Identification of mitogen‐activated protein kinase 7 inhibitors from natural products: Combined virtual screening and dynamic simulation studies

Abstract

AbstractMitogen‐activated protein kinase 7 (MAPK7) is a serine/threonine protein kinase that belongs to the MAPK family and plays a vital role in various cellular processes such as cell proliferation, differentiation, gene transcription, apoptosis, metabolism, and cell survival. The elevated expression of MAPK7 has been associated with the onset and progression of multiple aggressive tumors in humans, underscoring the potential of targeting MAPK7 pathways in therapeutic research. This pursuit holds promise for the advancement of anticancer drug development by developing potential MAPK7 inhibitors. To look for potential MAPK7 inhibitors, we exploited structure‐based virtual screening of natural products from the ZINC database. First, the Lipinski rule of five criteria was used to filter a large library of ~90,000 natural compounds, followed by ADMET and pan‐assay interference compounds (PAINS) filters. Then, top hits were chosen based on their strong binding affinity as determined by molecular docking. Further, interaction analysis was performed to find effective and specific compounds that can precisely bind to the binding pocket of MAPK7. Consequently, two compounds, ZINC12296700 and ZINC02123081, exhibited significant binding affinity and demonstrated excellent drug‐like properties. All‐atom molecular dynamics simulations for 200 ns confirmed the stability of MAPK7‐ZINC12296700 and MAPK7‐ZINC02123081 docked complexes. According to the molecular mechanics Poisson–Boltzmann surface area investigation, the binding affinities of both complexes were considerable. Overall, the result suggests that ZINC12296700 and ZINC02123081 might be used as promising leads to develop novel MAPK7 inhibitors. Since these compounds would interfere with the kinase activity of MAPK7, therefore, may be implemented to control cell growth and proliferation in cancer after required validations.