Pharmacophore modeling coupled with molecular dynamic simulation approach to identify new leads for meprin-β metalloprotease

Abstract

Human meprin beta metalloprotease, a small subgroup of the astacin family, is a potent drug target for the treatment of several disorders such as fibrosis, neurodegenerative disease in particular Alzheimer and inflammatory bowel diseases. In this study, a ligand-based pharmacophore approach has been used for the selection of potentially active compounds to understand the inhibitory activities of meprin-β by using the sulfonamide scaffold based inhibitors. Using this dataset, a pharmacophore model (Hypo1) was selected on the basis of a highest correlation coefficient (0.959), lowest total cost (105.89) and lowest root mean square deviation (1.31 Å) values. All the pharmacophore hypotheses generated from the candidate inhibitors comprised four features: two hydrogen-bond acceptor, one hydrogen-bond donor and one zinc binder feature. The best validated pharmacophore model (Hypo1) was used for virtual screening of compounds from several databases. The selective hit compounds were filtered by drug likeness property, acceptable ADMET profile, molecular docking and DFT study. Molecular dynamic simulations with the final 10 hit compounds revealed that a large number of non-covalent interactions were formed with the active site and specificity sub-pockets of the meprin beta metalloprotease. This study assists in the development of the new lead molecules as well as gives a better understanding of their interaction with meprin-β.

Keywords: Density functional theory; Hit lead; Hotspot; Inhibitors; MD simulation; Meprin-β; Pharmacophore model; Virtual screening.