In Silico identification of natural and synthetic inhibitors targeting KRAS mutants (G12D, G12V, and G12C) and wild-type in pancreatic cancer.

Pancreatic cancer is a highly aggressive malignancy with poor prognosis, largely driven by oncogenic KRAS mutations. Among these, codon 12 substitutions such as G12D and G12V are the most prevalent and contribute to sustained activation of proliferative and survival signaling pathways. In this study, an integrated in silico approach was employed to identify potential inhibitors targeting wild-type and mutant KRAS variants (G12D, G12V, and G12C). Virtual screening, molecular docking, molecular dynamics (MD) simulations, density functional theory (DFT) calculations, and ADME profiling were performed. Several compounds, including Pirbuterol, Levonordefrin, Mugineic acid, Irilin D, DH-DMX, and DXP, demonstrated favorable binding affinities relative to reference inhibitors MRTX1133, Daraxonrasib, and Adagrasib. MD simulations and principal component analysis indicated stable ligand-protein interactions supported by consistent hydrogen bonding patterns. DFT analysis provided insights into electronic properties and reactivity, while ADME profiling suggested acceptable pharmacokinetic characteristics. Notably, Levonordefrin showed consistent binding across multiple KRAS variants. These findings identify potential candidates for further experimental validation and support the application of computational approaches in KRAS-targeted drug discovery for Pancreatic cancer.