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The G protein-first activation mechanism of opioid receptors by Gi protein and agonists

Published online by Cambridge University Press:  05 August 2021

Amirhossein Mafi
Affiliation:
Materials and Process Simulation Center (139-74), California Institute of Technology, Pasadena, CA 91125, USA
Soo-Kyung Kim
Affiliation:
Materials and Process Simulation Center (139-74), California Institute of Technology, Pasadena, CA 91125, USA
William A. Goddard III*
Affiliation:
Materials and Process Simulation Center (139-74), California Institute of Technology, Pasadena, CA 91125, USA
*
*Author for correspondence: William A. Goddard III, E-mail: wag@caltech.edu
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Abstract

G protein-first mechanism of activation for opioid receptors and their cognate Gi protein. Σ0: In the absence of ligand and Gi protein, the opioid receptors adopt the inactive conformation, featuring a tight hydrogen bond between the cytosolic ends of TM3 and TM6 that keeps the cytoplasmic region tightly closed. Σ1: Before agonist binding, the inactive Gi protein tightly bound to GDP couples to inactive opioid receptor, to form a pre-coupled opioid receptor-Gi (GDP) complex. Σ2: Interactions between inactive opioid receptor and inactive Gi (GDP) leads to breaking the TM3-TM6 hydrogen bond and opening the cytoplasmic region of the receptors to accommodate the Gi protein. As a result, the pre-activated state (Σ2) emerges, which remains at this resting state until an agonist binds the receptor. Σ3′: agonist bound to the pre-activated state induces the Gi (GDP) to be activated. Activation of the Gi protein is associated with a remarkable opening in the cleft between AH and Ras-like domains of Gα, providing an exit path for GDP release or exchange with a GTP. Σ4′: Upon GDP release of exchange, the agonist-opioid receptor-Gi protein evolves to its fully active state.

We report the G protein-first mechanism for activation of G protein-coupled receptors (GPCR) for the three closest subtypes of the opioid receptors (OR), μOR, κOR and δOR. We find that they couple to the inactive Gi protein-bound guanosine diphosphate (GDP) prior to agonist binding. The inactive Gi protein forms anchors to the intracellular loops of the inactive apo-μOR, apo-κOR and apo-δOR, inducing opening of the cytoplasmic region to form a pre-activated state that holds Gi protein in place until agonist binds. Then, agonist binds to μOR, κOR and δOR already complexed with Gi protein, to trigger the Gαi to open up the tightly coupled GDP binding site, making GDP accessible for GTP exchange, an essential step for Gi signalling. We show that the agonist alone cannot open the intracellular region of μOR and κOR, requiring Gi protein to open the cytoplasmic region by itself. We consider that this G protein-first mechanism may apply to activation of other Class A GPCRs. However, for δOR, agonist binding can open up the intracellular region to encourage Gi protein recruitment. Thus, activation of Gi protein mediated by δOR favourably may proceed with either ligand-first or G protein-first activation mechanisms.

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Research Article
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© The Author(s), 2021. Published by Cambridge University Press
Figure 0

Fig. 1. G protein-first mechanism of activation for opioid receptors and their cognate Gi protein. Σ0: In the absence of ligand and Gi protein, the opioid receptors adopt the inactive conformation, featuring a tight hydrogen bond between the cytosolic ends of TM3 and TM6 that keeps the cytoplasmic region tightly closed. Σ1: Before agonist binding, the inactive Gi protein tightly bound to GDP couples to inactive opioid receptor, to form a pre-coupled opioid receptor-Gi (GDP) complex. Σ2: Interactions between inactive opioid receptor and inactive Gi (GDP) leads to breaking the TM3-TM6 hydrogen bond and opening the cytoplasmic region of the receptors to accommodate the Gi protein. As a result, the pre-activated state (Σ2) emerges, which remains at this resting state until an agonist binds the receptor. Σ3′: agonist bound to the pre-activated state induces the Gi (GDP) to be activated. Activation of the Gi protein is associated with a remarkable opening in the cleft between AH and Ras-like domains of Gα, providing an exit path for GDP release or exchange with a GTP. Σ4′: Upon GDP release of exchange, the agonist-opioid receptor-Gi protein evolves to its fully active state.

Figure 1

Fig. 2. Gi protein binds the mouse μOR by forming ionic anchors to each of three ICLs. (A) The energy minimised mouse μORGi complex derived from ~450 ns MD and ~1.8 μs metaMD simulations. After ~450 ns MD simulation the RMSD = 1.3 Å from the original Cryo-EM structure. (B) The salt bridge anchor from the Gβ subunit to the ICL1. (C) Salt bridge anchors from the Gαi subunit to ICL2 and cytoplasmic end of TM4. (D) Salt bridge and hydrogen bond anchors from the Gαi subunit to the ICL3 and to the cytoplasmic end of TM6. Binding free energy between ionic anchors from metaMD. (E) K98(NZ)-D312(CG) salt bridge coupling Gβ to ICL1, (F) D177(CG)-R32(CZ) salt bridge coupling Gα to ICL2, (G) K273(NZ)-E318(CD) and (H) R263(CZ)-E318(CD) salt bridges coupling Gα to ICL3 and TM6.) Comparison of the optimised complexes from MD simulations with the Cryo-EM structure. Alignment of the density-map obtained by MD simulation with the backbone atoms restrained to the Cryo-EM density map (left). Here, the explicit structure is the snapshot at ~450 ns of MD simulation. (Middle): Alignment of the Cryo-EM structure (PDB ID: 6ddf) to the Cryo-EM density map. (Right): Alignment of the Cryo-EM structure (PDB ID: 6ddf) to the density map obtained from MD simulation with the backbone atoms restrained. Interestingly, our optimised density map has a better correlation with the Cryo-EM structure (PDB ID: 6ddf). Thus, our refined mouse structure can be considered as an experimental structure enhanced to achieve the atomic resolution of the full Gi-μOR-agonist complex. The weighted averages and the standard deviations were calculated for the converged period between the initial configuration before metaMD ‘i’ and the final conformation ‘f’ after metaMD calculations (Supplementary Fig. S1).

Figure 2

Fig. 3. Gi protein binds the human μOR by forming ionic anchors to ICL1, ICL2 and the cytoplasmic end of TM6. (A) Structure of the human μOR–Gi protein complex derived from a ~950 ns MD simulation using Amber14. (B) The ionic anchor from the Gβ subunit to the ICL1. (C) Salt bridge anchors from the Gαi subunit to ICL2 and to the cytoplasmic end of TM4. (D) The network of polar interactions between ICL2 and the Gαi-α5 helix and (E) ionic anchors from the Gαi subunit to the ICL3 and the cytosolic end of TM6. (F) RMSD variation of the complex with time. Here, the RMSD calculated for the backbone atoms of the whole structures over the simulation and compared to the final snapshot. (G-I) Variation of the salt bridge anchors between Gi protein-μOR with time. The dotted red lines indicate hydrogen bonding. (J) Human μOR binding pocket after ~950 ns of MD simulation. The salt bridge between D149(CG) and morphine (the protonated N atom), locks morphine in the orthosteric binding pocket. (K) RMSD variation for the binding pocket and morphine with time. (L) The key salt bridge interaction between D1493.32 and the morphine protonated N atom (the protonated N atom) that holds morphine in tight contact with the human μOR.

Figure 3

Fig. 4. Gi protein binds the human κOR and δOR by forming ionic anchors to ICL1, ICL2 and the cytoplasmic end of TM6. (A) Structure of the human κOR–Gi protein-MP1104 obtained from MD simulation. (B) MP1104 binding pocket, where the salt bridge between D1383.32 and MP1104 (the protonated N atom) holds MP1104 in tight contact with the human κOR. (C) The ionic anchor from the Gβ subunit to the ICL1. (D) The salt bridge anchor from the Gαi subunit to ICL2. (E) The ionic anchor from the Gαi subunit to the cytosolic end of TM6. Here, (A-E) adapted from figs 3 and 4 of Mafi et al. (2020). (F) Structure of the human δOR–Gi protein-DPI-287 obtained from ~300 ns MD simulation using Charmm36m force field. (G) DPI-287 binding pocket, where the salt bridge between D1283.32 and DPI-287 (the protonated N atom) locks DPI-287 in the orthosteric binding pocket of the human δOR. (H) The ionic anchor from the Gβ subunit to the ICL1. (I) The salt bridge anchor from the Gαi subunit to ICL2. (J) The ionic anchor from the Gαi subunit to the cytosolic end of TM6.

Figure 4

Fig. 5. Formation of pre-activated complex (Σ2) between Gi protein and opioid receptors prior to ligand binding. (A) The structure of the pre-coupled state (Σ1 state), comprising the inactive human μOR and inactive Gi protein-bound GDP (tight); the Gi protein binds to the inactive μOR by forming salt bridge anchors to ICL1, ICL2 and ICL3. (B) MetaMD free energy profile for the salt bridge between the F354 (C) and R1673.50 (CZ). (C) MetaMD free energy for opening the polar interaction between R1673.50 (CZ) and T2816.34 (OG1) while F354 makes a strong salt bridge with R1673.50. (D) The structure of the pre-activated state (Σ2) showing open μOR (broken polar interaction R1673.50-T2816.34), and the salt bridge between F354-R1673.50. (E) The pre-activated complex (Σ2) between human μOR and the Gαi-α5 peptide (the rest of the Gi protein is eliminated) showing that formation of the pre-activated state is not dependent on a specific rigid-body orientation modelled in our Σ1 state. (F) MetaMD free energy profile for the interaction between the F354 (C) terminal carboxylate and R1673.50 (CZ). (G) MetaMD free energy for breaking the polar interaction between R1673.50 and T2816.34. (H) The salt bridge between F354 (C) and R1673.50 breaks the polar interaction between R1673.50-T2816.34. (I) Detailed structural analysis for the intracellular region of pre-activated complex between human μOR and the Gαi-α5 peptide. (J,N) The pre-activated complex between Gi protein and κOR/δOR, respectively. (K,O) MetaMD free energy profiles for the interaction between the F354 (C) and κOR-R1563.50 (CZ) and δOR-R1463.50 (CZ), respectively. (L,P) MetaMD free energy for breaking the coupling between TM3 and TM6 κOR: R1563.50-T2736.34 δOR: R1463.50-T2606.34. (M,Q) Detailed structural analysis for the intracellular region of pre-activated complex between human κOR/δOR and Gi protein. The weighted averages and the standard deviations were calculated for the converged period between the initial configuration before metaMD ‘i’ and the final conformation ‘f’ after metaMD calculations (Supplementary Figs S4–S6).

Figure 5

Fig. 6. Agonist promotes the activation of Gi protein by inducing opening of the Gαi subunit. Gi protein activation mediated by (A) morphine binding to pre-activated μOR-Gi protein complex, (B) MP1104 binding to pre-activated κOR-Gi protein complex and (C) DPI-287 binding to pre-activated δOR-Gi protein complex. Overall, we performed an aggregate ~1.1 μs metaMD simulations to evaluate the energetics relevant to opening the Gαi subunit from its GDP binding site. For these free energy calculations, the collective variable was the distance between the AH domain (the centre of mass of the Cα atoms for the residues 147–181) and the Ras-like domain (the centre of mass of the Cα atoms for the residues 42–59), which define the GDP binding site. The weighted averages and the standard deviations were calculated for the converged period between the initial configuration before metaMD ‘i’ and the final conformation ‘f’ after metaMD calculations.

Figure 6

Fig. 7. μOR possesses a weak allosteric coupling. (A,F,J) Our minimised structures of human μOR-morphine, mouse μOR-DAMGO and mouse μOR-BU72, respectively, in the absence of Gi protein or a mimetic Gi protein nanobody. Agonists alone cannot open up the cytoplasmic region of μOR, especially the hydrogen bond between R3.50 and T6.34. (B) Comparison of the minimised human μOR-bound morphine (pink) with the crystallographic inactive conformation of mouse μOR (green) resolved by crystallography (Manglik et al.,2012). MetaMD free energy of (C) the distance between TM3 (the centre of mass of Cα for residues 161–172) and TM6 (the centre of mass of Cα for residues 274–285). (D) The interaction between R1673.50(NH1)-T2816.34(OG1). (E) The interaction between R1673.50 (NH2)-T2816.34(OG1). (G) Comparison of the minimised mouse μOR-bound DAMGO (pink) with the crystallographic active state conformation of mouse μOR (green) resolved by Cryo-EM (Koehl et al.,2018), which indicates that removing Gi protein from the fully active state leads to remarkable contraction in the cytoplasmic region of μOR. MetaMD free energy of (H) Left: the distance between TM3 (the centre of mass of Cα for residues 159–170) and TM6 (the centre of mass of Cα for residues 272–283), middle: the interaction between R1673.50 (NE)-T2816.34(OG1), right: the interaction between R1673.50 (NH1)-T2816.34(OG1). (I) Comparison of the minimised mouse μOR-bound DAMGO (pink) with the crystallographic inactive conformation of mouse μOR (green). Comparison of the minimised mouse μOR-bound BU72 (pink) with: (K) The crystallographic active state (Huang et al.,2015) of mouse μOR (green). (L) The crystallographic inactive state of mouse μOR (green). BU72 alone (a nanobody removed from the complex) cannot maintain the active state conformation. (M) MetaMD free energy of the distance between TM3 (the centre of mass of Cα for residues 159–170) and TM6 (the centre of mass of Cα for residues 272–283). All RMSDs were calculated for the Cα atoms on the TM domains. The weighted averages and the SD were calculated for the converged period between the initial configuration before metaMD ‘i’ and the final conformation ‘f’ after metaMD calculations (Supplementary Fig. S9).

Figure 7

Fig. 8. Activation of Gi protein mediated by δOR favourably proceeds with both ligand-first and G protein-first activation mechanisms. (A,E) Our minimised structures of human κOR-MP1104 and human δOR-DPI-287, respectively, in the absence of Gi protein. MetaMD free energy of (B) the interaction between R1563.50 (NH2)-T2736.34(OG1) and (C) the interaction between R1563.50 (NE)-T2736.34(OG1). (D) Comparison of the minimised human κOR-MP1104 (pink) with the crystallographic inactive conformation of human κOR (green) resolved by crystallography (Wu et al.,2012). MetaMD free energy of (F) the interaction between R1463.50(NH1)-T2606.34(OG1), (G) the interaction between R1463.50 (NH2)-T2736.34(OG1) and (H) the interaction between R1463.50 (NE)-T2736.34(OG1). (I) Comparison of the minimised human δOR-DPI-287 (pink) with the crystallographic inactive conformation of human δOR (green) resolved by crystallography (Fenalti et al.,2014). All RMSDs were calculated for the Cα atoms on the TM domains. Variation of the free energy difference with time was monitored to evaluate the convergence of metaMD simulations. The weighted averages and the standard deviations were calculated for the converged period between the initial configuration before metaMD ‘i’ and the final conformation ‘f’ after metaMD calculations (Supplementary Fig. S10).

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Review: The G protein-first activation mechanism of opioid receptors by Gi protein and agonists — R0/PR1

Conflict of interest statement

Reviewer declares none.

Comments

Comments to Author: This is an interesting study of the activation of opiod receptors, with a focus on differences between the G-protein coupled receptors μOR, κOR, and δOR regarding their interaction with the Gi protein, differences that may help in the design of drugs with reduced side effects.

The authors use model building based on available Cryo-EM and X-ray structures to create receptor-Gi complex structures that are subjected to extensive (a total of 17 μs) molecular dynamics simulations. The results strongly suggest that in order for the receptor to activate the Gi protein the agonist first has to bind to the receptor.

In the metadynamics simulations used to characterize the strength of specific interactions, the quantitative end result is sensitive to the choice of reaction coordinate (or collective variable). Qualitatively the observed differences are likely to be reliable indicators of the differences between the systems.

Review: The G protein-first activation mechanism of opioid receptors by Gi protein and agonists — R0/PR2

Conflict of interest statement

Reviewer declares none.

Comments

Comments to Author: The manuscript presents an impressive exploratory work on different phases of the mechanism of activation of the complex between human opioid receptors, Gi proteins and agonists, using extensive meta-molecular dynamics simulation. Activation involve large conformational changes in the opioid receptor as well as the Gi protein complex. One question the study aims at enlightening concerns the order in which the partnersactto trigger allosteric responses in the opioid receptor or in the Gi protein. Notably, the "in silico" observations are confronted to two possible mechanisms, the Ligand-First or the G Protein-First mechanisms. To test whether observations arising from the simulation represent general properties of opioid receptors, and whether they are robust, the authors reproduce the study on three closely related receptors and use three different force fields. The work involves modeling unknown forms of opioid receptor substates, notably based on homology or combining parts of the system with known structure. It also involves free energy calculations of different transition pathways within the receptors or the Gi proteins. Overall, this is a very consequent and convincing work, that reveals new elements of the mechanism such as the pre-positioning and pre-anchoring of the G-protein to the inactive opioid receptor via strong interactions with the ICL loops, and provides interpretation for known mutational effects in the μOR receptor (e.g. R181C).Discussion of the Ligand-First or the G Protein-First mechanisms elaborates on the simulation results and the observation that one of the studied receptors, δOR, presents conformational change properties that differ from the other two. Finally, the gained knowledge has strong importance for therapeutical applications in pain-relief treatments that would avoid side effects.

The manuscript is clearly written and presents the results of a a large body of carefully executed and analyzed integrative work. Questions and comments below intend to help further clarifying the results and conclusions of this dense study of a very complex system, since there is space for improving the understanding for a general audience that is non-necessarily specialist of the question.

A. Main comments.

1) The authors study several steps of the activation process, named from Σ0 to Σ4', but it is not always clear in the main text which step, or the transition between which steps, is studied. It would be useful for the comprehension that the names of the steps be linked to the different substate models that are studied. I am conscious that since the mechanism is still not well established, an unequivocal correspondence between the mechanistic steps and the conformational substates may not yet be possible. In that case, I recommend the authors name the conformational substates they study using different labels (e.g. A, B, C…), that they describe the characteristics of each substate (i.e. inactive/active receptor; inactive/active G protein, no/with ligand) and they explicit the possible routes the activation process may follow along these substates in the Ligand-Fist or G Protein-First mechanisms, together with the possible correspondence with the Σ steps. A scheme would be very useful in this purpose, that the reader could relate to in the course of the reading instead of struggling with activity shades such as "fully active", "active", "pre-activated", "inactive" that do not directly tell which component is in which form.

2) The authors performed very long simulations aiming at ensuring correct equilibration. However, when it comes to sampling the optimal binding geometry (p11 "…allowed the pre-coupled complex to equilibrate by performing a ~1μs metaMD simulation allowing the complex to find the optimum position and orientation of Gαi-α5"), even a μs metadynamics sampling may be insufficient if another favorable position exists in the space perpendicular to the sampled coordinate, that would be separated by a high energy barrier. The authors address this possibility by sampling the position of the isolated Gαi-α5 helix, again using metaMD (p.12).They write that the helix explored "various positions and orientations" but without quantifying how much "varied" the sampling happened to be. Could the authors quantify the sampling? Why did not the authors use methods that sample discrete positions and orientations on the receptor surface, independent from each other, such as macromolecular docking methods, in order to pre-identify possible geometries of interaction that could further be thoroughly sampled via metaMD? This would ensure that all possible positions and orientations have been considered.

3) Role of the ligand:the authors showed that at least for two receptors, the presence of the ligand alone is not sufficient for the transition to the receptor active state (with separated TM3 and TM6 helices) to occur. In another work cited in the manuscript (Huang et al., Nature 2015), it was proposed that a cation occupies the binding site in addition to the ligand; the authors of this other work did add a positive charge during molecular dynamics simulations they performed on the system. Was a charge added in the present simulation? May an added charge modify the observed results about the transition of the receptor to an active state?

4) (a) I did not understand whether the conformation of the receptor in the sigma2 state is the same as the conformation of the receptor in the fully active state, or if the binding of the ligand further changes the conformation of the receptor: could the authors provide this precision ? (b) The authors write that the presence of the ligand induces a large conformational change in the Gi protein; however, unless I missed something (see comment 1), it seems that the transition of the Gi protein to its the fully active state is only explored in the presence of the ligand: would it be possible to have the same exploration done in the absence of the ligand but with the receptor in its active state in order to understand what exact role the ligand plays ?I could not understand the exact role of the ligand based on the present description; (c) the authors refer several times to a "weak coupling" (e.g. p.21: "Thus, κOR possesses a weak allosteric coupling")? In which way do their observation support the existence of a coupling between the presence of the ligand and the Gi protein conformational change?

5) I am not sure whether the present calculations definitely speak for the G protein-first mechanism in the case of the mu- and kappa-ORs: what the authors clearly showed is that the ligand alone cannot turn an inactive state of the receptor towards an active one, nor can they stabilize the active state and impede it to return to an inactive state in the absence of the Gi protein. However, the authors also write "We showed that this critical event of activation is common to both Ligand-First and G Protein-First mechanisms of activation". In fact, what I understand of their argument in support of the G protein-First mechanism is that the Gi protein binding is ruled by collisions and is therefore slow, while "we expect that agonists will contact opioid receptors that are already pre-activated by the tight Gi protein, making ligand activation independent from slow random collisions." Is agonist binding accelerated by the fact that the receptor is in a pre-activated state? Are there arguments in favor of the agonist binding process not being based on slow random collisions? And again, how exactly does ligand activation function (question 4)? I recommend the authors explain their point more clearly and separate arguments that arise from their present results from what arguments taken from the literature.

B. Minor comments

1) Figures: I recommend labelling helix α5 of Gαi, helices TM3 and TM6 as well as the GDP, the Ras-like and the AH domains, in at least one of the figures (e.g. Fig.1); these structural elements are essential for the activation pathway, therefore it would be useful to easily locate them in the models. In addition, the extensive direct use of Ballesteros-Weinstein numbering for GPCRs in some places make make it difficult for non-specialists to follow the results description (e.g. p 6, "E28^( GαiN)-R182⁴.⁴⁰": which protein does R182⁴.⁴⁰ belong to?).

2) Please, indicate in the main text (in both the Results and the Methods sections) that the full description of the modeling process can be found in supplementary information. The methods section is very short and little informative, this is all right if the reader is referred to the supplementary information but this needs to be plainly written.

3) p.8: while the authors fully convinced me they reached a higher resolution state than the Cryo-EM structure, and notably that they revealed the highly probable existence of anchoring interactions between the receptor and the G protein, I do not understand the interest of building a density map from the results of ~ 1 μs MD simulation with restrained backbone atoms. Clearly, this map better correlates with the protein coordinates solved by CryoEM than the CryoEM map itself, but the MD map was created directly from the protein coordinates solved by Cryo-EM. The fact that the map is "closer" to the coordinates may simply reflect the fact that the MD sampling was not sufficient (notably because of the restrained backbone atoms).Could the authors better justify their argument?

4) p.8, and p.1 SI, the authors use the mouse operator as a template to generate the active human form and to position the morphine ligand. What is the degree of sequence similarity between the mouse and the human receptors ? specifically, what is the degree of sequence similarity of the morphine binding sites?

5) p.8 "We discovered that the Gi protein interfaces the human μOR by forming salt bridge anchors to ICL1, ICL2, ICL3, and the cytoplasmic end of TM6.tOur analysis shows that the Gβ subunit makes a direct and stable ionic contact from D312Gβ to K100ICL1 (Figure 2B & 2H).": While the described investigations and the comparison with other systems are very convincing in favor of the existence of an interaction network between the ICLs and the Gi protein, one cannot be 100% sure that an alternative interaction network is not possible. I would prefer that the authors use a formulation that still leaves place for uncertainty, even while keeping the word "discovery" (which is justified by the discovery of a highly probable and yet unknown interaction network between the ICLs and the G protein).

6) p.10 : "Prior to the ligand binding, Gi protein has sufficient time to couple to the opioid receptors to form a pre-coupled state.": could the authors provide some support to this affirmation ?

7) p11 "Subsequently, allowed the pre-coupled complex to equilibrate by performing a ~1μs metaMD simulation allowing the complex to find the optimum position and orientation of Gαi-α5.":"we" allowed is probably missing.

8) p.12, the formation of a salt bridge contact between the Gαi-α5 helix and the receptor is presented as a trigger to weaken, and then break the interaction between helices TM3 and TM6. Could the authors show a plot with the chronology of α5-receptor salt bridge formation/TM3-TM6 interaction breaking in support to their description ?

9) (a) Fig.4 & Fig.5 Could the authors provide additional explanation about what do these relevant free energy minima represent and why the passage between them need to be damped? I am not sure I understand that point, and the mention of the two minima treatment somewhat blurs the main description.

(b) In a general way, I think most of the caption of Figure 5 should be displaced to the Material and Methods section, or to the protocol description in supplementary information.

Decision: The G protein-first activation mechanism of opioid receptors by Gi protein and agonists — R0/PR3

Comments

Comments to Author: Reviewer #2: This is an interesting study of the activation of opiod receptors, with a focus on differences between the G-protein coupled receptors μOR, κOR, and δOR regarding their interaction with the Gi protein, differences that may help in the design of drugs with reduced side effects.

The authors use model building based on available Cryo-EM and X-ray structures to create receptor-Gi complex structures that are subjected to extensive (a total of 17 μs) molecular dynamics simulations. The results strongly suggest that in order for the receptor to activate the Gi protein the agonist first has to bind to the receptor.

In the metadynamics simulations used to characterize the strength of specific interactions, the quantitative end result is sensitive to the choice of reaction coordinate (or collective variable). Qualitatively the observed differences are likely to be reliable indicators of the differences between the systems.

Reviewer #3: The manuscript presents an impressive exploratory work on different phases of the mechanism of activation of the complex between human opioid receptors, Gi proteins and agonists, using extensive meta-molecular dynamics simulation. Activation involve large conformational changes in the opioid receptor as well as the Gi protein complex. One question the study aims at enlightening concerns the order in which the partnersactto trigger allosteric responses in the opioid receptor or in the Gi protein. Notably, the "in silico" observations are confronted to two possible mechanisms, the Ligand-First or the G Protein-First mechanisms. To test whether observations arising from the simulation represent general properties of opioid receptors, and whether they are robust, the authors reproduce the study on three closely related receptors and use three different force fields. The work involves modeling unknown forms of opioid receptor substates, notably based on homology or combining parts of the system with known structure. It also involves free energy calculations of different transition pathways within the receptors or the Gi proteins. Overall, this is a very consequent and convincing work, that reveals new elements of the mechanism such as the pre-positioning and pre-anchoring of the G-protein to the inactive opioid receptor via strong interactions with the ICL loops, and provides interpretation for known mutational effects in the μOR receptor (e.g. R181C).Discussion of the Ligand-First or the G Protein-First mechanisms elaborates on the simulation results and the observation that one of the studied receptors, δOR, presents conformational change properties that differ from the other two. Finally, the gained knowledge has strong importance for therapeutical applications in pain-relief treatments that would avoid side effects.

The manuscript is clearly written and presents the results of a a large body of carefully executed and analyzed integrative work. Questions and comments below intend to help further clarifying the results and conclusions of this dense study of a very complex system, since there is space for improving the understanding for a general audience that is non-necessarily specialist of the question.

A. Main comments.

1) The authors study several steps of the activation process, named from Σ0 to Σ4', but it is not always clear in the main text which step, or the transition between which steps, is studied. It would be useful for the comprehension that the names of the steps be linked to the different substate models that are studied. I am conscious that since the mechanism is still not well established, an unequivocal correspondence between the mechanistic steps and the conformational substates may not yet be possible. In that case, I recommend the authors name the conformational substates they study using different labels (e.g. A, B, C…), that they describe the characteristics of each substate (i.e. inactive/active receptor; inactive/active G protein, no/with ligand) and they explicit the possible routes the activation process may follow along these substates in the Ligand-Fist or G Protein-First mechanisms, together with the possible correspondence with the Σ steps. A scheme would be very useful in this purpose, that the reader could relate to in the course of the reading instead of struggling with activity shades such as "fully active", "active", "pre-activated", "inactive" that do not directly tell which component is in which form.

2) The authors performed very long simulations aiming at ensuring correct equilibration. However, when it comes to sampling the optimal binding geometry (p11 "…allowed the pre-coupled complex to equilibrate by performing a ~1μs metaMD simulation allowing the complex to find the optimum position and orientation of Gαi-α5"), even a μs metadynamics sampling may be insufficient if another favorable position exists in the space perpendicular to the sampled coordinate, that would be separated by a high energy barrier. The authors address this possibility by sampling the position of the isolated Gαi-α5 helix, again using metaMD (p.12).They write that the helix explored "various positions and orientations" but without quantifying how much "varied" the sampling happened to be. Could the authors quantify the sampling? Why did not the authors use methods that sample discrete positions and orientations on the receptor surface, independent from each other, such as macromolecular docking methods, in order to pre-identify possible geometries of interaction that could further be thoroughly sampled via metaMD? This would ensure that all possible positions and orientations have been considered.

3) Role of the ligand:the authors showed that at least for two receptors, the presence of the ligand alone is not sufficient for the transition to the receptor active state (with separated TM3 and TM6 helices) to occur. In another work cited in the manuscript (Huang et al., Nature 2015), it was proposed that a cation occupies the binding site in addition to the ligand; the authors of this other work did add a positive charge during molecular dynamics simulations they performed on the system. Was a charge added in the present simulation? May an added charge modify the observed results about the transition of the receptor to an active state?

4) (a) I did not understand whether the conformation of the receptor in the sigma2 state is the same as the conformation of the receptor in the fully active state, or if the binding of the ligand further changes the conformation of the receptor: could the authors provide this precision ? (b) The authors write that the presence of the ligand induces a large conformational change in the Gi protein; however, unless I missed something (see comment 1), it seems that the transition of the Gi protein to its the fully active state is only explored in the presence of the ligand: would it be possible to have the same exploration done in the absence of the ligand but with the receptor in its active state in order to understand what exact role the ligand plays ?I could not understand the exact role of the ligand based on the present description; (c) the authors refer several times to a "weak coupling" (e.g. p.21: "Thus, κOR possesses a weak allosteric coupling")? In which way do their observation support the existence of a coupling between the presence of the ligand and the Gi protein conformational change?

5) I am not sure whether the present calculations definitely speak for the G protein-first mechanism in the case of the mu- and kappa-ORs: what the authors clearly showed is that the ligand alone cannot turn an inactive state of the receptor towards an active one, nor can they stabilize the active state and impede it to return to an inactive state in the absence of the Gi protein. However, the authors also write "We showed that this critical event of activation is common to both Ligand-First and G Protein-First mechanisms of activation". In fact, what I understand of their argument in support of the G protein-First mechanism is that the Gi protein binding is ruled by collisions and is therefore slow, while "we expect that agonists will contact opioid receptors that are already pre-activated by the tight Gi protein, making ligand activation independent from slow random collisions." Is agonist binding accelerated by the fact that the receptor is in a pre-activated state? Are there arguments in favor of the agonist binding process not being based on slow random collisions? And again, how exactly does ligand activation function (question 4)? I recommend the authors explain their point more clearly and separate arguments that arise from their present results from what arguments taken from the literature.

B. Minor comments

1) Figures: I recommend labelling helix α5 of Gαi, helices TM3 and TM6 as well as the GDP, the Ras-like and the AH domains, in at least one of the figures (e.g. Fig.1); these structural elements are essential for the activation pathway, therefore it would be useful to easily locate them in the models. In addition, the extensive direct use of Ballesteros-Weinstein numbering for GPCRs in some places make make it difficult for non-specialists to follow the results description (e.g. p 6, "E28^( GαiN)-R182⁴.⁴⁰": which protein does R182⁴.⁴⁰ belong to?).

2) Please, indicate in the main text (in both the Results and the Methods sections) that the full description of the modeling process can be found in supplementary information. The methods section is very short and little informative, this is all right if the reader is referred to the supplementary information but this needs to be plainly written.

3) p.8: while the authors fully convinced me they reached a higher resolution state than the Cryo-EM structure, and notably that they revealed the highly probable existence of anchoring interactions between the receptor and the G protein, I do not understand the interest of building a density map from the results of ~ 1 μs MD simulation with restrained backbone atoms. Clearly, this map better correlates with the protein coordinates solved by CryoEM than the CryoEM map itself, but the MD map was created directly from the protein coordinates solved by Cryo-EM. The fact that the map is "closer" to the coordinates may simply reflect the fact that the MD sampling was not sufficient (notably because of the restrained backbone atoms).Could the authors better justify their argument?

4) p.8, and p.1 SI, the authors use the mouse operator as a template to generate the active human form and to position the morphine ligand. What is the degree of sequence similarity between the mouse and the human receptors ? specifically, what is the degree of sequence similarity of the morphine binding sites?

5) p.8 "We discovered that the Gi protein interfaces the human μOR by forming salt bridge anchors to ICL1, ICL2, ICL3, and the cytoplasmic end of TM6.tOur analysis shows that the Gβ subunit makes a direct and stable ionic contact from D312Gβ to K100ICL1 (Figure 2B & 2H).": While the described investigations and the comparison with other systems are very convincing in favor of the existence of an interaction network between the ICLs and the Gi protein, one cannot be 100% sure that an alternative interaction network is not possible. I would prefer that the authors use a formulation that still leaves place for uncertainty, even while keeping the word "discovery" (which is justified by the discovery of a highly probable and yet unknown interaction network between the ICLs and the G protein).

6) p.10 : "Prior to the ligand binding, Gi protein has sufficient time to couple to the opioid receptors to form a pre-coupled state.": could the authors provide some support to this affirmation ?

7) p11 "Subsequently, allowed the pre-coupled complex to equilibrate by performing a ~1μs metaMD simulation allowing the complex to find the optimum position and orientation of Gαi-α5.":"we" allowed is probably missing.

8) p.12, the formation of a salt bridge contact between the Gαi-α5 helix and the receptor is presented as a trigger to weaken, and then break the interaction between helices TM3 and TM6. Could the authors show a plot with the chronology of α5-receptor salt bridge formation/TM3-TM6 interaction breaking in support to their description ?

9) (a) Fig.4 & Fig.5 Could the authors provide additional explanation about what do these relevant free energy minima represent and why the passage between them need to be damped? I am not sure I understand that point, and the mention of the two minima treatment somewhat blurs the main description.

(b) In a general way, I think most of the caption of Figure 5 should be displaced to the Material and Methods section, or to the protocol description in supplementary information.

Decision: The G protein-first activation mechanism of opioid receptors by Gi protein and agonists — R1/PR4

Comments

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