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  • 1.
    Azuaje, Jhonny
    et al.
    Univ Santiago de Compostela, Ctr Singular Invest Quim Biol & Mat Mol CIQUS, Santiago De Compostela 15782, Spain.;Univ Santiago de Compostela, Fac Farm, Dept Quim Organ, Santiago De Compostela 15782, Spain..
    Jespers, Willem
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Yaziji, Vicente
    Univ Santiago de Compostela, Ctr Singular Invest Quim Biol & Mat Mol CIQUS, Santiago De Compostela 15782, Spain.;Univ Santiago de Compostela, Fac Farm, Dept Quim Organ, Santiago De Compostela 15782, Spain..
    Mallo, Ana
    Univ Santiago de Compostela, Ctr Singular Invest Quim Biol & Mat Mol CIQUS, Santiago De Compostela 15782, Spain.;Univ Santiago de Compostela, Fac Farm, Dept Quim Organ, Santiago De Compostela 15782, Spain..
    Majellaro, Maria
    Univ Santiago de Compostela, Ctr Singular Invest Quim Biol & Mat Mol CIQUS, Santiago De Compostela 15782, Spain.;Univ Santiago de Compostela, Fac Farm, Dept Quim Organ, Santiago De Compostela 15782, Spain..
    Caamano, Olga
    Univ Santiago de Compostela, Fac Farm, Dept Quim Organ, Santiago De Compostela 15782, Spain..
    Loza, Maria I.
    Univ Santiago de Compostela, Ctr Singular Invest Med Mol & Enfermedades Cronic, Santiago De Compostela 15782, Spain..
    Cadavid, Maria I.
    Univ Santiago de Compostela, Ctr Singular Invest Med Mol & Enfermedades Cronic, Santiago De Compostela 15782, Spain..
    Brea, Jose
    Univ Santiago de Compostela, Ctr Singular Invest Med Mol & Enfermedades Cronic, Santiago De Compostela 15782, Spain..
    Åqvist, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Sotelo, Eddy
    Univ Santiago de Compostela, Ctr Singular Invest Quim Biol & Mat Mol CIQUS, Santiago De Compostela 15782, Spain.;Univ Santiago de Compostela, Fac Farm, Dept Quim Organ, Santiago De Compostela 15782, Spain..
    Gutiérrez-de-Terán, Hugo
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Effect of Nitrogen Atom Substitution in A(3) Adenosine Receptor Binding: N-(4,6-Diarylpyridin-2-yl)acetamides as Potent and Selective Antagonists2017In: Journal of Medicinal Chemistry, ISSN 0022-2623, E-ISSN 1520-4804, Vol. 60, no 17, p. 7502-7511Article in journal (Refereed)
    Abstract [en]

    We report the first family of 2-acetamidopyridines as potent and selective A, adenosine receptor (AR) antagonists. The computer -assisted design was focused on the bioisosteric replacement of the N1 atom by a CH group in a previous series of diarylpyrimidines. Some of the generated 2-acetamidopyridines elicit an antagonistic effect with excellent affinity (K-j < 10 nM) and outstanding selectivity profiles, providing an alternative and simpler chemical scaffold to the parent series of diarylpyrimidines. In addition, using molecular dynamics and free energy perturbation simulations, we elucidate the effect of the second nitrogen of the parent diarylpyrimidines, which is revealed as a stabilizer of a water network in the binding site. The discovery of 2,6-diaryl-2-acetamidopyridines represents a step forward in the search of chemically simple, potent, and selective antagonists for the hA(3)AR, and exemplifies the benefits of a joint theoretical- experimental approach to identify novel hA(3)AR antagonists through succinct and efficient synthetic methodologies.

  • 2.
    Jandova, Zuzana
    et al.
    Univ Nat Resources & Life Sci, Inst Mol Modeling & Simulat, A-1190 Vienna, Austria.
    Jespers, Willem
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Sotelo, Eddy
    Univ Santiago de Compostela, Ctr Singular Invest Quim Biol & Mat Mol CIQUS, Santiago De Compostela 15782, Spain;Univ Santiago de Compostela, Fac Farm, Dept Quim Organ, Santiago De Compostela 15782, Spain.
    Gutiérrez-de-Terán, Hugo
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Oostenbrink, Chris
    Univ Nat Resources & Life Sci, Inst Mol Modeling & Simulat, A-1190 Vienna, Austria.
    Free-Energy Calculations for Bioisosteric Modifications of A(3) Adenosine Receptor Antagonists2019In: International Journal of Molecular Sciences, ISSN 1422-0067, E-ISSN 1422-0067, Vol. 20, no 14, article id 3499Article in journal (Refereed)
    Abstract [en]

    Adenosine receptors are a family of G protein-coupled receptors with increased attention as drug targets on different indications. We investigate the thermodynamics of ligand binding to the A(3) adenosine receptor subtype, focusing on a recently reported series of diarylacetamidopyridine inhibitors via molecular dynamics simulations. With a combined approach of thermodynamic integration and one-step perturbation, we characterize the impact of the charge distribution in a central heteroaromatic ring on the binding affinity prediction. Standard charge distributions according to the GROMOS force field yield values in good agreement with the experimental data and previous free energy calculations. Subsequently, we examine the thermodynamics of inhibitor binding in terms of the energetic and entropic contributions. The highest entropy penalties are found for inhibitors with methoxy substituents in meta position of the aryl groups. This bulky group restricts rotation of aromatic rings attached to the pyrimidine core which leads to two distinct poses of the ligand. Our predictions support the previously proposed binding pose for the o-methoxy ligand, yielding in this case a very good correlation with the experimentally measured affinities with deviations below 4 kJ/mol.

  • 3.
    Jespers, Willem
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Esguerra, Mauricio
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Åqvist, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Gutiérrez-de-Terán, Hugo
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics. Uppsala University, Science for Life Laboratory, SciLifeLab.
    QligFEP: an automated workflow for small molecule free energy calculations in Q2019In: Journal of Cheminformatics, ISSN 1758-2946, E-ISSN 1758-2946, Vol. 11, article id 26Article in journal (Refereed)
    Abstract [en]

    The process of ligand binding to a biological target can be represented as the equilibrium between the relevant solvated and bound states of the ligand. This which is the basis of structure-based, rigorous methods such as the estimation of relative binding affinities by free energy perturbation (FEP). Despite the growing capacity of computing power and the development of more accurate force fields, a high throughput application of FEP is currently hampered due to the need, in the current schemes, of an expert user definition of the alchemical transformations between molecules in the series explored. Here, we present QligFEP, a solution to this problem using an automated workflow for FEP calculations based on a dual topology approach. In this scheme, the starting poses of each of the two ligands, for which the relative affinity is to be calculated, are explicitly present in the MD simulations associated with the (dual topology) FEP transformation, making the perturbation pathway between the two ligands univocal. We show that this generalized method can be applied to accurately estimate solvation free energies for amino acid sidechain mimics, as well as the binding affinity shifts due to the chemical changes typical of lead optimization processes. This is illustrated in a number of protein systems extracted from other FEP studies in the literature: inhibitors of CDK2 kinase and a series of A(2A) adenosine G protein-coupled receptor antagonists, where the results obtained with QligFEP are in excellent agreement with experimental data. In addition, our protocol allows for scaffold hopping perturbations to identify the binding affinities between different core scaffolds, which we illustrate with a series of Chk1 kinase inhibitors. QligFEP is implemented in the open-source MD package Q, and works with the most common family of force fields: OPLS, CHARMM and AMBER.

  • 4.
    Jespers, Willem
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Isaksen, Geir V
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics. Arctic Univ Norway, Univ Tromso, Dept Chem, Hylleraas Ctr Quantum Mol Sci, N-9037 Tromso, Norway.
    Andberg, Tor A H
    Arctic Univ Norway, Univ Tromso, Dept Chem, Hylleraas Ctr Quantum Mol Sci, N-9037 Tromso, Norway.
    Vasile, Silvana
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    van Veen, Amber
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Åqvist, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Brandsdal, Bjørn Olav
    Arctic Univ Norway, Univ Tromso, Dept Chem, Hylleraas Ctr Quantum Mol Sci, N-9037 Tromso, Norway.
    Gutiérrez-de-Terán, Hugo
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    QresFEP: An Automated Protocol for Free Energy Calculations of Protein Mutations in Q2019In: Journal of Chemical Theory and Computation, ISSN 1549-9618, E-ISSN 1549-9626, Vol. 15, no 10, p. 5461-5473Article in journal (Refereed)
    Abstract [en]

    Predicting the effect of single-point mutations on protein stability or protein-ligand binding is a major challenge in computational biology. Free energy calculations constitute the most rigorous approach to this problem, though the estimation of converged values for amino acid mutations remains challenging. To overcome this limitation, we developed tailored protocols to calculate free energy shifts associated with single-point mutations. We herein describe the QresFEP protocol, which includes an extension of our recent protocols to cover all amino acids mutations, based on the latest versions of the OPLS-AA force field. QresFEP is implemented in an application programming interface framework and the graphic interface QGui, for the molecular dynamics software Q. The complete protocol is benchmarked in several model systems, optimizing a number of sampling parameters and the implementation of Zwanzig's exponential formula and Bennet's acceptance ratio methods. QresFEP shows an excellent performance on estimating the hydration free energies of amino acid side-chain mimics, including their charged analogues. We also examined its performance on a protein-ligand binding problem of pharmaceutical relevance, the antagonism of neuropeptide Y1 G protein-coupled receptor. Here, the calculations show very good agreement with the experimental effect of 16 mutations on the binding of antagonists BIBP3226, in line with our recent applications in this field. Finally, the characterization of 43 mutations of T4-lysozyme reveals the capacity of our protocol to assess variations of the thermal stability of proteins, achieving a similar performance to alternative free energy perturbation (FEP) approaches. In summary, QresFEP is a robust, versatile, and user-friendly computational FEP protocol to examine biochemical effects of single-point mutations with high accuracy.

  • 5.
    Jespers, Willem
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Oliveira, Ana
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Prieto-Diaz, Ruben
    Univ Santiago Compostela, Fac Farm, Dept Quim Organ, Ctr Singular Invest Quim Biol & Mat Mol CIQUS, Santiago De Compostela 15782, Spain..
    Majellaro, Maria
    Univ Santiago Compostela, Fac Farm, Dept Quim Organ, Ctr Singular Invest Quim Biol & Mat Mol CIQUS, Santiago De Compostela 15782, Spain..
    Åqvist, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Sotelo, Eddy
    Univ Santiago Compostela, Fac Farm, Dept Quim Organ, Ctr Singular Invest Quim Biol & Mat Mol CIQUS, Santiago De Compostela 15782, Spain..
    Gutiérrez-de-Terán, Hugo
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Structure-Based Design of Potent and Selective Ligands at the Four Adenosine Receptors2017In: Molecules, ISSN 1420-3049, E-ISSN 1420-3049, Vol. 22, no 11, article id 1945Article in journal (Refereed)
    Abstract [en]

    The four receptors that signal for adenosine, A(1), A(2A), A(2B) and A(3) ARs, belong to the superfamily of G protein-coupled receptors (GPCRs). They mediate a number of (patho)physiological functions and have attracted the interest of the biopharmaceutical sector for decades as potential drug targets. The many crystal structures of the A(2A), and lately the A(1) ARs, allow for the use of advanced computational, structure-based ligand design methodologies. Over the last decade, we have assessed the efficient synthesis of novel ligands specifically addressed to each of the four ARs. We herein review and update the results of this program with particular focus on molecular dynamics (MD) and free energy perturbation (FEP) protocols. The first in silico mutagenesis on the A(1)AR here reported allows understanding the specificity and high affinity of the xanthine-antagonist 8-Cyclopentyl-1,3-dipropylxanthine (DPCPX). On the A(2A)AR, we demonstrate how FEP simulations can distinguish the conformational selectivity of a recent series of partial agonists. These novel results are complemented with the revision of the first series of enantiospecific antagonists on the A(2B)AR, and the use of FEP as a tool for bioisosteric design on the A(3)AR.

  • 6.
    Jespers, Willem
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics. Leiden Amsterdam Ctr Drug Res, Drug Discovery & Safety, Leiden.; Univ Copenhagen, Dept Drug Design & Pharmacol, Copenhagen.
    Schiedel, Anke C.
    PharmaCtr Bonn, Pharmaceut Inst, Pharmaceut Chem 1, Bonn.
    Heitman, Laura H.
    Leiden Amsterdam Ctr Drug Res, Drug Discovery & Safety, Leiden.
    Cooke, Robert M.
    Heptares Therapeut, Biopk, Broadwater Rd, Welwyn Garden City, Herts.
    Kleene, Lisa
    PharmaCtr Bonn, Pharmaceut Inst, Pharmaceut 1, Bonn.
    van Westen, Gerard J. P.
    Leiden Amsterdam Ctr Drug Res, Drug Discovery & Safety, Leiden.
    Gloriam, David E.
    Univ Copenhagen, Dept Drug Design & Pharmacol, Copenhagen.
    Müller, Christa E.
    PharmaCtr Bonn, Pharmaceut Inst, Pharmaceut Chem 1, Bonn.
    Sotelo, Eddy
    Univ Santiago de Compostela, Fac Farm, Ctr Singular Invest Quim Biolox & Mat Mol CIQUS, Santiago De Compostela 15782, Spain.; Univ Santiago de Compostela, Fac Farm, Dept Quim Organ, Santiago De Compostela.
    Gutiérrez-de-Terán, Hugo
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Structural Mapping of Adenosine Receptor Mutations: Ligand Binding and Signaling Mechanisms2018In: TIPS - Trends in Pharmacological Sciences, ISSN 0165-6147, E-ISSN 1873-3735, Vol. 39, no 1, p. 75-89Article, review/survey (Refereed)
    Abstract [en]

    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.

  • 7.
    Lind, Christoffer
    et al.
    Univ Maryland, Sch Pharm, Dept Pharmaceut Sci, Baltimore, MD 21201 USA.
    Esguerra, Mauricio
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Jespers, Willem
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Satpati, Priyadarshi
    Indian Inst Technol Guwahati, Dept Biosci & Bioengn, Gauhati 781039, Assam, India.
    Gutiérrez-de-Terán, Hugo
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Åqvist, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Free energy calculations of RNA interactions2019In: Methods, ISSN 1046-2023, E-ISSN 1095-9130, Vol. 162-163, p. 85-95Article in journal (Refereed)
    Abstract [en]

    This review discusses the use of molecular dynamics free energy calculations for characterizing RNA interactions, with particular emphasis on molecular recognition events involved in mRNA translation on the ribosome. The general methodology for efficient free energy calculations is outlined and our specific implementation for binding free energy changes due to base mutations in mRNA and tRNA is described, We show that there are a number of key problems related to the accuracy of protein synthesis that can be addressed with this type of computational approach and several such examples are discussed in detail. These include the decoding of mRNA during peptide chain elongation, initiation and termination of translation, as well as the energetic effects of base tautomerization and tRNA modifications. It is shown that free energy calculations can be made sufficiently reliable to allow quantitative conclusions to be drawn regarding the energetics of cognate versus non-cognate interactions and its structural origins.

  • 8.
    Mallo-Abreu, Ana
    et al.
    Univ Santiago De Compostela, Fac Farm, Ctr Singular Invest Quim Biol & Mat Mol CIQUS, Santiago De Compostela 15782, Spain;Univ Santiago De Compostela, Fac Farm, Dept Quim Organ, Santiago De Compostela 15782, Spain.
    Majellaro, Maria
    Univ Santiago De Compostela, Fac Farm, Ctr Singular Invest Quim Biol & Mat Mol CIQUS, Santiago De Compostela 15782, Spain;Univ Santiago De Compostela, Fac Farm, Dept Quim Organ, Santiago De Compostela 15782, Spain.
    Jespers, Willem
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Azuaje, Jhonny
    Univ Santiago De Compostela, Fac Farm, Ctr Singular Invest Quim Biol & Mat Mol CIQUS, Santiago De Compostela 15782, Spain;Univ Santiago De Compostela, Fac Farm, Dept Quim Organ, Santiago De Compostela 15782, Spain.
    Caamano, Olga
    Univ Santiago De Compostela, Fac Farm, Dept Quim Organ, Santiago De Compostela 15782, Spain.
    Garcia-Mera, Xerardo
    Univ Santiago De Compostela, Fac Farm, Dept Quim Organ, Santiago De Compostela 15782, Spain.
    Brea, Jose M.
    Univ Santiago De Compostela, Ctr Singular Invest Med Mol & Enfermedades Cron C, Santiago De Compostela 15782, Spain.
    Loza, Maria I.
    Univ Santiago De Compostela, Ctr Singular Invest Med Mol & Enfermedades Cron C, Santiago De Compostela 15782, Spain.
    Gutiérrez-de-Terán, Hugo
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Sotele, Eddy
    Univ Santiago De Compostela, Fac Farm, Ctr Singular Invest Quim Biol & Mat Mol CIQUS, Santiago De Compostela 15782, Spain;Univ Santiago De Compostela, Fac Farm, Dept Quim Organ, Santiago De Compostela 15782, Spain.
    Trifluorinated Pyrimidine-Based A(2B) Antagonists: Optimization and Evidence of Stereospecific Recognition2019In: Journal of Medicinal Chemistry, ISSN 0022-2623, E-ISSN 1520-4804, Vol. 62, no 20, p. 9315-9330Article in journal (Refereed)
    Abstract [en]

    We report the identification of two subsets of fluorinated nonxanthine A(2B) adenosine receptor antagonists. The novel derivatives explore the effect of fluorination at different positions of two pyrimidine-based scaffolds. The most interesting ligands combine excellent hA(2B) affinity (K-i < 15 nM) and remarkable subtype selectivity. The results of functional cAMP experiments confirmed the antagonistic behavior of representative ligands. The compounds were designed on the basis of previous molecular models of the stereoselective binding of the parent scaffolds to the hA(2B) receptor, and we herein provide refinement of such models with the fluorinated compounds, which allows the explanation of the spurious effects of the fluorination at the different positions explored. These models are importantly confirmed by a synergistic study combining chiral HPLC, circular dichroism, diastereoselective synthesis, molecular modeling, and X-ray crystallography, providing experimental evidence toward the stereospecific interaction between optimized trifluorinated stereoisomers and the hA(2B) receptor.

  • 9.
    Nohr, Anne Cathrine
    et al.
    Univ Copenhagen, Dept Drug Design & Pharmacol, Univ Pk 2, DK-2100 Copenhagen, Denmark..
    Jespers, Willem
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Shehata, Mohamed A.
    Univ Copenhagen, Dept Drug Design & Pharmacol, Univ Pk 2, DK-2100 Copenhagen, Denmark..
    Floryan, Leonard
    Swiss Fed Inst Technol, Dept Chem & Appl Biosci, Vladimir Prelog Weg 1-5-10, CH-8093 Zurich, Switzerland..
    Isberg, Vignir
    Univ Copenhagen, Dept Drug Design & Pharmacol, Univ Pk 2, DK-2100 Copenhagen, Denmark..
    Andersen, Kirsten Bayer
    Univ Copenhagen, Dept Drug Design & Pharmacol, Univ Pk 2, DK-2100 Copenhagen, Denmark..
    Åqvist, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Gutiérrez-de-Terán, Hugo
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Bräuner-Osborne, Hans
    Univ Copenhagen, Dept Drug Design & Pharmacol, Univ Pk 2, DK-2100 Copenhagen, Denmark..
    Gloriam, David E.
    Univ Copenhagen, Dept Drug Design & Pharmacol, Univ Pk 2, DK-2100 Copenhagen, Denmark..
    The GPR139 reference agonists 1a and 7c, and tryptophan and phenylalanine share a common binding site2017In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 7, article id 1128Article in journal (Refereed)
    Abstract [en]

    GPR139 is an orphan G protein-coupled receptor expressed in the brain, in particular in the habenula, hypothalamus and striatum. It has therefore been suggested that GPR139 is a possible target for metabolic disorders and Parkinson's disease. Several surrogate agonist series have been published for GPR139. Two series published by Shi et al. and Dvorak et al. included agonists 1a and 7c respectively, with potencies in the ten-nanomolar range. Furthermore, Isberg et al. and Liu et al. have previously shown that tryptophan (Trp) and phenylalanine (Phe) can activate GPR139 in the hundred-micromolar range. In this study, we produced a mutagenesis-guided model of the GPR139 binding site to form a foundation for future structure-based ligand optimization. Receptor mutants studied in a Ca2+ assay demonstrated that residues F109(3x33), H187(5x43), W241(6x48) and N271(7x38), but not E108(3x32), are highly important for the activation of GPR139 as predicted by the receptor model. The initial ligand-receptor complex was optimized through free energy perturbation simulations, generating a refined GPR139 model in agreement with experimental data. In summary, the GPR139 reference surrogate agonists 1a and 7c, and the endogenous amino acids L-Trp and L-Phe share a common binding site, as demonstrated by mutagenesis, ligand docking and free energy calculations.

  • 10.
    Vasile, Silvana
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Esguerra, Mauricio
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Jespers, Willem
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Oliveira, Ana
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Sallander, Jessica
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Åqvist, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Gutiérrez-de-Terán, Hugo
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Characterization of Ligand Binding to GPCRs Through Computational Methods.2018In: Computational Methods for GPCR Drug Discovery, New York, NY: Humana Press, 2018, Vol. 1705, p. 23-44Chapter in book (Refereed)
    Abstract [en]

    The recent increase in available G protein-coupled receptor structures now contributes decisively to the structure-based ligand design. In this context, computational approaches in combination with medicinal chemistry and pharmacology are extremely helpful. Here, we provide an update on our structure-based computational protocols, used to answer key questions related to GPCR-ligand binding. All combined, these techniques can shed light on ligand binding modes, determine the molecular basis of conformational selection, for agonists and antagonists, as well as of subtype selectivity. To illustrate each of these questions, we will consider examples from existing projects on three families of class A (rhodopsin-like) GPCRs: one small-molecule (nucleotide-like) family, i.e., the adenosine receptors, and two peptide-binding receptors: neuropeptide-Y and angiotensin II receptors. The successful application of the same computational protocols to investigate this diverse group of receptor families gives an idea of the general applicability of our methodology in the characterization of GPCR-ligand binding.

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