Discovery of potent inhibitor for matrix metalloproteinase-9 by pharmacophore based modeling and dynamics simulation studies

• Ligand based pharmacophore model for MMP-9 has been developed.
• This pharmacophore model picked up some natural MMP-9 inhibitors.
• Docking and MD analysis were used to find the potent hit for MMP-9.
• Inhibition of MMP-9 in the presence of inhibitor was detected by in vitro studies.

Matrix metalloproteinase-9 (MMP-9) is an attractive target for anticancer therapy. In the present study ligand based pharmacophore modeling was performed to elucidate the structural elements for a diverse class of MMP-9 inhibitors. The pharmacophore model was validated through Güner-Henry (GH) scoring method. The final pharmacophore model consisted of three hydrogen bond acceptors (HBA), and two ring aromatic regions (RA). This model was utilized to screen the natural compound database to seek novel compounds as MMP-9 inhibitors. The identified hits were validated using molecular docking and molecular dynamics simulation studies. Finally, one compound named Hinokiflavone from Juniperus communis had high binding free energy of −26.54 kJ/mol compared with the known inhibitors of MMP-9. Cytotoxicity for hinokiflavone was evaluated by MTT assay. Inhibition of MMP-9 in the presence of hinokiflavone was detected by gelatin zymography and gelatinolytic inhibition assay. Results revealed that the natural compounds derived based on the developed pharmacophore model would be useful for further design and development of MMP-9 inhibitors.

This study reports the natural inhibitor for an attractive target MMP-9 using in silico and in vitro techniques. Computational strategies like pharmacophore modeling and molecular dynamics simulation studies picked one natural compound named hinokiflavone which showed high binding free energy compared with the known inhibitors of MMP-9. Inhibition of MMP-9 in the presence of hinokiflavone was detected by gelatin zymography and colorimetric gelatinolytic assay.Figure optionsDownload high-quality image (166 K)Download as PowerPoint slide