Two Dimensional QSAR of Novel Pyrazole-Benzimidazole Derivatives for Anti-Tumor Activity Against Hct116 Cell Line

Abstract

The present study aimed to develop and validate two-dimensional Quantitative Structure–Activity Relationship (2D-QSAR) models for novel pyrazole-benzimidazole derivatives to predict their anti-tumor activity against the HCT116 cancer cell line. A dataset of 37 derivatives reported in previous studies was selected, and IC50 values were converted into pIC50 for correlation analysis. Molecular structures were drawn using ChemDraw, energy-minimized with Chem3D MM2, and further optimized using MOPAC. Physicochemical descriptors, including molar refractivity, molecular mass, partition coefficient (LogP), LogS, and polar surface area, were calculated. Statistical analysis and model generation were performed using VALSTAT through multiple linear regression (MLR) with stepwise variable selection. Several QSAR models were generated, among which Model 1 showed the best statistical performance with r² = 0.1078 and standard deviation = 0.1464. The study revealed that molar refractivity, lipophilicity, and polar surface area significantly influenced cytotoxic activity. Increased molar refractivity and lipophilicity were associated with enhanced anti-tumor activity, indicating that bulky and less polar substituents favored enzyme inhibition. In contrast, higher polar surface area negatively affected activity. Validation using cross-validation and external test set prediction confirmed the predictive reliability of the developed models, with predicted pIC50 values closely matching experimental observations except for a few outliers. Overall, the findings demonstrate that steric and electronic properties play a crucial role in determining the anti-tumor potential of pyrazole-benzimidazole derivatives and may assist in designing improved chemotherapeutic candidates.