How Does Agonist and Antagonist Binding Lead to Different

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How Does Agonist and Antagonist Binding Lead to Different Conformational Ensemble Equilibria of #-opioid Receptor: Insight from Long-time Gaussian Accelerated Molecular Dynamics Simulation Xiaoli An, Qifeng Bai, Zhitong Bing, Shuangyan Zhou, Danfeng Shi, Huanxiang Liu, and Xiaojun Yao ACS Chem. Neurosci., Just Accepted Manuscript • DOI: 10.1021/acschemneuro.8b00535 • Publication Date (Web): 29 Oct 2018 Downloaded from http://pubs.acs.org on October 31, 2018

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ACS Chemical Neuroscience

How Does Agonist and Antagonist Binding Lead to Different Conformational Ensemble Equilibria of κ-opioid Receptor: Insight from Long-time Gaussian Accelerated Molecular Dynamics Simulation Xiaoli An1, Qifeng Bai2, Zhitong Bing2,3, Shuangyan Zhou1,4, Danfeng Shi1, Huanxiang Liu4*, Xiaojun Yao1,5* 1State

Key Laboratory of Applied Organic Chemistry and Department of Chemistry, Lanzhou University, Lanzhou 730000, China 2

3Institute

School of Basic Medical Science, Lanzhou University, Lanzhou, China

of Modern Physics of Chinese Academy of Sciences, Gansu Province, Lanzhou, China

4School 5State

of Pharmacy, Lanzhou University, Lanzhou 730000, P. R. China

Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for

Applied Research in Medicine and Health, Macau University of Science and Technology, Taipa, Macau, China

* Corresponding author Tel.: +86-931-891-2578 Fax: +86-931-891-2582 E-mail address: [email protected], [email protected]

1

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ABSTRACT: The opioid receptors belong to the class A seven transmembrane-spanning (7TM) G protein-coupled receptors (GPCRs). The κ-opioid receptor (KOR) is a subfamily of four opioid receptors. The endogenous peptide and a variety of selective agonists and antagonists of KOR have been developed. The structurally similar ligands at the same site cause completely opposite biological functions and induce different conformational changes. To shed light on the conformation ensembles and conformational dynamics in activation and deactivation processes of KOR, we performed all-atom, long-time Gaussian accelerated molecular dynamics simulation (GaMD) on KOR binding with agonist epoxymorphinan MP1104 and antagonist JDTic respectively. Our results revealed the different conformation ensembles of KOR binding with agonist and with antagonist. Agonist binding stabilizes active state of key motifs including DYYNM motif and CWxP motif, and biases the conformation equilibria towards active state. Antagonist binding will not destroy inactive conformation equilibria, by keeping the stable inactive state of these crucial motifs. We found that the inactive apo form of KOR is the most stable state, while the active apo form relaxes readily to inactive state. Our results also revealed a stable intermediate (I), which is attributed to the hydrophobic interactions between Tyr2465.58 and TM6, as well as the steric hindrance of them. Our results not only show the conformation equilibria bias of KOR by binding with agonist and antagonist, but also provided the structural information for the design and discovery of potential ligands with different functions. Key words κ-opioid receptor; Gaussian accelerated molecular dynamics simulation; 2


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agonist; antagonist; conformational change

INTRODUCTION The κ-opioid receptor (KOR) is one of four opioid receptors that bind opioid-like compounds, belongs to the class A γ subfamily of GPCRs1, 2, having the common architecture with generic seven transmembrane (TM) α-helices connected by alternating intracellular (IC) and extracellular (EC) loops. Activation of KOR by endogenous peptide or exogenous synthetic agonists is associated with behavioral and mood effects that include analgesia, sedation, and perceptual distortions3-5. The binding of antagonists to the same site blocks the activation of KOR, used for treatment of depression, anxiety, addictive disorders and other psychiatric conditions produced or exacerbated by stress6. KOR was considered to be an alternative target for the discovery of safer analgesics to avoid the side effects including respiratory depression, tolerance, dependence and constipation7. The crystal structure of human KOR in complex with the selective antagonist JDTic8 has been resolved in 20129. Che et al provided the active-state crystal structure of human KOR in complex with the agonist MP1104 and an active-state-stabilizing nanobody (NB)10. The crystal structures of KOR reveal substantial conformational difference between the inactive and active states, and provided details of interactions of ligand and receptor. Nevertheless, GPCRs are not simple ligand-induced “on/off” switches but present an ensemble of multiple inactive, intermediate and active states11-13, the equilibrium of conformational ensemble can be shifted upon ligand binding. The static crystal structures 3



cannot provide enough information about the dynamic process of these conformational changes. Moreover, crucial dynamic details, such as how ligands trigger activation and deactivation of GPCRs and how active-state and inactive-state transform, are still unclear. Knowledge about these details could contribute to the development of effective and selective GPCRs ligands. Thus, we intend to elucidate the details of how agonist and antagonist binding lead to different conformational ensemble equilibria of KOR by computational studies. The results will be helpful to develop more selective KOR ligands with fewer side effects. Molecular dynamics simulation (MD) has been widely used to investigate the conformational dynamics and protein-ligand interaction of GPCRs. To overcome the limitations of conventional dynamics simulation sampling, a number of enhanced sampling dynamics simulations, by applying external forces to a set of pre-defined collective variables (metadynamics14) or to the system (targeted15, steered16, and accelerated MD17, 18)

, has been developed and effectively applied to GPCRs19-21. Among them, Gaussian

accelerated molecular dynamics simulation (GaMD)18 was developed using harmonic functions to construct the boost potential that is added to smoothen the biomolecular potential energy surface. Compared with locally enhanced sampling methods, GaMD without need to set predefined reaction coordinates, hence which allows exploring the biomolecular conformational space without a priori knowledge or restraints. Moreover, GaMD is presented to reduce the energetic noise during reweighting comparing with aMD18,

22.

These advantages make GaMD very suitable for large proteins. GaMD 4


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simulation method has been successfully applied on the muscarinic GPCR and μ-opioid receptor (MOR), investigating ligand-dependent behavior, dissociation and binding of ligands, as well as identification the intermediate18, 23-26. Herein, we carried out the all-atom, long-time GaMD on KOR binding with agonist MP1104 and antagonist JDTic respectively to investigate the conformation dynamics of KOR. We found that the inactive apo form of KOR is the most stable. The antagonist JDTic binding will not destroy the inactive conformation equilibria. The agonist MP1104 binding biases the conformation equilibria towards active state. Once the agonist was removed from KOR, the active apo form relaxes towards the inactive state readily and finally stabilizes in the intermediate (I) in our simulation scale. We revealed that the Asp1383.32, Asn1413.35 of DYYNM motif and Trp2876.48 of CWxP motif play key roles in the activation and inhibition of KOR. Our results also revealed a stable intermediate (I), which is attributed to the hydrophobic interactions and steric hindrance between Tyr2465.58 and TM6. The rotameric transition of Tyr2465.58 is the barrier of intracellular conformational transition of KOR between active and inactive states. These results present the different conformation ensembles of KOR binding with agonist and antagonist. Moreover, the intermediate (I) can provide structural information for the discovery more selective KOR ligands. RESULTS AND DISCUSSION The Conformational Dynamics of KOR upon Binding with Different Ligands. Ligand binding promotes or stabilizes specific conformations that lead to the activation or deactivation of KOR. The conformational bias of KOR binding different ligands is the 5



foundation for its physiological role. Herein, we intended to explore the conformational equilibria of KOR lead by agonist and antagonist binding. Moreover, identification of intermediate states of conformational ensemble may facilitate the development of more effective and selective ligands of KOR. Hence the long-time GaMD simulations were carried out. A rotation and displacement of transmembrane (TM) helix 6 is hallmark of GPCR activation27, hence we characterized the conformational changes of intracellular side of KOR by measuring the mass center distance (called D1) between the TM2 and TM6 intracellular end. The RMSD of transmembrane domain (TMD) of each system relative to the initial coordinate were used to characterize the conformational changes of KOR. The conformational spatial distributions of the six systems were obtained in the two dimensions (Figure 1, S2). To gain insight into the detailed structures of conformational change in each system, we carried out clustering analysis combined with the conformational ensemble distribution in the PMF (Figure 1). Each system was clustered into four clusters, which labeled in the PMF map. The representative structures are shown in Figure 2 and 3. The KOR*-apo show considerably conformational changes with the wider RMSD distribution (~1.3 Å – ~3.2 Å) compared to KOR*-MP1104 (~1.1 Å – ~2.5 Å) (Figure 1A, B, S3A). D1 decreases during the simulation of KOR*-apo and stabilizes at about 23 Å after about 650 ns (Figure 1A, S4A). Compared to D1 (D1 ≥ 25 Å) of KOR*-NB and KOR*-MP1104-NB (Figure S4B), the main stable state of KOR*-apo is an intermediate (I) between the active and inactive states. It can be seen in Figure 2A, the intracellular 6


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domain (ICD) of KOR*-apo has significant conformational change, the TM6 shifts inward, TM5 deviates from TM6, TM7 and TM3 shift outward. At the extracellular side (Figure 2B), the TM6 and TM7 shift toward the helix core, which makes the entrance of active pocket slightly shrink. The D1 of KOR*-MP1104 fluctuates remarkably during the simulation (Figure S4A), active state is still the dominant conformation in our simulation scale (Figure 1B). As shown in Figure 2D, the extracellular domain (ECD) of KOR*-MP1104 is relatively stable, the main conformational change takes place on the intracellular side (Figure 2C). During the simulation, TM6 shifts inward (Figure 2C, S4A). Similarly, the intermediate (I) characterized by D1 appears in the KOR*-MP1104 (Figure 1, 2, S4A) as well, the D1 is about 23 Å. Therefore, agonist binding by itself is not sufficient to completely stabilize the active state of the KOR compared with KOR*-MP1104-BN (Figure S1, S4B). The RMSD (~1.1 Å – ~3.2 Å) of inactive KOR-apo has more notable fluctuation than KOR-JDTic (~1.0 Å – ~2.5 Å) (Figure 1C, 1D, S3C). Conversely, D1 of KOR-apo fluctuates steadily (Figure 1C, S4C), indicating the KOR-apo is more stable at the intracellular side. The lager RMSD and steady D1 indicate a significant ECD conformational change of KOR-apo. As shown in Figure 3A, we obtained a stable inactive state of ICD of KOR-apo. The extracellular end of TM7 shifts significantly outward, showing a striking open entrance of active pocket (Figure 3B, S6C). The D1 of KOR-JDTic slowly increases during the simulation. D1 reaches the value of representing the intermediate (I) similar in the KOR*-apo (D1 is about 23 Å) at around 7



1600 ns, but D1 decreases after a short period of time (Figure 1D, S4C). As seen in the Figure 3C, at the intracellular side, the TM6 shifts outward, the TM5 shifts toward TM6, the TM3 and TM7 shift inward. KOR-JDTic also presents the conformational state of intermediate (I) in intracellular side, with a minor energy basin (Figure 1D). Similar to the KOR*-MP1104, the ECD of KOR-JDTic stabilizes by the antagonist binding (Figure 3D). In general, the antagonist binding confers greater flexibility of ICD. The KOR-JDTic complex is not as stable as KOR-apo, but does not destroy the inactive conformation equilibria. The conformational changes shown in our results are consistent with the experimental results27-29. The most significant conformational changes in deactivation of GPCRs are that TM6 shifts inward, TM5 deviates from TM6, and TM7 shifts outward, and vice versa. By comparison of all systems, it can be seen that the active state of KOR apo form is not stable, spontaneously relaxes towards inactive conformation (Figure 1A, S4A). Agonist binding is not sufficient to completely stabilize the active state compared with the KOR*-MP1104NB (Figure 1B, S1). Agonist binding motivates conformational equilibrium towards active state. The inactive apo form is the naturally stable conformation, the open entrance of active site prepared for the binding of ligands. Antagonist binding confers flexibility of ICD, but does not destroy the inactive conformation equilibria. In addition, the intermediate (I) characterized by D1 (the D1 is about 23 Å) between the active and inactive states is the stable state of the KOR*-apo, the similar intermediate (I) characterized by D1 appears in the KOR*-MP1104 and KOR-JDTic (Figure 1B, 1D). 8


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The Conformational Equilibria Bias by Agonist and Antagonist Binding. As seen in Figure 1, the intermediate (I) characterized by D1 is the dominant conformation of KOR*-apo with a major energy basin, while is a minor energy basin in the conformational ensemble of KOR*-MP1104 and KOR-apo respectively. KOR*-apo, KOR*-MP1104 and KOR-JDTic sample in a wide conformational space characterized by D1. Therefore, the conformation equilibria and conformation bias take place upon agonist and antagonist binding. According the conformational dynamics of each system, we constructed a cartoon schematic of conformational equilibria of KOR. Figure 4 shows the conformational equilibria and conformational bias of KOR upon binding of agonist and antagonist. The inactive apo form is the most stable state, the open entrance of pocket accepts distinct effective molecules. While the active apo form is the most unstable state and relaxes to inactive state easily. Upon agonist binding, KOR mainly samples between the active state and the intermediate (I) state (Figure 1B, 2C, 4), the conformational equilibria mainly bias towards active state. Therefore, agonist binding enhances the probability for the downstream effectors binding. Otherwise, in case the antagonist occupies the active site, the KOR samples between the inactive state and the intermediate (I) state (Figure 1D, 3C, 4). This will result in a much lower probability of downstream effectors binding. The importance of the antagonist of KOR is that the antagonist occupies the active site and blocks agonist binding, so that blocks activation of KOR. The spontaneous relaxation of active receptor to the inactive conformation and the agonist-induced conformational dynamics have been observed in the β2-adrenergic 9



receptor, the MOR and the A2a adenosine receptor by long-time cMD or nuclear magnetic resonance (NMR) experiment30-34. Hence, it can be seen from the above analysis, the KOR samples in a wide conformational space (Figure 1, 4) upon binding of agonist or antagonist. The conformational changes of KOR are not the simple “on-off” switch induced by ligands, but present multiple conformational states and the conformational equilibria shifts upon ligands binding. Conformational Changes of the Key Motifs in Active Site. The binding of agonist or antagonist can lead to different conformational ensemble equilibria of KOR. The inactive apo form of KOR is very stable during the simulation, while the active apo form of KOR rapidly relaxes towards inactive state and stabilizes in the intermediate (I) in our simulation. Since the key conservative motifs and microswitch play key roles in the conformational activation of GPCRs35-40, we monitored the conformational changes of key motifs and microswitch during the simulation. TM3 is considered to be the hub of structure and function of GPCRs35. DYYNM motif on TM3 is critical to KOR structure rearrangement and directly participates in the ligand binding. By comparing the conformational changes of DYYNM motif of representative structures of the each system, the most significant conformational changes are Asp1383.32 and Asn1413.35 (Figure 5). As shown in Figure 5A, Asn1413.35 points to the outside of helix bundle in active state of KOR*-MP1104. Asn1413.35 points to the helix core in the stable intermediate (I) of KOR*-apo, as well as in the inactive states of KOR-apo and KOR-JDTic. Similarly, Asp1383.32 of KOR*10


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MP1104 shifts compared with the others. As can be seen in Figure 5B, Asp1383.32 shifts and Asn1413.35 rotates to the inactive state in the KOR*-apo during the simulation. TM3 shifts inward along with (Figure 5C). The active and inactive states of DYYNM motif revealed in the simulation are consistent with crystal structures of MOR41-43 and δ-opioid receptor (DOR)44, 45. Therefore, the conformation changes of Asp1383.32 and Asn1413.35 are crucial to initiate the conformational transition of KOR, and the importance of Asn1413.35 in the activation of KOR has been proved in a mutation experiment10. The CWxP motif of TM6 is considered to be a TM6 torsion switch46, 47, where the highly conserved Trp2876.48 plays a vital role in the activation of most rhodopsin-like GPCRs and is an essential residue of “transmission switches”48, 49. Trp2876.48 is located at the bottom of the active site, interacts directly with the ligand of KOR9, 10. As seen in the Figure 6A, 6B, 6C, in the active state of KOR*-MP1104, Trp2876.48 directs to TM3-TM5, and the indole ring is almost parallel to the membrane plane (Figure 6A, 6C), which is indicated in the activation of GPCRs46. In the intermediate (I) of KOR*-apo, as well as the inactive states of KOR-apo and KOR-JDTic, Trp2876.48 points to the helix core, and the axle of indole ring is in the direction of helix (Figure 6A, 6B, 6C). The deflection of Trp2876.48 is correlated with the rotation and displacement of intracellular end of TM6 (Figure 6A, 6B, S4). In the active site (Figure 6D), the piperidine ring of bulky agonist MP1104 forms steric hindrance with Asp1383.32, pushing Asp1383.32 away. The shift of Asp1383.32 results in the DYYNM motif significant shift, especially the rotameric transition of side chain of 11



Asn1413.35. The opposite side, the hydrophobic group of the PM1104, cyclopropylmethyl group, extends into the hydrophobic pocket at the bottom of the active site. The cyclopropylmethyl group hydrophobicity interacts with Trp2876.48. Simultaneously, the steric hindrance between them deflects the Trp2876.48. Once the agonist was removed in KOR*-apo, the Asp1383.32 shifts inward, the Asn1413.35 and Trp2876.48 deflects back toward the helix core (Figure 5B, 5C, 6A, 6C) as similar as the inactive state. Therefore, the active state of initial KOR*-apo is unstable and relaxes towards inactive state spontaneously during the simulation. Compared with agonist MP1104, the structure of antagonist JDTic is slim. In the KOR-JDTic, the abovementioned steric hindrances are missing, the Asp1383.32, Asn1413.35 and Trp2876.48 stay in the inactive state. The stable hydrogen bond formed between the Asp1383.32 and antagonist JDTic keeps the DYYNM motif in inactive state (Figure 6D, S7). Therefore, these results show that the DYYNM motif and CWxP motif trigger activation or deactivation of KOR. The bulky agonist MP1104 destroys the stable inactive state of DYYNM motif and CWxP motif, biases the conformation equilibria towards active conformation. The bulky architecture ligands are potential agonist of KOR. The DYYNM motif and CWxP motif should be considered in the discovery of more selective ligands of KOR. Conformational Changes of the Key Motifs of ICDs. At the intracellular side, Arg1563.50 of DRY motif on TM3, Tyr2465.58 of TM5 and Tyr3307.53 of NPxxY motif on TM7 point towards the helix core and close to each other, which is important for stabilizing 12


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active state of class A GPCRs38, 40. In the KOR*-apo and KOR*-MP1104 (Figure 7A, B), the contacts of the three residues are not stable. Tyr3307.53 rotates and transits to inactive state, and stabilizes in the inactive state of the two systems after about 400 ns and 750 ns respectively (Figure 7A, 7B, S8C, S8D). The side chain of Arg1563.50 of KOR*-apo is unstable during the simulation, and stabilizes in inactive state after about 1300 ns (Figure 7A, S8A). In KOR*-MP1104, the side chain of Arg1563.50 transitions between active and inactive states during the simulation (Figure 7B, S8A). Therefore, the intracellular conformation of the KOR upon agonist binding is not fully stabilized, only when the binding of downstream effector (Figure S2). In the KOR-apo and KOR-JDTic complexes (Figure 7C, 7D, S8B, S8D), the inactive states of the three residues maintain stability as initial states. Hence, it can be seen that the upstream critical motifs trigger the activation or inactivation of KOR, the intracellular critical motifs stabilize active or inactive state. The Stabilization of ICD of Stable Intermediate (I). The last question is that stable intermediate (I) of KOR*-apo, appears in the KOR*-MP1104 and KOR-JDTic with minor basins (Figure 1B, D). In order to explore how the intermediate (I) is stable, we extracted the intermediate (I) structures of the KOR*-apo, KOR*-MP1104 and KOR-JDTic respectively, superimposed and compared with the active and inactive crystal structures. As shown in Figure 8A, the conformations of ICDs of the intermediate (I) are very similar between the KOR*-apo, KOR*-MP1104 and KOR-JDTic. Obviously, the conformation of intermediate (I) is between the active state and the inactive state. Similarly, we focused on the critical motifs of stabilizing active or inactive state of KOR to reveal the stabilization 13



of intermediate (I). As mentioned above, the critical residue Arg1563.50 is not unstable in the KOR*-apo and KOR*-MP1104. Tyr3307.53 stabilizes in inactive state after a period of simulation. It should also be noted that the behavior of Tyr2465.58 of TM5 is different. In KOR*-apo and KOR*MP1104, Tyr2465.58 is always stretching to the helix core (Figure 7A, 7B), while Tyr2465.58 of KOR-apo and KOR-JDTic are deflected towards outside of the helix bundle (Figure 7C, 7D). Even in the similar intermediates (I) (Figure 8B), Tyr2465.58 always maintains a conformation similar to their initial state. We inferred that the conformation change of Tyr2465.58 is the barrier for the conformation transition of ICD between active and inactive states. The mutation and NMR spectroscopy experiments also proved that the conserved Tyr2465.58 plays different roles in the activation and G-protein interaction of Rhodopsin50, 51.

We further analyzed the interactions of Tyr2465.58 with the around residues. As shown in Figure 8C and 8D, the hydrophobic center formed by residues Leu2756.36-Val2766.37Leu2776.38-Val2786.39-Val2796.40-Val2806.41 on TM6 interacts with Tyr2465.58. The stretched bulky side chain of Tyr2465.58 forms steric hindrance with the hydrophobic center of TM6. The hydrophobic interactions and steric hindrance between them limit the rotameric transition of Tyr2465.58. Consequently, the TM5 and TM6 of ICD hardly further move whether it is a transition to active state or inactive state. The other abovementioned key motifs stabilizes readily in inactive state in KOR*-apo (Figure 7A), Try2465.58 maintains active state in our simulation. Therefore, the intermediate (I) is stabilized. The 14


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rotameric transition of Tyr2465.58 is energy barrier of the conformation transition between active and inactive states of KOR. CONCLUSIONS In this work, we carried out long-time GaMD simulations with different initial states of KOR to investigate the conformational dynamics and conformational ensemble equilibria upon binding of different ligands. We found that the KOR is not in a single conformational state upon binding agonist or antagonist, but rather samples in different conformational ensembles. The agonist binding biases the conformation equilibria towards active state. The antagonist occupies the active pocket of KOR, and will not destroy inactive conformation equilibria. The simulation results indicate that the inactive apo form of KOR is the most stable state, while the active apo form is unstable state. The key motifs including DYYNM motif and CWxP motif transit towards and stabilize in inactive state in the KOR*-apo, thus allowing the intracellular conformation transitions to inactive state. Agonist binding stabilizes the active state of the ECD, while by itself is not sufficient to completely stabilize the active conformation of the ICD. Moreover, the crucial residues Asp1383.32, Asn1413.35 of DYYNM-motif and Trp2876.48 of CWxP-motif closely relate to trigger activation and deactivation of KOR. These results also yielded a stable intermediate (I) in KOR*-apo. The interactions between Tyr2465.58 of TM5 and the hydrophobic residues of TM6 as well as the steric hindrance between them stabilize the intermediate (I), limiting further conformational transitions of intracellular side of TMs. The revealed key motifs participating activation and deactivation of KOR and the stable intermediate (I) may 15



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facilitate the development of more selective ligands of KOR. MATERIALS AND METHODS Preparation of Simulation Systems. As a starting point for the simulations, we used the crystal structures of human KOR in complex with antagonist JDTic, agonist MP1104 (Figure S1) and an active-state-stabilizing nanobody (NB) as the initial coordinates respectively. The crystal structures were obtained from the PDB database (PDB codes: 4DJH, 6B73)9, 10. The chain A of inactive-state KOR-JDTic complex (hereafter called KOR-JDTic) and the chain B of active-state KOR-MP104 complex (hereafter called KOR*-MP1104) were selected, the mutational residues were mutated back. The lysozyme, soluble cytochrome B-562 and solvate molecules were omitted except the water molecules. The missing residues of KOR-JDTic (Ser262, Thr302-Thr306) and KOR*-MP1104 (Arg202-Asp206, Leu259-Gly261, Ser301-His304, Glu335-Phe346) were built by Schrodinger 201552,

53

respectively. The missing residues of KOR*-MP1104 were built

according the refined structure of 5C1M42 extracted from the GPCRdb54,

55,

since the

RMSD is 0.66 Å by aligning the crystal structures of 6B73 and 5C1M. Finally, we built six systems including the inactive initial states KOR-apo (omitted JDTic) and KOR-JDTic, active initial states KOR*-apo (omitted MP1104 and nanobody), KOR*-MP1104 (omitted nanobody), KOR*-NB (omitted MP1104) and KOR*-MP1104-NB. The membrane around the transmembrane domain (TMD) of KOR was built by 85 Å x 85 Å POPC using CHARMM-GUI web server56-58, the receptor crystal structure prealigned in the OPM (Orientations of Proteins in Membranes) database59. Each system was 16


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solvated by 12 Å with a truncated rectangular box of TIP3P water60 and neutralized to a concentration of 0.15 M NaCl. The proteins were modeled using the AMBER FF14SB force field61, the ligands were modeled using the generalized AMBER force field (GAFF)62, and the LIPID11 force filed63 was utilized for POPC. Geometry optimization and the electrostatic potential calculations on the ligands were performed at the HF/6-31G* level in the Gaussian09 software64. The partial charges were calculated with the RESP65. The force field parameters for the ligands were created by the Antechamber package. Gaussian Accelerated Molecular Dynamics (GaMD) Simulations. Gaussian accelerated molecular dynamics (GaMD)18 is an enhanced sampling method of biomolecules by adding a harmonic boost potential to smoothen the system potential energy surface, which enables unconstrained enhanced sampling and free energy profiles obtained from reweighting of the GaMD simulations without the need to set predefined reaction coordinates. GaMD has been successfully applied on the simulation of biomolecules, investigating of protein folding, dissociation and binding of ligands, and ligand-dependent conformational changes of the GPCRs18, 23, 24, 26. In the present study, we used Amber16 software and a GaMD patch to simulate the conformational dynamics of the KOR. Before GaMD simulation, the energy minimization and equilibration were conducted in order to equilibrate the systems. Firstly, to remove bad contacts in the initial structures, the steepest descent and the conjugated gradient methods were carried out. After energy minimization, each system was gradually heated in NVT ensemble from 0 to 300 K in 300 ps. Subsequently, constant temperature equilibration at 17



300 K for a total of 5 ns was performed to adjust the solvent density. Finally, 100 ns conventional molecular dynamic simulations (cMD) were carried out for each system in NPT ensemble with periodic boundary conditions; an integration step of 2 fs was used. The Particle Mesh Ewald (PME) algorithm66 was employed to treat long-range electrostatic interactions, while the non-bonded interactions were calculated based on a cutoff of 10 Å. The SHAKE algorithm67 was applied to constrain all covalent bonds involving hydrogen atoms. The final structures from abovementioned cMD were used in the GaMD simulations. Initially, 𝜅0 = 1.0, σD = 6, σV = 6. The GaMD simulations included 10 ns short cMD simulation used to collect potential statistics (𝑉𝑚𝑎𝑥 and Vmin) for calculating the GaMD acceleration parameters, 50 ns equilibration after adding the boost potential, and finally 2000 ns dual-boost GaMD production produced with randomized initial atomic velocities for each system.

ASSOCIATED CONTENT Supporting Information The structures of agonist MP1104 and antagonist JDTic, the conformational space distribution of the KOR*-NB and KOR*-MP1104-NB, the conformation dynamics of KOR binding with different ligands

AUTHOR INFORMATION Corresponding Authors *E-mail: [email protected]; Phone: +86-931-891-2578. 18


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*E-mail: [email protected]; Phone: +86-931-891-2582. Author Contribution H. L. and X. Y. conceived the project. X. A., Q. B., S. Z. and D.S. performed the molecular dynamics simulations, and analyzed the data. X. A. and X. Y. wrote and reviewed the manuscript. Z.B. contributed to provide computing resources. Funding This work was supported by the National Natural Science Foundation of China (Grant Nos. 21475054, 2175060). Notes The authors declare no competing financial interest.

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FIGURE CAPTIONS Figure 1. The PMF distribution between the RMSD of TMD of KOR and the center mass distance between the TM2-TM6 intracellular ends (A: KOR*-apo, B: KOR*-MP1104, C: KOR-apo, D: KOR-JDTic). Figure 2. The representative structures of KOR*-apo (A, B) and KOR*-MP1104 (C, D). Figure 3. The representative structures of KOR-apo (A, B) and KOR-JDTic (C, D).

Figure 4. The cartoon diagram of conformation equilibria of KOR upon binding with agonist and antagonist. Figure 5. The conformation changes of DYYNM motif on TM3. A: The representative structures of each system (cyan: KOR*-apo, pink: KOR*-MP1104, blue: KOR-apo, gold: KOR-JDTic); B, C: The represent structures of KOR*-apo. Figure 6. The conformation changes of CWxP motif on TM6. A, B: The dihedral of N of Thr2886.49 and C, CA, CB of Trp2876.48 evolves over time. C: The conformation changes of representative structures of each system. D The active site of representative structures 24


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of KOR*-MP1104 and KOR-JDTic Figure 7. The conformation changes of DRY motif, Tyr2465.58, Tyr3307.35, A: KOR*-apo, B: KOR*-MP1104, C: KOR-apo, D: KOR-JDTic. Figure 8. The stable intermediates (I) of KOR*-apo (cyan), KOR*-MP1104 (pink) and KOR-JDTic (gold) (The 4djh represented in white, 6b73 represented in gray). (A) The conformations of ICD of the stable intermediate (I). (B, C, D) The conformation variants of Tyr2465.58 in the stable intermediate (I).

Figure 1

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Figure 2 26


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Figure 3

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Figure 4

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Figure 6

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Graphical Table of Contents

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How Does Agonist and Antagonist Binding Lead to Different

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