QSAR coupled to principal component analysis-adaptive neuro-fuzzy inference systems-Artificial Neural Network (PCA-ANFIS-ANN) and docking studies for the modeling of the flavonoid compounds

Flavonoids are phenolic compounds, secondary metabolites of plants that cause several benefits to our health, including helping the treatment against HIV [1] Quantitative structure–activity relationship (QSAR) methods are used to predict the pharmaceutically relevant properties of drug candidates whenever it is applicable. The aim of this study was to use three different techniques, namely principal component analysis (PCA), adaptive neuro fuzzy inference system (ANFIS) and artificial neural networks (ANNs) in predicting the activity (i.e. p ) of flavonoids compounds. Docking study was performed using HEX program on all the compounds. Using docking study, it has shown that all the studied DATAs derivatives bind to the Human immunodeficiency virus 1 receptor and have a common binding modes. These computational studies can offer useful references for understanding the action mechanism and molecular design or modification of this series of the anti-HIV agents [2].