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Adediwura VA, Koirala K, Do HN, Wang J, Miao Y. Understanding the impact of binding free energy and kinetics calculations in modern drug discovery. Expert Opin Drug Discov 2024; 19:671-682. [PMID: 38722032 PMCID: PMC11108734 DOI: 10.1080/17460441.2024.2349149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 04/25/2024] [Indexed: 05/22/2024]
Abstract
INTRODUCTION For rational drug design, it is crucial to understand the receptor-drug binding processes and mechanisms. A new era for the use of computer simulations in predicting drug-receptor interactions at an atomic level has begun with remarkable advances in supercomputing and methodological breakthroughs. AREAS COVERED End-point free energy calculation methods such as Molecular Mechanics/Poisson Boltzmann Surface Area (MM/PBSA) or Molecular-Mechanics/Generalized Born Surface Area (MM/GBSA), free energy perturbation (FEP), and thermodynamic integration (TI) are commonly used for binding free energy calculations in drug discovery. In addition, kinetic dissociation and association rate constants (k off and k on ) play critical roles in the function of drugs. Nowadays, Molecular Dynamics (MD) and enhanced sampling simulations are increasingly being used in drug discovery. Here, the authors provide a review of the computational techniques used in drug binding free energy and kinetics calculations. EXPERT OPINION The applications of computational methods in drug discovery and design are expanding, thanks to improved predictions of the binding free energy and kinetic rates of drug molecules. Recent microsecond-timescale enhanced sampling simulations have made it possible to accurately capture repetitive ligand binding and dissociation, facilitating more efficient and accurate calculations of ligand binding free energy and kinetics.
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Affiliation(s)
- Victor A. Adediwura
- Department of Pharmacology and Computational Medicine Program, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Kushal Koirala
- Department of Pharmacology and Computational Medicine Program, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Hung N. Do
- Center for Computational Biology, University of Kansas, Lawrence, KS, USA
- Present address: Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, USA
| | - Jinan Wang
- Department of Pharmacology and Computational Medicine Program, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Yinglong Miao
- Department of Pharmacology and Computational Medicine Program, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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Stampelou M, Ladds G, Kolocouris A. Computational Workflow for Refining AlphaFold Models in Drug Design Using Kinetic and Thermodynamic Binding Calculations: A Case Study for the Unresolved Inactive Human Adenosine A 3 Receptor. J Phys Chem B 2024; 128:914-936. [PMID: 38236582 DOI: 10.1021/acs.jpcb.3c05986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
A structure-based drug design pipeline that considers both thermodynamic and kinetic binding data of ligands against a receptor will enable the computational design of improved drug molecules. For unresolved GPCR-ligand complexes, a workflow that can apply both thermodynamic and kinetic binding data in combination with alpha-fold (AF)-derived or other homology models and experimentally resolved binding modes of relevant ligands in GPCR-homologs needs to be tested. Here, as test case, we studied a congeneric set of ligands that bind to a structurally unresolved G protein-coupled receptor (GPCR), the inactive human adenosine A3 receptor (hA3R). We tested three available homology models from which two have been generated from experimental structures of hA1R or hA2AR and one model was a multistate alphafold 2 (AF2)-derived model. We applied alchemical calculations with thermodynamic integration coupled with molecular dynamics (TI/MD) simulations to calculate the experimental relative binding free energies and residence time (τ)-random accelerated MD (τ-RAMD) simulations to calculate the relative residence times (RTs) for antagonists. While the TI/MD calculations produced, for the three homology models, good Pearson correlation coefficients, correspondingly, r = 0.74, 0.62, and 0.67 and mean unsigned error (mue) values of 0.94, 1.31, and 0.81 kcal mol-1, the τ-RAMD method showed r = 0.92 and 0.52 for the first two models but failed to produce accurate results for the multistate AF2-derived model. With subsequent optimization of the AF2-derived model by reorientation of the side chain of R1735.34 located in the extracellular loop 2 (EL2) that blocked ligand's unbinding, the computational model showed r = 0.84 for kinetic data and improved performance for thermodynamic data (r = 0.81, mue = 0.56 kcal mol-1). Overall, after refining the multistate AF2 model with physics-based tools, we were able to show a strong correlation between predicted and experimental ligand relative residence times and affinities, achieving a level of accuracy comparable to an experimental structure. The computational workflow used can be applied to other receptors, helping to rank candidate drugs in a congeneric series and enabling the prioritization of leads with stronger binding affinities and longer residence times.
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Affiliation(s)
- Margarita Stampelou
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771 Athens, Greece
| | - Graham Ladds
- Department of Pharmacology, University of Cambridge, Tennis Court Road, Cambridge CB2 1PD, U.K
| | - Antonios Kolocouris
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771 Athens, Greece
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3
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Papadourakis M, Sinenka H, Matricon P, Hénin J, Brannigan G, Pérez-Benito L, Pande V, van Vlijmen H, de Graaf C, Deflorian F, Tresadern G, Cecchini M, Cournia Z. Alchemical Free Energy Calculations on Membrane-Associated Proteins. J Chem Theory Comput 2023; 19:7437-7458. [PMID: 37902715 PMCID: PMC11017255 DOI: 10.1021/acs.jctc.3c00365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Indexed: 10/31/2023]
Abstract
Membrane proteins have diverse functions within cells and are well-established drug targets. The advances in membrane protein structural biology have revealed drug and lipid binding sites on membrane proteins, while computational methods such as molecular simulations can resolve the thermodynamic basis of these interactions. Particularly, alchemical free energy calculations have shown promise in the calculation of reliable and reproducible binding free energies of protein-ligand and protein-lipid complexes in membrane-associated systems. In this review, we present an overview of representative alchemical free energy studies on G-protein-coupled receptors, ion channels, transporters as well as protein-lipid interactions, with emphasis on best practices and critical aspects of running these simulations. Additionally, we analyze challenges and successes when running alchemical free energy calculations on membrane-associated proteins. Finally, we highlight the value of alchemical free energy calculations calculations in drug discovery and their applicability in the pharmaceutical industry.
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Affiliation(s)
- Michail Papadourakis
- Biomedical
Research Foundation, Academy of Athens, 4 Soranou Ephessiou, 11527 Athens, Greece
| | - Hryhory Sinenka
- Institut
de Chimie de Strasbourg, UMR7177, CNRS, Université de Strasbourg, F-67083 Strasbourg Cedex, France
| | - Pierre Matricon
- Sosei
Heptares, Steinmetz Building,
Granta Park, Great Abington, Cambridge CB21 6DG, United
Kingdom
| | - Jérôme Hénin
- Laboratoire
de Biochimie Théorique UPR 9080, CNRS and Université Paris Cité, 75005 Paris, France
| | - Grace Brannigan
- Center
for Computational and Integrative Biology, Rutgers University−Camden, Camden, New Jersey 08103, United States of America
- Department
of Physics, Rutgers University−Camden, Camden, New Jersey 08102, United States
of America
| | - Laura Pérez-Benito
- CADD,
In Silico Discovery, Janssen Research &
Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Vineet Pande
- CADD,
In Silico Discovery, Janssen Research &
Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Herman van Vlijmen
- CADD,
In Silico Discovery, Janssen Research &
Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Chris de Graaf
- Sosei
Heptares, Steinmetz Building,
Granta Park, Great Abington, Cambridge CB21 6DG, United
Kingdom
| | - Francesca Deflorian
- Sosei
Heptares, Steinmetz Building,
Granta Park, Great Abington, Cambridge CB21 6DG, United
Kingdom
| | - Gary Tresadern
- CADD,
In Silico Discovery, Janssen Research &
Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Marco Cecchini
- Institut
de Chimie de Strasbourg, UMR7177, CNRS, Université de Strasbourg, F-67083 Strasbourg Cedex, France
| | - Zoe Cournia
- Biomedical
Research Foundation, Academy of Athens, 4 Soranou Ephessiou, 11527 Athens, Greece
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Han R, Yoon H, Yoo J, Lee Y. Systematic analyses of the sequence conservation and ligand interaction patterns of purinergic P1 and P2Y receptors provide a structural basis for receptor selectivity. Comput Struct Biotechnol J 2023; 21:889-898. [PMID: 36698973 PMCID: PMC9860165 DOI: 10.1016/j.csbj.2023.01.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 01/09/2023] [Accepted: 01/09/2023] [Indexed: 01/11/2023] Open
Abstract
Purinergic receptors are membrane proteins that regulate numerous cellular functions by catalyzing reactions involving purine nucleotides or nucleosides. Among the three receptor families, i.e., P1, P2X, and P2Y, the P1 and P2Y receptors share common structural features of class A GPCR. Comprehensive sequence and structural analysis revealed that the P1 and P2Y receptors belong to two distinct groups. They exhibit different ligand-binding site features that can distinguish between specific activators. These specific amino acid residues in the binding cavity may be involved in the selectivity and unique pharmacological behavior of each subtype. In this study, we conducted a structure-based analysis of purinergic P1 and P2Y receptors to identify their evolutionary signature and obtain structural insights into ligand recognition and selectivity. The structural features of the P1 and P2Y receptor classes were compared based on sequence conservation and ligand interaction patterns. Orthologous protein sequences were collected for the P1 and P2Y receptors, and sequence conservation was calculated based on Shannon entropy to identify highly conserved residues. To analyze the ligand interaction patterns, we performed docking studies on the P1 and P2Y receptors using known ligand information extracted from the ChEMBL database. We analyzed how the conserved residues are related to ligand-binding sites and how the key interacting residues differ between P1 and P2Y receptors, or between agonists and antagonists. We extracted new similarities and differences between the receptor subtypes, and the results can be used for designing new ligands by predicting hotspot residues that are important for functional selectivity.
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5
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Mahmood A, Iqbal J. Purinergic receptors modulators: An emerging pharmacological tool for disease management. Med Res Rev 2022; 42:1661-1703. [PMID: 35561109 DOI: 10.1002/med.21888] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 03/16/2022] [Accepted: 05/04/2022] [Indexed: 11/10/2022]
Abstract
Purinergic signaling is mediated through extracellular nucleotides (adenosine 5'-triphosphate, uridine-5'-triphosphate, adenosine diphosphate, uridine-5'-diphosphate, and adenosine) that serve as signaling molecules. In the early 1990s, purines and pyrimidine receptors were cloned and characterized drawing the attention of scientists toward this aspect of cellular signaling. This signaling pathway is comprised of four subtypes of adenosine receptors (P1), eight subtypes of G-coupled protein receptors (P2YRs), and seven subtypes of ligand-gated ionotropic receptors (P2XRs). In current studies, the pathophysiology and therapeutic potentials of these receptors have been focused on. Various ligands, modulating the functions of purinergic receptors, are in current clinical practices for the treatment of various neurodegenerative disorders and cardiovascular diseases. Moreover, several purinergic receptors ligands are in advanced phases of clinical trials as a remedy for depression, epilepsy, autism, osteoporosis, atherosclerosis, myocardial infarction, diabetes, irritable bowel syndrome, and cancers. In the present study, agonists and antagonists of purinergic receptors have been summarized that may serve as pharmacological tools for drug design and development.
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Affiliation(s)
- Abid Mahmood
- Centre for Advanced Drug Research, COMSATS University Islamabad, Abbottabad, Pakistan
| | - Jamshed Iqbal
- Centre for Advanced Drug Research, COMSATS University Islamabad, Abbottabad, Pakistan
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IJzerman AP, Jacobson KA, Müller CE, Cronstein BN, Cunha RA. International Union of Basic and Clinical Pharmacology. CXII: Adenosine Receptors: A Further Update. Pharmacol Rev 2022; 74:340-372. [PMID: 35302044 PMCID: PMC8973513 DOI: 10.1124/pharmrev.121.000445] [Citation(s) in RCA: 56] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Our previous International Union of Basic and Clinical Pharmacology report on the nomenclature and classification of adenosine receptors (2011) contained a number of emerging developments with respect to this G protein-coupled receptor subfamily, including protein structure, protein oligomerization, protein diversity, and allosteric modulation by small molecules. Since then, a wealth of new data and results has been added, allowing us to explore novel concepts such as target binding kinetics and biased signaling of adenosine receptors, to examine a multitude of receptor structures and novel ligands, to gauge new pharmacology, and to evaluate clinical trials with adenosine receptor ligands. This review should therefore be considered a further update of our previous reports from 2001 and 2011. SIGNIFICANCE STATEMENT: Adenosine receptors (ARs) are of continuing interest for future treatment of chronic and acute disease conditions, including inflammatory diseases, neurodegenerative afflictions, and cancer. The design of AR agonists ("biased" or not) and antagonists is largely structure based now, thanks to the tremendous progress in AR structural biology. The A2A- and A2BAR appear to modulate the immune response in tumor biology. Many clinical trials for this indication are ongoing, whereas an A2AAR antagonist (istradefylline) has been approved as an anti-Parkinson agent.
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Affiliation(s)
- Adriaan P IJzerman
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands (A.P.IJ.); National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Molecular Recognition Section, Bethesda, Maryland (K.A.J.); Universität Bonn, Bonn, Germany (C.E.M.); New York University School of Medicine, New York, New York (B.N.C.); and Center for Neurosciences and Cell Biology and Faculty of Medicine, University of Coimbra, Coimbra, Portugal (R.A.C.)
| | - Kenneth A Jacobson
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands (A.P.IJ.); National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Molecular Recognition Section, Bethesda, Maryland (K.A.J.); Universität Bonn, Bonn, Germany (C.E.M.); New York University School of Medicine, New York, New York (B.N.C.); and Center for Neurosciences and Cell Biology and Faculty of Medicine, University of Coimbra, Coimbra, Portugal (R.A.C.)
| | - Christa E Müller
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands (A.P.IJ.); National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Molecular Recognition Section, Bethesda, Maryland (K.A.J.); Universität Bonn, Bonn, Germany (C.E.M.); New York University School of Medicine, New York, New York (B.N.C.); and Center for Neurosciences and Cell Biology and Faculty of Medicine, University of Coimbra, Coimbra, Portugal (R.A.C.)
| | - Bruce N Cronstein
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands (A.P.IJ.); National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Molecular Recognition Section, Bethesda, Maryland (K.A.J.); Universität Bonn, Bonn, Germany (C.E.M.); New York University School of Medicine, New York, New York (B.N.C.); and Center for Neurosciences and Cell Biology and Faculty of Medicine, University of Coimbra, Coimbra, Portugal (R.A.C.)
| | - Rodrigo A Cunha
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands (A.P.IJ.); National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Molecular Recognition Section, Bethesda, Maryland (K.A.J.); Universität Bonn, Bonn, Germany (C.E.M.); New York University School of Medicine, New York, New York (B.N.C.); and Center for Neurosciences and Cell Biology and Faculty of Medicine, University of Coimbra, Coimbra, Portugal (R.A.C.)
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Wang J, Bhattarai A, Do HN, Akhter S, Miao Y. Molecular Simulations and Drug Discovery of Adenosine Receptors. Molecules 2022; 27:2054. [PMID: 35408454 PMCID: PMC9000248 DOI: 10.3390/molecules27072054] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 03/18/2022] [Accepted: 03/20/2022] [Indexed: 02/02/2023] Open
Abstract
G protein-coupled receptors (GPCRs) represent the largest family of human membrane proteins. Four subtypes of adenosine receptors (ARs), the A1AR, A2AAR, A2BAR and A3AR, each with a unique pharmacological profile and distribution within the tissues in the human body, mediate many physiological functions and serve as critical drug targets for treating numerous human diseases including cancer, neuropathic pain, cardiac ischemia, stroke and diabetes. The A1AR and A3AR preferentially couple to the Gi/o proteins, while the A2AAR and A2BAR prefer coupling to the Gs proteins. Adenosine receptors were the first subclass of GPCRs that had experimental structures determined in complex with distinct G proteins. Here, we will review recent studies in molecular simulations and computer-aided drug discovery of the adenosine receptors and also highlight their future research opportunities.
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Affiliation(s)
| | | | | | | | - Yinglong Miao
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66047, USA; (J.W.); (A.B.); (H.N.D.); (S.A.)
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8
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Merighi S, Borea PA, Varani K, Vincenzi F, Jacobson KA, Gessi S. A 2A Adenosine Receptor Antagonists in Neurodegenerative Diseases. Curr Med Chem 2022; 29:4138-4151. [PMID: 34844537 PMCID: PMC9148371 DOI: 10.2174/0929867328666211129122550] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Revised: 10/01/2021] [Accepted: 10/07/2021] [Indexed: 01/03/2023]
Abstract
BACKGROUND Alzheimer's disease (AD) is the most common form of dementia worldwide, with approximately 6 million cases reported in America in 2020. The clinical signs of AD include cognitive dysfunction, apathy, anxiety and neuropsychiatric signs, and pathogenetic mechanisms that involve amyloid peptide-β extracellular accumulation and tau hyperphosphorylation. Unfortunately, current drugs to treat AD can provide only symptomatic relief but are not disease-modifying molecules able to revert AD progression. The endogenous modulator adenosine, through A2A receptor activation, plays a role in synaptic loss and neuroinflammation, which are crucial for cognitive impairment and memory damage. OBJECTIVE In this review, recent advances covering A2A adenosine receptor antagonists will be extensively reviewed, providing a basis for the rational design of future A2A inhibitors. METHODS Herein, the literature on A2A adenosine receptors and their role in synaptic plasticity and neuroinflammation, as well as the effects of A2A antagonism in animal models of AD and in humans, are reviewed. Furthermore, current chemical and structure-based strategies are presented. RESULTS Caffeine, the most widely consumed natural product stimulant and an A2A antagonist, improves human memory. Similarly, synthetic A2A receptor antagonists, as described in this review, may provide a means to fight AD. CONCLUSION This review highlights the clinical potential of A2A adenosine receptor antagonists as a novel approach to treat patients with AD.
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Affiliation(s)
- Stefania Merighi
- Department of Translational Medicine and for Romagna, University of Ferrara, 44121, Ferrara, Italy;,Address correspondence to these authors at the Department Translational Medicine and for Romagna, University of Ferrara, 44121, Ferrara, Italy; ; ; Molecular Recognition Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, United States;
| | | | - Katia Varani
- Department of Translational Medicine and for Romagna, University of Ferrara, 44121, Ferrara, Italy
| | - Fabrizio Vincenzi
- Department of Translational Medicine and for Romagna, University of Ferrara, 44121, Ferrara, Italy
| | - Kenneth A. Jacobson
- Molecular Recognition Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, United States,Address correspondence to these authors at the Department Translational Medicine and for Romagna, University of Ferrara, 44121, Ferrara, Italy; ; ; Molecular Recognition Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, United States;
| | - Stefania Gessi
- Department of Translational Medicine and for Romagna, University of Ferrara, 44121, Ferrara, Italy;,Address correspondence to these authors at the Department Translational Medicine and for Romagna, University of Ferrara, 44121, Ferrara, Italy; ; ; Molecular Recognition Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, United States;
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Ballante F, Kooistra AJ, Kampen S, de Graaf C, Carlsson J. Structure-Based Virtual Screening for Ligands of G Protein-Coupled Receptors: What Can Molecular Docking Do for You? Pharmacol Rev 2021; 73:527-565. [PMID: 34907092 DOI: 10.1124/pharmrev.120.000246] [Citation(s) in RCA: 53] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
G protein-coupled receptors (GPCRs) constitute the largest family of membrane proteins in the human genome and are important therapeutic targets. During the last decade, the number of atomic-resolution structures of GPCRs has increased rapidly, providing insights into drug binding at the molecular level. These breakthroughs have created excitement regarding the potential of using structural information in ligand design and initiated a new era of rational drug discovery for GPCRs. The molecular docking method is now widely applied to model the three-dimensional structures of GPCR-ligand complexes and screen for chemical probes in large compound libraries. In this review article, we first summarize the current structural coverage of the GPCR superfamily and the understanding of receptor-ligand interactions at atomic resolution. We then present the general workflow of structure-based virtual screening and strategies to discover GPCR ligands in chemical libraries. We assess the state of the art of this research field by summarizing prospective applications of virtual screening based on experimental structures. Strategies to identify compounds with specific efficacy and selectivity profiles are discussed, illustrating the opportunities and limitations of the molecular docking method. Our overview shows that structure-based virtual screening can discover novel leads and will be essential in pursuing the next generation of GPCR drugs. SIGNIFICANCE STATEMENT: Extraordinary advances in the structural biology of G protein-coupled receptors have revealed the molecular details of ligand recognition by this large family of therapeutic targets, providing novel avenues for rational drug design. Structure-based docking is an efficient computational approach to identify novel chemical probes from large compound libraries, which has the potential to accelerate the development of drug candidates.
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Affiliation(s)
- Flavio Ballante
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden (F.B., S.K., J.C.); Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark (A.J.K.); and Sosei Heptares, Steinmetz Building, Granta Park, Great Abington, Cambridge, United Kingdom (C.d.G.)
| | - Albert J Kooistra
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden (F.B., S.K., J.C.); Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark (A.J.K.); and Sosei Heptares, Steinmetz Building, Granta Park, Great Abington, Cambridge, United Kingdom (C.d.G.)
| | - Stefanie Kampen
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden (F.B., S.K., J.C.); Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark (A.J.K.); and Sosei Heptares, Steinmetz Building, Granta Park, Great Abington, Cambridge, United Kingdom (C.d.G.)
| | - Chris de Graaf
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden (F.B., S.K., J.C.); Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark (A.J.K.); and Sosei Heptares, Steinmetz Building, Granta Park, Great Abington, Cambridge, United Kingdom (C.d.G.)
| | - Jens Carlsson
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden (F.B., S.K., J.C.); Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark (A.J.K.); and Sosei Heptares, Steinmetz Building, Granta Park, Great Abington, Cambridge, United Kingdom (C.d.G.)
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10
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Jespers W, Heitman LH, IJzerman AP, Sotelo E, van Westen GJP, Åqvist J, Gutiérrez-de-Terán H. Deciphering conformational selectivity in the A2A adenosine G protein-coupled receptor by free energy simulations. PLoS Comput Biol 2021; 17:e1009152. [PMID: 34818333 PMCID: PMC8654218 DOI: 10.1371/journal.pcbi.1009152] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 12/08/2021] [Accepted: 11/11/2021] [Indexed: 12/25/2022] Open
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 A2A adenosine receptor (AR). These cycles were solved with efficient free energy perturbation (FEP) protocols, allowing to distinguish the pharmacological profile of different series of A2AAR 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. The design of new ligands as chemical modulators of G protein-coupled receptors (GPCRs) has benefited considerably during the last years of advances in both the structural and computational biology disciplines. Within the last area, the use of free energy calculation methods has arisen as a computational tool to predict ligand affinities to explain structure-affinity relationships and guide lead optimization campaigns. However, our comprehension of the structural determinants of ligands with different pharmacological profile is scarce, and knowledge of the chemical modifications associated with an agonistic or antagonistic profile would be extremely valuable. We herein report an original implementation of the thermodynamic cycles associated with free energy perturbation (FEP) simulations, to mimic the conformational equilibrium between active and inactive GPCRs, and establish a framework to describe pharmacological profiles as a function of the ligands selectivity for a given receptor conformation. The advantage of this method resides into its simplicity of use, and the only consideration of active and inactive conformations of the receptor, with no simulation of the transitions between them. This model can accurately predict the pharmacological profile of series of full and partial agonists as opposed to antagonists of the A2A adenosine receptor, and moreover, how certain mutations associated with modulation of basal activity can influence this pharmacological profiles, which enables our understanding of such clinically relevant mutations.
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Affiliation(s)
- Willem Jespers
- Department of Cell and Molecular Biology, Uppsala University, Biomedical Center (BMC), Uppsala, Sweden
- Drug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden, The Netherlands
- * E-mail: (WJ); (HGT)
| | - Laura H. Heitman
- Drug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden, The Netherlands
- Oncode Institute, Leiden, Leiden
| | - Adriaan P. IJzerman
- Drug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden, The Netherlands
| | - Eddy Sotelo
- Centro Singular de Investigación en Química Biolóxica y Materiais Moleculares (CIQUS), Santiago de Compostela, Spain
- Departamento de Química Orgánica, Facultade de Farmacia, Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Gerard J. P. van Westen
- Drug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden, The Netherlands
| | - Johan Åqvist
- Department of Cell and Molecular Biology, Uppsala University, Biomedical Center (BMC), Uppsala, Sweden
| | - Hugo Gutiérrez-de-Terán
- Department of Cell and Molecular Biology, Uppsala University, Biomedical Center (BMC), Uppsala, Sweden
- Science for Life Laboratories, BMC, Uppsala, Sweden
- * E-mail: (WJ); (HGT)
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11
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Salmaso V, Jain S, Jacobson KA. Purinergic GPCR transmembrane residues involved in ligand recognition and dimerization. Methods Cell Biol 2021; 166:133-159. [PMID: 34752329 PMCID: PMC8620127 DOI: 10.1016/bs.mcb.2021.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/25/2023]
Abstract
We compare the GPCR-ligand interactions and highlight important residues for recognition in purinergic receptors-from both X-ray crystallographic and cryo-EM structures. These include A1 and A2A adenosine receptors, and P2Y1 and P2Y12 receptors that respond to ADP and other nucleotides. These receptors are important drug discovery targets for immune, metabolic and nervous system disorders. In most cases, orthosteric ligands are represented, except for one allosteric P2Y1 antagonist. This review catalogs the residues and regions that engage in contacts with ligands or with other GPCR protomers in dimeric forms. Residues that are in proximity to bound ligands within purinergic GPCR families are correlated. There is extensive conservation of recognition motifs between adenosine receptors, but the P2Y1 and P2Y12 receptors are each structurally distinct in their ligand recognition. Identifying common interaction features for ligand recognition within a receptor class that has multiple structures available can aid in the drug discovery process.
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Affiliation(s)
- Veronica Salmaso
- Molecular Recognition Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, United States
| | - Shanu Jain
- Molecular Recognition Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, United States
| | - Kenneth A Jacobson
- Molecular Recognition Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, United States.
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12
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Identification of V6.51L as a selectivity hotspot in stereoselective A 2B adenosine receptor antagonist recognition. Sci Rep 2021; 11:14171. [PMID: 34238993 PMCID: PMC8266863 DOI: 10.1038/s41598-021-93419-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 06/24/2021] [Indexed: 12/15/2022] Open
Abstract
The four adenosine receptors (ARs) A1AR, A2AAR, A2BAR, and A3AR 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 A2BAR 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 A2A and A2B receptors demonstrate the stereospecific and selective recognition of (S)-ISAM140 to the A2BAR. The molecular modeling suggested that the structural determinants of this selectivity profile would be residue V2506.51 in A2BAR, which is a leucine in all other ARs including the closely related A2AAR. This was herein confirmed by radioligand binding assays and rigorous free energy perturbation (FEP) calculations performed on the L249V6.51 mutant A2AAR receptor. Taken together, this study provides further insights in the binding mode of these A2BAR antagonists, paving the way for future ligand optimization.
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13
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Cheng J, Chen M, Wang S, Liang T, Chen H, Chen CJ, Feng Z, Xie XQ. Binding Characterization of Agonists and Antagonists by MCCS: A Case Study from Adenosine A 2A Receptor. ACS Chem Neurosci 2021; 12:1606-1620. [PMID: 33856784 DOI: 10.1021/acschemneuro.1c00082] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Characterizing the structural basis of ligand recognition of adenosine A2A receptor (AA2AR) will facilitate its rational design and development of small molecules with high affinity and selectivity, as well as optimal therapeutic effects for pain, cancers, drug abuse disorders, etc. In the present work, we applied our reported algorithm, molecular complex characterizing system (MCCS), to characterize the binding features of AA2AR based on its reported 3D structures of protein-ligand complexes. First, we compared the binding score to the reported experimental binding affinities of each compound. Then, we calculated an output example of residue energy contribution using MCCS and compared the results with data obtained from MM/GBSA. The consistency in results indicated that MCCS is a powerful, fast, and accurate method. Sequentially, using a receptor-ligand data set of 57 crystallized structures of AA2ARs, we characterized the binding features of the binding pockets in AA2AR, summarized the key residues that distinguish antagonist from agonist, produced heatmaps of residue energy contribution for clustering various statuses of AA2ARs, explored the selectivity between AA2AR and AA1AR, etc. All the information provided new insights into the protein features of AA2AR and will facilitate its rational drug design.
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Affiliation(s)
- Jin Cheng
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, and National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States.,Department of Pharmacy, Jiangsu Vocational College of Medicine, Yancheng, Jiangsu 224005, China
| | - Maozi Chen
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, and National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Siyi Wang
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, and National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Tianjian Liang
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, and National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Hui Chen
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, and National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Chih-Jung Chen
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, and National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Zhiwei Feng
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, and National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Xiang-Qun Xie
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, and National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
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14
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Do HN, Akhter S, Miao Y. Pathways and Mechanism of Caffeine Binding to Human Adenosine A 2A Receptor. Front Mol Biosci 2021; 8:673170. [PMID: 33987207 PMCID: PMC8111288 DOI: 10.3389/fmolb.2021.673170] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 03/24/2021] [Indexed: 11/13/2022] Open
Abstract
Caffeine (CFF) is a common antagonist to the four subtypes of adenosine G-protein-coupled receptors (GPCRs), which are critical drug targets for treating heart failure, cancer, and neurological diseases. However, the pathways and mechanism of CFF binding to the target receptors remain unclear. In this study, we have performed all-atom-enhanced sampling simulations using a robust Gaussian-accelerated molecular dynamics (GaMD) method to elucidate the binding mechanism of CFF to human adenosine A2A receptor (A2AAR). Multiple 500–1,000 ns GaMD simulations captured both binding and dissociation of CFF in the A2AAR. The GaMD-predicted binding poses of CFF were highly consistent with the x-ray crystal conformations with a characteristic hydrogen bond formed between CFF and residue N6.55 in the receptor. In addition, a low-energy intermediate binding conformation was revealed for CFF at the receptor extracellular mouth between ECL2 and TM1. While the ligand-binding pathways of the A2AAR were found similar to those of other class A GPCRs identified from previous studies, the ECL2 with high sequence divergence serves as an attractive target site for designing allosteric modulators as selective drugs of the A2AAR.
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Affiliation(s)
- Hung N Do
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS, United States
| | - Sana Akhter
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS, United States
| | - Yinglong Miao
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS, United States
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15
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Vanga SR, Åqvist J, Hallberg A, Gutiérrez-de-Terán H. Structural Basis of Inhibition of Human Insulin-Regulated Aminopeptidase (IRAP) by Benzopyran-Based Inhibitors. Front Mol Biosci 2021; 8:625274. [PMID: 33869280 PMCID: PMC8047434 DOI: 10.3389/fmolb.2021.625274] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Accepted: 03/10/2021] [Indexed: 12/01/2022] Open
Abstract
Inhibition of the insulin-regulated aminopeptidase (IRAP) improves memory and cognition in animal models. The enzyme has recently been crystallized and several series of inhibitors reported. We herein focused on one series of benzopyran-based inhibitors of IRAP known as the HFI series, with unresolved binding mode to IRAP, and developed a robust computational model to explain the structure-activity relationship (SAR) and potentially guide their further optimization. The binding model here proposed places the benzopyran ring in the catalytic binding site, coordinating the Zn2+ ion through the oxygen in position 3, in contrast to previous hypothesis. The whole series of HFI compounds was then systematically simulated, starting from this binding mode, using molecular dynamics and binding affinity estimated with the linear interaction energy (LIE) method. The agreement with experimental affinities supports the binding mode proposed, which was further challenged by rigorous free energy perturbation (FEP) calculations. Here, we found excellent correlation between experimental and calculated binding affinity differences, both between selected compound pairs and also for recently reported experimental data concerning the site directed mutagenesis of residue Phe544. The computationally derived structure-activity relationship of the HFI series and the understanding of the involvement of Phe544 in the binding of this scaffold provide valuable information for further lead optimization of novel IRAP inhibitors.
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Affiliation(s)
| | - Johan Åqvist
- Department of Cell and Molecular Biology, BMC, Uppsala University, Uppsala, Sweden
| | - Anders Hallberg
- Department of Pharmaceutical Chemistry, BMC, Uppsala University, Uppsala, Sweden
| | - Hugo Gutiérrez-de-Terán
- Department of Cell and Molecular Biology, BMC, Uppsala University, Uppsala, Sweden.,Science for Life Laboratory, Uppsala University, Uppsala, Sweden
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The Specificity of Downstream Signaling for A 1 and A 2AR Does Not Depend on the C-Terminus, Despite the Importance of This Domain in Downstream Signaling Strength. Biomedicines 2020; 8:biomedicines8120603. [PMID: 33322210 PMCID: PMC7764039 DOI: 10.3390/biomedicines8120603] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 12/07/2020] [Accepted: 12/09/2020] [Indexed: 11/17/2022] Open
Abstract
Recent efforts to determine the high-resolution crystal structures for the adenosine receptors (A1R and A2AR) have utilized modifications to the native receptors in order to facilitate receptor crystallization and structure determination. One common modification is a truncation of the unstructured C-terminus, which has been utilized for all the adenosine receptor crystal structures obtained to date. Ligand binding for this truncated receptor has been shown to be similar to full-length receptor for A2AR. However, the C-terminus has been identified as a location for protein-protein interactions that may be critical for the physiological function of these important drug targets. We show that variants with A2AR C-terminal truncations lacked cAMP-linked signaling compared to the full-length receptor constructs transfected into mammalian cells (HEK-293). In addition, we show that in a humanized yeast system, the absence of the full-length C-terminus affected downstream signaling using a yeast MAPK response-based fluorescence assay, though full-length receptors showed native-like G-protein coupling. To further study the G protein coupling, we used this humanized yeast platform to explore coupling to human-yeast G-protein chimeras in a cellular context. Although the C-terminus was essential for Gα protein-associated signaling, chimeras of A1R with a C-terminus of A2AR coupled to the A1R-specific Gα (i.e., Gαi1 versus Gαs). This surprising result suggests that the C-terminus is important in the signaling strength, but not specificity, of the Gα protein interaction. This result has further implications in drug discovery, both in enabling the experimental use of chimeras for ligand design, and in the cautious interpretation of structure-based drug design using truncated receptors.
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17
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Torrens-Fontanals M, Stepniewski TM, Aranda-García D, Morales-Pastor A, Medel-Lacruz B, Selent J. How Do Molecular Dynamics Data Complement Static Structural Data of GPCRs. Int J Mol Sci 2020; 21:E5933. [PMID: 32824756 PMCID: PMC7460635 DOI: 10.3390/ijms21165933] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 08/11/2020] [Accepted: 08/15/2020] [Indexed: 01/08/2023] Open
Abstract
G protein-coupled receptors (GPCRs) are implicated in nearly every physiological process in the human body and therefore represent an important drug targeting class. Advances in X-ray crystallography and cryo-electron microscopy (cryo-EM) have provided multiple static structures of GPCRs in complex with various signaling partners. However, GPCR functionality is largely determined by their flexibility and ability to transition between distinct structural conformations. Due to this dynamic nature, a static snapshot does not fully explain the complexity of GPCR signal transduction. Molecular dynamics (MD) simulations offer the opportunity to simulate the structural motions of biological processes at atomic resolution. Thus, this technique can incorporate the missing information on protein flexibility into experimentally solved structures. Here, we review the contribution of MD simulations to complement static structural data and to improve our understanding of GPCR physiology and pharmacology, as well as the challenges that still need to be overcome to reach the full potential of this technique.
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Affiliation(s)
- Mariona Torrens-Fontanals
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM)—Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), 08003 Barcelona, Spain; (M.T.-F.); (T.M.S.); (D.A.-G.); (A.M.-P.); (B.M.-L.)
| | - Tomasz Maciej Stepniewski
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM)—Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), 08003 Barcelona, Spain; (M.T.-F.); (T.M.S.); (D.A.-G.); (A.M.-P.); (B.M.-L.)
- InterAx Biotech AG, PARK innovAARE, 5234 Villigen, Switzerland
- Faculty of Chemistry, Biological and Chemical Research Centre, University of Warsaw, 02-093 Warsaw, Poland
| | - David Aranda-García
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM)—Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), 08003 Barcelona, Spain; (M.T.-F.); (T.M.S.); (D.A.-G.); (A.M.-P.); (B.M.-L.)
| | - Adrián Morales-Pastor
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM)—Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), 08003 Barcelona, Spain; (M.T.-F.); (T.M.S.); (D.A.-G.); (A.M.-P.); (B.M.-L.)
| | - Brian Medel-Lacruz
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM)—Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), 08003 Barcelona, Spain; (M.T.-F.); (T.M.S.); (D.A.-G.); (A.M.-P.); (B.M.-L.)
| | - Jana Selent
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM)—Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), 08003 Barcelona, Spain; (M.T.-F.); (T.M.S.); (D.A.-G.); (A.M.-P.); (B.M.-L.)
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