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Computational Modelling of Ligand Complexes with G-Protein Coupled Receptors, Ion Channels and Enzymes
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Accurate predictions of binding free energies from computer simulations are an invaluable resource for understanding biochemical processes and drug action. The primary aim of the work described in the thesis was to predict and understand ligand binding to several proteins of major pharmaceutical importance using computational methods.

We report a computational strategy to quantitatively predict the effects of alanine scanning and ligand modifications based on molecular dynamics free energy simulations. A smooth stepwise scheme for free energy perturbation calculations is derived and applied to a series of thirteen alanine mutations of the human neuropeptide Y1 G-protein coupled receptor and a series of eight analogous antagonists. The robustness and accuracy of the method enables univocal interpretation of existing mutagenesis and binding data. We show how these calculations can be used to validate structural models and demonstrate their ability to discriminate against suboptimal ones. Site-directed mutagenesis, homology modelling and docking were further used to characterize agonist binding to the human neuropeptide Y2 receptor, which is important in feeding behavior and an obesity drug target.  In a separate project, homology modelling was also used for rationalization of mutagenesis data for an integron integrase involved in antibiotic resistance.

Blockade of the hERG potassium channel by various drug-like compounds, potentially causing serious cardiac side effects, is a major problem in drug development. We have used a homology model of hERG to conduct molecular docking experiments with a series of channel blockers, followed by molecular dynamics simulations of the complexes and evaluation of binding free energies with the linear interaction energy method. The calculations are in good agreement with experimental binding affinities and allow for a rationalization of three-dimensional structure-activity relationships with implications for design of new compounds. Docking, scoring, molecular dynamics, and the linear interaction energy method were also used to predict binding modes and affinities for a large set of inhibitors to HIV-1 reverse transcriptase. Good agreement with experiment was found and the work provides a validation of the methodology as a powerful tool in structure-based drug design. It is also easily scalable for higher throughput of compounds.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2014. , 61 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1105
Keyword [en]
computer simulations, molecular dynamics, ligand binding, free energy perturbation, linear interaction energy, binding free energy, homology modelling, structure prediction, alanine scanning, site-directed mutagenesis, hERG, GPCR, neuropeptide Y, HIV-1 reverse transcriptase, integron integrase
National Category
Theoretical Chemistry Structural Biology Biochemistry and Molecular Biology
Research subject
Molecular Biotechnology
Identifiers
URN: urn:nbn:se:uu:diva-212103ISBN: 978-91-554-8823-9 (print)OAI: oai:DiVA.org:uu-212103DiVA: diva2:676234
Public defence
2014-01-31, B42, BMC, Husargatan 3, Uppsala, 13:15 (English)
Opponent
Supervisors
Available from: 2014-01-10 Created: 2013-12-05 Last updated: 2014-01-24
List of papers
1. Mutagenesis of human neuropeptide Y/peptide YY receptor Y2 reveals additional differences to Y1 in interactions with highly conserved ligand positions
Open this publication in new window or tab >>Mutagenesis of human neuropeptide Y/peptide YY receptor Y2 reveals additional differences to Y1 in interactions with highly conserved ligand positions
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2010 (English)In: Regulatory Peptides, ISSN 0167-0115, E-ISSN 1873-1686, Vol. 163, no 1-3, 120-129 p.Article in journal (Refereed) Published
Abstract [en]

Neuropeptide Y (NPY) and peptide YY (PYY) share similar to 70% of their 36 amino acids and bind to the same three human receptor subtypes, Y1, Y2 and Y5, even though these receptors only share similar to 30% sequence identity Based on our previous investigation of human Y1 we describe here a mutagenesis study of three corresponding positions in human Y2, i e Tyr(2 64), Val(6 58) and Tyr(7 31) Pharmacological characterization was performed with the four peptide agonists PYY, NPY, PYY(3-36) and NPY(13-36) as well as the non-peptide antagonist BIIE0246 Results from mutants where Tyr(2 64) has been substituted by Ala suggest that Tyr(2 64) is involved in the interaction with all investigated ligands whereas position Tyr(7 31) seems to be more important for interaction with the truncated peptide PYY(3-36) than with intact NPY Surprisingly, substitution of Tyr(7 31) with His, the corresponding residue in Y1, resulted in total loss of binding of iodinated porcine PYY The third position. Val(6 58), did not influence binding of any of the ligands. These findings differ from those obtained for Y1 where Ala substitution resulted in lost or changed binding for each of the three positions. Although Tyr(2 64) and Tyr(7 31) in Y2 are involved in ligand binding, their interactions with the peptide ligands seem to be different from the corresponding positions in Y1 This suggests that the receptor-ligand interactions have changed during evolution after Y1 and Y2 arose from a common ancestral receptor.

Keyword
Site-directed mutagenesis, G-protein coupled receptor, Three dimensional model, Evolution
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-135756 (URN)10.1016/j.regpep.2010.04.011 (DOI)000280050000018 ()
Note

Manuscript title: Investigation of receptor-ligand interactions of the human neuropeptide Y receptor Y2 by site-directed mutagenesis: comparison with the structurally divergent Y1 subtype

Available from: 2010-12-08 Created: 2010-12-08 Last updated: 2017-12-11Bibliographically approved
2. Mutagenesis and Computational Modeling of Human G‑Protein-Coupled Receptor Y2 for Neuropeptide Y and Peptide YY
Open this publication in new window or tab >>Mutagenesis and Computational Modeling of Human G‑Protein-Coupled Receptor Y2 for Neuropeptide Y and Peptide YY
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2013 (English)In: Biochemistry, ISSN 0006-2960, E-ISSN 1520-4995, Vol. 52, no 45, 7987-7998 p.Article in journal (Refereed) Published
Abstract [en]

Neuropeptide Y and peptide YY receptor type 2 (Y2) is involved in appetite regulation and several other physiological processes. We have investigated the structure of the human Y2 receptor. Computational modeling of receptor–agonist interactions was used as a guide to design a series of receptor mutants, followed by binding assays using full-length and truncated peptide agonists and the Y2-specific antagonist BIIE0246. Our model suggested a hydrogen bond network among highly conserved residues Thr2.61, Gln3.32, and His7.39, which could play roles in ligand binding and/or receptor structure. In addition, the C-terminus of the peptide could make contact with residues Tyr5.38 and Leu6.51. Mutagenesis of all these positions, followed by binding assays, provides experimental support for our computational model: most of the mutants for the residues forming the proposed hydrogen bond network displayed reduced peptide agonist affinities as well as reduced hPYY3-36 potency in a functional assay. The Ala and Leu mutants of Gln3.32 and His7.39 disrupted membrane expression of the receptor. Combined with the modeling, the experimental results support roles for these hydrogen bond network residues in peptide binding as well as receptor architecture. The reduced agonist affinity for mutants of Tyr5.38 and Leu6.51 supports their role in a binding pocket surrounding the invariant tyrosine at position 36 of the peptide ligands. The results for antagonist BIIE0246 suggest several differences in interactions compared to those of the peptides. Our results lead to a new structural model for NPY family receptors and peptide binding.

Place, publisher, year, edition, pages
American Chemical Society (ACS), 2013
National Category
Natural Sciences Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-154994 (URN)10.1021/bi400830c (DOI)000330017700012 ()
Available from: 2011-08-04 Created: 2011-06-14 Last updated: 2017-12-08Bibliographically approved
3. Computational prediction of alanine scanning and ligand binding energetics in G-protein coupled receptors
Open this publication in new window or tab >>Computational prediction of alanine scanning and ligand binding energetics in G-protein coupled receptors
2014 (English)In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 10, no 4, e1003585- p.Article in journal (Refereed) Published
Abstract [en]

Site-directed mutagenesis combined with binding affinity measurements is widely used to probe the nature of ligand interactions with GPCRs. Such experiments, as well as structure-activity relationships for series of ligands, are usually interpreted with computationally derived models of ligand binding modes. However, systematic approaches for accurate calculations of the corresponding binding free energies are still lacking. Here, we report a computational strategy to quantitatively predict the effects of alanine scanning and ligand modifications based on molecular dynamics free energy simulations. A smooth stepwise scheme for free energy perturbation calculations is derived and applied to a series of thirteen alanine mutations of the human neuropeptide Y1 receptor and series of eight analogous antagonists. The robustness and accuracy of the method enables univocal interpretation of existing mutagenesis and binding data. We show how these calculations can be used to validate structural models and demonstrate their ability to discriminate against suboptimal ones. Author Summary G-protein coupled receptors constitute a family of drug targets of outstanding interest, with more than 30% of the marketed drugs targeting a GPCR. The combination of site-directed mutagenesis, biochemical experiments and computationally generated 3D structural models has traditionally been used to investigate these receptors. The increasing number of GPCR crystal structures now paves the way for detailed characterization of receptor-ligand interactions and energetics using advanced computer simulations. Here, we present an accurate computational scheme to predict and interpret the effects of alanine scanning experiments, based on molecular dynamics free energy simulations. We apply the technique to antagonist binding to the neuropeptide Y receptor Y1, the structure of which is still unknown. A structural model of a Y1-antagonist complex was derived and used as starting point for computational characterization of the effects on binding of alanine substitutions at thirteen different receptor positions. Further, we used the model and computational scheme to predict the binding of a series of seven antagonist analogs. The results are in excellent agreement with available experimental data and provide validation of both the methodology and structural models of the complexes.

National Category
Bioinformatics (Computational Biology) Biochemistry and Molecular Biology
Identifiers
urn:nbn:se:uu:diva-212102 (URN)10.1371/journal.pcbi.1003585 (DOI)000336507500014 ()
Available from: 2013-12-05 Created: 2013-12-05 Last updated: 2017-12-06Bibliographically approved
4. Computer Simulations of Structure-Activity Relationships for hERG Channel Blockers
Open this publication in new window or tab >>Computer Simulations of Structure-Activity Relationships for hERG Channel Blockers
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2011 (English)In: Biochemistry, ISSN 0006-2960, E-ISSN 1520-4995, Vol. 50, no 27, 6146-6156 p.Article in journal (Refereed) Published
Abstract [en]

The hERG potassium channel is of major pharmaceutical importance, and its blockade by various compounds, potentially causing serious cardiac side effects, is a major problem in drug development. Despite the large amounts of existing biochemical data on blockade of hERG by drugs and druglike compounds, relatively little is known regarding the structural basis of binding of blockers to the channel. Here, we have used a recently developed homology model of hERG to conduct molecular docking experiments with a series of channel blockers, followed by molecular dynamics simulations of the complexes and evaluation of binding free energies with the linear interaction energy method. The calculations yield a remarkably good agreement with experimental binding affinities and allow for a rationalization of three-dimensional structure-activity relationships in terms of a number of key interactions. Two main interaction regions of the channel are thus identified with implications for further mutagenesis experiments and design of new compounds.

National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-156474 (URN)10.1021/bi200173n (DOI)000292430600018 ()
Available from: 2011-07-27 Created: 2011-07-25 Last updated: 2017-12-08Bibliographically approved
5. Combining docking, molecular dynamics and the linear interaction energy method to predict binding modes and affinities for non-nucleoside inhibitors to HIV-1 reverse transcriptase
Open this publication in new window or tab >>Combining docking, molecular dynamics and the linear interaction energy method to predict binding modes and affinities for non-nucleoside inhibitors to HIV-1 reverse transcriptase
2008 (English)In: Journal of Medicinal Chemistry, ISSN 0022-2623, E-ISSN 1520-4804, Vol. 51, no 9, 2648-56 p.Article in journal (Refereed) Published
Abstract [en]

Docking, scoring, molecular dynamics (MD), and the linear interaction energy (LIE) method are used here to predict binding modes and affinities for a set of 43 non-nucleoside inhibitors to HIV-1 reverse transcriptase. Starting from a crystallographic structure, the binding modes of 43 inhibitors are predicted using automated docking. The Goldscore scoring function and the LIE method are then used to determine the relative binding free energies for the inhibitors. The Goldscore scoring function does not reproduce the relative binding affinities for the inhibitors, while the standard parametrization of the LIE method reproduces the experimental binding free energies for 39 inhibitors with an R (2) = 0.70 and an unsigned average error of 0.8 kcal/mol. The present calculations provide a validation of the combination of docking, MD, and LIE as a powerful tool in structure-based drug design, and the methodology is easily scalable for attaining a higher throughput of compounds.

National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-97214 (URN)10.1021/jm7012198 (DOI)000255500000010 ()18410085 (PubMedID)
Available from: 2008-04-29 Created: 2008-04-29 Last updated: 2017-12-14Bibliographically approved
6. Mutagenesis and homology modelling of the Tn21 integron integrase IntI1
Open this publication in new window or tab >>Mutagenesis and homology modelling of the Tn21 integron integrase IntI1
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2009 (English)In: Biochemistry, ISSN 0006-2960, E-ISSN 1520-4995, Vol. 48, no 8, 1743-1753 p.Article in journal (Refereed) Published
Abstract [en]

Horizontal DNA transfer between bacteria is widespread and a major cause of antibiotic resistance. For logistic reasons, single or combined genes are shuttled between vectors such as plasmids and   bacterial chromosomes. Special elements termed integrons operate in such shuttling and are therefore vital for horizontal gene transfer. Shorter elements carrying genes, cassettes, are integrated in the integrons, or excised from them, by virtue of a recombination site, attC, positioned in the 3' end of each unit. It is a remarkable and   possibly restricting elementary feature of attC that it must be single-stranded while the partner target site, attI, may be double-stranded. The integron integrases belong to the tyrosine recombinase family, and this work reports mutations of the integrase IntI1 from transposon Tn21, chosen within a well-conserved region characteristic of the integron integrases. The mutated proteins were  tested for binding to a bottom strand of an attC substrate, by using an electrophoresis mobility shift assay. To aid in interpreting the   results, a homology model was constructed on the basis of the crystal structure of integron integrase VchIntIA from Vibrio cholerae bound to its cognate attC substrate VCRbs. The local stability and hydrogen bonding network of key domains of the modeled structure were further examined using molecular dynamics simulations. The homology model allowed us to interpret the roles of several amino acid residues, four of which were clearly binding assay responsive upon mutagenesis. Notably, we also observed features indicating that IntI1 may be more prone to base-specific contacts with VCRbs than VchIntIA.

National Category
Biological Sciences
Identifiers
urn:nbn:se:uu:diva-95309 (URN)10.1021/bi8020235 (DOI)000263697300009 ()
Available from: 2007-01-02 Created: 2007-01-02 Last updated: 2017-12-14Bibliographically approved

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