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Targeting drug-efflux pumps -- a pharmacoinformatic approach.
Author(s) -
Karin Pleban,
Dominik Kaiser,
Stefan Kopp,
Michael Peer,
Peter Chiba,
Gerhard F. Ecker
Publication year - 2005
Publication title -
acta biochimica polonica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.452
H-Index - 78
eISSN - 1734-154X
pISSN - 0001-527X
DOI - 10.18388/abp.2005_3439
Subject(s) - pharmacophore , virtual screening , computational biology , transmembrane protein , transmembrane domain , homology modeling , chemistry , propafenone , ligand (biochemistry) , efflux , photoaffinity labeling , drug , target protein , combinatorial chemistry , biochemistry , binding site , biology , pharmacology , amino acid , medicine , enzyme , gene , receptor , cardiology , atrial fibrillation
In line with our studies on propafenone-type inhibitors of P-glycoprotein (P-gp), we applied several methods to approach virtual screening tools for identification of new P-gp inhibitors on one hand and the molecular basis of ligand-protein interaction on the other hand. For virtual screening, a combination of autocorrelation vectors and selforganising artificial neural networks proved extremely valuable in identifying P-gp inhibitors with structurally new scaffolds. For a closer view on the binding region for propafenone-type ligands we applied a combination of pharmacophore-driven photoaffinity labeling and protein homology modeling. On LmrA, a bacterial homologue of P-gp, we were able to identify distinct regions on transmembrane helices 3, 5 and 6 which show significant changes in the labeling pattern during different steps of the catalytic cycle.

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