3D-QSAR-Based Pharmacophore Modeling, Virtual Screening, and Molecular Docking Studies for Identification of Tubulin Inhibitors with Potential Anticancer Activity

Abstract

In this study, we aimed to develop a pharmacophore-based three-dimensional quantitative structure activity relationship (3D-QSAR) for a set including sixty-two cytotoxic quinolines (1-62) as anticancer agents with tubulin inhibitory activity. A total of 279 pharmacophore hypotheses were generated based on the survival score to build QSAR models. A six-point pharmacophore model (AAARRR.1061) was identified as the best model which consisted of three hydrogen bond acceptors (A) and three aromatic ring (R) features. The model showed a high correlation coefficient ( R 2 = 0.865 ), cross-validation coefficient ( Q 2 = 0.718 ), and F value (72.3). The best pharmacophore model was then validated by the Y-Randomization test and ROC-AUC analysis. The generated 3D contour maps were used to reveal the structure activity relationship of the compounds. The IBScreen database was screened against AAARRR.1061, and after calculating ADMET properties, 10 compounds were selected for further docking study. Molecular docking analysis showed that compound STOCK2S-23597 with the highest docking score (-10.948 kcal/mol) had hydrophobic interactions and can form four hydrogen bonds with active site residues.

Recent Advances of Tubulin Inhibitors Targeting the Colchicine Binding Site for Cancer Therapy

“…In recent work, researchers innovated a quinoline series by using the three-dimensional quantitative SAR strategy, and these series were virtually designed and evaluated as new anticancer/tubulin inhibitor agents. St.44 ( Figure 9 ) was one of the most active ligands regarding its possible binding interactions with the colchicine binding site [ 110 ].…”

Development of pharmacophore models for AcrB protein and the identification of potential adjuvant candidates for overcoming efflux-mediated colistin resistance

“…The correlation coefficient ( R 2 = 0.8766), cross-validated correlation coefficient ( Q 2 = 0.3237), and Fisher ratio ( F = 92.3) scores were calculated using a set of 32 compounds ( Table 3 ) and suggested the statistical significance of the 3D-QSAR model. 66 In subsequent enrichment analysis using a decoy of 32 compounds (50 decoys for each active compound), the false-positive rate (FP = 1 − Specificity) was plotted as a function of the valid positive rate (TP = Sensitivity) (Fig. S1 † ).…”