Abstract

Helicobacter pylori urease is a key virulence factor and a validated target for anti-infective strategies. In this study, a comprehensive computational workflow was applied to identify potential urease inhibitors through a drug repurposing approach. A curated library was first filtered using permeability-related descriptors and multiparametric scoring. The resulting compounds were evaluated through ensemble and consensus docking across multiple protein conformations and docking engines, followed by XP rescoring, metal-ligand distance analysis, and molecular dynamics simulations. Binding stability and thermodynamic profiles were further assessed using MM-GBSA and well-tempered metadynamics. This integrative strategy led to the identification of several candidate compounds exhibiting favorable docking scores, stable coordination with the catalytic Ni2+ center, and consistent binding behavior during molecular dynamics simulations. Notably, selected compounds showed improved relative binding free energy profiles compared to reference inhibitors within the applied computational framework. Overall, this study provides a robust computational pipeline for urease inhibitor identification and highlights repurposed compounds as promising candidates for further experimental validation.