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  • 1.
    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.

  • 2.
    Shebanits, Kateryna
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Vasile, Silvana
    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.
    Xu, Bo
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular tools. Uppsala University, Science for Life Laboratory, SciLifeLab.
    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.
    Larhammar, Dan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Functional characterization in vitro of twelve naturally occurring variants of the human pancreatic polypeptide receptor NPY4R2019In: Neuropeptides, ISSN 0143-4179, E-ISSN 1532-2785, Vol. 76, article id 101933Article in journal (Refereed)
    Abstract [en]

    Obesity has become a global health problem and therefore understanding of the mechanisms regulating hunger and satiety is of utmost importance for the development of new treatment strategies. The Y4 receptor, encoded by the NPY4R gene, and its ligand pancreatic polypeptide (PP) have been reported to mediate a satiety signal. Multiple genetic studies have reported an association between NPY4R copy number and body weight. The gene also displays several SNP variants, many of which lead to amino acid differences, making it interesting to study. We have investigated the functional properties of 12 naturally occurring amino acid sequence variants of the Y4 and interpret the results in relation to sequence conservation and our structural model of the human Y4 receptor protein. Three receptor variants, Cys201ECL2Tyr, Val2716.41Leu and Asn3187.49Asp, were found to completely lose functional response, measured as inositol phosphate turnover, while retaining membrane expression. They display high sequence conservation and have important roles in the receptor structure. For two receptor variants the potency of PP was significantly decreased, Cys34NTSer (EC50 = 2.9 nM, p < .001) and Val1353.46Met (EC50 = 3.0 nM, p < .01), compared to wild-type Y4 (EC50 = 0.68 nM). Cys34 forms a disulphide bond with Cys298, linking the N-terminal part to ECL3. The Val1353.46Met variant has an amino acid replacement located in the TM3 helix, one helix turn above the highly conserved ERH motif. This position has influence on the network of residues involved in receptor activation and subsequent inactivation. Sequence conservation and the structural model are consistent with these results. The remaining seven positions had no significant effect on the receptor's functional response compared to wild-type Y4. These positions display more variation during evolution. Understanding of the interactions between the Y4 receptor and its native PP agonist and the effects of amino acid variation on its functional response will hopefully lead to future therapeutic possibilities.

  • 3.
    Vasile, Silvana
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology. Uppsala University.
    Computational prediction of ligand binding in peptide G-protein coupled receptors2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    G-protein coupled receptors (GPCRs) are a superfamily of membrane receptors involved in a wide variety of biological processes, and their malfunction is associated with many diseases. Consequently, GPCRs are targeted by one-third of the drugs on the market, and constitute the focus of active public and private research in the search of more effective drugs. The GPCR families that are activated by endogenous peptides are particularly challenging for the drug design process, which in this case contemplates peptides, peptidomimetics and small molecules, as selective activators (agonists) or blockers (antagonists) of the particular receptor subtype of interest. This process benefits of a detailed understanding of how known ligands bind to the receptors. Homology modelling, molecular dynamics (MD) and free energy perturbation (FEP) are computational methods used to predict binding modes and binding affinities. In this thesis, these techniques are applied (and even further developed) in combination with novel experimental data provided by our collaborators, in order to elucidate the molecular determinants of endogenous peptide ligands, analogues and mimetics to two families of peptide-binding receptors: the neuropeptide Y (NPY) and the Angiotensin II receptors.

    The NPY signaling system is responsible for the regulation of food intake and its malfunction is connected to obesity, a risk factor for diseases such as diabetes and cancer. In this thesis, we focused on the elucidation of the binding mode of endogenous peptide ligands and studied the structural effect of receptor mutants, with the aim of helping in future drug design on the Y2 receptor subtype, as well as understanding the effect of receptor polymorphisms on the Y4 subtype. We further used this system to refine and test our computational protocol for the prediction of binding free energies, by characterizing the binding mode of a peptidomimetic antagonist to the Y1 receptor.

    The AT2 receptor is another interesting drug target, as its activation by the Angiotensin II peptide elicits responses that counterbalance the hypertensive effects caused by activation of the AT1 receptor by the same ligand. Moreover, AT2 is upregulated in events of tissue damage. We characterized the chemical evolution of peptide and peptidomimetic agonists at this receptor, with the aim to identify a set of pharmacophoric points and key interactions with AT2. The outcome of this study allowed the establishment of a clear explanation of structure-activity relationships, and will be the starting point for further ligand-design efforts at this receptor.

    List of papers
    1. Elucidation of the Binding Mode of the Carboxyterminal Region of Peptide YY to the Human Y-2 Receptor
    Open this publication in new window or tab >>Elucidation of the Binding Mode of the Carboxyterminal Region of Peptide YY to the Human Y-2 Receptor
    Show others...
    2018 (English)In: Molecular Pharmacology, ISSN 0026-895X, E-ISSN 1521-0111, Vol. 93, no 4, p. 323-334Article in journal (Refereed) Published
    Abstract [en]

    Understanding the agonist-receptor interactions in the neuropeptide Y (NPY)/peptide YY (PYY) signaling system is fundamental for the design of novel modulators of appetite regulation. We report here the results of a multidisciplinary approach to elucidate the binding mode of the native peptide agonist PYY to the human Y2 receptor, based on computational modeling, peptide chemistry and in vitro pharmacological analyses. The preserved binding orientation proposed for full-length PYY and five analogs, truncated at the amino terminus, explains our pharmacological results where truncations of the N-terminal proline helix showed little effect on peptide affinity. This was followed by receptor mutagenesis to investigate the roles of several receptor positions suggested by the modeling. As a complement, PYY-(3-36) analogs were synthesized with modifications at different positions in the common PYY/NPY C-terminal fragment (32TRQRY36-amide). The results were assessed and interpreted by molecular dynamics and Free Energy Perturbation (FEP) simulations of selected mutants, providing a detailed map of the interactions of the PYY/NPY C-terminal fragment with the transmembrane cavity of the Y2 receptor. The amidated C-terminus would be stabilized by polar interactions with Gln2886.55 and Tyr2195.39, while Gln1303.32 contributes to interactions with Q34 in the peptide and T32 is close to the tip of TM7 in the receptor. This leaves the core, α-helix of the peptide exposed to make potential interactions with the extracellular loops. This model agrees with most experimental data available for the Y2 system and can be used as a basis for optimization of Y2 receptor agonists.

    National Category
    Biochemistry and Molecular Biology Pharmacology and Toxicology
    Identifiers
    urn:nbn:se:uu:diva-381397 (URN)10.1124/mol.117.110627 (DOI)000461898900005 ()29367257 (PubMedID)
    Funder
    Swedish Research Council, 521-2014-2118Novo NordiskeSSENCE - An eScience Collaboration
    Available from: 2019-04-17 Created: 2019-04-17 Last updated: 2019-10-23Bibliographically approved
    2. Functional characterization in vitro of twelve naturally occurring variants of the human pancreatic polypeptide receptor NPY4R
    Open this publication in new window or tab >>Functional characterization in vitro of twelve naturally occurring variants of the human pancreatic polypeptide receptor NPY4R
    Show others...
    2019 (English)In: Neuropeptides, ISSN 0143-4179, E-ISSN 1532-2785, Vol. 76, article id 101933Article in journal (Refereed) Published
    Abstract [en]

    Obesity has become a global health problem and therefore understanding of the mechanisms regulating hunger and satiety is of utmost importance for the development of new treatment strategies. The Y4 receptor, encoded by the NPY4R gene, and its ligand pancreatic polypeptide (PP) have been reported to mediate a satiety signal. Multiple genetic studies have reported an association between NPY4R copy number and body weight. The gene also displays several SNP variants, many of which lead to amino acid differences, making it interesting to study. We have investigated the functional properties of 12 naturally occurring amino acid sequence variants of the Y4 and interpret the results in relation to sequence conservation and our structural model of the human Y4 receptor protein. Three receptor variants, Cys201ECL2Tyr, Val2716.41Leu and Asn3187.49Asp, were found to completely lose functional response, measured as inositol phosphate turnover, while retaining membrane expression. They display high sequence conservation and have important roles in the receptor structure. For two receptor variants the potency of PP was significantly decreased, Cys34NTSer (EC50 = 2.9 nM, p < .001) and Val1353.46Met (EC50 = 3.0 nM, p < .01), compared to wild-type Y4 (EC50 = 0.68 nM). Cys34 forms a disulphide bond with Cys298, linking the N-terminal part to ECL3. The Val1353.46Met variant has an amino acid replacement located in the TM3 helix, one helix turn above the highly conserved ERH motif. This position has influence on the network of residues involved in receptor activation and subsequent inactivation. Sequence conservation and the structural model are consistent with these results. The remaining seven positions had no significant effect on the receptor's functional response compared to wild-type Y4. These positions display more variation during evolution. Understanding of the interactions between the Y4 receptor and its native PP agonist and the effects of amino acid variation on its functional response will hopefully lead to future therapeutic possibilities.

    Keywords
    Y4, SNP, Mutagenesis, Functional pharmacology, Structural modelling
    National Category
    Biochemistry and Molecular Biology
    Identifiers
    urn:nbn:se:uu:diva-356572 (URN)10.1016/j.npep.2019.05.004 (DOI)000482249700004 ()31230758 (PubMedID)
    Funder
    Swedish Research Council, K2013-55 x -22189-01-2The Swedish Brain Foundation, F02016-0217
    Available from: 2018-08-01 Created: 2018-08-01 Last updated: 2019-12-06Bibliographically approved
    3. QresFEP: An Automated Protocol for Free Energy Calculations of Protein Mutations in Q
    Open this publication in new window or tab >>QresFEP: An Automated Protocol for Free Energy Calculations of Protein Mutations in Q
    Show others...
    2019 (English)In: Journal of Chemical Theory and Computation, ISSN 1549-9618, E-ISSN 1549-9626, Vol. 15, no 10, p. 5461-5473Article in journal (Refereed) Published
    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.

    National Category
    Bioinformatics (Computational Biology)
    Identifiers
    urn:nbn:se:uu:diva-395642 (URN)10.1021/acs.jctc.9b00538 (DOI)000489678700026 ()31436990 (PubMedID)
    Funder
    The Research Council of Norway, 262695 274858Swedish Research CouncilKnut and Alice Wallenberg FoundationeSSENCE - An eScience Collaboration
    Available from: 2019-10-22 Created: 2019-10-22 Last updated: 2019-11-06Bibliographically approved
    4. Evolution of Angiotensin Peptides and Peptidomimetics as AT2 Receptor Agonists
    Open this publication in new window or tab >>Evolution of Angiotensin Peptides and Peptidomimetics as AT2 Receptor Agonists
    Show others...
    (English)Manuscript (preprint) (Other academic)
    Abstract [en]

    The biological functions of Angiotensin II (Ang II), a central peptide in the Renin-Angiotensin System (RAS), are mediated by two G-protein coupled receptors, AT1R and AT2R. Activation of AT1R by Ang II elicits strong hypertensive effects and inhibitors of the enzymes responsible for the synthesis of Ang II, as well as compounds that act as antagonists at AT1R, have served important targets for drug intervention. On the other hand, AT2R is upregulated in events of tissue damage and its activation by Ang II results in opposite consequences to AT1R activation, i.e. vasodilation, anti-fibrotic and anti-inflammatory effects. Hence, in recent years AT2R emerged as a promising drug target. The first drug-like selective AT2R agonist C21 was discovered by our group and is in Phase II clinical trials for idiopathic pulmonary fibrosis (IPF). Herein, the chemical evolution of AT2R peptide agonists was studied by identification of pharmacophoric points, bioactive conformations and key interactions with the receptor. Eleven important peptides and peptidomimetics, with different structure, affinity and selectivity, were selected. All compounds, including sarile, an Ang II analogue, were previously confirmed to act as AT2R agonists. Based on the recently released crystal structures of AT1R and AT2R in complex with sarile (which acts as a partial agonist at AT1R), we proposed a common binding model for the series of peptides. The binding modes were analysed by means of molecular docking and Molecular Dynamics simulations, and further explanation of structure-activity relationships was achieved by binding affinity predictions with Free Energy Perturbation calculations on short peptides. In light of the long-term goal of designing potent and AT2R selective drugs with long duration in vivo, the calculations on C21 can be used to cover the gap between peptides and drug-like AT2R agonists.  

    National Category
    Bioinformatics (Computational Biology)
    Identifiers
    urn:nbn:se:uu:diva-395742 (URN)
    Available from: 2019-10-23 Created: 2019-10-23 Last updated: 2019-11-07
  • 4.
    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.

  • 5.
    Vasile, Silvana
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology. Uppsala University.
    Hallberg, Anders
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Medicinal Chemistry.
    Sallander, Jessica
    Hallberg, Mathias
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. eThe Beijer Laboratory, Department of Pharmaceutical Biosciences, Division of Biological Research on Drug Dependence, BMC, Uppsala University, P.O. Box 591, SE-751 24 Uppsala, Sweden.
    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. Science for Life Laboratory, BMC, Box 596, Uppsala University, SE-751 24 Uppsala, Sweden.
    Evolution of Angiotensin Peptides and Peptidomimetics as AT2 Receptor AgonistsManuscript (preprint) (Other academic)
    Abstract [en]

    The biological functions of Angiotensin II (Ang II), a central peptide in the Renin-Angiotensin System (RAS), are mediated by two G-protein coupled receptors, AT1R and AT2R. Activation of AT1R by Ang II elicits strong hypertensive effects and inhibitors of the enzymes responsible for the synthesis of Ang II, as well as compounds that act as antagonists at AT1R, have served important targets for drug intervention. On the other hand, AT2R is upregulated in events of tissue damage and its activation by Ang II results in opposite consequences to AT1R activation, i.e. vasodilation, anti-fibrotic and anti-inflammatory effects. Hence, in recent years AT2R emerged as a promising drug target. The first drug-like selective AT2R agonist C21 was discovered by our group and is in Phase II clinical trials for idiopathic pulmonary fibrosis (IPF). Herein, the chemical evolution of AT2R peptide agonists was studied by identification of pharmacophoric points, bioactive conformations and key interactions with the receptor. Eleven important peptides and peptidomimetics, with different structure, affinity and selectivity, were selected. All compounds, including sarile, an Ang II analogue, were previously confirmed to act as AT2R agonists. Based on the recently released crystal structures of AT1R and AT2R in complex with sarile (which acts as a partial agonist at AT1R), we proposed a common binding model for the series of peptides. The binding modes were analysed by means of molecular docking and Molecular Dynamics simulations, and further explanation of structure-activity relationships was achieved by binding affinity predictions with Free Energy Perturbation calculations on short peptides. In light of the long-term goal of designing potent and AT2R selective drugs with long duration in vivo, the calculations on C21 can be used to cover the gap between peptides and drug-like AT2R agonists.  

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