted protein, we virtually screened the numerous natural compound categories in the current study. Rhamnetin, quercetin, piperine, eugenol, and umbelliferone showed the highest dock scores in the case of MAO-B, with scores of -10.57, -9.938, -9.445, and 7.821, respectively. For MAO-A, umbelliferone, curcumin, caffeic acid, and quercetin, the corresponding dock scores were -8.001, -7.941, -7.357, and -6.658. Additionally, an in vitro MAO inhibitory experiment was utilized to assess the top-ranked compounds with the best docking scores. The most potent Human Monoamine oxidase (hMAO-A) inhibitor, with an IC50 of 10.98±0.006 M and a selectivity index (SI) of 0.607, was discovered to be the compound umbelliferone. Rhamnetin, the lead chemical, has demonstrated hMAO-B activity with a value of 10.32±0.044 M (SI value of 3.096). These natural potential ligands have been found remarkable to the standard compounds against MAO-A and MAO-B, and they could be used as a lead chemical in the development of novel therapeutic candidates. The in silico screening results and in vitro hMAO inhibitory efficacy exhibited strong correlations.

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