title: Identification of novel selective MMP-9 inhibitors as potential anti-metastatic lead using structure-based hierarchical virtual screening and molecular dynamics simulation.
abstract: MMP-9 is an attractive target for the development of new anticancer drugs. In the current study, pharmacophore modeling was employed using two highly active and selective gelatinase inhibitors obtained from two X-ray crystal structures (PDB IDs: and ) to identify novel selective MMP-9 inhibitors. The derived model was refined manually and also validated by the GH scoring method. The refined pharmacophore model, ADRR, was able to retrieve 86% of actives with a GH score of 0.774, indicating that the model was capable of retrieving the active MMP-9 inhibitors. ADRR was used to screen 2 838 166 unique structures. Hit filtration was carried out using a fitness score >1.5 and drug-likeness properties. Hierarchical clustering generates 33 clusters based on diversity. A total of 33 molecules were obtained and these molecules were taken for cross-docking studies with 5 subtype MMPs. Among 33 tested, 2 molecules, P10A-0000088030 (Lig-1) and P10A-0001383812 (Lig-2), were found to have the highest docking scores (-8.59 kcal mol(-1) and -8.27 kcal mol(-1)) towards MMP-9 compared with the other MMPs. Further MM-GBSA analysis was performed for two hits with 5 subtype MMPs to reveal the essential features that contribute to selectivity. The results showed that van der Waals contributions play a central role in determining the selectivity of MMP-9 inhibitors. Molecular dynamics studies were carried out for total time of 330 ns to assess the stability of ligands at the active site. MD analysis showed that binding of Lig-1 with MMP-9 is stable compared to that with Lig-2. Hence, we suggest the Lig-1 compound as a good lead in designing novel potent inhibitors of MMP-9.
authors.affiliation: Department of Pharmacy, University of Kwazulu Natal, Durban, South Africa.
authors.forename: Sukesh
authors.initials: S
authors.lastname: Kalva
authors.affiliation: Department of Pharmacy, University of Kwazulu Natal, Durban, South Africa.
authors.forename: Nikhil
authors.initials: N
authors.lastname: Agrawal
authors.affiliation: Department of Pharmacy, University of Kwazulu Natal, Durban, South Africa.
authors.forename: Adam A
authors.initials: AA
authors.lastname: Skelton
authors.affiliation: Department of Bioinformatics, School of Bioengineering, SRM University, Kancheepuram, Tamil nadu, India. saleena.m@ktr.srmuniv.ac.in.
authors.forename: Lilly M
authors.initials: LM
authors.lastname: Saleena
mesh_terms: D000970:Antineoplastic Agents / Q000737:chemistry* / Q000494:pharmacology; D016000:Cluster Analysis; D006801:Humans; D006860:Hydrogen Bonding; D057927:Hydrophobic and Hydrophilic Interactions; D020780:Matrix Metalloproteinase 9 / Q000737:chemistry*; D061965:Matrix Metalloproteinase Inhibitors / Q000737:chemistry* / Q000494:pharmacology; D008968:Molecular Conformation; D062105:Molecular Docking Simulation; D056004:Molecular Dynamics Simulation; D011485:Protein Binding; D015203:Reproducibility of Results; D013329:Structure-Activity Relationship
chemical_list: D000970:Antineoplastic Agents; D061965:Matrix Metalloproteinase Inhibitors; D020780:Matrix Metalloproteinase 9