Inhibitors of Helicobacter pylori protease HtrA found by 'virtual ligand' screening combat bacterial invasion of epithelia.

<h4>Background</h4>The human pathogen Helicobacter pylori (H. pylori) is a main cause for gastric inflammation and cancer. Increasing bacterial resistance against antibiotics demands for innovative strategies for therapeutic intervention.<h4>Methodology/principal findings</h4>...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Martin Löwer, Tim Geppert, Petra Schneider, Benjamin Hoy, Silja Wessler, Gisbert Schneider
Formato: article
Lenguaje:EN
Publicado: Public Library of Science (PLoS) 2011
Materias:
R
Q
Acceso en línea:https://doaj.org/article/5d55323295b44fc4a0f7665cde6b9ee5
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
Descripción
Sumario:<h4>Background</h4>The human pathogen Helicobacter pylori (H. pylori) is a main cause for gastric inflammation and cancer. Increasing bacterial resistance against antibiotics demands for innovative strategies for therapeutic intervention.<h4>Methodology/principal findings</h4>We present a method for structure-based virtual screening that is based on the comprehensive prediction of ligand binding sites on a protein model and automated construction of a ligand-receptor interaction map. Pharmacophoric features of the map are clustered and transformed in a correlation vector ('virtual ligand') for rapid virtual screening of compound databases. This computer-based technique was validated for 18 different targets of pharmaceutical interest in a retrospective screening experiment. Prospective screening for inhibitory agents was performed for the protease HtrA from the human pathogen H. pylori using a homology model of the target protein. Among 22 tested compounds six block E-cadherin cleavage by HtrA in vitro and result in reduced scattering and wound healing of gastric epithelial cells, thereby preventing bacterial infiltration of the epithelium.<h4>Conclusions/significance</h4>This study demonstrates that receptor-based virtual screening with a permissive ('fuzzy') pharmacophore model can help identify small bioactive agents for combating bacterial infection.