In recent years, various virtual screening (VS) tools have been developed, and many successful screening campaigns have been showcased. However, whether by conventional molecular docking or pharmacophore screening, the selection of virtual hits is based on the ranking of compounds by scoring functions or fit values, which remains the bottleneck of VS due to insufficient accuracy. As the limitations of individual methods persist, a comprehensive comparison and integration of different methods may provide insights into selecting suitable methods for VS. Here, we evaluated the performance of molecular docking, fingerprint-based 2D similarity and multicomplex pharmacophore in an individual and a combined manner, through a retrospective VS study on VEGFR-2 inhibitors. An integrated two-layer workflow was developed and validated through VS of VEGFR-2 inhibitors against the DUD-E database, which demonstrated improved VS performance through a ligand-based method ECFP_4, followed by molecular docking, and then a strict multicomplex pharmacophore. Through a retrospective comparison with six published papers, this integrated approach outperformed 43 out of 45 methods, indicating a great effectiveness. This kind of integrated VS approach can be extended to other targets for the screening and discovery of inhibitors.

Kinase insert Domain-containing Receptor (KDR) is one of the currently validated targets for anticancer drug discovery and development. Herein, a series of o-amino-arylurea derivatives have been synthesized and evaluated for their kinase inhibitory activity. The optimization on the basis of biological screening and molecular modeling resulted in obvious increase in KDR kinase inhibitory activity compared with the hit compound. Eventually, we identified a potent inhibitor 5a of 1-(4-chloro-3-(trifluoromethyl)phenyl)-3-(2-((quinolin-4-ylmethyl) amino)pyridin-3-yl)urea scaffold against KDR (IC50 = 0.0689 µM), which can serve as good starting point for further KDR inhibitor optimization and development.