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Since high MAO-B levels are present in early stages of AD, the MAO-B system can be designated as an appropriate and prospective tracer target of molecular imaging biomarkers for the detection of early AD. According to the preceding investigations of Mishra et al. the aim of this work was the development of a compound library of selective and reversible MAO-B inhibitors by performing bioisosteric modifications of the core structure of 3-(anthracen-9-yl)-5-phenyl-4,5-dihydro-1H-pyrazoles. In conclusion, 13 new pyrazoline based derivatives have been prepared, which will serve as precursor substances for future radiolabeling as well as reference compounds for the investigation of increased MAO-B levels in AD.

Screening a library of small-molecule compounds using a cell line expressing human GABA transporter 3 (hGAT3) in a [(3)H]GABA uptake assay identified isatin derivatives as a new class of hGAT3 inhibitors. A subsequent structure-activity relationship (SAR) study led to the identification of hGAT3-selective inhibitors (i.e., compounds 20 and 34) that were superior to the reference hGAT3 inhibitor, (S)-SNAP-5114, in terms of potency (low micromolar IC50 values) and selectivity (30-fold selective for hGAT3 over hGAT1/hGAT2/hBGT1). Further pharmacological characterization of compound 20 (5-(thiophen-2-yl)indoline-2,3-dione) revealed a noncompetitive mode of inhibition at hGAT3. This suggests that this compound class, which has no structural resemblance to GABA, has a binding site different from the substrate, GABA. This was supported by a molecular modeling study that suggested a unique binding site that matched the observed selectivity, inhibition kinetics, and SAR of the compound series. These compounds are the most potent GAT3 inhibitors reported to date that provide selectivity for GAT3 over other GABA transporter subtypes.

Elevating GABA levels in the synaptic cleft by inhibiting its reuptake carrier GAT1 is an established approach for the treatment of CNS disorders like epilepsy. With the increasing availability of crystal structures of transmembrane transporters, structure-based approaches to elucidate the molecular basis of ligand–transporter interaction also become feasible. Experimental data guided docking of derivatives of the GAT1 inhibitor tiagabine into a protein homology model of GAT1 allowed derivation of a common binding mode for this class of inhibitors that is able to account for the distinct structure–activity relationship pattern of the data set. Translating essential binding features into a pharmacophore model followed by in silico screening of the DrugBank identified liothyronine as a drug potentially exerting a similar effect on GAT1. Experimental testing further confirmed the GAT1 inhibiting properties of this thyroid hormone.

A series of β-amino acids with lipophilic diaromatic side chain was synthesized and characterized pharmacologically on mouse γ-amino butyric acid (GABA) transporter subtypes mGAT1-4 in order to investigate structure activity relationships (SAR) for mGAT2 (corresponding to hBGT-1). Variation in the lipophilic diaromatic side chain was probed to understand the role of the side chain for activity. This yielded several selective compounds of which the best (1R,2S)-5a was more than 10 fold selective towards other subtypes, although potency was moderate. A docking study was performed to investigate possible binding modes of the compounds in mGAT2 suggesting a binding mode similar to that proposed for Tiagabine in hGAT1. Specific interactions between the transporter and the amino acid part of the ligands may account for a reverted preference towards mGAT2 over mGAT1.

Neurotransmitter:sodium symporters are located on presynaptic neurons and terminate neurotransmission by removing the monoamine substrates from the synaptic cleft. Until very recently, only several conformational snapshots/structures of a bacterial homolog of neurotransmitter:sodium symporters, namely, the leucine/alanine transporter LeuT from Aquifex aeolicus, were available. However, this transporter shares only 21b % overall sequence identity with its human homologs. In this chapter, we describe how a model can be developed from a template with such low identity. The effort of model building will strongly depend on the purpose. We discuss this process and focus on the important steps that allowed us to obtain a model which can be used for molecular dynamics simulations. Furthermore, we also highlight the inherent limitations of the proposed approaches. Prediction of ligand binding brings in additional complexity. Therefore, experimental scrutiny of the resulting models is a key component to successful validation. We describe two specific examples: model building of the dopamine transporter and ligand docking to the serotonin transporter. We evaluate our modeling approach by direct comparison of our models to the recently published first eukaryotic neurotransmitter:sodium symporter, the drosophila melanogaster DAT transporter.

Membranes fulfill the essential need of all living species to separate different compartments. On the other hand, in a cell the homeostatic environment can only be maintained by the cellular membrane acting as a selective ‘filter’, which allows the cell to continuously communicate with other cells. Mechanisms which facilitate the translocation of materials across the membrane regulate the entrance and disposal of ions, amino acids, nutrients, and signaling molecules.

Cocaine and amphetamine are psychostimulant drugs that are illicitly used; they affect sensory perception by targeting the neurotransmitter: sodium symporters (NSS) at the synapses between neurons. They both increase the concentration of the neurotransmitter in the synaptic cleft but by different means.

Tiagabine (Gabitril®) is a selective inhibitor of the human gamma-aminobutyric acid (GABA) transporter 1 (hGAT-1), a transport protein belonging to the family of neurotransmitter-sodium-symporters (NSS). It is a marketed drug, used for treatment of epilepsy. However, the molecular basis of protein-ligand interaction remains obscure due to the lack of a 3D structure of the target protein. In order to identify activity-determining structural features of a series of tiagabine analogs taken from literature [1-3], we chose an approach combining traditional methods of molecular modeling with exhaustive sampling of docking poses, and a pairwise comparison of structural features and their respective bioactivity values. We determined a common binding mode of tiagabine analogs, which is in nice agreement with literature [4]. Further, we were able to trace back considerable differences in inhibitory activities to distinct molecular attributes of the analogs. Our study revealed the molecular explanation for the importance of a polar linker region and thus paves the way for subsequent screening efforts in the search for novel GAT-1 inhibitors.

Background Neuronal functions, such as excitability or endoand exocytosis, require phosphatidylinositol-4,5-bisphosphate (PIP2) since ion channels and other proteins involved in these processes are regulated by PIP2. Monoamine transporters control neurotransmission by removing monoamines from the extracellular space. They also display channel properties, but their regulation by PIP2 has not been reported. The psychostimulant amphetamine acts on monoamine transporters to stimulate transportermediated currents and efflux and thereby increases the levels of extracellular monoamines.

The human serotonin transporter (hSERT), embedded in the presynaptic membrane, is responsible for the reuptake of serotonin from the synaptic cleft, thus terminating neurotransmission. The structure of the SERT has not yet been resolved by experimental means. Determining hypothese for binding modes between ligands and the binding site of a protein with no available high-resolution structural data can be realized by creating a protein homology model, which further can be used as basis for ligand-protein docking experiments. Recently, an efficient docking method taking into account flexibility both of ligand and target, called Induced Fit Docking, has been introduced. Within this study we compare the results obtained with induced fit docking with those which have been obtained recently by applying a statistical approach [1].

The human transporters for the inhibitory neurotransmitter gamma-aminobutyric acid (GABA) hGAT-1, 2, and 3, and hBGT-1 belong to the neurotransmittersodium symporter (NSS) family of membrane transport proteins. hGAT-1 has been a target for the design of antiepileptic therapeutics [1], with tiagabine (Gabitril ® ) being the only GAT inhibitor on the market. The lack of specific inhibitors for the other hGAT subtypes, results from a still missing detailed understanding of the molecular basis of drug-transporter interactions of the respective subtypes. We aim at elucidating plausible binding modes for ligands of each subtype, respectively. In our first studies, we built up homology models for hGAT-1 in the occluded and outward-facing conformation based on the respective high resolution structures of the leucine transporter of Aquifex aeolicus (LeuT) (pdb-codes: 2A65 and 3F3A). Afterwards, the natural substrate GABA was docked into the occluded state model and tiagabine into the outward-facing model by making use of the Induced Fit Docking module of Schrodinger, LLC. Both models were further subject to extensive Molecular Dynamics (MD) simulation studies (GROMACS 4.5.3 was used). By the aid of MD simulations we could detect the existence of conserved water molecules into the GABA (occluded) and tiagabine (open-to-out) binding sites, respectively. Average structures from the equilibrated trajectories were extracted and subsequently served for further docking experiments. Docking of small ligands (GABA, Guvacine and R-/S Nipecotic Acid) into the occluded state model nicely indicated their preference to bind in an extended conformation (also demonstrated by long-term MD with GABA). MD and Docking of tiagabine and analogues into the open-to-out state model revealed a common binding mode. Additionally, our studies will be extended to the other hGAT subtypes so as to elucidate the secret of subtype selectivity of GABA Transporters.