Publications by authors named "Gerhard F Ecker"

144 Publications

Effects of Hydroxylated Mephedrone Metabolites on Monoamine Transporter Activity .

Front Pharmacol 2021 9;12:654061. Epub 2021 Apr 9.

Institute of Applied Synthetic Chemistry, TU Wien, Vienna, Austria.

Mephedrone is a largely abused psychostimulant. It elicits the release of monoamines via the high affinity transporters for dopamine (DAT), norepinephrine (NET) and serotonin (SERT). Stereoselective metabolic reactions are involved in the inactivation and the elimination of its chemical structure. However, during these processes, several structures are generated and some of them have been reported to be still pharmacologically active. In this study 1) we have newly synthetized several putative mephedrone metabolites, 2) compared their activity at monoamine transporters, 3) generated quantitative structure activity relationships, and 4) exploited the chemical structure of the putative metabolites to screen a urine sample from a drug user and dissect mephedrone metabolism. We have found that most of the tested metabolites are weak inhibitors of monoamine transporters and that all of them are more potent at DAT and NET in comparison to SERT. The only exception is represented by the COOH-metabolite which shows no pharmacological activity at all three monoamine transporters. The enantioselectivity of mephedrone and its metabolites is present mainly at SERT, with only minor effects at DAT and NET being introduced when the β-keto group is reduced to an OH-group. Importantly, while at DAT the putative metabolites did not show changes in inhibitory potencies, but rather changes in their substrate/blocker profile, at SERT they showed mainly changes in inhibitory potencies. Molecular modeling suggests that the hydrophobic nature of a specific SERT subpocket may be involved in such loss of affinity. Finally, the assessment of the putative metabolites in one urine sample of mephedrone user displayed two previously uncharacterized metabolites, 4-COOH-nor-mephedrone (4-COOH-MC) and dihydro-4- nor-mephedrone (dihydro-4-MC). These results confirm and expand previous studies highlighting the importance of the stereochemistry in the pharmacodynamics of phase-1 metabolites of mephedrone, established their structure-activity relationships at DAT, NET and SERT and pave the way for a systematic dissection of mephedrone metabolic routes. Given the number of structures found having residual and modified pharmacological profiles, these findings may help in understanding the complex subjective effects of administered mephedrone. Moreover, the dissection of mephedrone metabolic routes may help in developing new therapies for treating psychostimulants acute intoxications.
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http://dx.doi.org/10.3389/fphar.2021.654061DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8063026PMC
April 2021

Functional alterations by a subgroup of neonicotinoid pesticides in human dopaminergic neurons.

Arch Toxicol 2021 Mar 29. Epub 2021 Mar 29.

In Vitro Toxicology and Biomedicine, Department Inaugurated by the Doerenkamp-Zbinden Foundation, University of Konstanz, Universitaetsstr. 10, 78457, Konstanz, Germany.

Neonicotinoid pesticides, originally developed to target the insect nervous system, have been reported to interact with human receptors and to activate rodent neurons. Therefore, we evaluated in how far these compounds may trigger signaling in human neurons, and thus, affect the human adult or developing nervous system. We used SH-SY5Y neuroblastoma cells as established model of nicotinic acetylcholine receptor (nAChR) signaling. In parallel, we profiled dopaminergic neurons, generated from LUHMES neuronal precursor cells, as novel system to study nAChR activation in human post-mitotic neurons. Changes of the free intracellular Ca concentration ([Ca]) were used as readout, and key findings were confirmed by patch clamp recordings. Nicotine triggered typical neuronal signaling responses that were blocked by antagonists, such as tubocurarine and mecamylamine. Pharmacological approaches suggested a functional expression of α7 and non-α7 nAChRs on LUHMES cells. In this novel test system, the neonicotinoids acetamiprid, imidacloprid, clothianidin and thiacloprid, but not thiamethoxam and dinotefuran, triggered [Ca] signaling at 10-100 µM. Strong synergy of the active neonicotinoids (at low micromolar concentrations) with the α7 nAChR-positive allosteric modulator PNU-120596 was observed in LUHMES and SH-SY5Y cells, and specific antagonists fully inhibited such signaling. To provide a third line of evidence for neonicotinoid signaling via nAChR, we studied cross-desensitization: pretreatment of LUHMES and SH-SY5Y cells with active neonicotinoids (at 1-10 µM) blunted the signaling response of nicotine. The pesticides (at 3-30 µM) also blunted the response to the non-α7 agonist ABT 594 in LUHMES cells. These data show that human neuronal cells are functionally affected by low micromolar concentrations of several neonicotinoids. An effect of such signals on nervous system development is a toxicological concern.
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http://dx.doi.org/10.1007/s00204-021-03031-1DOI Listing
March 2021

COVER: conformational oversampling as data augmentation for molecules.

J Cheminform 2020 Mar 18;12(1):18. Epub 2020 Mar 18.

Department of Pharmaceutical Chemistry, University of Vienna, Althanstr 14, Vienna, Austria.

Training neural networks with small and imbalanced datasets often leads to overfitting and disregard of the minority class. For predictive toxicology, however, models with a good balance between sensitivity and specificity are needed. In this paper we introduce conformational oversampling as a means to balance and oversample datasets for prediction of toxicity. Conformational oversampling enhances a dataset by generation of multiple conformations of a molecule. These conformations can be used to balance, as well as oversample a dataset, thereby increasing the dataset size without the need of artificial samples. We show that conformational oversampling facilitates training of neural networks and provides state-of-the-art results on the Tox21 dataset.
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http://dx.doi.org/10.1186/s13321-020-00420-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7080709PMC
March 2020

ATP modulates SLC7A5 (LAT1) synergistically with cholesterol.

Sci Rep 2020 10 7;10(1):16738. Epub 2020 Oct 7.

Department of DiBEST (Biologia, Ecologia, Scienze Della Terra) Unit of Biochemistry and Molecular Biotechnology, University of Calabria, via Bucci 4C, 87036, Arcavacata di Rende, Italy.

The plasma membrane transporter hLAT1 is responsible for providing cells with essential amino acids. hLAT1 is over-expressed in virtually all human cancers making the protein a hot-spot in the fields of cancer and pharmacology research. However, regulatory aspects of hLAT1 biology are still poorly understood. A remarkable stimulation of transport activity was observed in the presence of physiological levels of cholesterol together with a selective increase of the affinity for the substrate on the internal site, suggesting a stabilization of the inward open conformation of hLAT1. A synergistic effect by ATP was also observed only in the presence of cholesterol. The same phenomenon was detected with the native protein. Altogether, the biochemical assays suggested that cholesterol and ATP binding sites are close to each other. The computational analysis identified two neighboring regions, one hydrophobic and one hydrophilic, to which cholesterol and ATP were docked, respectively. The computational data predicted interaction of the ϒ-phosphate of ATP with Lys 204, which was confirmed by site-directed mutagenesis. The hLAT1-K204Q mutant showed an impaired function and response to ATP. Interestingly, this residue is conserved in several members of the SLC7 family.
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http://dx.doi.org/10.1038/s41598-020-73757-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7541457PMC
October 2020

Exploring the molecular determinants for subtype-selectivity of 2-amino-1,4,5,6-tetrahydropyrimidine-5-carboxylic acid analogs as betaine/GABA transporter 1 (BGT1) substrate-inhibitors.

Sci Rep 2020 08 3;10(1):12992. Epub 2020 Aug 3.

Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, 2100, Copenhagen, Denmark.

We have previously identified 2-amino-1,4,5,6-tetrahydropyrimidine-5-carboxylic acid (ATPCA) as the most potent substrate-inhibitor of the betaine/GABA transporter 1 (BGT1) (IC 2.5 µM) reported to date. Herein, we characterize the binding mode of 20 novel analogs and propose the molecular determinants driving BGT1-selectivity. A series of N-, exocyclic-N-, and C-substituted analogs was synthesized and pharmacologically characterized in radioligand-based uptake assays at the four human GABA transporters (hGATs) recombinantly expressed in mammalian cells. Overall, the analogs retained subtype-selectivity for hBGT1, though with lower inhibitory activities (mid to high micromolar IC values) compared to ATPCA. Further characterization of five of these BGT1-active analogs in a fluorescence-based FMP assay revealed that the compounds are substrates for hBGT1, suggesting they interact with the orthosteric site of the transporter. In silico-guided mutagenesis experiments showed that the non-conserved residues Q299 and E52 in hBGT1 as well as the conformational flexibility of the compounds potentially contribute to the subtype-selectivity of ATPCA and its analogs. Overall, this study provides new insights into the molecular interactions governing the subtype-selectivity of BGT1 substrate-inhibitors. The findings may guide the rational design of BGT1-selective pharmacological tool compounds for future drug discovery.
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http://dx.doi.org/10.1038/s41598-020-69908-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7400577PMC
August 2020

Studies of structural determinants of substrate binding in the Creatine Transporter (CreaT, SLC6A8) using molecular models.

Sci Rep 2020 04 10;10(1):6241. Epub 2020 Apr 10.

University of Vienna, Department of Pharmaceutical Chemistry, Vienna, Austria.

Creatine is a crucial metabolite that plays a fundamental role in ATP homeostasis in tissues with high-energy demands. The creatine transporter (CreaT, SLC6A8) belongs to the solute carrier 6 (SLC6) transporters family, and more particularly to the GABA transporters (GATs) subfamily. Understanding the molecular determinants of specificity within the SLC6 transporters in general, and the GATs in particular is very challenging due to the high similarity of these proteins. In the study presented here, our efforts focused on finding key structural features involved in binding selectivity for CreaT using structure-based computational methods. Due to the lack of three-dimensional structures of SLC6A8, our approach was based on the realization of two reliable homology models of CreaT using the structures of two templates, i.e. the human serotonin transporter (hSERT) and the prokaryotic leucine transporter (LeuT). Our models reveal that an optimal complementarity between the shape of the binding site and the size of the ligands is necessary for transport. These findings provide a framework for a deeper understanding of substrate selectivity of the SLC6 family and other LeuT fold transporters.
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http://dx.doi.org/10.1038/s41598-020-63189-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7148354PMC
April 2020

Pharmacological Characterization of a Betaine/GABA Transporter 1 (BGT1) Inhibitor Displaying an Unusual Biphasic Inhibition Profile and Anti-seizure Effects.

Neurochem Res 2020 Jul 4;45(7):1551-1565. Epub 2020 Apr 4.

Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark.

Focal epileptic seizures can in some patients be managed by inhibiting γ-aminobutyric acid (GABA) uptake via the GABA transporter 1 (GAT1) using tiagabine (Gabitril®). Synergistic anti-seizure effects achieved by inhibition of both GAT1 and the betaine/GABA transporter (BGT1) by tiagabine and EF1502, compared to tiagabine alone, suggest BGT1 as a target in epilepsy. Yet, selective BGT1 inhibitors are needed for validation of this hypothesis. In that search, a series of BGT1 inhibitors typified by (1R,2S)-2-((4,4-bis(3-methylthiophen-2-yl)but-3-en-yl)(methyl)amino)cyclohexanecarboxylic acid (SBV2-114) was developed. A thorough pharmacological characterization of SBV2-114 using a cell-based [H]GABA uptake assay at heterologously expressed BGT1, revealed an elusive biphasic inhibition profile with two IC values (4.7 and 556 μM). The biphasic profile was common for this structural class of compounds, including EF1502, and was confirmed in the MDCK II cell line endogenously expressing BGT1. The possibility of two binding sites for SBV2-114 at BGT1 was assessed by computational docking studies and examined by mutational studies. These investigations confirmed that the conserved residue Q299 in BGT1 is involved in, but not solely responsible for the biphasic inhibition profile of SBV2-114. Animal studies revealed anti-seizure effects of SBV2-114 in two mouse models, supporting a function of BGT1 in epilepsy. However, as SBV2-114 is apparent to be rather non-selective for BGT1, the translational relevance of this observation is unknown. Nevertheless, SBV2-114 constitutes a valuable tool compound to study the molecular mechanism of an emerging biphasic profile of BGT1-mediated GABA transport and the putative involvement of two binding sites for this class of compounds.
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http://dx.doi.org/10.1007/s11064-020-03017-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7297817PMC
July 2020

A widespread role for SLC transmembrane transporters in resistance to cytotoxic drugs.

Nat Chem Biol 2020 04 9;16(4):469-478. Epub 2020 Mar 9.

CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.

Solute carriers (SLCs) are the largest family of transmembrane transporters in humans and are major determinants of cellular metabolism. Several SLCs have been shown to be required for the uptake of chemical compounds into cellular systems, but systematic surveys of transporter-drug relationships in human cells are currently lacking. We performed a series of genetic screens in a haploid human cell line against 60 cytotoxic compounds representative of the chemical space populated by approved drugs. By using an SLC-focused CRISPR-Cas9 library, we identified transporters whose absence induced resistance to the drugs tested. This included dependencies involving the transporters SLC11A2/SLC16A1 for artemisinin derivatives and SLC35A2/SLC38A5 for cisplatin. The functional dependence on SLCs observed for a significant proportion of the screened compounds suggests a widespread role for SLCs in the uptake and cellular activity of cytotoxic drugs and provides an experimentally validated set of SLC-drug associations for a number of clinically relevant compounds.
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http://dx.doi.org/10.1038/s41589-020-0483-3DOI Listing
April 2020

Using Machine Learning Methods and Structural Alerts for Prediction of Mitochondrial Toxicity.

Mol Inform 2020 05 23;39(5):e2000005. Epub 2020 Mar 23.

University of Vienna, Department of Pharmaceutical Chemistry, Althanstr. 14, 1090, Vienna, Austria.

Over the last few years more and more organ and idiosyncratic toxicities were linked to mitochondrial toxicity. Despite well-established assays, such as the seahorse and Glucose/Galactose assay, an in silico approach to mitochondrial toxicity is still feasible, particularly when it comes to the assessment of large compound libraries. Therefore, in silico approaches could be very beneficial to indicate hazards early in the drug development pipeline. By combining multiple endpoints, we derived the largest so far published dataset on mitochondrial toxicity. A thorough data analysis shows that molecules causing mitochondrial toxicity can be distinguished by physicochemical properties. Finally, the combination of machine learning and structural alerts highlights the suitability for in silico risk assessment of mitochondrial toxicity.
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http://dx.doi.org/10.1002/minf.202000005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7317375PMC
May 2020

Vienna LiverTox Workspace-A Set of Machine Learning Models for Prediction of Interactions Profiles of Small Molecules With Transporters Relevant for Regulatory Agencies.

Front Chem 2019 10;7:899. Epub 2020 Jan 10.

Pharmacoinformatics Research Group, Department of Pharmaceutical Chemistry, University of Vienna, Vienna, Austria.

Transporters expressed in the liver play a major role in drug pharmacokinetics and are a key component of the physiological bile flow. Inhibition of these transporters may lead to drug-drug interactions or even drug-induced liver injury. Therefore, predicting the interaction profile of small molecules with transporters expressed in the liver may help medicinal chemists and toxicologists to prioritize compounds in an early phase of the drug development process. Based on a comprehensive analysis of the data available in the public domain, we developed a set of classification models which allow to predict-for a small molecule-the inhibition of and transport by a set of liver transporters considered to be relevant by FDA, EMA, and the Japanese regulatory agency. The models were validated by cross-validation and external test sets and comprise cross validated balanced accuracies in the range of 0.64-0.88. Finally, models were implemented as an easy to use web-service which is freely available at https://livertox.univie.ac.at.
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http://dx.doi.org/10.3389/fchem.2019.00899DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6966498PMC
January 2020

Image Based Liver Toxicity Prediction.

J Chem Inf Model 2020 03 7;60(3):1111-1121. Epub 2020 Feb 7.

Department of Pharmaceutical Chemistry, University of Vienna, Althanstrasse 14, A-1090 Vienna, Austria.

The drugs we use to cure our diseases can cause damage to the liver as it is the primary organ responsible for metabolism of environmental chemicals and drugs. To identify and eliminate potentially problematic drug candidates in the early stages of drug discovery, in silico techniques provide quick and practical solutions for toxicity determination. Deep learning has emerged as one of the solutions in recent years in the field of pharmaceutical chemistry. Generally, in the case of small data sets as used in toxicology, these data-hungry algorithms are prone to overfitting. We approach the problem from two sides. First, we use images of the three-dimensional conformations and benefit from convolutional neural networks which have fewer parameters than the standard deep neural networks with similar depth. Using images allows connecting various chemical features to the geometry of the compounds. Second, we employ the method COVER to up-sample the data set. It is used not only for increasing the size of the data set, but also for balancing the two classes, i.e., toxic and not toxic. The proof of concept is performed on the p53 end point from the Tox21 data set. The results, which are compatible with the winners of the data challenge, encouraged us to use our methods to predict liver toxicity. We use the most extensive publicly available liver toxicity data set by Mulliner et al. and obtain a sensitivity of 0.79 and a specificity of 0.52. These results demonstrate the applicability of image based toxicity prediction using deep neural networks.
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http://dx.doi.org/10.1021/acs.jcim.9b00713DOI Listing
March 2020

Propafenone analogue with additional H-bond acceptor group shows increased inhibitory activity on P-glycoprotein.

Arch Pharm (Weinheim) 2020 Mar 9;353(3):e1900269. Epub 2020 Jan 9.

Department of Pharmaceutical Chemistry, University of Vienna, Vienna, Austria.

P-glycoprotein (P-gp) is an ATP-dependent efflux pump that has a marked impact on the absorption, distribution, and excretion of therapeutic drugs. As P-gp inhibition can result in drug-drug interactions and altered drug bioavailability, identifying molecular properties that are linked to inhibition is of great interest in drug development. In this study, we combined chemical synthesis, in vitro testing, quantitative structure-activity relationship analysis, and docking studies to investigate the role of hydrogen bond (H-bond) donor/acceptor properties in transporter-ligand interaction. In a previous work, it has been shown that propafenone analogs with a 4-hydroxy-4-piperidine moiety exhibit a generally 10-fold higher P-gp inhibitory activity than expected based on their lipophilicity. Here, we specifically expanded the data set by introducing substituents at position 4 of the 4-phenylpiperidine moiety to assess the importance of H-bond donor/acceptor features in this region. The results suggest that indeed an H-bond acceptor, such as hydroxy and methoxy, increases the affinity by forming a H-bond with Tyr310.
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http://dx.doi.org/10.1002/ardp.201900269DOI Listing
March 2020

Rigorous sampling of docking poses unveils binding hypothesis for the halogenated ligands of L-type Amino acid Transporter 1 (LAT1).

Sci Rep 2019 10 21;9(1):15061. Epub 2019 Oct 21.

Department of Pharmaceutical Chemistry, University of Vienna, Althanstrasse 14, 1090, Wien, Austria.

L-type Amino acid Transporter 1 (LAT1) plays a significant role in the growth and propagation of cancer cells by facilitating the cross-membrane transport of essential nutrients, and is an attractive drug target. Several halogen-containing L-phenylalanine-based ligands display high affinity and high selectivity for LAT1; nonetheless, their molecular mechanism of binding remains unclear. In this study, a combined in silico strategy consisting of homology modeling, molecular docking, and Quantum Mechanics-Molecular Mechanics (QM-MM) simulation was applied to elucidate the molecular basis of ligand binding in LAT1. First, a homology model of LAT1 based on the atomic structure of a prokaryotic homolog was constructed. Docking studies using a set of halogenated ligands allowed for deriving a binding hypothesis. Selected docking poses were subjected to QM-MM calculations to investigate the halogen interactions. Collectively, the results highlight the dual nature of the ligand-protein binding mode characterized by backbone hydrogen bond interactions of the amino acid moiety of the ligands and residues I63, S66, G67, F252, G255, as well as hydrophobic interactions of the ligand's side chains with residues I139, I140, F252, G255, F402, W405. QM-MM optimizations indicated that the electrostatic interactions involving halogens contribute to the binding free energy. Importantly, our results are in good agreement with the recently unraveled cryo-Electron Microscopy structures of LAT1.
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http://dx.doi.org/10.1038/s41598-019-51455-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6803698PMC
October 2019

A structural model of the human serotonin transporter in an outward-occluded state.

PLoS One 2019 28;14(6):e0217377. Epub 2019 Jun 28.

Computational Structural Biology Unit, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, United States of America.

The human serotonin transporter hSERT facilitates the reuptake of its endogenous substrate serotonin from the synaptic cleft into presynaptic neurons after signaling. Reuptake regulates the availability of this neurotransmitter and therefore hSERT plays an important role in balancing human mood conditions. In 2016, the first 3D structures of this membrane transporter were reported in an inhibitor-bound, outward-open conformation. These structures revealed valuable information about interactions of hSERT with antidepressant drugs. Nevertheless, the question remains how serotonin facilitates the specific conformational changes that open and close pathways from the synapse and to the cytoplasm as required for transport. Here, we present a serotonin-bound homology model of hSERT in an outward-occluded state, a key intermediate in the physiological cycle, in which the interactions with the substrate are likely to be optimal. Our approach uses two template structures and includes careful refinement and comprehensive computational validation. According to microsecond-long molecular dynamics simulations, this model exhibits interactions between the gating residues in the extracellular pathway, and these interactions differ from those in an outward-open conformation of hSERT bound to serotonin. Moreover, we predict several features of this state by monitoring the intracellular gating residues, the extent of hydration, and, most importantly, protein-ligand interactions in the central binding site. The results illustrate common and distinct characteristics of these two transporter states and provide a starting point for future investigations of the transport mechanism in hSERT.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0217377PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6599148PMC
February 2020

Structural and molecular aspects of betaine-GABA transporter 1 (BGT1) and its relation to brain function.

Neuropharmacology 2019 12 18;161:107644. Epub 2019 May 18.

University of Copenhagen, Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, 2 Universitetsparken, 2100, Copenhagen, Denmark. Electronic address:

ɣ-aminobutyric-acid (GABA) functions as the principal inhibitory neurotransmitter in the central nervous system. Imbalances in GABAergic neurotransmission are involved in the pathophysiology of various neurological diseases such as epilepsy, Alzheimer's disease and stroke. GABA transporters (GATs) facilitate the termination of GABAergic signaling by transporting GABA together with sodium and chloride from the synaptic cleft into presynaptic neurons and surrounding glial cells. Four different GATs have been identified that all belong to the solute carrier 6 (SLC6) transporter family: GAT1-3 (SLC6A1, SLC6A13, SLC6A11) and betaine/GABA transporter 1 (BGT1, SLC6A12). BGT1 has emerged as an interesting target for treating epilepsy due to animal studies that reported anticonvulsant effects for the GAT1/BGT1 selective inhibitor EF1502 and the BGT1 selective inhibitor RPC-425. However, the precise involvement of BGT1 in epilepsy remains elusive because of its controversial expression levels in the brain and the lack of highly selective and potent tool compounds. This review gathers the current structural and functional knowledge on BGT1 with emphasis on brain relevance, discusses all available compounds, and tries to shed light on the molecular determinants driving BGT1 selectivity. This article is part of the issue entitled 'Special Issue on Neurotransmitter Transporters'.
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http://dx.doi.org/10.1016/j.neuropharm.2019.05.021DOI Listing
December 2019

para-Trifluoromethyl-methcathinone is an allosteric modulator of the serotonin transporter.

Neuropharmacology 2019 12 24;161:107615. Epub 2019 Apr 24.

Institute of Pharmacology, Medical University, Vienna, Austria. Electronic address:

The transporters for dopamine (DAT) and serotonin (SERT) are important targets in the treatment of psychiatric disorders including major depression, anxiety and attention-deficit hyperactivity disorder. Drugs acting at these transporters can act as inhibitors or as releasers. In addition, it has been recently appreciated that some compounds are less efficacious releasers than amphetamine. Thus, they are classified as partial releasers. Compounds can act on both SERT and DAT or display exquisite selectivity for either SERT or DAT, but the structural basis for selectivity is poorly understood. The trifluoromethyl-substitution of methcathinone in the para-position has been shown to dramatically shift the selectivity of methcathinone (MCAT) towards SERT. Here, we examined MCAT, para-trifluoromethyl-methcathinone (pCFMCAT) and other analogues to understand (i) the determinants of selectivity and (ii) the effects of the para-CF-substitution of MCAT on the transport cycle. We systematically tested different para-substituted MCATs by biochemical, computational and electrophysiological approaches: addition of the pCFgroup, but not of other substituents with larger van der Waal's volume, lipophilicity or polarity, converted the DAT-selective MCAT into a SERT-selective partial releaser. Electrophysiological and superfusion experiments, together with kinetic modelling, showed that pCFMCAT, but not MCAT, trapped a fraction of SERTs in an inactive state by occupying the S2-site. These findings define a new mechanism of action for partial releasers, which is distinct from the other two known binding modes underlying partial release. Our observations highlight the fact that the substrate permeation pathway of monoamine transporters supports multiple binding modes, which can be exploited for drug design. This article is part of the issue entitled 'Special Issue on Neurotransmitter Transporters'.
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http://dx.doi.org/10.1016/j.neuropharm.2019.04.021DOI Listing
December 2019

In Silico Approaches to Predict Drug-Transporter Interaction Profiles: Data Mining, Model Generation, and Link to Cholestasis.

Methods Mol Biol 2019 ;1981:383-396

Department of Pharmaceutical Chemistry, University of Vienna, Althanstrasse 14, Vienna, 1090, Austria.

Transport proteins play a crucial role in drug distribution, disposition, and clearance by mediating cellular drug influx and efflux. Inhibition of these transporters may lead to drug-drug interactions or even drug-induced liver injury, such as cholestasis, which comprises a major challenge in drug development process. Thus, computer-based (in silico) models that can predict the pharmacological and toxicological profiles of these small molecules with respect to liver transporters may help in the early prioritization of compounds and hence may lower the high attrition rates. In this chapter, we provide a protocol for in silico prediction of cholestasis by generating validated predictive models. In addition to the two-dimensional molecular descriptors, we include transporter inhibition predictions as descriptors and evaluate the influence of the same on the performance of the cholestasis models.
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http://dx.doi.org/10.1007/978-1-4939-9420-5_26DOI Listing
August 2019

Discovery of Potent Inhibitors for the Large Neutral Amino Acid Transporter 1 (LAT1) by Structure-Based Methods.

Int J Mol Sci 2018 Dec 21;20(1). Epub 2018 Dec 21.

Department of Pharmaceutical Chemistry, University of Vienna, Althanstrasse 14, 1090 Wien, Austria.

The large neutral amino acid transporter 1 (LAT1) is a promising anticancer target that is required for the cellular uptake of essential amino acids that serve as building blocks for cancer growth and proliferation. Here, we report a structure-based approach to identify chemically diverse and potent inhibitors of LAT1. First, a homology model of LAT1 that is based on the atomic structures of the prokaryotic homologs was constructed. Molecular docking of nitrogen mustards (NMs) with a wide range of affinity allowed for deriving a common binding mode that could explain the structure-activity relationship pattern in NMs. Subsequently, validated binding hypotheses were subjected to molecular dynamics simulation, which allowed for extracting a set of dynamic pharmacophores. Finally, a library of ~1.1 million molecules was virtually screened against these pharmacophores, followed by docking. Biological testing of the 30 top-ranked hits revealed 13 actives, with the best compound showing an IC value in the sub-μM range.
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http://dx.doi.org/10.3390/ijms20010027DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6337383PMC
December 2018

Predicting Residence Time and Drug Unbinding Pathway through Scaled Molecular Dynamics.

J Chem Inf Model 2019 01 13;59(1):535-549. Epub 2018 Dec 13.

Department of Pharmacy and Biotechnology , Alma Mater Studiorum-Università di Bologna , via Belmeloro 6 , I-40126 Bologna , Italy.

Computational approaches currently assist medicinal chemistry through the entire drug discovery pipeline. However, while several computational tools and strategies are available to predict binding affinity, predicting the drug-target binding kinetics is still a matter of ongoing research. Here, we challenge scaled molecular dynamics simulations to assess the off-rates for a series of structurally diverse inhibitors of the heat shock protein 90 (Hsp90) covering 3 orders of magnitude in their experimental residence times. The derived computational predictions are in overall good agreement with experimental data. Aside from the estimation of exit times, unbinding pathways were assessed through dimensionality reduction techniques. The data analysis framework proposed in this work could lead to better understanding of the mechanistic aspects related to the observed kinetic behavior.
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http://dx.doi.org/10.1021/acs.jcim.8b00614DOI Listing
January 2019

GRAIL: GRids of phArmacophore Interaction fieLds.

J Chem Theory Comput 2018 Sep 20;14(9):4958-4970. Epub 2018 Aug 20.

Inte:Ligand GmbH , Mariahilferstrasse 74B/11 , A-1070 Vienna , Austria.

In the absence of experimentally derived, three-dimensional structures of receptors in complex with active ligands, it is of high value to be able to gain knowledge about energetically favorable interaction sites solely from the structure of the receptor binding site. For de novo ligand design as well as for lead optimization, this information retrieved from the protein is inevitable. The herein presented method called GRAIL combines the advantages of traditional grid-based approaches for the identification of interaction sites and the power of the pharmacophore concept. A reduced pharmacophoric abstraction of the target system enables the computation of all relevant interaction grid maps in short amounts of time. This allows one to extend the utility of a grid-based method for the analysis of large amounts of coordinate sets obtained by long-time MD simulations. In this way it is possible to assess conformation dependent characteristics of key interactions over time. Furthermore, conformational changes of the protein can be taken into account easily and information thus obtained well-guides a rational ligand design process. A study employing MD trajectories of the oncology target heat shock protein 90 showcases how well our novel approach GRAIL performs for a set of different inhibitors bound to their target protein and how molecular features of the inhibitors are subject to optimization.
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http://dx.doi.org/10.1021/acs.jctc.8b00495DOI Listing
September 2018

SAR-Guided Scoring Function and Mutational Validation Reveal the Binding Mode of CGS-8216 at the α1+/γ2- Benzodiazepine Site.

J Chem Inf Model 2018 08 8;58(8):1682-1696. Epub 2018 Aug 8.

Department of Pharmaceutical Chemistry , University of Vienna , Althanstrasse 14 , 1090 Vienna , Austria.

The structural resolution of a bound ligand-receptor complex is a key asset to efficiently drive lead optimization in drug design. However, structural resolution of many drug targets still remains a challenging endeavor. In the absence of structural knowledge, scientists resort to structure-activity relationships (SARs) to promote compound development. In this study, we incorporated ligand-based knowledge to formulate a docking scoring function that evaluates binding poses for their agreement with a known SAR. We showcased this protocol by identifying the binding mode of the pyrazoloquinolinone (PQ) CGS-8216 at the benzodiazepine binding site of the GABA receptor. Further evaluation of the final pose by molecular dynamics and free energy simulations revealed a close proximity between the pendent phenyl ring of the PQ and γ2D56, congruent with the low potency of carboxyphenyl analogues. Ultimately, we introduced the γ2D56A mutation and in fact observed a 10-fold potency increase in the carboxyphenyl analogue, providing experimental evidence in favor of our binding hypothesis.
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http://dx.doi.org/10.1021/acs.jcim.8b00199DOI Listing
August 2018

Interspecies comparison of putative ligand binding sites of human, rat and mouse P-glycoprotein.

Eur J Pharm Sci 2018 Sep 22;122:134-143. Epub 2018 Jun 22.

University of Vienna, Department of Pharmaceutical Chemistry, Althanstrasse 14, 1090 Vienna, Austria. Electronic address:

Prior to the clinical phases of testing, safety, efficacy and pharmacokinetic profiles of lead compounds are evaluated in animal studies. These tests are primarily performed in rodents, such as mouse and rats. In order to reduce the number of animal experiments, computational models that predict the outcome of these studies and thus aid in prioritization of preclinical candidates are heavily needed. However, although computational models for human off-target interactions with decent quality are available, they cannot easily be transferred to rodents due to lack of respective data. In this study, we assess the transferability of human P-glycoprotein activity data for development of in silico models to predict in vivo effects in rats and mouse using a structure-based approach. P-glycoprotein (P-gp) is an ATP-dependent efflux transporter that transports xenobiotic compounds such as toxins and drugs out of cells and has a broad substrate and inhibitor specificity. Being mostly expressed at barriers, it influences the bioavailability of drugs and thus contributes also to toxicity. Comparison of the binding site interaction profiles of human, rat and mouse P-gp derived from docking studies with a set of common inhibitors suggests that the inhibitors share potentially similar binding modes. These findings encourage the use of in vitro human P-gp data for predicting in vivo effects in rodents and thus contributes to the 3Rs (Replace, Reduce and Refine) of animal experiments.
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http://dx.doi.org/10.1016/j.ejps.2018.06.022DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6422297PMC
September 2018

Predicting drug resistance related to ABC transporters using unsupervised Consensus Self-Organizing Maps.

Sci Rep 2018 05 1;8(1):6803. Epub 2018 May 1.

University of Vienna, Department of Pharmaceutical Chemistry, Althanstrasse 14, 1090, Vienna, Austria.

ATP binding cassette (ABC) transporters play a pivotal role in drug elimination, particularly on several types of cancer in which these proteins are overexpressed. Due to their promiscuous ligand recognition, building computational models for substrate classification is quite challenging. This study evaluates the use of modified Self-Organizing Maps (SOM) for predicting drug resistance associated with P-gp, MPR1 and BCRP activity. Herein, we present a novel multi-labelled unsupervised classification model which combines a new clustering algorithm with SOM. It significantly improves the accuracy of substrates classification, catching up with traditional supervised machine learning algorithms. Results can be applied to predict the pharmacological profile of new drug candidates during the drug development process.
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http://dx.doi.org/10.1038/s41598-018-25235-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5931609PMC
May 2018

Ligand Desolvation Steers On-Rate and Impacts Drug Residence Time of Heat Shock Protein 90 (Hsp90) Inhibitors.

J Med Chem 2018 05 10;61(10):4397-4411. Epub 2018 May 10.

Department of Pharmaceutical Chemistry , University of Vienna , UZA 2, Althanstrasse 14 , 1090 Vienna , Austria.

Residence time and more recently the association rate constant k are increasingly acknowledged as important parameters for in vivo efficacy and safety of drugs. However, their broader consideration in drug development is limited by a lack of knowledge of how to optimize these parameters. In this study on a set of 176 heat shock protein 90 inhibitors, structure-kinetic relationships, X-ray crystallography, and molecular dynamics simulations were combined to retrieve a concrete scheme of how to rationally slow down on-rates. We discovered that an increased ligand desolvation barrier by introducing polar substituents resulted in a significant k decrease. The slowdown was accomplished by introducing polar moieties to those parts of the ligand that point toward a hydrophobic cavity. We validated this scheme by increasing polarity of three Hsp90 inhibitors and observed a 9-, 13-, and 45-fold slowdown of on-rates and a 9-fold prolongation in residence time. This prolongation was driven by transition state destabilization rather than ground state stabilization.
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http://dx.doi.org/10.1021/acs.jmedchem.8b00080DOI Listing
May 2018

Insights into the Structure, Function, and Ligand Discovery of the Large Neutral Amino Acid Transporter 1, LAT1.

Int J Mol Sci 2018 Apr 24;19(5). Epub 2018 Apr 24.

Department of Pharmaceutical Chemistry, University of Vienna, Althanstrasse 14, 1090 Wien, Austria.

The large neutral amino acid transporter 1 (LAT1, or SLC7A5) is a sodium- and pH-independent transporter, which supplies essential amino acids (e.g., leucine, phenylalanine) to cells. It plays an important role at the Blood⁻Brain Barrier (BBB) where it facilitates the transport of thyroid hormones, pharmaceuticals (e.g., l-DOPA, gabapentin), and metabolites into the brain. Moreover, its expression is highly upregulated in various types of human cancer that are characterized by an intense demand for amino acids for growth and proliferation. Therefore, LAT1 is believed to be an important drug target for cancer treatment. With the crystallization of the arginine/agmatine antiporter (AdiC) from , numerous homology models of LAT1 have been built to elucidate the substrate binding site, ligand⁻transporter interaction, and structure⁻function relationship. The use of these models in combination with molecular docking and experimental testing has identified novel chemotypes of ligands of LAT1. Here, we highlight the structure, function, transport mechanism, and homology modeling of LAT1. Additionally, results from structure⁻function studies performed on LAT1 are addressed, which have enhanced our knowledge of the mechanism of substrate binding and translocation. This is followed by a discussion on ligand- and structure-based approaches, with an emphasis on elucidating the molecular basis of LAT1 inhibition. Finally, we provide an exhaustive summary of different LAT1 inhibitors that have been identified so far, including the recently discovered irreversible covalent inhibitors.
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http://dx.doi.org/10.3390/ijms19051278DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5983779PMC
April 2018

Comparing the performance of meta-classifiers-a case study on selected imbalanced data sets relevant for prediction of liver toxicity.

J Comput Aided Mol Des 2018 05 6;32(5):583-590. Epub 2018 Apr 6.

Department of Pharmaceutical Chemistry, University of Vienna, Althanstrasse 14, 1090, Vienna, Austria.

Cheminformatics datasets used in classification problems, especially those related to biological or physicochemical properties, are often imbalanced. This presents a major challenge in development of in silico prediction models, as the traditional machine learning algorithms are known to work best on balanced datasets. The class imbalance introduces a bias in the performance of these algorithms due to their preference towards the majority class. Here, we present a comparison of the performance of seven different meta-classifiers for their ability to handle imbalanced datasets, whereby Random Forest is used as base-classifier. Four different datasets that are directly (cholestasis) or indirectly (via inhibition of organic anion transporting polypeptide 1B1 and 1B3) related to liver toxicity were chosen for this purpose. The imbalance ratio in these datasets ranges between 4:1 and 20:1 for negative and positive classes, respectively. Three different sets of molecular descriptors for model development were used, and their performance was assessed in 10-fold cross-validation and on an independent validation set. Stratified bagging, MetaCost and CostSensitiveClassifier were found to be the best performing among all the methods. While MetaCost and CostSensitiveClassifier provided better sensitivity values, Stratified Bagging resulted in high balanced accuracies.
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http://dx.doi.org/10.1007/s10822-018-0116-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5919997PMC
May 2018

Translation Termination Factor GSPT1 Is a Phenotypically Relevant Off-Target of Heterobifunctional Phthalimide Degraders.

ACS Chem Biol 2018 03 29;13(3):553-560. Epub 2018 Jan 29.

CeMM Research Center for Molecular Medicine of the Austrian Academy of Science , Lazarettgasse 14, AKH Bt. 25.3 , 1090 Vienna , Austria.

Protein degradation is an emerging therapeutic strategy with a unique molecular pharmacology that enables the disruption of all functions associated with a target. This is particularly relevant for proteins depending on molecular scaffolding, such as transcription factors or receptor tyrosine kinases (RTKs). To address tractability of multiple RTKs for chemical degradation by the E3 ligase CUL4-RBX1-DDB1-CRBN (CRL4), we synthesized a series of phthalimide degraders based on the promiscuous kinase inhibitors sunitinib and PHA665752. While both series failed to induce degradation of their consensus targets, individual molecules displayed pronounced efficacy in leukemia cell lines. Orthogonal target identification supported by molecular docking led us to identify the translation termination factor G1 to S phase transition 1 (GSPT1) as a converging off-target, resulting from inadvertent E3 ligase modulation. This research highlights the importance of monitoring degradation events that are independent of the respective targeting ligand as a unique feature of small-molecule degraders.
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http://dx.doi.org/10.1021/acschembio.7b00969DOI Listing
March 2018

Legacy data sharing to improve drug safety assessment: the eTOX project.

Nat Rev Drug Discov 2017 Dec 13;16(12):811-812. Epub 2017 Oct 13.

Universitat Politècnica de València, 46022 València, Spain.

The sharing of legacy preclinical safety data among pharmaceutical companies and its integration with other information sources offers unprecedented opportunities to improve the early assessment of drug safety. Here, we discuss the experience of the eTOX project, which was established through the Innovative Medicines Initiative to explore this possibility.
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http://dx.doi.org/10.1038/nrd.2017.177DOI Listing
December 2017

Structure-Activity Relationship, Pharmacological Characterization, and Molecular Modeling of Noncompetitive Inhibitors of the Betaine/γ-Aminobutyric Acid Transporter 1 (BGT1).

J Med Chem 2017 11 19;60(21):8834-8846. Epub 2017 Oct 19.

Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen , 2100 Copenhagen, Denmark.

N-(1-Benzyl-4-piperidinyl)-2,4-dichlorobenzamide 5 (BPDBA) is a noncompetitive inhibitor of the betaine/GABA transporter 1 (BGT1). We here report the synthesis and structure-activity relationship of 71 analogues. We identify 26m as a more soluble 2,4-Cl substituted 3-pyridine analogue with retained BGT1 activity and an improved off-target profile compared to 5. We performed radioligand-based uptake studies at chimeric constructs between BGT1 and GAT3, experiments with site-directed mutated transporters, and computational docking in a BGT1 homology model based on the newly determined X-ray crystal structure of the human serotonin transporter (hSERT). On the basis of these experiments, we propose a binding mode involving residues within TM10 in an allosteric site in BGT1 that corresponds to the allosteric binding pocket revealed by the hSERT crystal structure. Our study provides first insights into a proposed allosteric binding pocket in BGT1, which accommodates the binding site for a series of novel noncompetitive inhibitors.
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http://dx.doi.org/10.1021/acs.jmedchem.7b00924DOI Listing
November 2017

Development of Non-GAT1-Selective Inhibitors: Challenges and Achievements.

Adv Neurobiol 2017 ;16:315-332

Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Universitetsparken 2, 2100, Copenhagen, Denmark.

γ-Aminobutyric acid (GABA) neurotransmission is terminated by the GABA transporters (GATs) via uptake of GABA into neurons and surrounding glial cells. Four different transporters have been identified: GAT1, GAT2, GAT3, and the betaine/GABA transporter 1 (BGT1). The GAT1 subtype is the most explored transporter due to its high abundance in the brain and the existence of selective and potent GAT1 inhibitors. Consequently, less is known about the role and therapeutic potential of the non-GAT1 subtypes. Emerging pharmacological evidence suggests that some of these transporters pose interesting targets in several brain disorders. Pharmacological non-GAT1-selective tool compounds are important to further investigate the involvement of GATs in different pathological conditions. Extensive medicinal chemistry efforts have been put into the development of subtype-selective inhibitors, but truly selective and potent inhibitors of non-GAT1 subtypes are still limited. This review covers the advances within the medicinal chemistry area and the structural basis for obtaining non-GAT1-selective inhibitors.
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http://dx.doi.org/10.1007/978-3-319-55769-4_16DOI Listing
September 2018