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Molecular Simulations of G Protein-Coupled Receptors Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology 2011 Molecular simulations of G protein-coupled receptors A journey into structure-based ligand design and receptor function PIERRE MATRICON ACTA UNIVERSITATIS UPSALIENSIS ISSN 1651-6214 ISBN 978-91-513-1134-0 UPPSALA urn:nbn:se:uu:diva-434103 2021 Dissertation presented at Uppsala University to be publicly examined in A1:111a, Uppsala Biomedical Centre (BMC), Husargatan 3, Uppsala, Friday, 26 March 2021 at 13:15 for the degree of Doctor of Philosophy. The examination will be conducted in English. Faculty examiner: Professor Bjørn Olav Brandsdal (The Arctic University of Norway). Abstract Matricon, P. 2021. Molecular simulations of G protein-coupled receptors: A journey into structure-based ligand design and receptor function. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology 2011. 82 pp. Uppsala: Acta Universitatis Upsaliensis. ISBN 978-91-513-1134-0. The superfamily of G protein-coupled receptors (GPCRs) contains a large number of important drug targets. These cell surface receptors recognize extracellular signaling molecules, which stimulates intracellular pathways that play major roles in human physiology. Breakthroughs in structural biology have led to an exponentially increasing number of atomic resolution GPCR structures, which have provided insights into the molecular basis of ligand binding and receptor activation. However, in order to use these structures in rational drug design, computational methods able to predict ligand binding modes and affinities are required. In the first part of this thesis, molecular simulations were used to explore the potential of using structure- based approaches to discover and optimize GPCR ligands. In paper I, molecular dynamics (MD) simulations in combination with free energy perturbation (FEP) guided improvements of binding affinities for fragment-like ligands of the A2A adenosine receptor (A2AAR), which is a target for Parkinson’s disease and cancer. Two computational approaches were then explored to design selective GPCR ligands. MD/FEP was first used to guide the optimization of a weak fragment ligand for subtype selectivity. Simulations of the A1- and A2AARs led to the discovery of high affinity and selective A1AR antagonists (paper II). In the second approach, a molecular docking screen of millions of molecules was carried out against AR crystal structures with the goal to identify A1AR ligands. Structure-based optimization of two hits resulted in the discovery of potent and selective A1AR antagonists (paper III). In paper IV, the role of a binding site water in agonist binding to the A2AAR was probed by modifying the endogenous agonist adenosine. MD simulations highlighted the complexity of ligand binding and the benefits of using FEP calculations to guide ligand optimization. In the second part of the thesis, MD simulations were used to study the activation mechanism of class A GPCRs and the function of class F receptors. The allosteric communication between the orthosteric and G protein binding sites of the β2 adrenergic receptor was investigated, which revealed the roles of structural motifs in receptor activation (paper V). Finally, MD simulations of a homology model of the Frizzled 4 receptor, which is a target for the development of anticancer drugs, led to the identification of a conserved structural motif that is important for receptor signaling (paper VI). The results of the thesis show that computer simulations can be valuable tools in structure-based drug discovery and studies of GPCR function. Keywords: G Protein-Coupled Receptor, Molecular Dynamics Simulations, Free Energy Perturbation, Ligand Binding, Fragment-Based Lead Discovery, Molecular Docking Screens, Homology Modeling, GPCR Activation Mechanism Pierre Matricon, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics, Box 596, Uppsala University, SE-751 24 Uppsala, Sweden. © Pierre Matricon 2021 ISSN 1651-6214 ISBN 978-91-513-1134-0 urn:nbn:se:uu:diva-434103 (http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-434103) The fire burns in the night sky Hollow Coves To you, who had the courage to open this book List of Papers This thesis is based on the following papers, which are referred to in the text by their Roman numerals. I Matricon, P.,‡ Ranganathan, A.,‡ Warnick, E., Gao, Z.G., Rud- ling, A., Lambertucci, C., Marucci, G., Ezzati, A., Jaiteh, M., Dal Ben, D., Jacobson, K.A. and Carlsson, J. (2017) Fragment opti- mization for GPCRs by molecular dynamics free energy calcula- tions: Probing druggable subpockets of the A2A adenosine recep- tor binding site. Nature Scientific Reports, 7: 6398. II Matricon, P., Vo, D.D., Gao, Z.G., Kihlberg, J., Jacobson, K.A. and Carlsson, J. Fragment-based lead design guided by free en- ergy calculations identifies high affinity and selective GPCR lig- ands. Manuscript. III Matricon, P.,‡ Nguyen, A.T.N.,‡ Vo, D.D.,‡ Baltos, J.A.,‡ Jaiteh, M., Luttens, A., Christopoulos, A., Kihlberg, J., May, L.T. and Carlsson, J. Structure-based virtual screening discovers potent and selective adenosine A1 receptor antagonists. Manuscript. IV Matricon, P.,‡ Suresh, R.R.,‡ Gao, Z.G., Panel, N., Jacobson, K.A. and Carlsson, J. (2021) Ligand design by targeting a bind- ing site water. Chemical Science, 12: 960-968. V Fleetwood, O., Matricon, P., Carlsson, J. and Delemotte, L. (2020) Energy landscapes reveal agonist control of G protein- coupled receptor activation via microswitches. Biochemistry, 59(7):880-891. VI Strakova, K., Matricon, P., Yokota, C., Arthofer, E., Bernatik, O., Rodriguez, D., Arenas, E., Carlsson, J., Bryja, V. and Schulte, G. (2017) The tyrosine Y2502.39 in Frizzled 4 defines a conserved motif important for structural integrity of the receptor and re- cruitment of Disheveled. Cellular Signalling, 38:85–96. The following papers were not included in this thesis. VII Jacobson, K.A., Gao, Z.G., Matricon, P., Eddy, M.T. and Carls- son, J. (2020) Adenosine A2A receptor antagonists: from caffeine to selective non-xanthines. British Journal of Pharmacology (In Press). VIII Rodríguez-Espigares, I., Torrens-Fontanals, M., Tiemann, J.K.S., Aranda-García, D., Ramírez-Anguita, J.M., Stepniewski, T.M., Worp, N., Varela-Rial, A., Morales-Pastor, A., Medel- Lacruz, B., Pándy-Szekeres, G., Mayol, E., Giorgino, T., Carls- son, J., Deupi, X., Filipek, S., Filizola, M., Gómez-Tamayo, J.C., Gonzalez, A., Gutiérrez-de-Terán, H., Jiménez-Rosés, M., Jes- pers, W., Kapla, J., Khelashvili, G., Kolb, P., Latek, D., Marti- Solano, M., Matricon, P., Minos-Timotheos, M., Miszta, P., Olivella, M., Perez-Benito, L., Provasi, D., Ríos, S., Torrecillas, I.R., Sallander, S., Sztyler, A., Vasile, S., Weinstein, H., Zacha- riae, U., Hildebrand, P.W., De Fabritiis, G., Sanz, F., Gloriam, D.E., Cordomi, A., Guixà-González, R. and Selent, J. (2020). GPCRmd uncovers the dynamics of the 3D-GPCRome. Nature Methods, 17:777-787. IX Petersen, J., Wright, S.C., Rodríguez, D., Matricon, P., Lahav, N., Vromen, A., Friedler, A., Strömqvist, J., Wennmalm, S., Carlsson, J. and Schulte, G. (2017). Agonist-induced dimer dis- sociation as a macromolecular step in G protein-coupled receptor signaling. Nature Communications 8:226. X Wright, S.C., Cañizal, M.C.A, Benkel, T., Simon, K., Le Gouill, C., Matricon, P., Namkung, Y., Lukasheva, V., König, G.M., Laporte, S.A., Carlsson, J., Kostenis, E., Bouvier, M., Schulte, G. and Hoffmann, C. (2018). FZD5 is a Gαq-coupled receptor that exhibits the functional hallmarks of prototypical GPCRs. Science Signaling 11(559):eaar5536. ‡ These authors contributed equally. Reprints were made with permission from the respective publishers. Contents 1. Introduction .......................................................................................... 11 1.1 G protein-coupled receptors ........................................................... 11 1.1.1 The GPCR superfamily and its drug targets ........................... 11 1.1.2 Different modes of GPCR signaling ....................................... 11 1.1.3 Different types of orthosteric ligands ..................................... 13 1.2. Structure-based GPCR drug discovery ......................................... 14 1.2.1 Structural biology of GPCRs .................................................. 14 1.2.2 Structure-based virtual screening in drug discovery .............. 16 1.2.3 Fragment-based lead discovery .............................................. 17 1.3 Topics explored in this thesis ......................................................... 19 2. Methods................................................................................................. 20 2.1 Statistical thermodynamics ............................................................ 20 2.2 Molecular mechanics force fields .................................................. 22 2.3 Molecules in motion ....................................................................... 22 2.4 Molecular dynamics simulations .................................................... 23 2.5 Calculation of relative binding free energies ................................. 26 2.6 Ligand binding in vitro ................................................................... 27 2.7 Molecular docking .......................................................................... 29 2.8 Prediction of GPCR structures with homology modeling .............. 30 3. Optimization of adenosine receptor fragment ligands with molecular
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