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Indian J Biochem Biophys ; 2007 Jun; 44(3): 169-75
Article in English | IMSEAR | ID: sea-28714

ABSTRACT

Considering importance of developing selective COX-2 inhibitors, COX-2 binding affinity data of 4-(2-aryl-1-imidazolyl)-phenyl methyl sulfones and sulfonamides (n = 83) have been modeled using electrotopological state (E-state) index as electronic parameter, hydrophobic substituent constant (pi) and molar refractivity (MR) of aryl ring substituents as lipophilic and steric parameters, respectively. Additionally, suitable dummy parameters have been used for the development of multiple regression equations in a stepwise manner. The study suggests that lipophilicity of ortho, meta and para substituents of the aryl ring increases the binding affinity, while molar refractivity (MR) of ortho and meta substituents of the aryl ring decreases the binding affinity. Again, electron-withdrawing substituents at meta and para positions of the aryl ring increase the binding affinity. Additionally, a 4-fluoro substituent on the aryl ring, a trifluoromethyl substituent at R position and simultaneous presence of 3-chloro and 4-methyl groups on the aryl ring are conducive to the binding affinity. Also, an amino substituent is preferred over a methyl group at R2 position suggesting preference of the sulfonamide moiety over the methyl sulfone moiety for the COX-2 binding affinity. Furthermore, importance of E-state values of different atoms in the generated relations suggests the influence of electron density distribution over the 1,2-diarylimidazole nucleus for the binding affinity. For this data set, E-state parameters perform better as electronic parameters in comparison to Hammett sigma parameters. When lipophilic whole molecular descriptor (ClogP) is used, instead of hydrophobic substituent constant (pi), the former performs better than the latter.


Subject(s)
Animals , Chemistry, Physical/methods , Cyclooxygenase 2 Inhibitors/pharmacology , Electronics , Electrons , Humans , Imidazoles/chemistry , Models, Chemical , Molecular Structure , Multivariate Analysis , Quantitative Structure-Activity Relationship , Regression Analysis , Software , Sulfonamides/chemistry , Sulfones/chemistry
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