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

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2025-12

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journal article

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Ríos-Rozas, Sofía E., Morales, Natalia, Valdés-Muñoz, Elizabeth, Urra, Gabriela, Flores-Morales, Camila A., Farías-Abarca, Javier, Hernández-Rodríguez, Erix W., Palma, Jonathan M., Osorio, Manuel I., Yáñez-Osses, Osvaldo, Morales-Quintana, Luis, Suardíaz, Reynier, Bustos, Daniel

Publisher

Multidisciplinary Digital Publishing Institute (MDPI)

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https://repositorio.udla.cl/handle/udla/2254

DOI

https://doi.org/10.3390/ijms262311576

Keywords

virtual screening, machine learning, quantum-polarized ligand docking, metadynamics, urease

Citation

Ríos-Rozas, Sofía E.; Morales, Natalia; Valdés-Muñoz, Elizabeth; Urra, Gabriela; Flores-Morales, Camila A.; Farías-Abarca, Javier; Hernández-Rodríguez, Erix W.; Palma, Jonathan M.; Osorio, Manuel I.; Yáñez-Osses, Osvaldo; Morales-Quintana, Luis; Suardíaz, Reynier; Bustos, Daniel (2025). Integrative Computational Approaches for the Discovery of Triazole-Based Urease Inhibitors: A Machine Learning, Virtual Screening, and Meta-Dynamics Framework. International Journal of Molecular Sciences, 26(23), 11576. https://doi.org/10.3390/ijms262311576

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 colon...

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Creative Commons Attribution 4.0 International
Except where otherwised noted, this item's license is described as Creative Commons Attribution 4.0 International
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