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Bond‐Based 2D Quadratic Fingerprints in QSAR Studies: Virtual and In vitro Tyrosinase Inhibitory Activity Elucidation
Author(s) -
CasañolaMartin Gerardo M.,
MarreroPonce Yovani,
Khan Mahmud T. H.,
Khan Sher B.,
Torrens Francisco,
PérezJiménez Facundo,
Rescigno Antonio,
Abad Concepción
Publication year - 2010
Publication title -
chemical biology and drug design
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.59
H-Index - 77
eISSN - 1747-0285
pISSN - 1747-0277
DOI - 10.1111/j.1747-0285.2010.01032.x
Subject(s) - tyrosinase , quantitative structure–activity relationship , kojic acid , in silico , virtual screening , chemistry , linear discriminant analysis , stereochemistry , molecular descriptor , computational biology , computer science , artificial intelligence , biochemistry , enzyme , biology , pharmacophore , gene
In this report, we show the results of quantitative structure–activity relationship (QSAR) studies of tyrosinase inhibitory activity, by using the bond‐based quadratic indices as molecular descriptors (MDs) and linear discriminant analysis (LDA), to generate discriminant functions to predict the anti‐tyrosinase activity. The best two models [Eqs ( 6 ) and ( 12 )] out of the total 12 QSAR models developed here show accuracies of 93.51% and 91.21%, as well as high Matthews correlation coefficients ( C ) of 0.86 and 0.82, respectively, in the training set. The validation external series depicts values of 90.00% and 89.44% for these best two equations ( 6 ) and ( 12 ), respectively. Afterwards, a second external prediction data are used to perform a virtual screening of compounds reported in the literature as active (tyrosinase inhibitors). In a final step, a series of lignans is analysed using the in silico ‐developed models, and in vitro corroboration of the activity is carried out. An issue of great importance to remark here is that all compounds present greater inhibition values than Kojic Acid (standard tyrosinase inhibitor: IC 50 = 16.67 μ m ). The current obtained results could be used as a framework to increase the speed, in the biosilico discovery of leads for the treatment of skin disorders.