Browsing by Author "Jorge, Elizabeth Goya"

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    Development of an in Silico Model of DPPH‚ Free Radical Scavenging Capacity: Prediction of Antioxidant Activity of Coumarin Type Compounds
    (International Journal of Molecular Sciences, 2016) Jorge, Elizabeth Goya; Barigye, Stephen J.; Rodríguez, María Elisa Jorge; Veitía, Maité Sylla-Iyarreta
    A quantitative structure-activity relationship (QSAR) study of the 2,2-diphenyl-l-picrylhydrazyl (DPPH•) radical scavenging ability of 1373 chemical compounds, using DRAGON molecular descriptors (MD) and the neural network technique, a technique based on the multilayer multilayer perceptron (MLP), was developed. The built model demonstrated a satisfactory performance for the training (R2=0.713) and test set (Q2ext=0.654) , respectively. To gain greater insight on the relevance of the MD contained in the MLP model, sensitivity and principal component analyses were performed. Moreover, structural and mechanistic interpretation was carried out to comprehend the relationship of the variables in the model with the modeled property. The constructed MLP model was employed to predict the radical scavenging ability for a group of coumarin-type compounds. Finally, in order to validate the model’s predictions, an in vitro assay for one of the compounds (4-hydroxycoumarin) was performed, showing a satisfactory proximity between the experimental and predicted pIC50 values
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    DPPH• Free Radical Scavenging Activity of Coumarin Derivatives. In silico and in vitro Approach
    (Mol2Net, 2015) Jorge, Elizabeth Goya; Rayar, Anita Maria; Barigye, Stephen Jones; Rodríguez, María Elisa Jorge; Veitía, Maite Sylla Iyarreta
    The interest of coumarins as antioxidant agents has attracted much attention in recent years. A quantitative structure-activity relationship (QSAR) study of the DPPH• (2,2-diphenyl-lpicrylhydrazyl) radical scavenging ability of chemical compounds, based on the 0-3D DRAGON molecular descriptors and an artificial neural networks (ANN) technique was developed. The built mathematical model showed a correlation coefficient for the training set (R2) = 0.71, an external correlation coefficient (𝑄𝑒𝑥𝑡 2) = 0.65 and it was used to predict the antioxidant activity of 4-hydroxycoumarin derivatives. Besides, an experimental in vitro assay was developed for the reference compound of this group (4-hydroxycoumarin) and the results obtained confirmed the predictions made by the ANN.