Premium
Docking 3‐phenyltropane analogs into an ensemble of serotonin transporter homology model conformations
Author(s) -
Kuntz Charles Paul,
Lill Markus A.,
Carroll F Ivy,
Barker Eric L.
Publication year - 2011
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.25.1_supplement.1083.2
Subject(s) - aquifex aeolicus , docking (animal) , homology modeling , transporter , chemistry , stereochemistry , serotonin transporter , ligand (biochemistry) , serotonin plasma membrane transport proteins , binding site , computational biology , biochemistry , biology , serotonin , receptor , enzyme , gene , medicine , nursing , escherichia coli
Although no atomic‐resolution structures yet exist for the human serotonin transporter (hSERT), several structures of a bacterial homologue of the monoamine transporters, the Aquifex aeolicus leucine transporter (LeuT) have made it possible to generate homology models of hSERT that account for many aspects of its pharmacology. Explaining the selectivity and affinity of 3‐phenyltropane cocaine analogs for hSERT requires a model of ligand binding that accounts for the structural flexibility of the protein upon ligand binding, since small changes in protein conformation are likely associated with changes in the binding free energy that underlies affinity. We have therefore developed a novel approach to docking a series of 3‐phenyltropane analogs to hSERT by sequential docking of each compound to a series of conformations of hSERT generated by homology modeling from two template LeuT structures: one with LeuT bound to substrate exhibiting a conformation in which the substrate is occluded from solvent, and one with LeuT bound to a competitive inhibitor in which the transporter is locked in an open‐to‐out conformation. This approach has yielded docking poses and transporter conformations not previously observed. We therefore believe that this approach has great promise for future studies on other classes of compounds and other protein targets to provide computational support for models of ligand binding.