Quantitative Structure Activity Relationship (QSAR) Anticancer Modeling of the MCF-7 Cell Line of Phthalocyanine Derivatives
Francis Kouame, Mawa Koné, Lawson Ekossias Digre BEKE, Camille Medy Nongbe, Georges Stéphane Dembélé · International Research Journal of Pure and Applied Chemistry · 2025
Breast cancer is a major public health issue and justifies the ongoing search for new active and selective molecules. In this study, a QSAR (Quantitative Structure-Activity Relationship) model was developed to predict the anticancer activity of a series of phthalocyanine derivatives on the MCF-7 cell line. Experimental activity values were converted into pIC50 for better consistency and more reliable statistical analysis. Three molecular descriptors calculated using the DFT method (B3LYP/LanL2DZ), polarizability (α), molar refractivity (MR), and electron-acceptor power (ω+), were selected to establish the model through multiple linear regression. The obtained model exhibits excellent statistical performance (R2 = 0.9527; Q2CV = 0.9745), indicating a strong correlation between the experimental and predicted values. Internal and external validations, according to Tropsha's criteria, confirm its robustness and predictive reliability. The applicability domain analysis shows that all molecules fall within the model's valid range, with no outliers. Polarizability appears to be the most significant descriptor for anticancer activity, suggesting that greater electronic deformability enhances biological efficacy. This QSAR model thus provides a promising tool for guiding the rational design of new phthalocyanines with high anticancer potential.