Search

Pharmacophore modeling studies were undertaken for a series of quinoline derivatives as VEGFR-2 tyrosine kinase inhibitors. A five-point pharmacophore with two hydrogen bond acceptors (A), one hydrogen bond donor (D), and two aromatic rings (R) as pharmacophore features was developed. The pharmacophore hypothesis yielded a statistically significant 3D-QSAR model, with a correlation coefficient of r2 = 0.8621 for training set compounds. The model generated showed excellent predictive power, with a correlation coefficient of q2 = 0.6943 and for a test set of compounds. Furthermore, the structure–activity relationships of quinoline derivatives as VEGFR-2 tyrosine kinase inhibitors were elucidated and the activity differences between them discussed. Docking studies were also carried out wherein active and inactive compounds were docked into the active site of the VEGFR-2 crystal structure to analyze drug-receptor interactions. Further we analyzed all the compounds for Lipinski’s rule of five to evaluate drug likeness and established in silico ADME parameters using QikProp. The results provide insights that will aid the optimization of these classes of VEGFR-2 inhibitors for better activity, and may prove helpful for further lead optimization and virtual screening.

The three-dimensional quantitative structure–activity relationships (3D-QSAR) were established for 30 oxindole derivatives as vascular endothelial growth factor receptor-2 (VEGFR-2) tyrosine kinase inhibitors by using comparative molecular field analysis (CoMFA) and comparative similarity indices analysis comparative molecular similarity indices analysis (CoMSIA) techniques. With the CoMFA model, the cross-validated value (q2) was 0.777, the non-cross-validated value (R2) was 0.987, and the external cross-validated value () was 0.72. And with the CoMSIA model, the corresponding q2, R2 and values were 0.710, 0.988 and 0.78, respectively. Docking studies were employed to bind the inhibitors into the active site to determine the probable binding conformation. The binding mode obtained by molecular docking was in good agreement with the 3D-QSAR results. Based on the QSAR models and the docking binding mode, a set of new VEGFR-2 tyrosine kinase inhibitors were designed, which showed excellent predicting inhibiting potencies. The result revealed that both QSAR models have good predictive capability to guide the design and structural modification of homologic compounds. It is also helpful for further research and development of new VEGFR-2 tyrosine kinase inhibitors. [ABSTRACT FROM AUTHOR]

The synthesis and biological evaluation of novel 1-aryl-3-[2-, 3- or 4-(thieno[3,2- b ]pyridin-7-ylthio)phenyl]ureas 3 , 4 and 5 as VEGFR-2 tyrosine kinase inhibitors, are reported. The 1-aryl-3-[3-(thieno[3,2- b ]pyridin-7-ylthio)phenyl]ureas 4a – 4h , with the arylurea in the meta position to the thioether, showed the lowest IC 50 values in enzymatic assays (10–206 nM), the most potent compounds 4d – 4h (IC 50 10–28 nM) bearing hydrophobic groups (Me, F, CF 3 and Cl) in the terminal phenyl ring. A convincing rationalization was achieved for the highest potent compounds 4 as type II VEGFR-2 inhibitors, based on the simultaneous presence of: (1) the thioether linker and (2) the arylurea moiety in the meta position. For compounds 4 , significant inhibition of Human Umbilical Vein Endothelial Cells (HUVECs) proliferation (BrdU assay), migration (wound-healing assay) and tube formation were observed at low concentrations. These compounds have also shown to increase apoptosis using the TUNEL assay. Immunostaining for total and phosphorylated (active) VEGFR-2 was performed by Western blotting. The phosphorylation of the receptor was significantly inhibited at 1.0 and 2.5 μM for the most promising compounds. Altogether, these findings point to an antiangiogenic effect in HUVECs. [ABSTRACT FROM AUTHOR]

The present study is an attempt to formulate the three-dimensional quantitative structure-activity relationship (3D-QSARs) modeling of 3-benzimidazol-2-ylhydroquinolin-2-one derivatives inhibiting vascular endothelial growth factor receptor-2 (VEGFR-2) tyrosine kinase. The 3D-QSARs were established for 36 3-benzimidazol-2-ylhydroquinolin-2-one derivatives as VEGFR-2 tyrosine kinase inhibitors using comparative molecular field analysis (CoMFA) and comparative similarity indices analysis (CoMSIA) techniques. The negative logarithm of IC (pIC) was used as the biological activity in the 3D-QSAR study. With the CoMFA model, the cross-validated value ( q) was 0.516, the non-cross-validated value ( R) was 0.927, and the external cross-validated value (Q) was 0.855; with the CoMSIA model, the corresponding q, R, and Q values were 0.538, 0.980, and 0.809, respectively. The CoMFA and CoMSIA models were validated by a structurally diversified test set of nine compounds. Then, molecular docking was carried out to better understand of the interactions between VEGFR-2 tyrosine kinase target and inhibitors. Finally, based on results of the structure-activity relationship and of the molecular docking, seven VEGFR-2 tyrosine kinase inhibitors that showed excellent potencies have been constructed. [ABSTRACT FROM AUTHOR]

Pharmacophore modeling studies were undertaken for a series of quinoline derivatives as VEGFR-2 tyrosine kinase inhibitors. A five-point pharmacophore with two hydrogen bond acceptors (A), one hydrogen bond donor (D), and two aromatic rings (R) as pharmacophore features was developed. The pharmacophore hypothesis yielded a statistically significant 3D-QSAR model, with a correlation coefficient of r 2 = 0.8621 for training set compounds. The model generated showed excellent predictive power, with a correlation coefficient of q 2 = 0.6943 and for a test set of compounds. Furthermore, the structure–activity relationships of quinoline derivatives as VEGFR-2 tyrosine kinase inhibitors were elucidated and the activity differences between them discussed. Docking studies were also carried out wherein active and inactive compounds were docked into the active site of the VEGFR-2 crystal structure to analyze drug-receptor interactions. Further we analyzed all the compounds for Lipinski’s rule of five to evaluate drug likeness and established in silico ADME parameters using QikProp. The results provide insights that will aid the optimization of these classes of VEGFR-2 inhibitors for better activity, and may prove helpful for further lead optimization and virtual screening. [ABSTRACT FROM AUTHOR]