Pharmacophore and molecular dynamics based activity profiling of natural products for kinases involved in lung cancer

To determine the kinase inhibitory potential of natural products that could be utilized in lung cancer therapy in the near future, a pharmacophore-based activity profiling protocol using parallel pharmacophore-based virtual screening of ZINC-a natural product database-was employed. The work presented here is based on the previously explored fact that pharmacophore-based parallel screening is a reliable in silico protocol to predict the possible biological activities of any compound, or any compound library, by screening it with a number of pharmacophore models. The present study involves ligand-based pharmacophore modeling of various kinases, including EGFR (T790 M), cMET, ErbB2, FGFR and ALK, which are well established targets of normal as well resistant lung cancer. The generated pharmacophore models were then utilized for parallel and cross screening. The profiled molecules for each target were then validated using molecular docking and molecular dynamic simulations. The results show that kinase inhibitory activity profiling of some natural product molecules was successfully achieved. Graphical abstract Pharmacophore and activity profiling of natural products for kinases involved in lung cancer.