QSAR Modeling of phthalocyanine Derivatives as Potential Anticancer Agents against Hepatocellular Carcinoma

Liver cancer is one of the major public health challenges worldwide, characterized by high molecular heterogeneity and a poor prognosis. In this study, a QSAR (Quantitative Structure-Activity Relationship) analysis was conducted on a series of phthalocyanine derivatives to evaluate and predict their anticancer activity. The molecular descriptors logP (hydrophobicity) and TS (surface tension) were calculated using density functional theory (DFT/ B3LYP/LanL2DZ) with the Gaussian 09 software. The model, constructed using multiple linear regression, demonstrates excellent statistical performance (R² = 0.9772; S = 0.0602; F = 21.4383). External validation according to Roy's criteria confirms the robustness and predictive capability of the model. Contribution analysis reveals that logP is the key descriptor for anticancer activity, while TS plays a complementary role. The applicability domain demonstrates the model's reliability for predicting new molecules. These results offer promising prospects for the rational design of phthalocyanine derivatives with anticancer potential.