Integrative Computational Approaches for the Discovery of Triazole-Based Urease Inhibitors: A Machine Learning, Virtual Screening, and Meta-Dynamics Framework.

ABSTRACT: Helicobacter pylori urease (HpU) plays a central role in bacterial survival and virulence by hydrolyzing urea into ammonia and carbon dioxide, neutralizing gastric acidity, and facilitating host colonization. The increasing prevalence of antibiotic resistance underscores the need for alternative strategies targeting essential bacterial enzymes such as urease. In this study, a multistage computational pipeline integrating pharmacophore modeling, machine learning (ML), ensemble docking, and enhanced molecular dynamics simulations were applied to identify novel triazole-based HpU inhibitors. Starting from over seven million compounds in the ZINC15 database, pharmacophore- and ML-based filters progressively reduced the chemical space to 7062 candidates. Ensemble docking ac

SUBMITTER: Rios-Rozas SE 

PROVIDER: S-EPMC12692664 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature