Exploration of new scaffolds as potential MAO-A inhibitors using pharmacophore and 3D-QSAR based in silico screening

Monoamine oxidase-A (MAO-A) inhibitors are of particular importance in the treatment of depressive disorders. Herein described is pharmacophore generation and atom-based 3D-QSAR analysis of previously reported pyrrole based MAO-A inhibitors in order to get insight into their structural requirements responsible for high affinity. The best pharmacophore model generated consisted of four features DHHR: a hydrogen bond donor (D), two hydrophobic groups (H) and an aromatic ring (R). Based on model generated, a statistically valid 3D-QSAR with good predictability was developed. Derived pharmacophore was used as a query to search Zinc 'clean drug-like' database. Hits retrieved were passed progressively through filters like fitness score, predicted activity and docking scores. The survived hits present new scaffolds with a potential for MAO-A inhibition.