Cyclin-Dependent Kinase 2 (CDK2) and Vascular Endothelial Growth Factor Receptor (VEGFR2) have largely been considered as attractive targets for developing anticancer agents. However, there is no dual inhibitor commercially available in the market that interacts simultaneously with the allosteric back pocket of these enzymes. We applied a combined computational strategy that started with the generation of two overlapping pharmacophore models of both kinases at 'inactive' conformation. Next, several virtual libraries of natural products, including the databases TCM (Traditional Chinese Medicine), UEFS (Universidade Estadual de Feira de Santana), NuBBE (Nuclei of Bioassays, Biosynthesis, and Ecophysiology of Natural Products) and AfroDb (African Medicinal Plants Database) were deconstructed using a non-extensive version of the approach RECAP (retrosynthetic combinatorial analysis procedure). These natural-product-derived fragments (NPDFs) were screened and merged into drug-sized compounds, which were filtered by Lipinski's Rule-of-five (Ro5) and docking. As a result, two pharmacophore models, namely Hypo1 and Hypo2, were developed with an accuracy of 0.94 and 0.84, respectively. Deconstruction of natural products produced a set of 16655 unique non-extensive NPDFs that were screened against both pharmacophore models. Finally, after merging, Ro5-filtering and docking, we obtained a set of 20 hit compounds predicted to be diverse, developable, synthesizable and potent. The computational strategy proved successful to find virtual candidates of kinase inhibitors and therefore contributes to the identification of innovative multi-target compounds with potential anticancer activity. Communicated by Ramaswamy H. Sarma.
Keywords: RECAP; molecular docking; multi-target ligands; pharmacophore modeling; virtual screening.