ABSTRACT
A receptor-independent (RI) four-dimensional structure-activity relationship (4D-QSAR) formalism was applied to a set of sixty-four ß-N-biaryl ether sulfonamide hydroxamate derivatives, previously reported as potent inhibitors against matrix metalloproteinase subtype 9 (MMP-9). MMP-9 belongs to a group of enzymes related to the cleavage of several extracellular matrix components and has been associated to cancer invasiveness/metastasis. The best RI 4D-QSAR model was statistically significant (N=47; r(2) =0.91; q(2) =0.83; LSE=0.09; LOF=0.35; outliers=0). Leave-N-out (LNO) and y-randomization approaches indicated the QSAR model was robust and presented no chance correlation, respectively. Furthermore, it also had good external predictability (82 %) regarding the test set (N=17). In addition, the grid cell occupancy descriptors (GCOD) of the predicted bioactive conformation for the most potent inhibitor were successfully interpreted when docked into the MMP-9 active site. The 3D-pharmacophore findings were used to predict novel ligands and exploit the MMP-9 calculated binding affinity through molecular docking procedure.
Subject(s)
Antineoplastic Agents/chemistry , Matrix Metalloproteinase 9/chemistry , Matrix Metalloproteinase Inhibitors/chemistry , Melanoma/drug therapy , Skin Neoplasms/drug therapy , Catalytic Domain , Drug Screening Assays, Antitumor , Humans , Hydrogen Bonding , Hydrophobic and Hydrophilic Interactions , Hydroxamic Acids/chemistry , Melanoma/enzymology , Molecular Docking Simulation , Protein Binding , Quantitative Structure-Activity Relationship , Skin Neoplasms/enzymology , Sulfonamides/chemistryABSTRACT
Matrix metalloproteinases (MMP) are a group of enzymes related to extracelular matrix remodeling. Some types of MMP are overexpressed by malignant tumors, mainly the MMP-2 subtype, and have been associated to cancer invasiveness and metastasis. A receptor-independent (RI) 4D-QSAR formalism was applied, herein, to a set of forty ß-N-biaryl ether sulfonamide hydroxamates, previously reported as potent MMP-2 inhibitors, in order to map 3D-pharmacophore models and predict novel antitumor agents. The best RI 4D-QSAR model was statistically significant (N=30, r(2) =0.93, q(2) =0.88, five occupancy descriptors (GCOD), LSE=0.04, LOF=0.11, outliers=0), robust and not obtained by chance. The external predictability was 75 % (test set; N=8). A different orientation (binding mode) in the MMP-2 catalytic site was suggested regarding the most hydrophobic portion (R1 ) of the compounds' structure. Compounds were predicted and their inhibitory activity against MMP-2 was calculated by using the optimum RI 4D-QSAR model. The findings have provided interesting information to drive the designing and synthesis of novel potentially MMP-2 inhibitors against melanoma invasion.
