How Do Molecular Dynamics Data Complement Static Structural Data of Gpcrs

International Journal of Molecular Sciences Review How Do Molecular Dynamics Data Complement Static Structural Data of GPCRs Mariona Torrens-Fontanals 1 , Tomasz Maciej Stepniewski 1,2,3, David Aranda-García 1 , Adrián Morales-Pastor 1, Brian Medel-Lacruz 1 and Jana Selent 1,* 1 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; [email protected] (M.T.-F.); [email protected] (T.M.S.); [email protected] (D.A.-G.); [email protected] (A.M.-P.); [email protected] (B.M.-L.) 2 InterAx Biotech AG, PARK innovAARE, 5234 Villigen, Switzerland 3 Faculty of Chemistry, Biological and Chemical Research Centre, University of Warsaw, 02-093 Warsaw, Poland * Correspondence: [email protected] Received: 24 June 2020; Accepted: 15 August 2020; Published: 18 August 2020 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. Keywords: GPCRs; molecular dynamics; ligand binding; receptor (in)activation; receptor signaling; drug discovery 1. Introduction G protein-coupled receptors (GPCRs) are a large and versatile family of transmembrane proteins, encompassing over 800 identified members. These proteins act as receptors for a wide variety of extracellular stimuli including light, changes of pressure, and chemical ligands, odorants, neurotransmitters, chemokines, and metabolites among others, transducing their information into intracellular signaling cascades. Due to their participation in a wide range of pathways and physiological processes, as well as their druggability, GPCRs have become a drug target of major importance in the pharmaceutical industry [1]. As a consequence of their relevance for drug discovery, deciphering the molecular basis of GPCR signaling has become a major research focus. The signaling outcome of GPCRs is determined by their three-dimensional conformation, which is variable and depends on multiple factors, such as the binding of orthosteric and allosteric ligands, the lipidic environment, and post-translational modifications. Understanding how all of these factors contribute to a specific structure, and in turn, a specific signaling response, would not only expand our knowledge of GPCR biology but also provide Int. J. Mol. Sci. 2020, 21, 5933; doi:10.3390/ijms21165933 www.mdpi.com/journal/ijms Int.Int. J.J. Mol.Mol. Sci.Sci. 20202019,, 2120,, 5933x FOR PEER REVIEW 22 of of 26 26 provide structural blueprints for the design of novel and better therapeutics. To address this structuralambitious blueprints goal, numerous for the endeavors design of novelhave andbeen better undertaken therapeutics. to characterize To address the this three-dimensional ambitious goal, numerousstructure of endeavors GPCRs and have its been changes undertaken over time. tocharacterize the three-dimensional structure of GPCRs and itsImportant changes overadvances time. in protein engineering, X-ray crystallography, and cryo-electron microscopyImportant (cryo-EM) advances during in protein the past engineering, decade have X-ray led crystallography, to an exponential and cryo-electrongrowth in the microscopy number of (cryo-EM)known GPCR during structures. the past decadeSince then, have the led number to an exponential of available growth structures in the numberhas continued of known increasing GPCR structures.(Figure 1a). SinceThis large then, data the set number has been of availablecrucial for structures advancing has our continued understanding increasing of GPCR (Figure function.1a). ThisMoreover, large data it enabled set has beenthe application crucial for advancingof structure-based our understanding drug design of GPCRapproaches, function. which Moreover, aid the itdiscovery enabled the of novel application drug candidates of structure-based with improved drug design pharmacological approaches, which profiles aid [1–3]. the discovery of novel drug candidates with improved pharmacological profiles [1–3]. Figure 1. (a) Number of G protein-coupled receptors (GPCRs) structures available in GPCRdb [4,5] over time. (b) Number of publications per year indexed at Thomson Reuters’ Web of Science that contain theFigure topics 1. “molecular(a) Number dynamics”of G protein-coupled and (“GPCR” receptors or “GPCRs”). (GPCRs) The structures exponential available growth in GPCRdb of successful [4,5] GPCRover time. research (b) Number based on of molecular publications dynamics per year (MD) indexed simulations at Thomson is evidenced Reuters’ by theWeb rapid of Science upsurge that in thecontain number the oftopics publications “molecular per yeardynamics” related toand this (“GP subject.CR” or “GPCRs”). The exponential growth of successful GPCR research based on molecular dynamics (MD) simulations is evidenced by the rapid Despiteupsurge theirin the enormous number of utility, publications high-resolution per year related structures to this describe subject. proteins mainly as rigid entities, whereas information about their intrinsic flexibility and conformational plasticity cannot be appreciated. With theDespite goal totheir incorporate enormous atomic-level utility, high-resolution dynamic information structures to staticdescribe systems, proteins molecular mainly dynamics as rigid (MD)entities, simulations whereas wereinformation introduced about several their decadesintrinsic ago.flexibility The first and MD conformational simulation of plasticity a biomolecule cannot was be 9.2appreciated. ps-long and With consisted the goal of the to bovine incorporate pancreatic atomic trypsin-level inhibitor dynamic (~500 information atoms) in vacuumto static [ 6systems,]. In the casemolecular of GPCRs, dynamics the first (MD) MD simulations simulation were was obtainedintroduced in 1991,several before decades the ago. first The GPCR first crystal MD simulation structure wasof a resolvedbiomolecule [7]. was It corresponded 9.2 ps-long and to an consisted 80 ps-long of the trajectory bovine ofpancreatic a rat dopamine trypsin Dinhibitor2 receptor, (~500 modeled atoms) fromin vacuum its sequence [6]. In with the case molecular of GPCRs, mechanics. the first Ever MD since, simulation MD simulations was obtained have in greatly 1991, improvedbefore the their first performance,GPCR crystal allowingstructure thewas simulation resolved [7]. of It larger corresponded systems for to an longer 80 ps-long timescales. trajectory A major of a rat determinant dopamine ofD2 these receptor, advances modeled has from been its the sequence development with ofmolecular algorithms mechanics. optimized Ever for since, graphical MD simulations processor units have (GPUs),greatly improved a technology their first performance, designed toallowing improve the video simulation game of performance larger systems [8,9 for]. GPUlonger exploitation timescales. wasA major a major determinant breakthrough of these for the advances field, enabling has been researchers the development to perform of onalgorithms commodity optimized hardware for calculationsgraphical processor that were units previously (GPUs), only a technology possible with first the designed use of supercomputing to improve video clusters. game performance Along with these[8,9]. technologicalGPU exploitation advances, was thea majo expansionr breakthrough of free and for user-friendly the field, enabling software researchers for the input to preparationperform on (e.g.,commodity CHARMM-GUI hardware [10 ],calculations HomolWat [11that]) and were analysis previously (e.g., MDAnalysis only possible [12,13]) ofwith MD the simulations use of hassupercomputing greatly contributed clusters. to theAlong broad with application these technolo of thisgical technique. advances, the expansion of free and user- friendlyOwing software to the for aforementioned the input preparation technical (e.g., developments, CHARMM-GUI MD [10], simulations HomolWat currently [11]) and provide analysis a combination(e.g., MDAnalysis of temporal [12,13]) of and MD structural simulations resolution has greatly greater contributed than what to the is broad usually application achievable of this by experimentaltechnique. methods [14]. As a result, MD simulations are widely used for the study of GPCRs, as reflectedOwing by to thethe continuous aforementioned increase technical in publications developments, per year MD on thissimulations topic (Figure currently1b). Moreover, provide a mostcombination publications of temporal on crystallography

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