Discovery of novel natural compounds for inhibiting JNK signaling in cancer: Multi-step virtual screening, MM-GBSA calculations, and molecular dynamics simulations

Abstract

Human c-Jun N-terminal kinase 1 (JNK1) is a cytosolic kinase within the mitogen-activated protein kinase family, pivotal in intracellular signal transduction cascades. Overexpression of JNK1 implicated in various cancers. Despite some JNK1 inhibitors progressing to clinical trials, none have gained market approval, underscoring the urgent need for new candidates. Computer-aided drug design lowers the expenses and time required for drug development. Rough estimates indicate that computational processes take less than one-third of the usual time and cost. This research employs diverse in silico screening methods to rapidly identify inhibitors for JNK1 associated with cancer. Specifically, we employed pharmacophore modeling on the bound ligand of JNK1 protein to identify essential pharmacophoric features crucial for discovering potential inhibitors. These features were screened against 449,008 natural compounds sourced from the SN3 database. The identified compounds underwent docking and MM-GBSA calculations. Two compounds (SN0239242 and SN0263268) exhibited superior MM-GBSA binding affinity compared to the bound ligand, with values of -69.22, -62.2, and -57.68 kcal/mol, respectively. These compounds were subjected to 100 ns molecular dynamics experiments and exhibited stable interactions. Natural compounds from these in silico studies showed promising anticancer potential as JNK1 inhibitors and could be prioritized for future experimental validation.