4.7 Article

Development of an in Silico Model of DPPH• Free Radical Scavenging Capacity: Prediction of Antioxidant Activity of Coumarin Type Compounds

期刊

出版社

MDPI
DOI: 10.3390/ijms17060881

关键词

artificial neural networks; MLP; antioxidant; QSAR; DPPH center dot; free radical scavenger; coumarin

资金

  1. Ministry of National Education, Research and Technology
  2. program PYTHAGORAS II of EPEAEK II [MIS: 97436/073]
  3. Service de Cooperation et d'Action Culturelle of Embassy of France in Cuba

向作者/读者索取更多资源

A quantitative structure-activity relationship (QSAR) study of the 2,2-diphenyl-l-picrylhydrazyl (DPPH center dot) 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 (R-2 = 0.713) and test set Q(ext)(2) = 0.654 similar to, 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 pIC(50) values.

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