What can simulations tell us about GPCRs

Assessing Protein-Protein Docking Protocols: Case Studies of G-Protein-Coupled Receptor Interactions

The interactions of G-protein-coupled receptors (GPCRs) with other proteins are critical in several cellular processes but resolving their structural dynamics remains challenging. An increasing number of GPCR complexes have been experimentally resolved but others including receptor variants are yet to be characterized, necessitating computational predictions of their interactions. Although integrative approaches with multi-scale simulations would provide rigorous estimates of their conformational dynamics, protein-protein docking remains a first tool of choice of many researchers due to the availability of open-source programs and easy to use web servers with reasonable predictive power. Protein-protein docking algorithms have limited ability to consider protein flexibility, environment effects, and entropy contributions and are usually a first step towards more integrative approaches. The two critical steps of docking: the sampling and scoring algorithms have improved considerably and their performance has been validated against experimental data. In this chapter, we provide an overview and generalized protocol of a few docking protocols using GPCRs as test cases. In particular, we demonstrate the interactions of GPCRs with extracellular protein ligands and an intracellular protein effectors (G-protein) predicted from docking approaches and test their limitations. The current chapter will help researchers critically assess docking protocols and predict experimentally testable structures of GPCR complexes.

Molecular Mechanisms Underlying Caveolin-1 Mediated Membrane Curvature

Caveolin-1 is one of the main protein components of caveolae that acts as a mechanosensor at the cell membrane. The interactions of caveolin-1 with membranes have been shown to lead to complex effects such as curvature and the clustering of specific lipids. Here, we review the emerging concepts on the molecular interactions of caveolin-1, with a focus on insights from coarse-grain molecular dynamics simulations. Consensus structural models of caveolin-1 report a helix-turn-helix core motif with flanking domains of higher disorder that could be membrane composition dependent. Caveolin-1 appears to be mainly surface-bound and does not embed very deep in the membrane to which it is bound. The most interesting aspect of caveolin-1 membrane binding is the interplay of cholesterol clustering and membrane curvature. Although cholesterol has been reported to cluster in the vicinity of caveolin-1 by several approaches, simulations show that the clustering is maximal in membrane leaflet opposing the surface-bound caveolin-1. The intrinsic negative curvature of cholesterol appears to stabilize the negative curvature in the opposing leaflet. In fact, the simulations show that blocking cholesterol clustering (through artificial position restraints) blocks membrane curvature, and vice versa. Concomitant with cholesterol clustering is sphingomyelin clustering, again in the opposing leaflet, but in a concentration-dependent manner. The differential stress due to caveolin-1 binding and the inherent asymmetry of the membrane leaflets could be the determinant for membrane curvature and needs to be further probed. The review is an important step to reconcile the molecular level details emerging from simulations with the mesoscopic details provided by state of the art experimental approaches.

Molecular determinants of GPCR pharmacogenetics: Deconstructing the population variants in β2-adrenergic receptor

G protein-coupled receptors (GPCRs) are membrane proteins that play a central role in cell signaling and constitute one of the largest classes of drug targets. The molecular mechanisms underlying GPCR function have been characterized by several experimental and computational methods and provide an understanding of their role in physiology and disease. Population variants arising from nsSNPs affect the native function of GPCRs and have been implicated in differential drug response. In this chapter, we provide an overview on GPCR structure and activation, with a special focus on the β₂-adrenergic receptor (β₂-AR). First, we discuss the current understanding of the structural and dynamic features of the wildtype receptor. Subsequently, the population variants identified in this receptor from clinical and large-scale genomic studies are described. We show how computational approaches such as bioinformatics tools and molecular dynamics simulations can be used to characterize the variant receptors in comparison to the wildtype receptor. In particular, we discuss three examples of clinically important variants and discuss how the structure and function of these variants differ from the wildtype receptor at a molecular level. Overall, the chapter provides an overview of structure and function of GPCR variants and is a step towards the study of inter-individual differences and personalized medicine.

Cholesterol in GPCR Structures: Prevalence and Relevance

Bound cholesterol molecules are emerging as important hallmarks of GPCR structures. In this commentary, we analyze their statistical prevalence and biological relevance.

Insights into cellular signaling from membrane dynamics

Biological membranes allow morphological compartmentalization of cells and represent complex micro-heterogeneous fluids exhibiting a range of dynamics. The plasma membrane occupies a central place in cellular signaling which allows the cell to perform a variety of functions. In this review, we analyze cellular signaling in a dynamic biophysical framework guided by the "mobile receptor hypothesis". We describe a variety of examples from literature in which lateral diffusion of signaling membrane proteins acts as an important determinant in the efficiency of signaling. A major focus in our review is on membrane-embedded G protein-coupled receptors (GPCRs) which act as cellular signaling hubs for diverse cellular functions. Taken together, we describe a dynamics-based signaling paradigm with chosen examples from literature to elucidate how such a paradigm helps us understand signaling by GPCRs, maintenance of cellular polarity in yeast and infection by pathogens. We envision that with further technological advancement, it would be possible to explore cellular signaling more holistically as cells undergo development, differentiation and aging, thereby providing us a robust window into the dynamics of the cellular interior and its functional correlates.

Loss of a water-mediated network results in reduced agonist affinity in a β2-adrenergic receptor clinical variant

The β₂-adrenergic receptor (β₂AR) is a member of the G protein-coupled receptor (GPCR) family that is an important drug target for asthma and COPD. Clinical studies coupled with biochemical data have identified a critical receptor variant, Thr164Ile, to have a reduced response to agonist-based therapy, although the molecular mechanism underlying this seemingly "non-deleterious" substitution is not clear. Here, we couple molecular dynamics simulations with network analysis and free-energy calculations to identify the molecular determinants underlying the differential drug response. We are able to identify hydration sites in the transmembrane domain that are essential to maintain the integrity of the binding site but are absent in the variant. The loss of these hydration sites in the variant correlates with perturbations in the intra-protein interaction network and rearrangements in the orthosteric ligand binding site. In conjunction, we observe an altered binding and reduced free energy of a series of agonists, in line with experimental trends. Our work identifies a functional allosteric pathway connected by specific hydration sites in β₂AR that has not been reported before and provides insight into water-mediated networks in GPCRs in general. Overall, the work is one of the first step towards developing variant-specific potent and selective agonists.

Role of cholesterol-mediated effects in GPCR heterodimers

G protein-coupled receptors (GPCRs) are transmembrane receptors that mediate a large number of cellular responses. The organization of GPCRs into dimers and higher-order oligomers is known to allow a larger repertoire of downstream signaling events. In this context, a crosstalk between the adenosine and dopamine receptors has been reported, indicating the presence of heterodimers that are functionally relevant. In this paper, we explored the effect of membrane cholesterol on the adenosine_2A (A_2A) and dopamine D₃ (D₃) receptors using coarse-grain molecular dynamics simulations. We analyzed cholesterol interaction sites on the A_2A receptor and were able to reproduce the sites indicated by crystallography and previous atomistic simulations. We predict novel cholesterol interaction sites on the D₃ receptor that could be important in the reported cholesterol sensitivity in receptor function. Further, we analyzed the formation of heterodimers between the two receptors. Our results suggest that membrane cholesterol modulates the relative population of several co-existing heterodimer conformations. Both direct receptor-cholesterol interaction and indirect membrane effects contribute toward the modulation of heterodimer conformations. These results constitute one of the first examples of modulation of GPCR hetero-dimerization by membrane cholesterol, and could prove to be useful in designing better therapeutic strategies.

Understanding Ligand Binding to G-Protein Coupled Receptors Using Multiscale Simulations

Human G-protein coupled receptors (GPCRs) convey a wide variety of extracellular signals inside the cell and they are one of the main targets for pharmaceutical intervention. Rational drug design requires structural information on these receptors; however, the number of experimental structures is scarce. This gap can be filled by computational models, based on homology modeling and docking techniques. Nonetheless, the low sequence identity across GPCRs and the chemical diversity of their ligands may limit the quality of these models and hence refinement using molecular dynamics simulations is recommended. This is the case for olfactory and bitter taste receptors, which constitute the first and third largest GPCR groups and show sequence identities with the available GPCR templates below 20%. We have developed a molecular dynamics approach, based on the combination of molecular mechanics and coarse grained (MM/CG), tailored to study ligand binding in GPCRs. This approach has been applied so far to bitter taste receptor complexes, showing significant predictive power. The protein/ligand interactions observed in the simulations were consistent with extensive mutagenesis and functional data. Moreover, the simulations predicted several binding residues not previously tested, which were subsequently verified by carrying out additional experiments. Comparison of the simulations of two bitter taste receptors with different ligand selectivity also provided some insights into the binding determinants of bitter taste receptors. Although the MM/CG approach has been applied so far to a limited number of GPCR/ligand complexes, the excellent agreement of the computational models with the mutagenesis and functional data supports the applicability of this method to other GPCRs for which experimental structures are missing. This is particularly important for the challenging case of GPCRs with low sequence identity with available templates, for which molecular docking shows limited predictive power.

Approaching Pharmacological Space: Events and Components

With a view to introducing the concept of pharmacological space and its potential applications in investigating and predicting the toxic mechanisms of xenobiotics, this opening chapter describes the logical relations between conformational behavior, physicochemical properties and binding spaces, which are seen as the three key elements composing the pharmacological space. While the concept of conformational space is routinely used to encode molecular flexibility, the concepts of property spaces and, particularly, of binding spaces are more innovative. Indeed, their descriptors can find fruitful applications (a) in describing the dynamic adaptability a given ligand experiences when inserted into a specific environment, and (b) in parameterizing the flexibility a ligand retains when bound to a biological target. Overall, these descriptors can conveniently account for the often disregarded entropic factors and as such they prove successful when inserted in ligand- or structure-based predictive models. Notably, and although binding space parameters can clearly be derived from MD simulations, the chapter will illustrate how docking calculations, despite their static nature, are able to evaluate ligand's flexibility by analyzing several poses for each ligand. Such an approach, which represents the founding core of the binding space concept, can find various applications in which the related descriptors show an impressive enhancing effect on the statistical performances of the resulting predictive models.

Recent Advances in Structure-Based Drug Design Targeting Class A G Protein-Coupled Receptors Utilizing Crystal Structures and Computational Simulations

G protein-coupled receptors (GPCRs) represent the largest and most physiologically important integral membrane protein family, and these receptors respond to a wide variety of physiological and environmental stimuli. GPCRs are among the most critical therapeutic targets for numerous human diseases, and approximately one-third of the currently marketed drugs target this receptor family. The recent breakthroughs in GPCR structural biology have significantly contributed to our understanding of GPCR function, ligand binding, and pharmacological action as well as to the design of new drugs. This perspective highlights the latest advances in GPCR structures with a focus on the receptor-ligand interactions of each receptor family in class A nonrhodopsin GPCRs as well as the structural features for their activation, biased signaling, and allosteric mechanisms. The current state-of-the-art methodologies of structure-based drug design (SBDD) approaches in the GPCR research field are also discussed.

Interplay of G Protein-Coupled Receptors with the Membrane: Insights from Supra-Atomic Coarse Grain Molecular Dynamics Simulations

G protein-coupled receptors (GPCRs) are central to many fundamental cellular signaling pathways. They transduce signals from the outside to the inside of cells in physiological processes ranging from vision to immune response. It is extremely challenging to look at them individually using conventional experimental techniques. Recently, a pseudo atomistic molecular model has emerged as a valuable tool to access information on GPCRs, more specifically on their interactions with their environment in their native cell membrane and the consequences on their supramolecular organization. This approach uses the Martini coarse grain (CG) model to describe the receptors, lipids, and solvent in molecular dynamics (MD) simulations and in enough detail to allow conserving the chemical specificity of the different molecules. The elimination of unnecessary degrees of freedom has opened up large-scale simulations of the lipid-mediated supramolecular organization of GPCRs. Here, after introducing the Martini CGMD method, we review these studies carried out on various members of the GPCR family, including rhodopsin (visual receptor), opioid receptors, adrenergic receptors, adenosine receptors, dopamine receptor, and sphingosine 1-phosphate receptor. These studies have brought to light an interesting set of novel biophysical principles. The insights range from revealing localized and heterogeneous deformations of the membrane bilayer at the surface of the protein, specific interactions of lipid molecules with individual GPCRs, to the effect of the membrane matrix on global GPCR self-assembly. The review ends with an overview of the lessons learned from the use of the CGMD method, the biophysical-chemical findings on lipid-protein interplay.

Structural insights and functional implications of inter-individual variability in β2-adrenergic receptor

The human β₂-adrenergic receptor (β₂AR) belongs to the G protein-coupled receptor (GPCR) family and due to its central role in bronchodilation, is an important drug target. The inter-individual variability in β₂AR has been implicated in disease susceptibility and differential drug response. In this work, we identified nine potentially deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) using a consensus approach. The deleterious nsSNPs were found to cluster near the ligand binding site and towards the G-protein binding site. To assess their molecular level effects, we built structural models of these receptors and performed atomistic molecular dynamics simulations. Most notably, in the Phe290Ser variant we observed the rotameric flip of Trp286^6.48, a putative activation switch that has not been reported in β₂AR thus far. In contrast, the variant Met82Lys was found to be the most detrimental to epinephrine binding. Additionally, a few of the nsSNPs were seen to cause perturbations to the lipid bilayer, while a few lead to differences at the G-protein coupling site. We are thus able to classify the variants as ranging from activating to damaging, prioritising them for experimental studies.