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. 2025 Mar 17;147(12):10129–10138. doi: 10.1021/jacs.4c14293

CXC Chemokine Ligand 12 Facilitates Gi Protein Binding to CXC Chemokine Receptor 4 by Stabilizing Packing of the Proline–Isoleucine–Phenylalanine Motif: Insights from Automated Path Searching

Xinyu Li a, Yezhou Liu b, Jinchu Liu a, Wenzhuo Ma a, Rujuan Ti a, Arieh Warshel c,*, Richard D Ye b,d,*, Lizhe Zhu a,*
PMCID: PMC11951141  PMID: 40096846

Abstract

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The activation of G protein-coupled receptors (GPCRs) is a complex multibody multievent process involving agonist binding, receptor activation, G protein coupling, and subsequent G protein activation. The order and energetics of these events, though crucial for the rational design of selective GPCR drugs, are challenging to characterize and remain largely underexplored. Here, we employed molecular dynamics simulations and our recently developed traveling salesman-based automated path searching (TAPS) algorithm to efficiently locate the minimum free-energy paths for the coupling events of the CXC chemokine receptor 4 (CXCR4) with its endogenous ligand CXC chemokine ligand 12 (CXCL12) and Gi protein. We show that, after overcoming three low energy barriers (3.24–6.89 kcal/mol), Gi alone can precouple with CXCR4 even without CXCL12, consistent with previous reports on the existence of the apo CXCR4-Gi complex and our NanoBiT experiments. The highest barrier of 6.89 kcal/mol in this process corresponds to the packing of the proline–isoleucine–phenylalanine (PIF) motif of CXCR4. Interestingly, without Gi, CXCL12 alone cannot activate CXCR4 (high barrier of 18.89 kcal/mol). Instead, it can enhance Gi coupling by circumventing the energy barrier of PIF packing. Shedding new light on the activation mechanism of CXCR4, these results present TAPS as a promising tool for uncovering complete activation pathways of GPCRs and the corresponding agonist design.

1. Introduction

G protein-coupled receptors (GPCRs), also known as seven-transmembrane domain receptors, can detect molecules outside the cell and transmit the extracellular signal into the cell through coupling with G proteins.1 The human GPCR family is divided into four major classes based on their amino acid sequences and structural features: class A (rhodopsin family), class B (secretin and adhesion family), class C (glutamate family), and class F (Frizzled family) subfamilies. Over 800 genes in the human genome are found expressing GPCRs, and over 500 GPCR drugs target class A GPCRs. Biochemical and biophysical data have demonstrated that GPCRs are inherently flexible and dynamic proteins. Their activation is a complex multibody and multistep process that involves a series of intermediate conformational states,2−5 including agonist binding, receptor activation, G protein coupling, and subsequent G protein activation.6−8 A general idea (Figure 1A) is the ligand prebinding model9 that the agonist initially binds to a GPCR, inducing the GPCR to shift its conformation toward the activated state where the cavity on the cytoplasmic side was opened for G protein binding. Upon the G protein couples to the receptor, the nucleotide-binding pocket lying between the Ras-homology domain (RHD) and the α-helical (AH) domain opens to release the GDP and receives GTP. However, experimental10−12 and computational results13 have revealed that most potent agonists alone cannot stabilize GPCRs in their fully active conformation. Moreover, existing structures of the GPCR-G protein complexes,14−17 as well as previous computational17,18 and experimental studies,19−21 have pointed out that G proteins can couple with the GPCRs even in the absence of agonists. Based on these findings, a second model, G protein precoupling model18,22 (Figure 1B), has been proposed, which suggests that G protein may first bind to GPCR, leading to an intermediate state of the receptor-G protein complex, to which the agonist may bind and then propagate to full activation. In other words, the G protein can couple to the GPCR without the help of an agonist. To the best of our knowledge, no systematic comparison between these two models for GPCR activation has been conducted to date.

Figure 1.

Figure 1

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Two modes of the activation process of class A GPCRs: (A) ligand prebinding model; (B) G protein precoupling model.

Structural biology techniques typically can provide high-resolution atomistic structures for only an inactive state (bound to antagonists) or a fully active state (bound to agonists and G proteins). However, it is difficult for them to capture intermediate states, particularly the critical, short-lived transition state, which represents the highest energy point along the reaction coordinate and acts as a critical “bottleneck” for the transition between two stable intermediate states. Characterizing the transition state and its associated free-energy barriers is essential for advancing our understanding of GPCR activation mechanisms.6−8,23 For example, the energy barriers along the activation pathways of S1P receptors, which are activated by different agonists, provide insights into the agonist selectivity for specific S1P receptor subtypes.23

MD-based path searching methods can locate the minimum free-energy path (MFEP) of the transition process between the two states of interest, which is practical for identifying transition states, stable intermediate states, and their corresponding energy barriers along the transition process.24−29 Typically, path searching methods begin with an initial guess path for the transition process, defined in a specific coordinate space composed of a few preselected collective variables (CVs). Sampling is then conducted at each node along the path to explore low-energy conformations, followed by path reparameterization to reconstruct the path using these sampled low-energy states. Through iterative refinements, the path converges to the MFEP that is closest to the initial guess path. However, the efficiency of most path-based methods25−28 is limited by two key factors: (1) the preselection of CVs with well-defined physical meaning requires sufficient prior knowledge of the system and incorrectly defined CVs can result in tedious iterative input validation;30 (2) local sampling at each node leads to slow convergence of the path toward the MFEP.

To tackle these issues, our group developed the traveling salesman-based automated path searching (TAPS) algorithm,31 an all-atom MD simulation-based automated path searching approach. In TAPS, instead of choosing static CVs, path collective variables (PCVs)32 are employed as the temporary coordinate system for each iteration. PCVs require only a distance metric as input such as the root-mean-square deviation (RMSD) between any pair of conformations, thereby minimizing the need for prior knowledge about the system. Moreover, nonlocal perpendicular sampling at each node accelerates the search for low-free-energy conformations. TAPS has been successfully applied to the biomolecule systems of tens to hundreds of residues33−38 and particularly in the fine design of selective agonists for the sphingosine 1-phosphate receptor (S1PR) family (class A GPCRs),23 where we accurately evaluated the selectivity of agonist targeting distinct S1PR subtypes by selecting all the heavy atoms within the transmembrane helices and agonists to define PCV. This unbiased atom selection makes TAPS particularly suitable for studying class A GPCRs due to their conserved structural topology.39

CXC chemokine receptor 4 (CXCR4) belongs to the class A GPCRs, it is widely expressed in human tissue and plays an important role in diverse biological processes, such as angiogenesis,40 embryonic development,41 homing regulation of hematopoietic stem cells,42,43 metastasis,44−47 and immune cell chemotaxis toward its endogenous ligand CXC chemokine ligand 12 (CXCL12).48 In addition, CXCR4 also functions as a coreceptor for HIV-1 entry into CD4+ cells.49 Targeting CXCR4 has been proposed as a promising strategy in terms of CXCR4/CXCL12 signal related cancers,50 HIV,49 autoimmunity, as well as inflammation.51,52 Currently, three CXCR4 antagonists (Plerixafor, Mavorixafor, and Motixafortide) have been approved by the FDA, and three CXCR4 agonists (ATI-2341,53 NUCC-390,54 CTCE-021455) are under development. The crystal structures of CXCR4 bound to various antagonists have been resolved several years ago.56,57

Recently, we reported the Cryo-EM structure of the active state of CXCR4 bound to CXCL12.58 Compared to the inactive state, the fully active conformation of CXCR4 shows several common activation features that characteristic of most class A GPCRs59 involving the significant tilt of the helix 6 (H6), upward movement of the R1343.50(GPCRdb numbering60) in the DRY motif, the inward rotation of the Y3027.53 in the NPxxY motif, and packing of V1243.40, P2115.50, and F2486.44 residues (PIF motif). Additionally, we observed an intriguing structural difference in the reported CXCR4 structures (Table. S1). When the CXCR4 structure is resolved in complex with the Gi, residues Q233ICL3 to A2376.33 consistently adopt a helical conformation. But in the absence of the Gi, these residues display variability, with some adopting a helical structure, others forming a loop, or even being unresolved in the structures. However, the precise mechanisms underlying the conformational changes induced by CXCL12 binding or Gi coupling remain poorly understood.

In this work, we employed MD simulations combined with TAPS algorithm to explore the activation mechanism of CXCR4 in the G protein precoupling model and the ligand prebinding model. To explore the activation processes of the CXCR4 in the G protein precoupling model, we designed PathG (Figure S2A), where Gi couples to the CXCR4apo in the absence of CXCL12. To explore the activation process of CXCR4 in the general ligand prebinding model, we designed PathL (Figure S2B), where CXCL12 shifts the CXCR4apo to its fully active state without Gi, and PathLG (Figure S2C), where Gi couple to CXCR4 with exits of CXCL12. For each of these paths, the initial trajectory was generated using targeted molecular dynamics (tMD)61 and subsequently optimized using the TAPS method to locate the MFEP. Finally, umbrella sampling62 was employed to obtain the free-energy landscape along the MFEP, providing further insights into the energetics of CXCR4 activation. The free-energy landscape of PathG reveals that the Gi can precouple with CXCR4, forming a stable CXCR4-Gi complex that shifts CXCR4 into its active conformation, but must overcome a barrier of ∼6.89 kcal/mol for rearranging the PIF motif. NanoBiT assays and the recently reported apo CXCR4-Gi complex (PDB code: 8U4N) support the occurrence of precoupling events. By contrast, the free-energy landscapes of PathL and PathLG indicate that CXCL12 alone is insufficient to activate CXCR4. Instead, CXCL12 forms a stable complex with CXCR4, where the packing of the PIF motif is stabilized in a pure energy-releasing process. Consequently, energy consumption by subsequent Gi coupling for rearranging the PIF is no longer necessary. Overall, our study provides an atomistic description of CXCR4 activation in both the ligand prebinding and the G protein precoupling models and presents a valuable framework for investigating the activation mechanisms of other class A GPCRs.

2. Results

2.1. Gi Can Precouple to CXCR4 without CXCL12

To examine whether Gi alone can couple to CXCR4 and shift it to the fully active state before CXCL12 binds to the receptor, we evaluated the energetics of PathG, a transition process in which Gi couples to the inactive CXCR4apo to form the active CXCR4-Gi complex. To characterize the active state of CXCR4, we selected three conserved conformational changes typically observed in most class A GPCRs: (1) the tilt angle of H6, (2) the upward movement of R1343.50, and (3) the inward rotation angle of Y3027.53 (Figure S3). Along PathG, three energy barriers (5.87, 6.89, and 3.24 kcal/mol, Figure 2A) were identified, none of which are sufficiently high to prevent the transition. In other words, Gi can couple to inactive CXCR4apo to form the active CXCR4-Gi complex, even in the absence of CXCL12.

Figure 2.

Figure 2

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Analysis of PathG. (A) Free-energy landscape of PathG along the PCVs with the transparent bands denoting the errors. (B) Conformational change from InactiveG to Int_IG. (C) Conformational change from Int_IG to TS_IG. (D) Two different views of conformational change from Int_IIG to TS_IIG. (E) Conformational change from Int_IIIG to TS_IIIG. (F) Conformational change from TS_IIIG to Int_IVG. From panels (B–F), we show only the α5 helix of Gi for better visualization. (G) Conformation changes in detail. G-1 to G-3 correspond to the rectangular region in panels (B–D), respectively. (H) Schematic illustration of a NanoBiT-based Gi activation assay. NanoLuc was split into an SmBiT subunit and an LgBiT subunit. The SmBiT subunit was fused to the C-terminus of CXCR4, and the LgBiT subunit was attached to the Gαi protein. (I) The NanoBiT-based Gαi activation assay, involving coexpression of CXCR4-SmBiT and LgBiT-Gαi in HEK293 cells, unravels Gαi dynamics upon CXCL12 stimulation. Baseline NanoBiT signals were recorded for 5 min, followed by the addition of CXCL12 at varying concentrations. Readouts were collected for an additional 10 min. NanoBiT signal ratio data were normalized as (NanoBiT signal/average of baseline NanoBiT signal) from three independent experiments, each performed in duplicate, and are presented as the mean ± SEM. (J) Dose–response curve of CXCL12-induced Gαi dynamics from panel (I). The change in NanoBiT signal ratio was calculated as (average NanoBiT signal ratio after CXCL12 stimulation – average baseline NanoBiT signal ratio). Data were collected from three independent experiments, each in duplicate, and are presented as the mean ± SEM.

To elucidate the mechanism of this transition, we analyzed the structural changes for each intermediate state in detail. First, the free-energy curve decreases until Int_IG, where the α5 helix of the Gαi protein moves closer to ICL3 and H6 of CXCR4 (Figure 2B). This movement is driven by electrostatic attraction between the positively charged residues K2346.30 and K2366.32 and the negatively charged residue F354Giα (Figure 2G-1, Figure S4A). Consequently, this induces a partial tilt of H6 (Figure S3A, Table S7). Following this, a moderate energy barrier (5.87 kcal/mol) exists between Int_IG and TS_IG. At this stage, the structural part of H6 shows a downward movement (Figure 2C). However, hydrophobic residue L353 in Gi approaches hydrophilic residues K2346.30 and K2366.32 (Figure 2G-2), which push the upward movement of the intracellular loop 3 (ICL3) and unstructured part in H6. As a result, these face-to-face movements compact H6 on the cytoplasmic side, leading to the formation of a helical structure from R2356.31 to A2376.33 in Int_IIG (Figure S4D). Next, another moderate energy barrier (6.89 kcal/mol) is observed from Int_IIG to TS_IIG. During this phase, a synergetic rearrangement appearing between P2115.50, V1243.40, and F2486.44 (PIF motif) makes the F2486.44 close to P2115.50 and V1243.40 (Figure 2G-3, Figure S4B), which initiate the outward swing of the cytoplasmic part of H6 (Figure 2D). Then, the Y3027.53 could move deeper into the inner side of CXCR4. Finally, there is a small energy barrier (3.24 kcal/mol) between Int_IIIG and TS_IIIG, corresponding to the upward movement of R1343.50. The activation features in TS_IIIG (Figure 2E, Figure S4C) indicate the fully activated state of CXCR4, wherein the Gi can fully couple to CXCR4 (Figure 2F).

To validate our computational finding that Gi can couple to CXCR4 in the absence of CXCL12, we conducted a NanoBiT-based Gαi activation assay. In this assay, a SmBiT subunit of NanoLuc was fused to the C-terminus of CXCR4, and an LgBiT subunit was attached to the Gαi (Figure 2H). This setup allowed us to monitor the relative distance between the C-terminus of CXCR4 and Gαi through bioluminescence signal amplitudes, with stronger signals indicating closer proximity between the two proteins. The NanoBiT-based Gαi activation assay enabled us to track the changes in a distance between CXCR4 and Gαi during receptor activation. Initially, a strong bioluminescence signal indicated that Gαi is close enough to CXCR4. Upon ligand addition, the distance between CXCR4 and Gαi increases rapidly (Figure 2I), demonstrating concentration-dependent dissociation of Gαi from CXCR4 that increased with higher CXCL12 concentrations (Figure 2J). Furthermore, the recently resolved structure of the apo CXCR4-Gi complex (PDB code: 8U4N) also indicates that the Gi can couple to CXCR4 in the absence of CXCL12. Collectively, these experimental results support our computational findings, confirming that Gi can couple with CXCR4 and without the presence of the CXCL12.

2.2. CXCL12 Stabilizes CXCR4 in an Intermediate State

Generally, it has been assumed that the agonists bind to GPCRs and shift their equilibrium to an active state, which shows the remarkable tilt of H6 and the expansion of intracellular region to facilitate recruitment of the G protein. To examine whether CXCL12 alone could shift CXCR4 to its fully active state in the absence of Gi, we evaluated the energetics of PathL (Figure 3A). Similarly, we selected three features, the same as PathG to define the active state of the CXCR4. Along PathL, a remarkable energy barrier (18.89 kcal/mol) is observed between Int_IL and TS_IL, corresponding to the significant tilt of helix 6 (Figure 3C), which is an activation feature of the CXCR4. However, such a high barrier indicates that the activation of CXCR4 by CXCL12 alone is difficult. Additionally, the high energy difference (12.14 kcal/mol) between Int_IL and Int_IIL indicates the instability of Int_IIL, which is consistent with previously experimental10−12 and computational results13 that the agonist alone cannot stabilize GPCR in its fully active conformation. Consequently, without Gi, CXCL12 alone cannot fully activate CXCR4; instead, it binds to CXCR4 and then stabilizes in the Int_IL state, awaiting coupling of Gi.

Figure 3.

Figure 3

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Analysis of PathL. (A) Free-energy landscape of the PathL along the PCVs with the transparent bands denoting the errors. (B) Two different views of conformational change from InactiveL to Int_IL. InactiveL is the last frame generated from the initial path of the PathL. (C) Conformational change from Int_IL to TS_IL. (D) Conformational change from Int_IIL to ActiveL. (E) Conformation changes in detail. E1–E3 correspond to the rectangular region in panels (B–D), respectively.

To elucidate the conformational changes of CXCR4 induced by CXCL12, we analyzed the key intermediate states in detail. We observed that the energy curve decreases to the Int_IL as CXCL12 penetrates deeper into the binding pocket. Specifically, V3 of CXCL12 induces a downward movement of Y2556.51, which in turn pushes W2526.48 downward, subsequently triggering the outward movement of F2486.44 (Figure 3E-1). Additionally, R12CXCL12 interacts with D1935.32 and E2686.64 (Figure 3E-2), inducing the packing of helices H5 and H6 (Figure 3B, Figure S5A). This interaction brings P2115.50 closer to F2486.44 (Figure 3E-3, Figure S5B). These conformational changes lead to the synergistic rearrangement of the PIF motif (P2115.50, V1243.40, and F2486.44), initiating a partial tilt of H6 (Figure S3B, Table S7). Interestingly, this free-energy-decreasing rearrangement of the PIF motif contrasts with the second energy barrier in PathG. The previous experiment63 has shown that mutation of R12E in CXCL12 significantly decreases downstream signaling, also highlighting the importance of R12CXCL12. In addition, we found that although the residues R2356.31 to A2376.33 in ActiveL show a helical structure (Figure 4D, Figure S5D), they exhibit nonhelical structure in the transition from InactiveL to Int_IIL (Figure S5D). However, in PathG, these five residues form a stable helical structure in Int_IIIG with the assistance of the Gi, suggesting that the Gi may contribute to the formation of the helical structure on the cytoplasmic side of H6.

Figure 4.

Figure 4

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Analysis of PathLG. (A) Free-energy landscape of PathLG along the PCVs with the transparent bands denoting the errors. (B) Conformational changes from InactiveLG to Int_ILG. (C) Conformational change from Int_ILG to TS_ILG. (D) Conformational changes from Int_IVLG to TS_IVLG. (E) Conformational change from TS_IVLG to Int_VLG. (F) Conformation changes are shown in detail. F1 and F2 correspond to the rectangular region in panels (B) and (C), respectively. We only show the α5 helix of Gi for better visualization.

2.3. CXCL12 Stabilizes Packing of the PIF Motif to Facilitate Gi Coupling

PathL verified that CXCL12 can partially activate CXCR4 by inducing the tilt of H6, stabilizing CXCR4 in Int_IL rather than shifting it completely to its fully active state. This observation led us to hypothesize that this partial tilting of H6 could facilitate Gi coupling more effectively. To test this hypothesis, we evaluated the energetics of PathLG. Compared to PathG, we observed only two moderate energy barriers (5.66 and 3.57 kcal/mol) in PathLG (Figure 4A), indicating that the partial activation of CXCR4 induced by CXCL12 decreases the energy barrier for subsequent Gi coupling. Similarly, compared to PathL, PathLG significantly decreases the energy barrier for CXCR4 activation, indicating that Gi is necessary for the full activation of CXCR4.

To clarify the process that the Gi couples to the CXCR4-CXCL12 complex, we analyzed the key conformational states in detail. Initially, the free-energy curve decreases until it reaches the Int_ILG state, where the hydrophobic residue L353Gαi in the α5 helix of the Gαi moves closer to the ICL3 and H6 of CXCR4. This interaction causes L353Gαi to push the hydrophilic residue Q233ICL3 (Figure 4F-1), inducing a tilt of H6 (Figure 4B). Subsequently, there is an energy barrier (5.66 kcal/mol) between Int_ILG and TS_ILG, corresponding to the formation of a helical structure in residues Q233ICL3 to A2376.33 (Figure 4C, Figure S6B). This conformational change is driven by the electrostatic attraction between the positively charged residues H232ICL3 and K2366.32 and the negatively charged residue F354Gαi (Figure 4F-2, Figure S6A). From Int_IILG to Int_IVLG, there is no significant energy barrier during these transitions, suggesting that the complex may fluctuate between these states (Figures S6B and S7). In the TS_IVLG state, the upward movement of R1343.50 (Figure S6B) signifies that CXCR4 has reached its fully activated conformation. This structural change allows Gi to fully couple to CXCR4 in the subsequent Int_VLG state (Figure 4E).

3. Discussion

Most previous studies on GPCR activation5,64,65 have focused only on receptor activation by the agonist, without considering the effects of the G protein. Here, we investigate the activation of not only the receptor but also the subsequent G protein coupling, using the CXCL12-CXCR4-Gi complex as a model system. The highest energy barriers observed in PathG (6.89 kcal/mol) and PathLG (5.66 kcal/mol) are relatively similar, suggesting that CXCR4 activation may involve both paths. The activation paths that CXCR4 follows depend on the sequence of CXCL12 binding and Gi coupling. PathG aligns with the Gi precoupling model, in which Gi alone can precouple with CXCR4, shifting CXCR4 to its fully active state. Conversely, PathL and PathLG follow the ligand prebinding model with a slight variation that CXCL12 binding alone does not fully stabilize CXCR4 in its active conformation, and Gi coupling is still required for complete activation. The role of CXCL12 is to bind to CXCR4 to form a stable CXCL12-CXCR4 complex (Int_IL). This complex circumvents the secondary energy barrier observed in PathG by stabilizing the packing of the PIF motif, thereby facilitating subsequent Gi coupling. Moreover, Gi plays a critical role in CXCR4 activation by pushing the H6 helix outward, shifting R1343.50 upward, and stabilizing the helical structure within the region of Q233ICL3–A2376.33. These structural changes collectively facilitate receptor activation. In addition, as shown in Table S4, rather than selecting specific atoms to define the PCVs, we adopt an unbiased selection of atom set, which is generalizable to other chemokine receptors and G proteins due to their similar structural topologies66,67 and potentially to the study of the activation of all class A GPCRs. These results present TAPS as a promising approach in boosting a comprehensive understanding of the activation mechanisms of class A GPCRs.

Despite the aforementioned merits, our results remain limited and warrant further investigation. First, the NanoBiT assay employed in this study does not directly validate the free-energy landscapes associated with the activation process of CXCR4. For example, it does not provide direct insights into the free-energy changes related to packing of the PIF motif. Future studies via techniques such as nuclear magnetic resonance (NMR)68−70 could be necessary to examine the subtle conformational changes and the corresponding energetics found in the present work. Second, we note that the full activation of GPCRs involves not only the activation of the GPCR but also the activation of G protein. In addition to the role of CXCL12 binding in facilitating Gi coupling, our finding that Gi can precouple with CXCR4 even in the absence of CXCL12 point to the potential role of CXCL12 binding to Gi activation, which has not been covered in the present work but worth further studies. Previous computational analyses71 have demonstrated that the β2-adrenergic receptor (β2AR) exhibits distinct effects on the opening of the AH and RHD depending on whether it is bound to an agonist, a reverse agonist, or is in an apo state. However, how different ligands induce these effects remain unclear. In the future, we shall further investigate the activation process of Gi to elucidate this potential effect of CXCL12 binding. Third, biased signaling, where distinct ligands binding to a GPCR preferentially activate specific signaling pathways, such as the G protein or β-arrestin pathways, presents significant potential for the development of safer and more effective drugs. In the context of CXCR4, both the K1R mutant72 of its endogenous ligand CXCL12 and the synthetic agonist ATI-234173 exhibit bias toward G protein-coupled signaling. Despite these findings, the structural basis of this biased signaling is poorly understood. Our future research will focus on uncovering the molecular mechanisms driving these conformational changes, thereby providing crucial insights into biased signaling and its potential applications in drug development.

4. Conclusions

In this study, we applied all-atom molecular dynamics simulations and our recently matured automated path searching method (TAPS) to reveal the detailed energetics and order of events for the activation of CXCR4 by its natural agonist CXCL12. Consistent with previous findings and our NanoBiT experiments, our calculations show that the Gi protein can precouple with CXCR4 in the absence of CXCL12. To achieve such precoupling, Gi only needs to overcome three low energy barriers (3.24–6.89 kcal/mol), where the highest barrier corresponds to the packing of the PIF motif. In addition, the binding of CXCL12 alone cannot activate CXCR4 due to a substantial energy barrier (18.89 kcal/mol); it facilitates Gi coupling through bypassing the barrier for PIF packing. These detailed mechanistic insights demonstrate not only the power of TAPS in dissecting the multievent process of GPCR activation but also its potential for guiding the rational design of GPCR agonists.

Acknowledgments

This work was supported by National Natural Science Foundation of China Projects 32471296 (L.Z.) and 32070950 (R.D.Y.) and Science, Technology, and Innovation Commission of Shenzhen Municipality Projects JCYJ-2020010915-0003938 (L.Z.), RCYX20200714114645019 (L.Z.), and GXWD2020123115722002-20200831175432002 (L.Z. and R.D.Y.). L.Z. was also supported in part by a Presidential Fellowship. This work is supported by the Warshel Institute for Computational Biology funding from Shenzhen City and Longgang District (LGKCSDPT2024001). This work is also supported by National Key R&D Program of China grant 2019YFA0906003 (R.D.Y.), Yunnan Key Research and Development Program grant 202402AA310032 (R.D.Y.), Shenzhen Medical Research Fund SMRF-D2403009 (R.D.Y.), the Kobilka Institute of Innovative Drug Discovery at The Chinese University of Hong Kong, Shenzhen. (R.D.Y.), the Ganghong Young Scholar Development Fund (R.D.Y.), and Shenzhen-Hong Kong Cooperation Zone for Technology and Innovation grant HZQB-KCZYB-2020056(R.D.Y.). X.L. was supported by the Ganghong Young Scholar Development Fund at The Chinese University of Hong Kong, Shenzhen.

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/jacs.4c14293.

  • Simulation methods and supplementary results(PDF)

Author Contributions

§ X.L. and Y.L. contributed equally to this work

The authors declare no competing financial interest.

Supplementary Material

ja4c14293_si_001.pdf (3.3MB, pdf)

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