Templates and Models of Monoamine Transporter Proteins
Abstract:X-ray crystallography, structural bioinformatics and computational chemistry have become important techniques in the discovery and development of effective and safe new drugs. From a drug discovery point of view, membrane proteins are among the most interesting molecular targets, but the current knowledge about detailed 3D structures of membrane proteins is sparse. Homology modeling techniques may provide structural knowledge about membrane proteins and their interactions with drugs and other molecules. The neurotransmitter sodium symporters (NSS) are the molecular targets of many pharmacologically active substances, and we have used three different secondary transporters as templates for modeling the NSS proteins DAT, NET and SERT. The first template was based on the electron density projection map of the Escherichia coli Na+/H+ antiporter (NhaA), while later the X-ray structure of Lac Permease (symporter) was used as a template. The helical architectures of these templates have a lot in common, and models based on both could contribute with structural explanations of several experimental studies in spite of low homology with NSS proteins. In 2005 the crystal structure of a bacterial homologue of the human monoamine neurotransmitter transporter Aquifex aeolicus (LeuTAa) was reported. This structure was the first experimental structure of a NSS family member, and represented a breakthrough for homology modeling of pharmacological important NSS proteins. Since then several X-ray structures LeuTAa in complex with pharmacologically important compounds have been published. Homology models of NSS proteins, combined with site-directed mutagenesis data, have identified ligand binding sites and contributed with important knowledge for new drug development.
Keywords: 3-Dimensional structure; NSS proteins; dopamine transporter; drug interactions; molecular mechanisms; molecular structure; monoamine transporters; noradrenaline transporter; serotonin transporter; structural bioinformatics
Document Type: Research Article
Publication date: October 1, 2011
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