Vascular endothelial growth factors (VEGFs) mediated VEGFR-2/KDR signaling cascade regulates endothelial cell migration and proliferation. Overexpression of VEGFR-2 has been perceived in different cancers, such as cervical cancer, triple-negative breast cancer, non-small-cell lung carcinoma, hepatocellular carcinoma, thyroid cancer, and renal cell carcinoma. Thus, the inhibition of VEGFR-2 has emerged as an alluring receptor in cancer therapy. The present research work intends to recognize the pharmacophoric features inhibiting VEGFR-2 by using the ligand-based drug design (LBDD) approach for 1,6-naphthyridine and pyridopyrimidine analogues by the 3D-QSAR technique, i.e., comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). 3D-QSAR models were established and validated using training and test set analogues. The alignment of the data set was achieved using the most active analogue (lowest energy conformer) of the series as a template structure. The partial least square analysis for CoMFA and CoMSIA models showed significant leave-one-out cross-validation coefficients of 0.659 and 0.689 and the conventional correlation coefficients (r2) of 0.987 and 0.985, respectively. Additionally, bootstrap analysis and cross-validation (leave-half-out method) were used to examine the quality of the generated models and internal reliability within the data set. The predictability of models was evaluated using a test set containing 14 analogues (r2pred = 0.719 and 0.697). Lastly, the outcomes of the generated models and contour maps were utilized to design the 1,6-naphthyridine and pyridopyrimidine analogues as VEGFR-2 inhibitors.
Key words: VEGFR-2, 1,6-naphthyridine, Pyridopyrimidine, 3D-QSAR, CoMFA, CoMSIA, Contour maps.
|
