In-silico identification and optimization of MMP-9 inhibitors for cerebral ischemia using structure based virtual screening, MD simulation, and binding free energy calculations

Abstract

Cerebral ischemia is a leading cause of disability and mortality due to the limited therapies of neuroprotection. Matrix metalloproteinase-9 (MMP-9) plays a major role in cerebral ischemia as it breaks down the components of extracellular matrix, which maintains the tissue structure and integrity, making MMP-9 a potential target for therapeutic intervention. The existing inhibitors show poor pharmacokinetics so in this study, we have designed a comprehensive pipeline which combines structure-based pharmacophore modelling, and MD simulation to identify selective MMP-9 inhibitors. We performed virtual screening and then hits were processed by molecular docking, ADMET analysis. Our results identify hit compound CHEMBL3990662 whose stability with MMP-9 was confirmed by MD Simulation. Further the binding free energy was calculated by employing MMGBSA and MMPBSA methods. This study highlights the potential of computational pipeline in the development of MMP-9 inhibitors.