| 1. |
- Burggraaff, Lindsey, et al.
(författare)
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Successive Statistical and Structure-Based Modeling to Identify Chemically Novel Kinase Inhibitors
- 2020
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Ingår i: Journal of Chemical Information and Modeling. - : AMER CHEMICAL SOC. - 1549-9596 .- 1549-960X. ; 60:9, s. 4283-4295
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Tidskriftsartikel (refereegranskat)abstract
- Kinases are frequently studied in the context of anticancer drugs. Their involvement in cell responses, such as proliferation, differentiation, and apoptosis, makes them interesting subjects in multitarget drug design. In this study, a workflow is presented that models the bioactivity spectra for two panels of kinases: (1) inhibition of RET, BRAF, SRC, and S6K, while avoiding inhibition of MKNK1, TTK, ERK8, PDK1, and PAK3, and (2) inhibition of AURKA, PAK1, FGFR1, and LKB1, while avoiding inhibition of PAK3, TAK1, and PIK3CA. Both statistical and structure-based models were included, which were thoroughly benchmarked and optimized. A virtual screening was performed to test the workflow for one of the main targets, RET kinase. This resulted in 5 novel and chemically dissimilar RET inhibitors with remaining RET activity of <60% (at a concentration of 10 mu M) and similarities with known RET inhibitors from 0.18 to 0.29 (Tanimoto, ECFP6). The four more potent inhibitors were assessed in a concentration range and proved to be modestly active with a pIC(50) value of 5.1 for the most active compound. The experimental validation of inhibitors for RET strongly indicates that the multitarget workflow is able to detect novel inhibitors for kinases, and hence, this workflow can potentially be applied in polypharmacology modeling. We conclude that this approach can identify new chemical matter for existing targets. Moreover, this workflow can easily be applied to other targets as well.
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| 2. |
- Béquignon, Olivier J. M., et al.
(författare)
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Collaborative SAR Modeling and Prospective In Vitro Validation of Oxidative Stress Activation in Human HepG2 Cells
- 2023
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Ingår i: Journal of Chemical Information and Modeling. - : American Chemical Society (ACS). - 1549-9596 .- 1549-960X. ; 63:17, s. 5433-5445
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Tidskriftsartikel (refereegranskat)abstract
- Oxidative stress is the consequence of an abnormal increase of reactive oxygen species (ROS). ROS are generated mainly during the metabolism in both normal and pathological conditions as well as from exposure to xenobiotics. Xenobiotics can, on the one hand, disrupt molecular machinery involved in redox processes and, on the other hand, reduce the effectiveness of the antioxidant activity. Such dysregulation may lead to oxidative damage when combined with oxidative stress overpassing the cell capacity to detoxify ROS. In this work, a green fluorescent protein (GFP)-tagged nuclear factor erythroid 2-related factor 2 (NRF2)-regulated sulfiredoxin reporter (Srxn1-GFP) was used to measure the antioxidant response of HepG2 cells to a large series of drug and drug-like compounds (2230 compounds). These compounds were then classified as positive or negative depending on cellular response and distributed among different modeling groups to establish structure-activity relationship (SAR) models. A selection of models was used to prospectively predict oxidative stress induced by a new set of compounds subsequently experimentally tested to validate the model predictions. Altogether, this exercise exemplifies the different challenges of developing SAR models of a phenotypic cellular readout, model combination, chemical space selection, and results interpretation.
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| 3. |
- Gao, Yongzhi, et al.
(författare)
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Potent Inhibition of Nicotinamide N-Methyltransferase by Alkene-Linked Bisubstrate Mimics Bearing Electron Deficient Aromatics
- 2021
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Ingår i: Journal of Medicinal Chemistry. - : American Chemical Society (ACS). - 0022-2623 .- 1520-4804. ; 64:17, s. 12938-12963
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Tidskriftsartikel (refereegranskat)abstract
- Nicotinamide N-methyltransferase (NNMT) methylates nicotinamide (vitamin B3) to generate 1-methylnicotinamide (MNA). NNMT overexpression has been linked to a variety of diseases, most prominently human cancers, indicating its potential as a therapeutic target. The development of small-molecule NNMT inhibitors has gained interest in recent years, with the most potent inhibitors sharing structural features based on elements of the nicotinamide substrate and the S-adenosyl-L-methionine (SAM) cofactor. We here report the development of new bisubstrate inhibitors that include electron-deficient aromatic groups to mimic the nicotinamide moiety. In addition, a trans-alkene linker was found to be optimal for connecting the substrate and cofactor mimics in these inhibitors. The most potent NNMT inhibitor identified exhibits an IC50 value of 3.7 nM, placing it among the most active NNMT inhibitors reported to date. Complementary analytical techniques, modeling studies, and cell-based assays provide insights into the binding mode, affinity, and selectivity of these inhibitors.
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| 4. |
- Tehrani, Kamaleddin H. M. E., et al.
(författare)
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Novel Cephalosporin Conjugates Display Potent and Selective Inhibition of Imipenemase-Type Metallo-beta-Lactamases
- 2021
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Ingår i: Journal of Medicinal Chemistry. - : American Chemical Society (ACS). - 0022-2623 .- 1520-4804. ; 64:13, s. 9141-9151
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Tidskriftsartikel (refereegranskat)abstract
- In an attempt to exploit the hydrolytic mechanism by which beta-lactamases degrade cephalosporins, we designed and synthesized a series of novel cephalosporin prodrugs aimed at delivering thiol-based inhibitors of metallo-beta-lactamases (MBLs) in a spatiotemporally controlled fashion. While enzymatic hydrolysis of the beta-lactam ring was observed, it was not accompanied by inhibitor release. Nonetheless, the cephalosporin prodrugs, especially thiomandelic acid conjugate (8), demonstrated potent inhibition of IMP-type MBLs. In addition, conjugate 8 was also found to greatly reduce the minimum inhibitory concentration of meropenem against IMP-producing bacteria. The results of kinetic experiments indicate that these prodrugs inhibit IMP-type MBLs by acting as slowly turned-over substrates. Structure-activity relationship studies revealed that both phenyl and carboxyl moieties of 8 are crucial for its potency. Furthermore, modeling studies indicate that productive interactions of the thiomandelic acid moiety of 8 with Trp28 within the IMP active site may contribute to its potency and selectivity.
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| 5. |
- Jespers, Willem, et al.
(författare)
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Deciphering conformational selectivity in the A(2A) adenosine G protein-coupled receptor by free energy simulations
- 2021
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Ingår i: PloS Computational Biology. - : Public Library of Science (PLoS). - 1553-734X .- 1553-7358. ; 17:11
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Tidskriftsartikel (refereegranskat)abstract
- Transmembranal G Protein-Coupled Receptors (GPCRs) transduce extracellular chemical signals to the cell, via conformational change from a resting (inactive) to an active (canonically bound to a G-protein) conformation. Receptor activation is normally modulated by extracellular ligand binding, but mutations in the receptor can also shift this equilibrium by stabilizing different conformational states. In this work, we built structure-energetic relationships of receptor activation based on original thermodynamic cycles that represent the conformational equilibrium of the prototypical A(2A) adenosine receptor (AR). These cycles were solved with efficient free energy perturbation (FEP) protocols, allowing to distinguish the pharmacological profile of different series of A(2A)AR agonists with different efficacies. The modulatory effects of point mutations on the basal activity of the receptor or on ligand efficacies could also be detected. This methodology can guide GPCR ligand design with tailored pharmacological properties, or allow the identification of mutations that modulate receptor activation with potential clinical implications.
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| 6. |
- Jespers, Willem, et al.
(författare)
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Structural Mapping of Adenosine Receptor Mutations : Ligand Binding and Signaling Mechanisms
- 2018
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Ingår i: TIPS - Trends in Pharmacological Sciences. - : Elsevier BV. - 0165-6147 .- 1873-3735. ; 39:1, s. 75-89
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Forskningsöversikt (refereegranskat)abstract
- The four adenosine receptors (ARs), A(1), A(2A), A(2B), and A(3), constitute a subfamily of G protein-coupled receptors (GPCRs) with exceptional foundations for structure-based ligand design. The vast amount of mutagenesis data, accumulated in the literature since the 1990s, has been recently supplemented with structural information, currently consisting of several inactive and active structures of the A(2A) and inactive conformations of the A(1) ARs. We provide the first integrated view of the pharmacological, biochemical, and structural data available for this receptor family, by mapping onto the relevant crystal structures all site-directed mutagenesis data, curated and deposited at the GPCR database (available through http://www.gpcrdb.org). This analysis provides novel insights into ligand binding, allosteric modulation, and signaling of the AR family.
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| 7. |
- Martens, Marvin, et al.
(författare)
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ELIXIR and Toxicology : a community in development
- 2021
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Ingår i: F1000 Research. - : F1000 Research Ltd. - 2046-1402. ; 10, s. 1129-1129
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Tidskriftsartikel (refereegranskat)abstract
- Toxicology has been an active research field for many decades, with academic, industrial and government involvement. Modern omics and computational approaches are changing the field, from merely disease-specific observational models into target-specific predictive models. Traditionally, toxicology has strong links with other fields such as biology, chemistry, pharmacology and medicine. With the rise of synthetic and new engineered materials, alongside ongoing prioritisation needs in chemical risk assessment for existing chemicals, early predictive evaluations are becoming of utmost importance to both scientific and regulatory purposes. ELIXIR is an intergovernmental organisation that brings together life science resources from across Europe. To coordinate the linkage of various life science efforts around modern predictive toxicology, the establishment of a new ELIXIR Community is seen as instrumental. In the past few years, joint efforts, building on incidental overlap, have been piloted in the context of ELIXIR. For example, the EU-ToxRisk, diXa, HeCaToS, transQST, and the nanotoxicology community have worked with the ELIXIR TeSS, Bioschemas, and Compute Platforms and activities. In 2018, a core group of interested parties wrote a proposal, outlining a sketch of what this new ELIXIR Toxicology Community would look like. A recent workshop (held September 30th to October 1st, 2020) extended this into an ELIXIR Toxicology roadmap and a shortlist of limited investment-high gain collaborations to give body to this new community. This Whitepaper outlines the results of these efforts and defines our vision of the ELIXIR Toxicology Community and how it complements other ELIXIR activities.
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| 8. |
- Tuerkova, Alzbeta, et al.
(författare)
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Identifying Novel Inhibitors for Hepatic Organic Anion Transporting Polypeptides by Machine Learning-Based Virtual Screening
- 2022
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Ingår i: Journal of Chemical Information and Modeling. - : American Chemical Society (ACS). - 1549-9596 .- 1549-960X. ; 62:24, s. 6323-6335
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Tidskriftsartikel (refereegranskat)abstract
- Integration of statistical learning methods with structure-based modeling approaches is a contemporary strategy to identify novel lead compounds in drug discovery. Hepatic organic anion transporting polypeptides (OATP1B1, OATP1B3, and OATP2B1) are classical off-targets, and it is well recognized that their ability to interfere with a wide range of chemically unrelated drugs, environmental chemicals, or food additives can lead to unwanted adverse effects like liver toxicity and drug-drug or drug-food interactions. Therefore, the identification of novel (tool) compounds for hepatic OATPs by virtual screening approaches and subsequent experimental validation is a major asset for elucidating structure-function relationships of (related) transporters: they enhance our understanding about molecular determinants and structural aspects of hepatic OATPs driving ligand binding and selectivity. In the present study, we performed a consensus virtual screening approach by using different types of machine learning models (proteochemometric models, conformal prediction models, and XGBoost models for hepatic OATPs), followed by molecular docking of preselected hits using previously established structural models for hepatic OATPs. Screening the diverse REAL drug-like set (Enamine) shows a comparable hit rate for OATP1B1 (36% actives) and OATP1B3 (32% actives), while the hit rate for OATP2B1 was even higher (66% actives). Percentage inhibition values for 44 selected compounds were determined using dedicated in vitro assays and guided the prioritization of several highly potent novel hepatic OATP inhibitors: six (strong) OATP2B1 inhibitors (IC50 values ranging from 0.04 to 6 μM), three OATP1B1 inhibitors (2.69 to 10 μM), and five OATP1B3 inhibitors (1.53 to 10 μM) were identified. Strikingly, two novel OATP2B1 inhibitors were uncovered (C7 and H5) which show high affinity (IC50 values: 40 nM and 390 nM) comparable to the recently described estrone-based inhibitor (IC50 = 41 nM). A molecularly detailed explanation for the observed differences in ligand binding to the three transporters is given by means of structural comparison of the detected binding sites and docking poses.
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| 9. |
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| 10. |
- Wang, Xuesong, et al.
(författare)
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Identification of V6.51L as a selectivity hotspot in stereoselective A(2B) adenosine receptor antagonist recognition
- 2021
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Ingår i: Scientific Reports. - : Springer Nature. - 2045-2322. ; 11
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Tidskriftsartikel (refereegranskat)abstract
- The four adenosine receptors (ARs) A(1)AR, A(2A)AR, A(2B)AR(,) and A(3)AR are G protein-coupled receptors (GPCRs) for which an exceptional amount of experimental and structural data is available. Still, limited success has been achieved in getting new chemical modulators on the market. As such, there is a clear interest in the design of novel selective chemical entities for this family of receptors. In this work, we investigate the selective recognition of ISAM-140, a recently reported A(2B)AR reference antagonist. A combination of semipreparative chiral HPLC, circular dichroism and X-ray crystallography was used to separate and unequivocally assign the configuration of each enantiomer. Subsequently affinity evaluation for both A(2A) and A(2B) receptors demonstrate the stereospecific and selective recognition of (S)-ISAM140 to the A(2B)AR. The molecular modeling suggested that the structural determinants of this selectivity profile would be residue V250(6.51) in A(2B)AR, which is a leucine in all other ARs including the closely related A(2A)AR. This was herein confirmed by radioligand binding assays and rigorous free energy perturbation (FEP) calculations performed on the L249V(6.51) mutant A(2A)AR receptor. Taken together, this study provides further insights in the binding mode of these A(2B)AR antagonists, paving the way for future ligand optimization.
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