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GPCR Dynamics: Structures in Motion

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† ‡ § ∥ Department of Computer Science, Biophysics Program, §Department of Molecular and Cellular Physiology, and Institute for Computational and Mathematical Engineering, Stanford University, Stanford, California 94305, United States
Cite this: Chem. Rev. 2017, 117, 1, 139–155
Publication Date (Web):September 13, 2016
https://doi.org/10.1021/acs.chemrev.6b00177

Copyright © 2016 American Chemical Society. This publication is licensed under these Terms of Use.

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Abstract

The function of G protein-coupled receptors (GPCRs)—which represent the largest class of both human membrane proteins and drug targets—depends critically on their ability to change shape, transitioning among distinct conformations. Determining the structural dynamics of GPCRs is thus essential both for understanding the physiology of these receptors and for the rational design of GPCR-targeted drugs. Here we review what is currently known about the flexibility and dynamics of GPCRs, as determined through crystallography, spectroscopy, and computer simulations. We first provide an overview of the types of motion exhibited by a GPCR and then discuss GPCR dynamics in the context of ligand binding, activation, allosteric modulation, and biased signaling. Finally, we discuss the implications of GPCR conformational plasticity for drug design.

SPECIAL ISSUE

This article is part of the G-Protein Coupled Receptors special issue.

1 Introduction

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G protein-coupled receptors (GPCRs)—which represent the largest family of human membrane proteins, with some 800 members—represent a “control panel” of the cell. These receptors are able to detect the presence of a strikingly diverse array of molecules outside the cell and to initiate a variety of intracellular signaling cascades in response. Drugs can induce, block, or modulate these effects, essentially hijacking the control panel. Indeed, GPCRs represent the largest class of drug targets, with roughly one-third of all drugs on the market acting by binding to a GPCR and modifying its intracellular signaling profile.
The ability of a GPCR to transmit a signal through the cell membrane depends on its ability to change shape. Extracellular ligands, ranging from small hormones and neurotransmitters to proteins such as chemokines, bind to the extracellular side of a GPCR and favor structural changes that allow G proteins, arrestins, and other signaling proteins to bind to a GPCR’s intracellular surface (Figure 1). This control mechanism is highly complex: for example, appropriately chosen ligands can stimulate different intracellular signaling pathways independently through a single GPCR, and many GPCRs possess multiple ligand-binding sites that influence intracellular signaling in distinct manners.

Figure 1

Figure 1. GPCR signaling: (A) an orthosteric ligand (orange) binds an inactive GPCR, the β2 adrenergic receptor (β2AR; PDB ID: 2RH1); (B) A ligand-bound GPCR undergoes a conformational change to its active state (PDB ID: 3SN6); and (C) an active GPCR binds a G protein (PDB ID: 3SN6), which subsequently promotes nucleotide release from, and activation of, the G protein α-subunit.

Understanding the structural basis for these dynamic signaling processes has represented a long-standing challenge, with critical implications for both basic science and rational drug design. The past decade has witnessed dramatic progress toward this goal. Most obvious are the recent breakthroughs in GPCR structure determination through crystallography, (1-5) part of the work recognized by the 2012 Nobel Prize in Chemistry to Brian Kobilka and Robert Lefkowitz. Atomic-resolution structures are now available for over 35 GPCRs. (6, 7)
To truly decipher the molecular basis for GPCR signaling, however, we must also understand GPCR dynamics—how a given GPCR changes its shape over time. A good deal of information is now available on this front as well, not only from crystallography but also from spectroscopic experiments and from computer simulations. Atomic-level molecular dynamics (MD) simulations, in particular, have become substantially more powerful in recent years, thanks to increased computer power, improved simulation algorithms, and refined potential energy functions that better represent the underlying physics. Starting from a static experimental structure, these simulations predict the motion of every atom in a receptor, as well as the motion of every atom in the molecules with which the receptor interacts. (8)
Here we review and synthesize what is known about GPCR dynamics. We describe the various ways in which GPCRs change conformation, both spontaneously and in response to binding or dissociation of various ligands and intracellular signaling partners. We discuss the role of receptor dynamics in functional processes such as ligand binding, activation, coupling to downstream binding partners (G proteins and arrestins), biased signaling, and allosteric modulation. We also outline a number of important, unsolved problems in this area. Finally, we discuss the implications of receptor dynamics for GPCR-targeted drug design.

2 GPCR Movement: An Overview

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All GPCRs share a transmembrane domain with a common structural architecture (Figure 2). This domain, which is essential for the transduction of a signal across the cell membrane, is composed of a bundle of seven α-helices embedded in the cell membrane connected by three extracellular and three intracellular loops. (9) The largest phylogenetic class of GPCRs, known as class A, contains only a transmembrane domain, with amino and carboxyl termini of varying lengths and sequence content (Figure 2). Native ligands of class A GPCRs thus bind directly to the transmembrane domain. Most GPCRs in other phylogenetic classes (including classes B, C, and F) also include an extracellular domain connected to the amino terminus of the transmembrane domain. (10, 11) These extracellular domains are generally involved in binding native ligands, either in addition to or in place of the transmembrane domain.

Figure 2

Figure 2. Structure and topology of GPCRs. (A) GPCRs contain seven transmembrane helices (gray), three extracellular loops (ECLs) and an amino terminus (orange), and three intracellular loops (ICLs) and a carboxyl terminus (purple). The transmembrane domain consists of the transmembrane helices, as well as the extracellular and intracellular loops. (B) Cartoon representation of the β2AR highlighting transmembrane helices (TMs), loops, and terminal tails.

This review focuses primarily on the dynamics of the transmembrane domain, which is common to all GPCRs and plays the critical role of mediating a GPCR’s interactions with its intracellular binding partners, such as G proteins and arrestins. We will refer to the native ligand-binding site of class A GPCRs—found in the transmembrane domain and accessible from the extracellular solvent—as the binding pocket.
Like other biomolecules, a GPCR is in constant atomic-level motion (Figure 3), even in the absence of any external stimulus. Some of these motions are highly localized and typically very fast (femtoseconds to nanoseconds): the lengths of chemical bonds and the angles between bonds fluctuate, and solvent-exposed amino acid side chains change from one rotamer to another. (12) Other motions involve a larger part of the protein and typically occur more slowly (nanoseconds to milliseconds): helices kink or change orientation relative to one another, loops change their orientation, and tightly packed side chains in the interior of a protein rearrange.

Figure 3

Figure 3. Atomic-level motions of a GPCR revealed through MD simulations. Representative frames from MD simulations (from ref 23) of agonist-bound β2AR as it transitions from an active state to an inactive state, with (A) all non-hydrogen atoms represented as lines and (B) protein backbone represented as ribbons. Transmembrane helix 6 (TM6) is colored red to highlight its high degre of mobility during the transition between active and inactive states.

We use the term conformation to refer to a particular three-dimensional arrangement of atoms in a protein—that is, a snapshot at a single point in time. Over the course of time, a GPCR can take on an essentially infinite number of conformations. These conformations, however, tend to cluster into groups, and we refer to a group of similar conformations as a conformational state (Figure 4). A GPCR typically moves very quickly among conformations within a conformational state and more slowly between conformational states, but it transitions spontaneously among multiple conformational states even in the absence of any change in bound ligand or environment.

Figure 4

Figure 4. Protein conformations cluster into distinct conformational states. Mapping an MD simulation trajectory to a well-chosen low-dimensional space can reveal distinct clusters of conformations. (A) Plotting an MD simulation trajectory along two geometric coordinates reveals three distinct conformational states during the process of β2AR deactivation (top). RMSD is the root-mean-square deviation. (B) Snapshots from simulation, representing each of the three conformational states (light pink, magenta and dark purple), are overlaid with the inactive-state crystal structure (blue). These are shown along with a simplified, qualitative one-dimensional energy landscape, where the depth of each energy well is inversely related to the population of the corresponding conformational state. Adapted by permission from ref 23. Copyright 2011 National Academy of Sciences.

Crystallography, spectroscopy, and simulation provide complementary sources of information on fluctuations within and across GPCR conformational states. Crystal structures usually represent only a single conformational state (typically the most common conformational state under the conditions in which the receptor was crystallized, but sometimes just the state most prone to crystallization), and the positions of atoms in the structure represent averages of conformations within that conformational state. Crystallizing a single GPCR in many conformational states has proven challenging. (13) NMR spectroscopy provides a useful way to detect subtle conformational changes within a protein, as the relative position and shape of a peak on the NMR spectrum can reflect the chemical microenvironment of a well-chosen probe atom. (14) DEER spectroscopy allows one to determine a distribution (histogram) of distances between two different probes. (15) Fluorescence spectroscopy, including fluorescence resonance energy transfer and fluorescence quenching approaches, provides a means to detect whether two probes are close to one another. (16-18) With the exception of one structure solved by NMR, (19) these spectroscopy studies have not provided a complete structural description of any one conformational state; rather, they provide localized information about the inserted chemical probes. MD simulations complement these studies, as they provide a full atomic-level picture of the structure as it changes over time, capturing atomic-level motion within conformational states as well as transitions between conformational states. These simulations are limited by the accuracy of the underlying physical models and by the fact that they are computationally intensive, but recent years have seen substantial improvements on both fronts. (20)
MD simulations reveal that GPCRs undergo substantial fluctuations even within a single conformational state. (21, 22) For example, in one simulation of the inactive-state β2-adrenergic receptor, (23) the root-mean-square deviation (RMSD) of helical backbone atoms from the crystal structure was approximately 1 Å, while the RMSD for TM helix side-chain atoms was approximately 2 Å, and the RMSD for atoms in loop regions was approximately 3 Å. The third intracellular loop and the C terminus—which are disordered in most GPCRs and unresolved in most GPCR crystal structures—can probably move substantially more. When a GPCR transitions between major conformational states, even transmembrane helices can move 10 Å or more.
Binding of a ligand to a GPCR can affect the GPCR’s dynamics in several ways. Generally, the largest effect is simply to alter the fraction of time the GPCR spends in each of its conformational states (also known as the “population” of each state); for example, binding of certain ligands may increase the population of active conformational states (Figure 5). In some cases, binding of a ligand may allow the GPCR to adopt conformations that it did not adopt previously, at least not to a measurable extent. (24) In addition, binding of a ligand may increase or decrease the rate at which the receptor transitions among different conformational states. Binding of an intracellular partner (e.g., a G protein or arrestin), dimerization with another GPCR, post-translational modifications such as phosphorylation of certain amino acids, or a change in the pH or lipid composition of the GPCR’s immediate environment can have similar effects. (25-29) The dynamics of a GPCR over the course of its lifetime will thus reflect a combination of structural changes due to the receptor’s intrinsic dynamics and “external” perturbations, such as those due to ligand binding or dissociation.

Figure 5

Figure 5. Perturbations alter the populations of conformational states. Hypothetical histograms (light pink, magenta, and purple) represent the relative populations of each of three hypothetical conformational states. Hypothetical energy landscapes (gray) are inversely related to the populations of the conformational states. Compared to the distribution of conformations visited by (A) an unliganded GPCR, (B) an agonist-bound GPCR samples intermediate and fully active conformations more frequently, and (C) an agonist-bound, G protein-bound GPCR more heavily populates fully active conformations. New conformational states may arise on this energy landscape under additional conditions (not shown).

Of all the conformational changes a GPCR undergoes, several appear to be particularly important from a functional perspective. Rearrangements of the transmembrane helices—particularly TM helices 5–7—appear to play a critical role in transmitting a signal across the membrane. (5) As a GPCR transitions from an inactive state (which does not couple to intracellular signaling proteins) to an active state (which does), these helices shift, tilt, and twist relative to one another; they can also bend or kink, usually at positions in the helical sequence where a proline or glycine disrupts backbone hydrogen bonds. (30) Several lines of evidence indicate that a GPCR’s transmembrane helices can adopt multiple distinct conformational states—not just a single active state and a single inactive state—and that these states have distinct implications for receptor signaling. (22, 24, 31, 32) Phosphorylation of residues in the C terminus and certain intracellular loops can also change a receptor’s propensity to couple to various intracellular partners, likely by causing structural changes in these regions. (33, 34)
While conformational changes tend to be largest on the intracellular side of the GPCR, the extracellular half of the receptor also changes conformation. In particular, the ligand-binding pocket undergoes subtle but important changes in structure that are coupled to the conformational changes of the helices on the intracellular side. (2, 3, 35) The mobility of a receptor’s extracellular loops can affect the binding kinetics of ligands that bind in the binding pocket. (36) These loops can also form alternative binding sites for ligands known as allosteric modulators, whose presence can cause localized conformational changes that alter the properties of the binding pocket, including its affinity for native ligands. (37-39)

3 GPCR Activation

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Structural change within a GPCR allows it to act as a molecular conduit, transmitting an extracellular signal across the cell membrane to elicit an intracellular response. Such conformational change is essential for GPCR activation, the process by which a GPCR assumes a conformation conducive to coupling with and activating an intracellular binding protein. In this section we will focus, in particular, on the process by which a GPCR goes from an inactive conformational state to a G protein-coupling conformational state, and we will refer to the crystallographically observed G protein-coupling conformational state as the canonical active state.

3.1 Mechanism of GPCR Activation

The β2-adrenergic receptor (β2AR) has served as a model system for studying GPCR activation. The crystal structure of the β2AR bound to a G protein indicates that the largest conformational changes to the receptor upon activation occur on the intracellular side, at the intracellular coupling interface, where transmembrane helices 5–7 rearrange to accommodate G protein insertion (Figure 6). TM6 rotates and swings nearly 14 Å away from the center of the helical bundle, accompanied by rotations and slight inward movements of TM5 and TM7. (2, 3) The ligand-binding pocket also rearranges: polar moieties on the ligand form hydrogen bonds with Ser5.42 and Ser5.46, pulling the upper portion of TM5 toward TM6 and causing the binding pocket to contract in volume. (Residues are identified using the Ballesteros–Weinstein numbering scheme, in which the first number refers to the transmembrane helix on which the residue resides. (40)) Crystal structures suggest, and simulations confirm, that motions of several residues in a “connector” or “transmission” region the conformational changes in the binding pocket to those at the intracellular coupling interface: in response to the inward movement of TM5, Ile3.40 shifts away from its position separating Pro5.50 and Phe6.44 in the inactive state, permitting the lower half of TM6 to move outward. (23, 35) An allosteric network of residues in TM3, TM5, TM6, and TM7 thus serves as a central hub for sensing and responding to conformational change in β2AR.

Figure 6

Figure 6. Structural rearrangements during GPCR activation. Inactive (light pink) and active (dark purple) conformations of the β2AR show differences in helix position and side-chain orientation in three distinct regions of the GPCR: the binding pocket (top, left); the connector region, or conserved core triad (bottom, left); and the intracellular coupling site (top and bottom, right).

How tight is the coupling between the conformation of the ligand-binding pocket and that of the intracellular coupling interface? A GPCR’s ability to transmit a transmembrane signal depends on the fact that the binding of an agonist (an activating ligand) in the binding pocket favors intracellular G protein binding. Conversely, G protein binding will favor agonist binding; that is, an agonist will bind with higher affinity to a GPCR in its active state than in its inactive state. (41, 42) One would thus expect conformational changes in one site to be coupled to conformational changes in the other. Recent evidence suggests that while the conformations of the two regions in the β2AR are indeed coupled, the coupling is surprisingly loose. (22-24) That is, the binding pocket conformation influences but does not dictate the intracellular coupling interface conformation, and vice versa.
The most explicit evidence for this “loose allosteric coupling” comes from simulation. (23, 43) We observed that, in simulations of the β2AR, each of the three regions described above—the binding pocket, the connector region, and the intracellular coupling interface—transitions spontaneously between two or more discrete conformations, including conformations matching the active and inactive crystal structure (Figure 7). (23) Each region could change conformation independently of the other regions, although the probability that a region would be in a particular conformation depended on the conformation of those other regions. NMR data also supports the notion of loose coupling between different regions of the β2AR. (22, 24)

Figure 7

Figure 7. Loose allosteric coupling underlies GPCR activation. (A) During simulations of β2AR deactivation, three key regions (the binding pocket, the connector region, and the intracellular coupling interface) spontaneously transition between at least two conformations independently of the other regions. (B) Horizontal bars represent the conformations sampled by each region over the course of four 2-μs deactivation simulations of the β2AR. Adapted by permission from ref 23. Copyright 2011 National Academy of Sciences.

MD simulations (23) suggest that activation of the β2AR does not typically occur “sequentially”, with an agonist inducing an active conformation of the ligand-binding pocket and the change then propagating toward the intracellular coupling interface. Instead, the intracellular coupling interface is likely in equilibrium between inactive conformations and more active-like conformations, even in the absence of an agonist. The presence of a bound agonist helps to stabilize active conformations of the binding pocket and thus increases the likelihood that the connector region and intracellular coupling interface will similarly adopt active conformations.
As a corollary, binding of a full agonist appears insufficient to stabilize the active, G protein-coupling state of the β2AR. Instead, this conformation only dominates when the receptor is also bound to a G protein (or to a G protein mimetic). (44) A crystal structure of β2AR bound to a potent agonist in the absence of an intracellular binding partner shows a conformation that matches the inactive, antagonist-bound crystal structure almost perfectly. (45) In simulation, agonist-bound β2AR transitions spontaneously from the crystallographic active conformation to the crystallographic inactive conformation upon removal of the bound G protein. (23) NMR and DEER studies indicate that, although agonist binding substantially increases the conformational heterogeneity of the receptor, binding of a G protein or G protein mimetic to the intracellular coupling interface is required to stabilize the β2AR in a single conformational state corresponding to the crystallographic, or canonical, active conformational state. (22, 24)

3.2 Conservation of Activation Mechanism across GPCRs

How does activation of other GPCRs compare to that of β2AR? Crystal structures of other GPCRs captured in both inactive and active states (in particular, the M2 muscarinic acetylcholine receptor (M2R), the μ-opioid receptor (μOR), and rhodopsin) indicate that the global conformational changes involved in receptor activation are similar, particularly on the cytoplasmic side. (35, 39, 46-48, 157) In each case, upon receptor activation, the intracellular end of TM6 moves away from the center of the helical bundle (though the extent of its motion ranges from 6 to 14 Å, at least partly due to the fact that different intracellular binding partners were used to stabilize the different active-state structures) (Figure 8). Outward movement of TM6 expands a crevice on the intracellular side, creating an opening flanked by TM3, TM5, and TM7. This crevice holds the G protein-binding interface and, along with the second and third intracellular loops, forms polar and hydrophobic interactions with the G protein. Similarly, TM5 and TM7 change conformation upon activation, and key residues on these helices (specifically, Tyr5.58 and Tyr7.53) form direct and water-mediated polar contacts that are unique to GPCR active states. (2, 35, 39, 49-51)

Figure 8

Figure 8. Conformational changes in class A GPCRs upon activation. Three class A GPCRs captured in their crystallographic inactive and active conformations reveal similar conformational changes upon activation. TM6 is highlighted. M2 is the M2 muscarinic acetylcholine receptor and μOR is the μ-opioid receptor.

Activation of different GPCRs varies in several ways. Most notably, the interactions of the agonist with the binding pocket differ markedly between GPCRs, likely reflecting the fact that different GPCRs have evolved to recognize vastly different ligands. (44, 52) In β2AR, for example, polar interactions with the agonist pull TM5 inward, whereas in the M2 muscarinic receptor, polar interactions with the agonist pull TM6 inward. (39) The μ-opioid receptor (μOR) undergoes very similar conformational changes to β2AR upon activation—including inward motion of TM5 near the binding pocket and rearrangement of the conserved core triad—but the μOR agonist does not form polar interactions with TM5. (35) MD simulations suggest that the agonist instead triggers activation by pushing aside TM3. (35) Thus, GPCRs appear to have evolved widely varying ligand recognition mechanisms, even though their intracellular surfaces undergo similar conformational changes upon activation and couple to a common set of intracellular proteins. (48)
Many GPCRs likely share the loose allosteric coupling of β2AR. (53) Some notable examples include μOR (54) and the adenosine A2A receptor (A2AR), (55) which appear to explore intermediate and active-like states even in the absence of bound agonist. By contrast, the light-activated GPCR rhodopsin appears to exhibit much tighter coupling between the binding pocket and the intracellular coupling interface. (56-59) Light-induced conversion of the native ligand retinal to an agonist shifts rhodopsin abruptly away from its inactive, dark state, allowing for extremely efficient activation and G protein coupling. (60)

4 Conformational Diversity and Biased Signaling

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In this section, we describe the global conformational states of a GPCR as observed through crystallography, spectroscopy, and simulation, and we speculate on how this conformational diversity affects the ability of the GPCR to signal downstream. We discuss global conformational states primarily in terms of features within the cytoplasmic half of the GPCR, because this region directly binds intracellular proteins. We also discuss potential links between these various conformational states and biased signaling, a phenomenon in which a ligand determines which of several possible signaling pathways a GPCR stimulates. Biased signaling, also known as functional selectivity, is of tremendous pharmaceutical interest, because it raises the possibility of creating drugs that stimulate desirable signaling pathways without stimulating harmful ones, thus dramatically reducing drug side effects and safety issues. (61) The structural basis for biased signaling remains poorly understood, but it most likely depends on the ability of the GPCR’s intracellular coupling interface to assume more than just a single inactive and a single active conformational state. (62)

4.1 Diverse Conformational States of a GPCR

Molecular dynamics simulations reveal several “intermediate” conformational states of a GPCR that differ from the crystallographically observed active and inactive conformations. For example, we performed simulations of an agonist-bound β2AR, which transitioned spontaneously from its crystallographic active conformation to its crystallographic inactive conformation (after removal of the G protein or G protein-mimetic nanobody). (23) These simulations revealed several intermediate conformational states en route between the crystallographic active and inactive states. These intermediate states are metastable, in the sense that once a simulation reaches one of them it generally remains there for at least several hundred nanoseconds before transitioning to another state. Perhaps the most notable intermediate state in these simulations is one where TM7 adopts its crystallographically observed inactive conformation while TM6 remains in its active, outward-shifted conformation (albeit with increased mobility) (Figure 9, intermediate A). This was the only major intermediate state observed in a number of the “deactivating” simulations of β2AR (Figure 9). Subsequent NMR studies revealed that differences in the core region of TM5 and TM7, rather than changes in the position of TM6, distinguished two states of the β2AR favored in the presence of agonist; these conformational states may correspond to the intermediate and fully active states observed in simulation. (22, 24)

Figure 9

Figure 9. Diverse conformational states of the β2AR. During MD simulations of β2AR beginning in the active state (dark gray; PDB ID: 3P0G) (A), β2AR transitions along (B) a dominant pathway through an intermediate (intermediate A) in which TM6 is still displaced outward relative to the inactive crystal structure but TM7 is straightened (light blue) or (C) an alternative pathway through two intermediates, B and C, which exhibit a conformation of TM7 distinct from that seen in the inactive and active crystal structures of the β2AR. Simulations were taken from ref 23.

In some of these simulations, the transition between active and inactive conformational states took place along a different pathway. This pathway had two intermediates, both characterized by a distinctive “alternative” conformation of TM7 different from that observed in either the active or the inactive β2AR crystal structures (Figure 9, intermediates B and C). The two intermediates differed in the position of TM6, which was in an outward, active-like conformation in the first intermediate (intermediate B) and in an inward, inactive-like conformation in the second (intermediate C). Intriguingly, simulations initiated from the crystallographic inactive structure with either an inverse agonist or no ligand bound occasionally transitioned to intermediate C, referred to as “intermediate 2” (23) and as an “alternative inactive” conformation (22) in previous publications. These simulation results were consistent with NMR data demonstrating an equilibrium between two conformations with either an inverse agonist or no ligand bound. (22)
Conformational fluctuations can also arise within the ensemble of inactive conformations. In simulations initiated from the crystallographic inactive β2AR conformation (whether unliganded or bound to the cocrystallized ligand), TM6 and TM7 as a whole remained in their crystallographic, inactive conformations, but the intracellular end of TM6 frequently alternated between two positions. (21) In one of these conformational substates—adopted a majority of the time—the intracellular end of TM6 is bent toward TM3, so that a network of salt bridges known as the ionic lock is formed. In particular, Glu6.30 at the base of TM6 forms a salt bridge with Arg3.50 at the base of TM3, which simultaneously forms a salt bridge with Asp3.49. In the other conformational substate, the intracellular end of TM6 straightens, moving away from TM3 and breaking the ionic lock. The observation of this equilibrium in these and other simulations (63, 158) resolved prior, seemingly conflicting experimental observations: the ionic lock is consistently formed in several inactive rhodopsin crystal structures, (64-66) and biochemical studies suggested it played a role in stabilizing the inactive state of β2AR as well, but it was broken in the initial crystal structures of inactive-state β2AR and β1AR. (67-70) Later crystal structures of β1AR showed both ionic-lock-broken and ionic-lock-formed conformations with the same ligand bound (71)—as observed in simulation—and more recently, DEER spectroscopy of β2AR has provided evidence for both ionic-lock-broken and ionic-lock-intact states. (24)
Additional evidence for the diversity of the global conformational states adopted by a GPCR comes from comparing crystal structures of different GPCRs, particularly those bound to agonists. Most GPCRs appear not to crystallize in a fully active conformation capable of binding to a G protein unless a G protein or G protein-mimetic nanobody is crystallized in complex with the receptor. Several agonist-bound GPCRs have instead adopted crystallographic conformations that appear to be partway between the canonical active and canonical inactive states. (52) These crystallized conformations are often referred to as “intermediates”, although they are not necessarily intermediates on the activation pathway. Structures of the adenosine A2A receptor (A2AR) bound to adenosine and other agonists reveal that structural elements on TM3, TM5, and TM7 take on conformations similar to those seen in fully active β2AR structures, while TM6 has moved slightly away from the center of the helical bundle but remains in an occluded position that would still likely prevent G protein binding. (52, 72, 73) Notably, one A2AR structure exhibits structural features of TM7 seen in intermediate C, described above. (73) The extent to which “active” features can be induced by the presence of agonist alone may depend on the physical properties of each type of GPCR. Many agonist-bound GPCRs resemble their inactive structures on the intracellular side (in the absence of an intracellular binding partner). (74) In contrast, the viral chemokine receptor US28 crystallized in a canonical active conformation with an agonist bound even in the absence of an intracellular binding partner, likely reflecting its high degree of constitutive activity. (75) Thus, the extent to which agonists induce “active-like” properties in GPCRs appears to reflect variable conformational plasticity within the GPCR family.

4.2 Implications for Biased Signaling

The relevance of alternative conformations on the intracellular side of the GPCR to downstream signaling has recently come into focus due to intensified interest in biased signaling. (61) For example, an active-state GPCR typically couples to both G proteins and arrestins and stimulates signaling through each, but some ligands favor G protein signaling without arrestin signaling or arrestin signaling without G protein signaling. This suggests that ligands select among not just one active and one inactive conformational state but among multiple conformational states with different abilities to couple to intracellular binding partners. (76) Biased ligands may also affect the kinetics of signaling, which might lead to apparent bias toward distinct pathways at different points in time. (77) What are the consequences of signaling through these distinct pathways? Upon binding to GPCRs, arrestins can not only sterically prevent coupling of GPCRs to G proteins (damping cAMP-mediated signaling) but also facilitate clathrin-mediated endocytosis of GPCRs and initiate G protein-independent signaling through downstream kinase cascades. (78-80) Although our focus here is on bias between arrestins and G proteins, we note that many different types of bias exist and include bias between, for example, different G protein subtypes. (81)
Recent spectroscopic efforts to characterize conformations induced by arrestin- and G protein-biased ligands have revealed some differences in conformation on the intracellular face of the GPCR. A 19F NMR study monitored how the local chemical environment on the intracellular ends of TM6 and TM7, and at a location on helix 8, changed in response to the binding of various ligands to the β2AR. (82) The authors observed differences in chemical shifts in the presence of unbiased ligands, which stimulate G protein-mediated and arrestin-mediated signaling equally, and arrestin-biased ligands, which stimulate arrestin-mediated signaling more than G protein-mediated signaling. Specifically, while unbiased agonists shifted the chemical environment near both TM6 and TM7, arrestin-biased ligands largely appeared to affect only the environment in the vicinity of TM7. A caveat is that for biophysical studies performed in the absence of intracellular binding partners, it might be challenging to determine how the observed conformational differences directly impact the formation or stability of GPCR–G protein or GPCR–arrestin complexes.
Crystal structures of GPCRs bound to ligands with biased signaling profiles have recently provided additional evidence that bias may involve subtle changes on the intracellular face of the GPCR. Recently, high-resolution structures of serotonin receptor subtypes 5-HT1BR and 5-HT2BR, each bound to an agonist ergotamine, have revealed structural features that might serve as determinants for functional selectivity. (83, 84) Ergotamine primarily stimulates arrestin signaling at the 5-HT2BR, but stimulates arrestin and G protein signaling roughly equally at the 5-HT1BR. The crystal structure of 5-HT1BR bound to ergotamine closely resembles the canonical active conformation in the intracellular region. In contrast, the ergotamine-bound 5-HT2BR structure is similar in conformation to the intermediates B and C observed in simulations of the β2AR (Figure 9), with the TM7 conformation matching almost perfectly. (22, 23, 31) Taken together, these spectroscopic, computational, and crystallographic data provide support for the notion that arrestin-biased ligands may work, in part, by favoring an alternative set of conformations for TM7.
The determination of a crystal structure of a GPCR bound to an arrestin was highly anticipated, as it held the potential to reveal arrestin-specific coupling conformations of the GPCR. This past year saw the determination of the first crystal structure of a GPCR–arrestin complex, rhodopsin bound to arrestin-1. (85) Comparison of this structure to the G protein-bound β2AR structure (3) reveals strikingly similar conformations of the two receptors, including in both TM6 and TM7 (Figure 10). Coupling between arrestin and rhodopsin appears to be primarily mediated by hydrophobic contacts within the intracellular coupling interface of the GPCR, in agreement with a structure of rhodopsin bound to an arrestin peptide. (86) In contrast, several polar interactions appear to mediate G protein coupling with β2AR. Despite the similarity in the receptor conformation observed in the G protein-bound and arrestin-bound crystal structures, conformational selectivity for arrestins and G proteins might still be achieved if (1) a GPCR adopts other conformational states that couple to only a G protein or only arrestin or (2) subtle fluctuations about the crystallographically observed conformational states favor G protein coupling or arrestin coupling by strengthening or weakening certain interactions between the proteins. To take advantage of functional selectivity for the development of safer and more effective therapeutics, we require a way to determine the molecular signatures of biased GPCRs and ligand-mediated bias at these receptors.

Figure 10

Figure 10. Structural comparison of G protein-bound and arrestin-bound GPCRs. Crystal structures of β2AR bound to Gs (left; PDB ID: 3SN6) and of rhodopsin bound to arrestin-1 (right; PDB ID: 4ZWJ) similar conformations of the GPCRs’ intracellular coupling sites.

A third potential mechanistic explanation for biased signaling depends upon the idea that biased ligands can induce differential phosphorylation patterns of residues in certain regions of the GPCR, including the C-terminus and third intracellular loop. (87) Arrestin-biased ligands may favor GPCR coupling with particular kinases, (88) which may give rise to these distinct phosphorylation patterns. (88-90) Recently, 19F NMR experiments have revealed that differently phosphorylated C-terminal peptides can induce variable structural changes in arrestin; these structural changes occurred in regions associated with downstream functions of arrestin, including association with clathrin and Src kinase. (91) The structural mechanism by which different GPCR phosphopeptides stabilize alternative arrestin conformations is currently not well understood, nor have the arrestin conformations that arise from the binding of different phosphopeptides been fully characterized, although crystal structures of a phosphopeptide-bound arrestin-2 and of a preactivated arrestin-1 reveal common phosphopeptide binding modes and active conformations of arrestin. (92, 93) Future research in this direction may improve our understanding of how the phosphorylation state of the GPCR C-terminus, in combination with the conformation of the transmembrane bundle, correlates with the conformational state of arrestin. Indeed, recent studies performed using fluorescence and bioluminescence spectroscopy support the idea that arrestin conformation varies depending on the identity of the coupled GPCR and that these arrestin conformations may lead to different downstream effects. (94, 95)

5 Allosteric Modulation of GPCRs

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The great majority of ligands generally bind a GPCR at the same site as the native ligand. This site (the binding pocket in class A GPCRs) is known as the orthosteric site and these ligands as orthosteric ligands. However, certain ligands—known as allosteric ligands or allosteric modulators—bind at other sites. Allosteric modulators can influence the structure, dynamics, and function of GPCRs in multiple ways. (37, 96) Pharmacologically, the classical effect of an allosteric modulator is to increase or decrease the affinity of orthosteric ligands. Allosteric modulators can also alter the efficacy of orthosteric ligands, that is, the extent to which these orthosteric ligands activate the GPCR when bound. (41) In some cases, allosteric ligands can also induce activation even in the absence of an orthosteric ligand and might thus be considered agonists in their own right.
Discovery and development of allosteric modulators for GPCRs represents an area of intense pharmaceutical interest. Allosteric modulators may achieve selectivity between receptor subtypes that possess nearly identical orthosteric sites [e.g., the M1 and M2 muscarinic acetylcholine receptors (M1R and M2R)]. (97-99) In addition, because they act largely by altering the affinity or efficacy of native ligands, allosteric modulators may provide a means to fine-tune cellular responses to the body’s natural signaling patterns. (97)
Many allosteric modulators appear to bind on the extracellular surface of the receptor. Until recently, this was inferred largely on the basis of mutagenesis data, (100-102) particularly for muscarinic acetylcholine receptors, which have served as model receptors for the study of allosteric modulation in GPCRs. In a recent simulation study, we determined the binding modes of multiple allosteric modulators at M2R by allowing each modulator to freely diffuse in surrounding water until it stably bound the receptor. (38) Each of the modulators consistently bound a site we refer to as the extracellular vestibule, located approximately 15 Å above the orthosteric binding site (Figure 11). A subsequently published crystal structure—the first of a drug-like modulator bound to a GPCR—showed a different allosteric modulator bound to the M2R at this same site and in a similar pose. (39)

Figure 11

Figure 11. Structural basis of allosteric modulation in GPCRs. (A) Conformational changes to the orthosteric and allosteric binding sites in the presence of different ligands. The presence of the orthosteric ligand (green) favors a widened allosteric site. The allosteric modulator in blue requires a widened allosteric site to bind, while the allosteric modulator in pink does not. Adapted by permission from ref 38. Copyright 2013 Macmillan Publishers Ltd. (B) Sites of allosteric modulation in GPCRs (gray) include the extracellular loops in the M2R (top; PDB ID: 4MQT), the centrally located sodium-binding site in the adenosine A2A receptor (middle, with sodium in yellow; PDB ID: 4EIY) and the base of TM6 in glucagon receptor (bottom; PDB ID: 5EE7).

Our simulation study also allowed us to determine two separate mechanisms by which certain allosteric modulators affect the affinity of certain orthosteric ligands at the M2R. The first mechanism, interestingly, does not require any structural change in the receptor: electrostatic repulsion between a positively charged allosteric ligand and a positively charged orthosteric ligand destabilizes the binding of one in the presence of the other. The second mechanism involves structural change: certain allosteric modulators increase the width of both the allosteric and orthosteric binding sites, and certain orthosteric antagonists have a similar effect (Figure 11A); thus, the presence of either the allosteric or orthosteric ligand increases the affinity of the other. By contrast, the modulator-bound M2R crystal structure provides an example of an allosteric modulator and an orthosteric ligand that both appear to favor narrow conformations of the two binding sites. (39)
Although the extracellular vestibule might represent the most common binding site for drug-like allosteric modulators, it is certainly not the only one. A recent crystal structure of the glucagon receptor shows an allosteric modulator bound on the intracellular surface, at the interface between TM6, TM7 and the surrounding lipids (Figure 11B). (103) Several allosteric modulators of the glucagon-like peptide 1 (GLP1) receptor appear to bind at a similar location by binding covalently to a cysteine residue proximal to TM6 in the third intracellular loop. (104) The molecular mechanism of these modulators is not clear, but they may act by aiding or blocking the outward motion of TM6 and thus favoring or preventing receptor activation, respectively. (105) Indeed, we note that at least one of these compounds, sometimes referred to as compound 2, can act as an allosteric agonist to induce receptor activation even in the absence of an orthosteric agonist. (106-108)
A number of endogenous ligands—those that occur naturally within the body—can also act as allosteric modulators. (41) For example, sodium is known to disfavor agonist binding and activation at many GPCRs. Several high-resolution crystal structures of inactive-state class A GPCRs reveal a bound sodium ion located in a hydrated pocket located below the binding pocket (Figure 11B) and stabilized by its interaction with conserved residues, particularly Asp2.50. (109, 110) In active-state GPCR structures and simulations, on the other hand, this pocket has collapsed, such that sodium can no longer be accommodated. (111) As a result, the binding of sodium tends to stabilize the inactive state.
Other endogenous ligands appear to bind on the GPCR’s intracellular surface. Experimental studies indicate that phospholipids can act as allosteric modulators, with phosphatidylgycerol lipids favoring agonist binding and facilitating receptor activation and phosphatidylethanolamine lipids favoring antagonist binding and impeding receptor activation. (29, 112-114) Recent simulation studies have suggested that phosphatidylglycerol lipids insert between the intracellular ends of TM6 and TM7, disrupting TM3–TM6 interactions and thus favoring the active state. (29, 115) G proteins also act as allosteric modulators, affecting the conformation of the orthosteric site, even in the absence of an orthosteric ligand. (42)

6 Importance of GPCR Dynamics in Drug Discovery

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The recent breakthroughs in GPCR crystallography have led to widespread adoption of structure-based drug design methodologies for GPCR targets. (116-120) Even single-crystal structures of a GPCR are very useful in this regard; docking to such structures has proven to be highly effective in discovery of novel ligands. (121-123) A number of drug candidates developed through structure-based methods are currently in preclinical development or clinical trials for indications ranging from Alzheimer’s disease to cancer. (124, 159) Fully exploiting the power of structure-based drug design at GPCRs, however, requires an understanding of the dynamic properties of these receptors. Here we describe several ways in which the dynamics of GPCRs are relevant to drug discovery.
GPCR binding pockets exhibit substantial flexibility. The binding pocket geometry generally differs from one conformational state to another. Even within a single conformational state, the binding pocket may be highly flexible, as illustrated by the distinct structures of agonist-bound A2A receptors. (52) Docking to a single structure will thus lead to identification of only a subset of the compounds that bind to the GPCR. Considering multiple possible receptor structures will generally increase the diversity of binding ligands identified.
Perhaps more importantly, the goal when designing a GPCR-targeted drug is typically to find a ligand that not only binds to the target but also achieves a particular signaling profile. One might wish to find a full agonist that strongly stimulates receptor activation and signaling, a partial agonist that stimulates receptor signaling to a lesser degree, a neutral antagonist that does not signal on its own but blocks the body’s native agonists from binding, or an inverse agonist that reduces signaling below its basal (unliganded) levels. Achieving a given signaling profile requires that the drug stabilize specific conformational states of the receptor and thus specific conformational states of the binding pocket. An agonist, for example, stabilizes active states relative to inactive states. Designing such a ligand with confidence requires an understanding of how subtle changes in the binding pocket are coupled to different signaling profiles and different conformations of the intracellular coupling interface. Rational design of a biased ligand—for example, a drug that stimulates arrestin signaling but not G protein signaling—is even more of a challenge, requiring an understanding of conformations associated with G protein signaling and arrestin signaling.
Information on binding pocket dynamics, and the relationship between binding pocket conformation and receptor signaling, thus promises to guide the design of drugs with desired signaling profiles. This information may come in the form of crystal structures of multiple conformational states; docking studies have already demonstrated that an active-state structure is helpful in identifying agonists. (122) Simulations can provide more detailed information on binding pocket dynamics, both when crystal structures of multiple conformational states are available (35) and when they are not, and can be used to compare a ligand’s interactions with different conformational states of the receptor. Simulations can also be used to identify differences in the dynamics of binding pockets of closely related receptor subtypes, pointing to opportunities for designing drugs that select for one subtype over another.
Dynamics are equally important in the lead optimization process, where one modifies a ligand to improve its efficacy or to preserve its efficacy while improving other properties. Simulations may help identify the key interactions the lead ligand makes with the binding pocket or rearrangements to the binding pocket induced by the ligand. These results suggest opportunities for ligand optimization. Biophysical measurements may also be useful in this process. (125)
Receptor dynamics are particularly critical to the design of allosteric modulators, an area of great interest in GPCR drug discovery. (126) Allosteric binding sites are often not evident from crystal structures; their very formation may depend on the fact that receptors are constantly changing conformation. Simulations have proven capable of capturing “cryptic” binding pockets in various proteins (127, 128) and of identifying allosteric ligand binding sites at GPCRs. (38) Moreover, the effects of an allosteric drug generally depend on the manner in which it alters the receptor’s conformation, either modulating signaling directly or altering the affinity or efficacy of the native, orthosteric ligand. Enabling the rational design of allosteric drugs with desired effects requires deciphering the coupling of allosteric sites to the orthosteric binding pocket and the intracellular-coupling interface. In a recent proof-of-concept study, we used a simulation-based approach to design chemical modifications that substantially altered a modulator’s allosteric effects. (38) Efforts in this direction will also benefit from additional crystal structures of GPCRs bound to allosteric modulators and from spectroscopic studies of the effects of modulators on receptor dynamics.
The kinetics of drug binding and unbinding have been recognized in recent years to be critical to the effectiveness and safety of many drugs. For example, the efficacy of ligands at certain GPCRs correlates better with residence time than with binding affinity. (129) Binding kinetics depend on receptor dynamics, as conformational change is often required for ligand binding and unbinding. In some cases, these conformational changes are subtle and short-lived rearrangements of amino acid side chains, as illustrated by a study in which we captured the full process of ligands binding to the β2AR spontaneously in simulation. (130) In other cases, large-scale motions of extracellular loops control binding kinetics, as observed in more recent simulation studies illuminating the clinically important differences in dissociation kinetics of the respiratory drug tiotropium at the M2 and M3 muscarinic acetylcholine receptors. (46, 131) Deciphering the factors that control binding kinetics, including receptor and ligand dynamics, promises to enable the rational design of drugs with desired kinetic properties.

7 Concluding Remarks

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We have reviewed, in broad strokes, what is currently known about the atomic-level motions of GPCRs and how those motions enable GPCR function. Our current understanding is based on a combination of experimental data and computational results. Experimental methods for studying GPCR structure and dynamics have advanced dramatically in recent years, not only leading to an explosion of GPCR crystal structures but also enabling multiple spectroscopy techniques and other biophysical experiments that were previously beyond reach for GPCRs. Likewise, computational methods such as MD simulations have benefited from substantial recent advances in speed and accuracy, as well as new techniques for analyzing simulation results to pick out subtle conformational changes and allosteric networks. (132-138) Computational approaches still suffer from a number of limitations, (139, 140) but they serve as a powerful complement to experimental methods. Advances on both computational and experimental fronts have also now enabled the experimental validation of a variety of computational predictions, including the “loose coupling” between the binding pocket and the intracellular coupling interface, (22-24, 55) the binding poses and molecular mechanisms of allosteric modulators, (38, 39) the distinct conformations of the ionic lock, (21, 24, 55, 71) and the role of G protein dynamics in nucleotide exchange. (141-144)
A complete description of GPCR dynamics will require far more investigation. Our understanding of activation mechanisms remains incomplete, and we are just beginning to grasp the mechanistic basis for allosteric modulation and biased signaling, even for the best-studied GPCRs. Much additional work will be necessary to understand how these properties vary across the large GPCR family. In the remainder of this section, we discuss several other important areas that call for further research.
First, we lack a clear understanding of the dynamics of disordered segments of GPCRs, including the C terminus and, in many receptors, the large third intracellular loop. These regions are typically unresolved in crystal structures, but they play important roles in interactions with intracellular binding partners and can become ordered in the presence of such partners. (33) What conformations can these disordered regions adopt, and how does the binding of intracellular proteins influence the disordered-to-ordered transition? How do post-translational modifications of these regions, such as phosphorylation, affect their dynamics and their propensity to bind intracellular partners? How do the C-termini of nearly 800 human GPCRs, which exhibit low sequence conservation and high variability in length, enable coupling to just four highly related arrestin subtypes?
Second, while we have a reasonable sense for how GPCRs catalyze nucleotide release from G proteins—thanks to extensive mutagenesis, spectroscopy, and simulation studies (141-144)—we have a poorer mechanistic understanding of how GPCRs couple with other intracellular proteins, including arrestins and GPCR kinases (GRKs). How do GPCRs activate arrestins? To what degree does GPCR coupling determine the downstream effects of arrestin—for example, whether it facilitates endocytosis, mediates downstream kinase signaling, or both? What does the GPCR-bound state of a GRK look like? We have some knowledge of the sites on a GRK responsible for GPCR binding, (145) but we do not know how certain GPCR ligands can selectively promote GPCR coupling to one kinase over another. (88)
Third, we now appreciate that GPCRs move extensively within cells; that is, they diffuse within lipid membranes and undergo trafficking among different membrane compartments. It remains unclear, however, how the intrinsic dynamics and signaling properties of a GPCR vary as the GPCR moves about the cell. (146-149) Some recent advances in this field include the development of fluorescently tagged, conformationally selective nanobodies to enable the detection of active-state GPCRs in cells. (150, 151) Single-molecule imaging of GPCRs in cell membrane has also revealed that various ligands may influence patterns of GPCR oligomerization in cells, (26, 152-156) but the mechanistic basis for these effects is not known. Moreover, how does the spatial distribution of GPCRs in cells affect the spatial organization of downstream signaling pathway components, and what are the functional consequences of changes in spatial organization?
Answering these questions will help us to understand how GPCRs, and the ligands that bind them, can achieve fine control over all their downstream signaling pathways. Doing so will likely require a variety of cutting-edge experimental methods, including single-molecule fluorescence microscopy and spectroscopy, electron microscopy, and X-ray free electron laser crystallography. Simulations at multiple scales—not limited to atomic-level MD simulations—will likely prove necessary, as will a computational framework to integrate data from a wide variety of experiments. We envision that this framework will allow us to predict how GPCRs communicate with downstream signaling proteins in cells as a function of all of the molecules in their surrounding environments. By combining information across multiple spatial and temporal scales, we will come closer to directly linking multiple facets of GPCR structure and dynamics to cellular physiology, a critical step in the rational design of finely tuned drugs to target difficult-to-treat human ailments and diseases.

Author Information

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  • Corresponding Author
    • Ron O. Dror - †Department of Computer Science, ‡Biophysics Program, §Department of Molecular and Cellular Physiology, and ∥Institute for Computational and Mathematical Engineering, Stanford University, Stanford, California 94305, United States Email: [email protected]
  • Authors
    • Naomi R. Latorraca - †Department of Computer Science, ‡Biophysics Program, §Department of Molecular and Cellular Physiology, and ∥Institute for Computational and Mathematical Engineering, Stanford University, Stanford, California 94305, United States
    • A. J. Venkatakrishnan - †Department of Computer Science, ‡Biophysics Program, §Department of Molecular and Cellular Physiology, and ∥Institute for Computational and Mathematical Engineering, Stanford University, Stanford, California 94305, United States
  • Notes
    The authors declare no competing financial interest.

Biographies

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Naomi R. Latorraca

Naomi R. Latorraca graduated from the University of Pittsburgh (Pittsburgh, PA) in 2013 with a B.A./B.S. in history and molecular biology, where she performed research under the mentorship of Prof. Michael Grabe. She is currently a Ph.D. student in the biophysics program at Stanford University (Stanford, CA). Under the advisorship of Prof. Ron Dror, she is using molecular dynamics simulations to investigate the conformational dynamics of various membrane proteins, including G protein-coupled receptors.

A. J. Venkatakrishnan

A. J. Venkatakrishnan completed his B.Tech in bioinformatics from VIT University (Tamil Nadu, India) in 2008 and a research assistantship at the Indian Institute of Science (Bangalore, India) with Dr. Nagasuma Chandra in 2009. He completed his Ph.D. in biological sciences (focusing on computational biology) as a St. Johns College Benefactor Scholar and an LMB-Cambridge International Scholar from the University of Cambridge and the MRC Laboratory of Molecular Biology (Cambridge, UK) in 2013. His Ph.D. was advised primarily by Dr. M. Madan Babu and coadvised by Prof. Gebhard Schertler. He then worked as an investigator scientist at the MRC Laboratory of Molecular Biology supported by an MRC Early Career Award. Presently, he is a postdoctoral researcher at Stanford University (Stanford, CA) working jointly with Profs. Ron Dror and Brian Kobilka. His research interests are focused on the structure, dynamics, and design of G protein-coupled receptors.

Ron O. Dror

Ron O. Dror completed a B.A./B.S. at Rice University (Houston, TX), an M.Phil. as a Churchill Scholar at the University of Cambridge (Cambridge, UK), and a Ph.D. at Massachusetts Institute of Technology (Cambridge, MA). He served for over a decade as second-in-command of D. E. Shaw Research, where he focused on biomolecular simulation and high-performance computing (part of a project highlighted by Science as one of the top 10 scientific breakthroughs of 2010). He is currently an associate professor of computer science and, by courtesy, molecular and cellular physiology at Stanford University (Stanford, CA), where he employs a broad range of computational methods to study the spatial organization and dynamics of biomolecules and cells.

Acknowledgment

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We thank Robin Betz, Connor Brinton, Brendan Kelly, João Rodrigues, Raphael Townshend, Aashish Manglik, Matthieu Masureel, Antoine Koehl, and Brian Kobilka for helpful comments and discussions. We also thank D. E. Shaw Research for access to published MD simulation trajectories. This work was supported by a Terman Faculty Fellowship, by Pfizer, Inc., by Eli Lilly and Co. through the Lilly Research Program, and by a National Science Foundation Graduate Research Fellowship.

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  • Abstract

    Figure 1

    Figure 1. GPCR signaling: (A) an orthosteric ligand (orange) binds an inactive GPCR, the β2 adrenergic receptor (β2AR; PDB ID: 2RH1); (B) A ligand-bound GPCR undergoes a conformational change to its active state (PDB ID: 3SN6); and (C) an active GPCR binds a G protein (PDB ID: 3SN6), which subsequently promotes nucleotide release from, and activation of, the G protein α-subunit.

    Figure 2

    Figure 2. Structure and topology of GPCRs. (A) GPCRs contain seven transmembrane helices (gray), three extracellular loops (ECLs) and an amino terminus (orange), and three intracellular loops (ICLs) and a carboxyl terminus (purple). The transmembrane domain consists of the transmembrane helices, as well as the extracellular and intracellular loops. (B) Cartoon representation of the β2AR highlighting transmembrane helices (TMs), loops, and terminal tails.

    Figure 3

    Figure 3. Atomic-level motions of a GPCR revealed through MD simulations. Representative frames from MD simulations (from ref 23) of agonist-bound β2AR as it transitions from an active state to an inactive state, with (A) all non-hydrogen atoms represented as lines and (B) protein backbone represented as ribbons. Transmembrane helix 6 (TM6) is colored red to highlight its high degre of mobility during the transition between active and inactive states.

    Figure 4

    Figure 4. Protein conformations cluster into distinct conformational states. Mapping an MD simulation trajectory to a well-chosen low-dimensional space can reveal distinct clusters of conformations. (A) Plotting an MD simulation trajectory along two geometric coordinates reveals three distinct conformational states during the process of β2AR deactivation (top). RMSD is the root-mean-square deviation. (B) Snapshots from simulation, representing each of the three conformational states (light pink, magenta and dark purple), are overlaid with the inactive-state crystal structure (blue). These are shown along with a simplified, qualitative one-dimensional energy landscape, where the depth of each energy well is inversely related to the population of the corresponding conformational state. Adapted by permission from ref 23. Copyright 2011 National Academy of Sciences.

    Figure 5

    Figure 5. Perturbations alter the populations of conformational states. Hypothetical histograms (light pink, magenta, and purple) represent the relative populations of each of three hypothetical conformational states. Hypothetical energy landscapes (gray) are inversely related to the populations of the conformational states. Compared to the distribution of conformations visited by (A) an unliganded GPCR, (B) an agonist-bound GPCR samples intermediate and fully active conformations more frequently, and (C) an agonist-bound, G protein-bound GPCR more heavily populates fully active conformations. New conformational states may arise on this energy landscape under additional conditions (not shown).

    Figure 6

    Figure 6. Structural rearrangements during GPCR activation. Inactive (light pink) and active (dark purple) conformations of the β2AR show differences in helix position and side-chain orientation in three distinct regions of the GPCR: the binding pocket (top, left); the connector region, or conserved core triad (bottom, left); and the intracellular coupling site (top and bottom, right).

    Figure 7

    Figure 7. Loose allosteric coupling underlies GPCR activation. (A) During simulations of β2AR deactivation, three key regions (the binding pocket, the connector region, and the intracellular coupling interface) spontaneously transition between at least two conformations independently of the other regions. (B) Horizontal bars represent the conformations sampled by each region over the course of four 2-μs deactivation simulations of the β2AR. Adapted by permission from ref 23. Copyright 2011 National Academy of Sciences.

    Figure 8

    Figure 8. Conformational changes in class A GPCRs upon activation. Three class A GPCRs captured in their crystallographic inactive and active conformations reveal similar conformational changes upon activation. TM6 is highlighted. M2 is the M2 muscarinic acetylcholine receptor and μOR is the μ-opioid receptor.

    Figure 9

    Figure 9. Diverse conformational states of the β2AR. During MD simulations of β2AR beginning in the active state (dark gray; PDB ID: 3P0G) (A), β2AR transitions along (B) a dominant pathway through an intermediate (intermediate A) in which TM6 is still displaced outward relative to the inactive crystal structure but TM7 is straightened (light blue) or (C) an alternative pathway through two intermediates, B and C, which exhibit a conformation of TM7 distinct from that seen in the inactive and active crystal structures of the β2AR. Simulations were taken from ref 23.

    Figure 10

    Figure 10. Structural comparison of G protein-bound and arrestin-bound GPCRs. Crystal structures of β2AR bound to Gs (left; PDB ID: 3SN6) and of rhodopsin bound to arrestin-1 (right; PDB ID: 4ZWJ) similar conformations of the GPCRs’ intracellular coupling sites.

    Figure 11

    Figure 11. Structural basis of allosteric modulation in GPCRs. (A) Conformational changes to the orthosteric and allosteric binding sites in the presence of different ligands. The presence of the orthosteric ligand (green) favors a widened allosteric site. The allosteric modulator in blue requires a widened allosteric site to bind, while the allosteric modulator in pink does not. Adapted by permission from ref 38. Copyright 2013 Macmillan Publishers Ltd. (B) Sites of allosteric modulation in GPCRs (gray) include the extracellular loops in the M2R (top; PDB ID: 4MQT), the centrally located sodium-binding site in the adenosine A2A receptor (middle, with sodium in yellow; PDB ID: 4EIY) and the base of TM6 in glucagon receptor (bottom; PDB ID: 5EE7).

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