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

Autor: Kerly Fernanda Mesquita Pasqualoto, Kely Medeiros Turra, Diogo Pineda Rivelli, Silvia Berlanga de Moraes Barros
Rok vydání: 2016
Předmět:
0301 basic medicine
Quantitative structure–activity relationship
Skin Neoplasms
Stereochemistry
Matrix metalloproteinase inhibitor
Quantitative Structure-Activity Relationship
Antineoplastic Agents
Plasma protein binding
Matrix Metalloproteinase Inhibitors
Matrix metalloproteinase
Hydroxamic Acids
Molecular Docking Simulation
03 medical and health sciences
0302 clinical medicine
Structural Biology
Catalytic Domain
Drug Discovery
Humans
Melanoma
chemistry.chemical_classification
Sulfonamides
biology
Organic Chemistry
Active site
Hydrogen Bonding
Computer Science Applications
030104 developmental biology
Enzyme
Matrix Metalloproteinase 9
chemistry
030220 oncology & carcinogenesis
biology.protein
RELAÇÕES QUANTITATIVAS ENTRE ESTRUTURA QUÍMICA E ATIVIDADE BIOLÓGICA
Molecular Medicine
Drug Screening Assays
Antitumor
Pharmacophore
Hydrophobic and Hydrophilic Interactions
Protein Binding
Zdroj: Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
ISSN: 1868-1743
DOI: 10.1002/minf.201600004
Popis: 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; 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.
Databáze: OpenAIRE
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