Constructing and Validating 3D-pharmacophore Models to a Set of MMP-9 Inhibitors for Designing Novel Anti-melanoma Agents

A receptor‐independent (RI) four‐dimensional structure‐activity relationship (4D‐QSAR) formalism was applied to a set of sixty‐four β‐N‐biaryl ether sulfonamide hydroxamate derivatives, previously reported as potent inhibitors against matrix metalloproteinase subtype 9 (MMP‐9). MMP‐9 belongs to a gr...

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Bibliographic Details
Published in:Molecular informatics 2016-07, Vol.35 (6-7), p.238-252
Main Authors: Medeiros Turra, Kely, Pineda Rivelli, Diogo, Berlanga de Moraes Barros, Silvia, Mesquita Pasqualoto, Kerly Fernanda
Format: Article
Language:English
Subjects:
4D-QSAR
Antineoplastic Agents - chemistry
Catalytic Domain
computer-aided drug design
Drug Screening Assays, Antitumor
Humans
Hydrogen Bonding
Hydrophobic and Hydrophilic Interactions
Hydroxamic Acids - chemistry
Matrix Metalloproteinase 9 - chemistry
Matrix Metalloproteinase Inhibitors - chemistry
melanoma
Melanoma - drug therapy
Melanoma - enzymology
MMP-9
molecular docking
Molecular Docking Simulation
Protein Binding
Quantitative Structure-Activity Relationship
Skin Neoplasms - drug therapy
Skin Neoplasms - enzymology
Sulfonamides - chemistry
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Summary:A receptor‐independent (RI) four‐dimensional structure‐activity relationship (4D‐QSAR) formalism was applied to a set of sixty‐four β‐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; r2=0.91; q2=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.
ISSN:1868-1743
1868-1751
DOI:10.1002/minf.201600004