Molecular Mechanism regarding Allosteric Modulation of Ligand

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Molecular Mechanism regarding Allosteric Modulation of Ligand Binding and the Impact of Mutations on Dimerization for CCR5 Homodimer Fuhui Zhang, Yuan Yuan, Minghui Xiang, Yan-Zhi Guo, Meng-Long Li, Yijing Liu, and Xue-Mei Pu J. Chem. Inf. Model., Just Accepted Manuscript • DOI: 10.1021/acs.jcim.8b00850 • Publication Date (Web): 28 Jan 2019 Downloaded from http://pubs.acs.org on January 29, 2019

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Molecular Mechanism regarding Allosteric Modulation of Ligand Binding and the Impact of Mutations on Dimerization for CCR5 Homodimer Fuhui Zhang a, Yuan Yuanb, Minghui Xiang a, Yanzhi Guo a, Menglong Li a,Yijing Liuc Xuemei Pu a,* a College

of Chemistry, Sichuan University, Chengdu, 610064, People’s Republic of

China b

College of Management, Southwest University for Nationalities, Chengdu 610041,

People’s Republic of China c College

of Computer Science, Sichuan University, Chengdu, 610064, People’s

Republic of China

* [email protected]

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Abstract In this work, we combined accelerated molecular dynamics (aMD) and conventional molecular dynamics (cMD) simulations coupled with the potential of mean force (PMF), correlation analysis, principal component analysis (PCA) and protein structure network (PSN) to study the effects of dimerization and the mutations of I52V and V150A on the CCR5 homodimer, in order to elucidate the mechanism regarding cooperativity of the ligand binding between two protomers and to address the controversy about the mutation-induced dimer-separation. The results reveal that the dimer with interface involved in TM1, TM2, TM3 and TM4 is stable for the CCR5 homodimer. The dimerization induces an asymmetric impact on the overall structure and the ligandbinding pocket. As a result, the two protomers exhibit an asymmetric binding to the maraviroc (one anti-HIV drug). The binding of one protomer to the drug is enhanced while the other is weakened. The PSN result further reveals the allosteric pathway of the ligand-binding pocket between the two protomers. Six important residues in the pathway were identified, including two residues unreported. The results from PMF, PCA and the correlation analysis clearly indicate that the two mutations induce strong anti-correlation motions in the interface, finally leading to its separation. The observations from the work could advance our understanding of the structure of the GPCR dimers and implications in their functions. Keywords: Accelerated molecular dynamics simulation; CCR5 dimer; ligand binding; mutations; PMF; protein structure network.

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1. Introduction G protein-coupled receptors (GPCRs) represent the most crucial target for therapeutic intervention and drug development due to its wide roles in many diverse cell response1. Recently, accumulating evidence has confirmed that GPCRs could form dimers or higher oligomers2,3, which significantly influence GPCR signaling process like receptor activation, internalization, ligand binding and coupling to G-protein3. For example, one protomer of the GPCR dimer binding to ligands or proteins would affect the binding of another protomer to ligands, presenting a positive or negative cooperativity between the two protomers4, 5. The cooperativity could modulate ligand pharmacology and trigger different signaling pathways. Thus, the oligomers are considered to be promising as novel targets6-8. However, unfortunately, there have been several oligomer structures resolved so far and the cooperativity mechanism between the protomers remains unclear. Chemokine receptors belong to one superfamily of GPCRs. They mediate cell responses to the extracellular levels of chemokines and play vital roles in immune systems involved in normal physiology, inflammatory and infectious diseases6, 7, for example, atherosclerosis, rheumatoid arthritis, asthma and cancer8-15. On the basis of the chemokine subclass ligand they bind, the chemokine receptors could be divided into four subtypes: C, CC, CXC and CX3C. Some chemokine receptors were already found to function as homo- or heterodimers or even oligomers of higher order in living cells1618.

CCR5, a member of the chemokine receptor, is a major co-receptor of HIV virus,

thus being an important drug target for the treatment of HIV19. Biochemical and energy transfer methods20 already demonstrated that CCR5 exist as dimers in cells. Its dimerization induced by the chemokines was considered to be crucial in impeding HIV1 infection. However, the mechanism has not been clearly elucidated.

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Although the crystal structure of monomeric human CCR5 bound to the marketed HIV drug maraviroc (4MBS) was determined in 201321, the crystal structure of dimeric CCR5 has not been available so far. Thus, there has been very limited knowledge about their structures and dynamics as well as functional implications, which result in many questions unanswered on experiments. For example, the results from fluorescence resonance energy transfer (FRET) experiments indicated that mutations of Ile52 in transmembrane region-1 (TM1) and Val150 in TM4 could block homo-dimerization for

CCR522,

23.

However,

observations

from

co-immunoprecipitation

and

bioluminescence resonance energy transfer (BRET) experiments reported that the two mutations didn’t reduce the formation of CCR5 dimers24, which was further supported by observations from size exclusion chromatograph25. The controversy is also attributed to the molecular nature of the issue while it is difficult for experimental techniques to detect microscopic changes of the large protein system in complicated environments. Molecular dynamics (MD) simulation is a powerful tool, through which we could observe the structural evolution and underlying dynamics of a protein at the atomic level. Thus, the computational tool has been successfully used to study structures and functions of some GPCRs26-31, including CCR532-35. However, previous MD studies mainly focused on the GPCR monomers to probe their structures, interactions between GPCRs and ligands, activation mechanisms and intramolecular water channel34-36, some of which were reported by our group26-28,

34.

The MD works of the CCR5

monomer also mainly concerned the interaction of CCR5 with ligands using conventional molecular dynamics (cMD) simulations. For example, some potential antagonists for CCR5 were identified through the molecular dynamic simulation and virtual screening37. The interaction mechanism between CCR5 and antagonist maraviroc was studied by the MD method35. However, there have been lack of MD

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studies on the CCR5 dimer. In addition, due to the limitation of simulation time, it is difficult for the conventional molecular dynamics to sample large conformation changes involved in biological functions, which generally occur in longer time scale than millisecond38. Accelerated molecular dynamics (aMD) is an effective method to enhance conformational sampling, in which the boost potential is added to the energy surface to decrease the energy barriers. Consequently, the transitions between the lowenergy states could be accelerated39-42. Compared to some other enhanced sampling techniques, one great advantage of aMD is that prior knowledge of the potential energy landscape is not required. The method has been successfully applied to study many protein systems43-47, including investigations on the activation mechanism, allosteric effect of sodium ion binding on the activation, free energy landscape and ligand binding for monomeric GPCRs. Based on all the considerations above, in the work, we combined the aMD and cMD methods to study the dimerization of CCR5. We especially concerned its impact on the ligand binding and effects of the Ile52 and Val125 mutations on the dimerization in order to address the controversial problems above. In additions, the potential of mean force (PMF) and protein structure network (PSN) methods were used to probe the allosteric mechanism between two subunits of the dimer and the mutation mechanism. Our observations reveal the cooperative modulation of the ligand-binding pockets between the two subunits and explain the asymmetric binding reported by experiments. In addition, our results clearly confirm the mutation-induced separation for the CCR5 dimer and reveal its separation process. 2. Materials and Methods 2.1 System preparation X-ray crystal structure of CCR5 was obtained from PDB bank (PDB ID: 4MBS).

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Rubredoxin, which was fused into CCR5 to replace intracellular loop 3 (ICL3) for crystallizing the complex structure, was removed and ligand was also omitted. Missing residues of ICL3 were repaired using Modeller 9.1648. The N-termini and C-termini of the chain were capped by neutral groups (acetylamide and methylamide). CCR5 monomer was constructed according to the X-ray crystal structure (labelled as CCR5 monomer). Wild type CCR5 dimer (labeled as CCR5wt) and mutated (I52V and V150A) CCR5 dimer (labeled as CCR5mut) were constructed using ROSETTA49, 50 based on the interaction interface of TM1-TM4/TM1-TM4, which was reported to play important role in the dimerization of CCR5 by experimental work22. With the aid of ROSETTA, the two monomeric receptors were firstly rigid docked, and then the side chain conformation was optimized and the backbone of the receptor was relaxed. The topranking one of all resulting conformations, which were ranked by the energy function, was selected as the initial structure of the CCR5 dimer. Two disulfide bonds (Cys1013.25 - Cys178ECL2, Cys20N-terminus - Cys2697.25) in the crystal structure were retained in the simulations. For the three systems constructed, we set all protein residues to the standard CHARMM protonation states at physiological pH. Then, the receptor was inserted into a palmitoyl-oleoyl-phosphatidyl-choline (POPC) bilayer and then solvated with TIP3P water model. The systems were neutralized at 0.15M NaCl using CHARMM-GUI51. Consequently, the CCR5 monomer system contains a total of 54033 atoms and the dimer system has 97905 atoms. 2.2 Molecular dynamics simulations Molecular dynamics (MD) simulations including the conventional MD (cMD) and the accelerated MD (aMD) were performed using Amber16 software52. The ff14SB forcefield53 was used for the receptor and lipid14 force-field was applied for the POPC lipids. To remove bad contacts, energy minimization was done in terms of four steps. First,

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the water molecules were energy minimized for 20000 steps with all other atoms fixed. Then, a 20000-step energy minimization was done for the POPC lipids, followed by the 20000-step minimization for the receptor. Finally, all the atoms were released in the 20000-step minimization. After the minimization, the system was heated from 0 K to 310 K within 250 ps and followed by a 5-ns NVT simulation for pre-equilibration at 310 K. Then, a 150-ns NPT simulation was performed at 1 atm pressure and 310 K temperature for each system. A cutoff distance of 10 Å was set for non-bonded interactions and the electrostatic interaction was computed via the particle mesh Ewald (PME)54 method. All hydrogen-containing bonds were constrained by the SHAKE algorithm55. 2-fs integration time-step was used for the MD simulations. 2.3 Accelerated molecular dynamics (aMD) simulations The aMD simulation was implemented in AMBER16 using the “dual-boost” version41. A non-negative boost potential was added to both dihedral angles and the total energy across all atoms in the three systems. In terms of eqns (1)-(2), the dihedral and total boost acceleration parameters were calculated: Edihed = 𝑉𝑑𝑖ℎ𝑒𝑑_𝑎𝑣𝑔 +λ × 𝑉𝑑𝑖ℎ𝑒𝑑_𝑎𝑣𝑔 ,𝛼dihed = λ × 𝑉dihed_avg/5 𝐸𝑡𝑜𝑡𝑎𝑙 = 𝑉𝑡𝑜𝑡𝑎𝑙_𝑎𝑣𝑔 +0.2 × 𝑁𝑎𝑡𝑜𝑚𝑠 , 𝛼𝑡𝑜𝑡𝑎𝑙 = 0.2 × 𝑁𝑎𝑡𝑜𝑚𝑠

(1) (2)

Where Natoms represents the total numbers of atoms, and Vdihed_avg and Vtotal_avg are the average dihedral and total potential energies, which were calculated from the 150 ns cMD simulations. λ is an adjustable acceleration parameter. Herein, λ=0.3 was used since the value was reported to be proper for enhanced sampling of GPCRs43, 56. The starting structure of aMD simulation was selected from the final structure of cMD simulation. Finally, a 1-s aMD simulation was performed for each system. 2.4 Free energy calculation As known, PMF could examine the changes of free energy as specific reaction

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coordinates in different systems. Thus, PMF profiles of the two CCR5 dimers (CCR5wt and CCR5mut) were calculated in term of two reaction coordinates selected: the centroid distance between two protomers of CCR5 dimer and the root-mean-squaredeviation (RMSD) of CCR5 dimer. Along the two reaction coordinates, the energy landscape could be calculated according to the following equation 3: A(𝜁𝐽,𝜁𝐼) = ― 𝑘𝐵𝑇ln (𝜌(𝜁𝐽,𝜁𝐼))

(3)

Where kB represents the Boltzmann constant, T denotes the temperature, ζJ and ζI are reaction coordinates, and ρ denotes the probability of distribution. In principle, the free energy landscape of the aMD simulation can be reweighted. However, due to the large size of the systems, overflow errors may occur in calculating the weight46. In previous study, the large energetic noise was observed in reweighting of aMD simulations of M2 muscarinic receptor, which led to the occurrence of large fluctuations in the free energy calculation. The unweighted PMF profiles of the aMD simulation was found to match well to PMF profiles of cMD simulations46. Although the aMD simulation changes the transition barriers between the low-energy states, the free energy shape could be maintained as the original one46. Therefore, the unweighted free energy landscapes were presented in the work. 2.5 Cross-correlation analysis The cross-correlation analysis was performed to reveal how atomic displacements are coupled, which could gain insight into impacts of the dimerization and mutations on the protein dynamics. The correlations between the residues were calculated using the dynamic cross-correlation algorithm (DCC)57, as follows: (𝑟𝑖 ― 𝑟𝑖)(𝑟𝑗 ― 𝑟𝑗)

𝐶𝑖𝑗 = ( 2 2)( 2 2) 𝑟𝑖 ― 𝑟𝑖 𝑟𝑗 ― 𝑟𝑗

Where i and j are atoms or residues and Cij is the covariance matrix of i and j. 2.6 Principal component analysis

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(4)

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Principal component analysis (PCA) can separate large amplitude motions based on MD trajectories. A covariance matrix between Ca atoms of i and j residues could be generated using the obtained trajectory data, which is defined by the following equation (eqn (5)): 𝐶𝑖𝑗 = 〈(𝑥𝑖 ― 〈𝑥𝑖〉)(𝑥𝑗 ― 〈𝑥𝑗〉)〉(𝑖,𝑗 = 1,2,3,…,3𝑁)

(5)

where xi and xj are Cartesian coordinates of the ith and jth Ca atoms, respectively, N denotes the number of the Ca atoms, and and represent the time average over all the configurations derived from the MD simulation. In this approach, a set of eigenvectors and corresponding eigenvalues was obtained through diagonalizing the covariance matrix of atomic fluctuations relative to the average structure, which could exhibit the axes of maximal variance of the protein motion. 2.7 Protein structure network The protein structure network (PSN) analysis28, 34, 58, 59 could provide information about intra-molecular and inter-molecular communications. The communications are important for proteins to complete their biological functions. In PSN, each residue is taken as the node of the network. The edge connecting two nodes is defined if the percentage of the interaction between them is larger than or equal to a given interaction strength cutoff (vide eqn (6)) 𝐼𝑖𝑗 =

𝑛𝑖𝑗 𝑁𝑖𝑁𝑗

100

(6)

where Iij denotes the interaction percentage between nodes i and j, nij represents the pair number of side-chain atoms within a given distance cutoff. Ni and Nj are the normalization factors for residues i and j, respectively. 2.8 MM-PBSA calculations Molecular mechanics Poisson Boltzmann surface area (MM/PBSA) calculation60 is a versatile method to calculate the binding energy between two molecules. In MM/PBSA,

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the binding free energy is calculated in terms of the following equation (eqn (7)): 𝐺binding = 𝐺complex ― (𝐺species A + 𝐺species B)

(7)

Where Gcomplex, Gspecies A , Gspecies B denote the free energy for the complex, the subunit A and the subunit B consisting the complex, respectively. The MMPBSA.py.MPI algorithm60 in SANDER program was utilized to calculate the free energy G of each species by following schemes: 𝐺 = 𝐸gas + 𝐺sol ―𝑇𝑆

(8)

𝐸𝑔𝑎𝑠 = 𝐸int + 𝐸ele + 𝐸vdw

(9)

𝐺𝑠𝑜𝑙 = 𝐺psolv + 𝐺npsolv

(10)

Where the gas-phase energy (Egas) is consisted of the internal energy (Eint), the electrostatic interaction energy (Eele) and van der Waals interaction energy (Evdw). Both polar solvation energy (Gpsolv) calculated by solving PoissonBoltzmann equation and the nonpolar solvation (Gnpsolv) are contributed to the solvation energy (Gsol). Gnpsolv is estimated by γ× SASA, where γ =0.0072 kcal Å-2 and SASA represents the solvent-accessible area of the molecular. The dielectric constants for the solute and the solvent were set to be 1 and 80, respectively. T is the temperature and S defines the total conformational

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entropy. Following many computational investigations61, 62, the entropy contribution was not considered in the work. The wordom software63 was used to carry out PCA, cross-correlation and PSN analysis. The cpptraj module of AMBER 1652 was utilized to perform the other MD analysis. 3. Results and discussion 3.1 Impact of dimerization on the CCR5 structure To observe the effect of the dimerization on the overall structure of CCR5, we calculated the RMSD of backbone atoms of CCR5 with respect to its initial structure over the 1us aMD trajectory for the monomer and the two protomers of the CCR5wt, as shown in Figure 1. It can be seen that the dimerization induces different structurechanges for the two subunits. Compared to the CCR5 monomer, the protomer A presents larger RMSD fluctuations while the protomer B has smaller RMSDs, exhibiting an asymmetrical effect of the dimerization on the two subunits. The observation is consistent with the experimental speculation that GPCR dimer regulate their biological functions through their asymmetric nature64-66. In addition, we especially concerned the structural change of the ligand-binding pocket due to its importance in the ligand binding, as shown in Figure 2. The ligand-binding pocket includes 16 residues, which involve in TM1, TM2, TM3, TM5, TM6 and TM7. The pocket residues of the protomer A in CCR5wt present much higher RMSD values than the monomer and the protomer B. The RMSD values of the protomer B are only slightly higher than that of the monomeric unit. To gain more insights to the structural changes of the pocket, we also calculated their volumes. After 1-s molecular dynamics simulation, the binding pocket volume of CCR5 monomer is 567 Å3. However, due to the dimerization, the pocket volumes of the protomer A is increased to be 650 Å3 while

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that of the protomer B is reduced to be 412 Å3. The asymmetric change in the pocket upon the dimerization implies the different impact of the dimerization on the ligand binding between the two protomers. 3.2 Important interface residues contributed to the dimerization In order to estimate stability of the dimer and identify important interface residues, we used the MM-PBSA method to calculate the binding free energy between the two subunits, based on fifty thousand frames from the last 100 ns aMD trajectory at the interval 2 ps. Table 1 lists subcomponents of the free energy. Although the electrostatic free energy high up to be 1320.92 kcal mol-1 significantly disfavors the dimerization, it is largely offset by the solvation energy of -1176.72 kcal mol-1. The vdw free energy is -194.21 kcal mol-1, which devotes main contributions to the dimerization. Ultimately, the binding energy for the dimerization is -50.01 kcal mol-1. To identify the important residues contributed to the dimerization, we decomposed the binding energy into corresponding residues. Figure 3a shows residues with great contribution larger than 2 kcal mol-1. It can be seen that the important residues are mainly hydrophobic amino acids like Phe, Ile, Leu, Val, Met and Trp. In addition, these important residues mainly involve in TM1, TM2, TM3 and TM4, as also reflected by Figure 3b. The observation further confirms that the interface involved in TM1, TM2, TM3 and TM4 is a stable for the CCR5 homo-dimerization. Recently, Jin utilized the cysteine cross-linking and homogeneous time-resolved fluorescence (HTRE) saturation experiments to study the interfaces of the CCR5 homodimer involved in TM5/TM5 (I5), TM5-TM6/TM5-TM6 (I5/6) and TM1-H8/TM1-H8 (I1/8), and indicated that the residues in TM5 and TM6 mainly contribute to the dimerization of CCR5 in apo form. However, they also found that mutations with lysine on TM5 and TM6 didn’t completely prevent CCR5 dimerization, indicating the possibility of other interfaces67. In addition, the receptor

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arrangements and helix associations were observed by super-resolution imaging approach and structural modeling for the oligomerization of luteinizing hormone receptor (LHR)-one of class A GPCR, revealing the complexity and diversity in structural assemblies of the dimer68. In fact, the observations from the dimerization of the GPCR neurotensin receptor 1 also indicated that multiple dimer conformation with different interfaces co-exist and interconvert, which proposed a “rolling dimer” interface model69. Taken together, it can be further confirmed that the interfaces should be diverse for the homo-dimerization of GPCRs. 3.3 Impact of the dimerization on the binding of maraviroc to CCR5 As revealed above, the dimerization induces the symmetric impact on the structure of the ligand-binding pocket, which may cause different roles in influencing the ligand binding. In order to confirm the assumption, we further study the effect of the dimerization on the ligand binding. The inhibitor maraviroc was found to prevent CCR5 from binding the chemokine and gp120, in turn blocking the HIV-1 infection70-73. Thus, we selected it as a representative ligand to probe the effect of the dimerization on its binding to CCR5. In order to obtain the representative conformation characterizing the dimer structure, we performed the PMF analysis for the dimer based on its 1 us aMD trajectory, in which the center of mass (COM) distance between the two protomers and the RMSD value of the CCR5 dimer are served as the two reaction coordinates. Figure 4 shows the energy landscape of the CCR5 dimer. It can be seen that the CCR5wt only presents a major deep well centered at the distance of 32.1 Å and RMSD of 4.1 Å, implying that the CCR5wt system is stable. Thus, one representative conformation from the stable state was selected as the dimer structure. As a reference, one representative monomeric structure with the lowest energy was selected from the last the 100 ns aMD trajectory. Then, we docked the maraviroc into the monomer, the protomer A and the

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protomer B of the CCR5wt, respectively. Consequently, there are three complex systems, in which the ligand bind to the CCR5 monomer, the protomer A of the dimer and the protomer B of the dimer, respectively. Similarly, the top-ranking conformation of the resulting dock structures was selected to perform a 200-ns equilibrium molecular dynamics simulation for each system. The binding free energy between CCR5 and the maraviroc was calculated by MM/PBSA method74, 75, based on the last 20 ns trajectory of the 200 ns equilibrium MD simulation. Table 2 list their binding free energies, which are -44.1 kcal mol−1 for the monomer, -49.2 kcal mol−1 for the protomer A and -22.5 kcal mol−1 for the protomer B. Compared with the CCR5 monomer, the dimerization enhances the binding of the maraviroc to the subunit A, which should contribute to the experimental finding that the receptor dimerization is acquired for the anti-HIV-1 activity 76, 77. In contrast, the dimerization weakens the interaction of the subunit B with the maraviroc. Namely, a negative cooperativity between the two subunits is presented for the ligand binding, which should be associated with the asymmetric change in the ligand-binding pocket between the two subunits, as revealed above. Some experimental studies already found that the high-affinity conformation of one subunit of β1AR dimer can promote the formation of a low-affinity conformation of the second subunit78, which is in line with our observations. 3.4 Impact of the binding of the maraviroc on the dimerization Some experimental studies reported that the binding of the ligands to GPCR dimers might induce rearrangements of the dimeric interfaces79-81. For example, the cysteine cross-linking experiment found that the interface of the mGluR2 dimer switches from TM4-TM5/TM4-TM5 (I4/5) in inactive state to TM6/TM6 (I6) interactions in the active conformation stimulated by agonist81. The observation from the homogeneous timeresolved fluorescence saturation experiment indicated that the maraviroc could drive

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CCR5 to form a new dimer interface engaged in TM3, TM4 and TM5, which is distinct from the I5 and I5/6 interfaces in the ligand-free state67. To gain insight into the impact of the maraviroc on the CCR5 dimerization with the interface of TM1-TM2-TM3-TM4, we used the MMPBSA method to calculate the binding energy between the two protomers after the binding of the maraviroc to the protomer A, based on the last 20-ns trajectory of the 200-ns equilibrium MD simulation on the complex of the CCR5 dimer and the maraviroc. The results show in Table 1 and Figure 3. It can be seen from Table 1 that the binding of the maraviroc weakens the interaction strength between the two protomers from -50.01 kcal mol-1 to -41.09 kcal mol-1, mainly resulted from the drop in the VDW interaction. In order to observe the effect of the maraviroc on the interface, we also decomposed the binding energy into corresponding residues. Figure 3c shows residues with great contribution larger than -2 kcal mol-1. We found that the number of important residues significantly contributed to the binding energy is reduced from 21 in absence of the ligand to 17 in presence of the ligand, leading to the drop in the binding strength. Four residues decreased mainly involve in TM1 and TM4 and are hydrophobic residues. Within our 200 ns simulation, the impact of the ligand binding is mainly reflected by the binding energy while the interface change is not as significant as the experimental reports. The difference should be attributed to two main reasons. One is the limitation of the short simulation time with respect to the experimental time scale. The other is the difference between the experimental condition and our simulation one. The experiments83,67 first mutated the residues of the monomer involved in one specific dimer interface so that the dimer with I5 or I5/6 interface was not formed for the CCR5 lysine mutants67 or the number of dimers with the I4/5 interface was increased for the mGluR2 cysteine mutants83. Then, the added ligands drove the mutated receptors to

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form a new interface different from the original one. Herein, we focused on the effect of the maraviroc on the binding strength of the CCR5 dimer and the TM1-TM2-TM3TM4 interface by means of adding the maraviroc to the CCR5wt dimer. Despite the differences above, all the observations indicate that the binding of the maraviroc indeed influences the dimerization. 3.5 The allosteric regulation of the ligand-binding pockets between the two subunits. As observed above, the two subunits of the dimer exhibit asymmetric ligand binding. In order to probe cooperativity between them, we used protein structure network (PSN) to identify the allosteric communication between the two pockets based on the last 100 ns aMD trajectory. In the PSN search, all the residues in the two ligand-binding pockets were selected as starting and end nodes, respectively. The shortest path with the highest frequency (vide Figure 5), which could characterize the main allosteric pathway, was obtained by means of integrating the internal links of the PSN nodes and the residue correlations. This pathway is composed of Trp862.60 (A)-Leu1043.28 (A)-Phe852.59 (A)Leu1073.31 (B) - Thr822.56 (B) - Tyr1083.32 (B), which only involve in TM2 and TM3. The observation indicates that the two helixes play important role in modulating the cooperativity of the ligand-binding pockets between the two subunits. As revealed above, Phe852.59 is one important interface residue with significant contribution to the dimer formation. Its appearance in the allosteric pathway confirms its importance for modulating the asymmetric ligand binding. With the aid of the interface residue, the dimer finally transmits the allosteric communication to the residues Trp862.60 (A) and Tyr1083.32 (B) located in the ligand-binding pockets of the two subunits through the Leu1043.28 (A), Leu1073.31 (B) and Thr822.56 (B) residues (vide Figure 5). As revealed above, the two residues Trp862.60 and Tyr1083.32 are key residues contributed to the

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ligand binding for CCR5 either in the monomeric or in the dimeric state. Thus, the pathway transmits the allosteric communication to the ligand binding mainly through the two residues. Thr822.56 in the pathway belongs to highly conserved TXP motif, which is associated with governing the conformation of extracellular part of TM2 and the activation of the chemokine receptor. Thus, its appearance in the pathway also implies that the allosteric modulation would influence the activity of the receptor, besides the ligand binding. Although there have not been reports regarding importance of the two residues of Leu1043.28 and Leu1073.31 in the pathway, our observations clearly indicate their crucial roles in modulating the cooperativity of the ligand binding for the CCR5 dimer with the TM1-TM2-TM3-TM4 interface. 3.6 Effects of the I52V and V150A mutations on the dimerization As mentioned in the introduction section, the effects of the two mutations (I52V and V150A) on the dimerization of CCR5 have been controversial on experiments. However, the binding energies above already reveal that the two residues devote great contributions to the dimerization, implying that the mutations on the two residues should disfavor the dimerization. In order to confirm the assumption and address the controversy, we mutated the two residues and utilized aMD and PMF to study the mutated dimer. 3.6.1

The distance and the contact area between the two subunits of the dimer

mutant In order to estimate the impact of the two mutations on the separation between the two protomers, two indicators were calculated for the wild dimer (CCR5wt) and the mutated one (CCR5mut). One is the center of mass (COM) distance between the two protomers. The other is the contact areas between two the protomers, which was calculated by the following equation82:

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1

contact area = 2[(𝑆𝐴𝑆protomerA + 𝑆𝐴𝑆protomerB) ― 𝑆𝐴𝑆complex] where SASprotomerA , SASprotomerB and

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SAScomplex are the solvent accessible surface

areas (SASA) of the protomer A, the protomer B and the dimer complex, respectively. Figure 6 shows the two indicators for CCR5wt and CCR5mut. For the crystal structures of several homodimers available for β1AR, CXCR4 and k-OR83-85, we also calculated their COM distances, which are approximately in the range of 32 Å - 34 Å. It was reported82, 86 that the interface surfaces of protein-protein, which are equal to twice of the contact area, are in the range of 1500 Å2 -3400 Å2. It can be seen from Figure 6 that the COM distance of the CCR5mut presents a significant expansion from 33 Å to 43 Å while the COM distance of the wild dimer has been stabilized in about 32 Å during the 1 s aMD simulation. In addition, the contact area of the wild CCR5 dimer has been approximately 1600 Å2 in the simulation process, implying its stability. However, the contact area of the dimer mutant is significantly declined to be 200 Å2. The two indicators all clearly indicate that the two mutations lead to the significant separation of the two subunits. 3.6.2

Impact of the mutations on the free energy profile of the dimer

To capture the dissociation process induced by the mutations, we used the potential of mean force (PMF) method to calculate the free energy profile for the dimer mutant (CCR5mut), in which the COM distance and the RMSD value of the CCR5 dimer were served as the two reaction coordinates, as shown in Figure 4. It can be seen that the CCR5wt is confined in a major deep well centered at the distance of 32.1 Å and RMSD of 4.1 Å. The contact area of the representative conformation from the stable state was calculated to be about 1577 Å2. The COM distance of this lowest state energy conformation is close to those of some class A GPCR dimer resolved (32 Å-34Å ), indicating that the CCR5wt could maintain its dimer conformation. In addition, we used

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2P2Idb87 to calculate the contact area, the number of non-bonded contacts and the number of the interface residues for the lowest-energy frame of the stable state of CCR5wt in order to characterize the dimer interfaces, as shown in Table 3. It can be seen that the stable conformation of the wild dimer presents 98 non-bonded contacts in the dimer interface, which involve in about 47 residues. Different from the wild dimer, the PMF result of the CCR5 dimer mutant (CCR5mut) exhibits four energy wells and samples four types of low-energy conformations, which are labeled as “s1”, “s2”, “s3” and “s4”, respectively. In the s1 state, the COM distance of the two protomers in dimer gives a free energy minimum at 34.0 Å, in which the RMSD value of dimer is 3.7 Å, as reflected by Figure 4. The distance of the state s1 slightly increases with respect to the stable state of CCR5wt. The representative conformation from the s2 state shows the COM distance of 35.5 Å and RMSD of 4.9 Å while the s3 state possesses the distance of 37.0 Å and RMSD of 6.5 Å. In the s4 state, the COM distance and the RMSD value are increased to 42.0 Å and 9.1 Å, respectively. Table 3 also lists the number of nonbonded contacts for the lowest energy frames from the four states of the dimer mutant, which present a decrease from 61 in the state s1 to 28 in the state s4. The number of the residues involved in the interface are reduced from 27 to 12 and the contact area changes from 823.7 Å2 in the state 1 to 347.5 Å2 in the state 4. Figure 7 representatively shows the interfaces for the stable conformation from the wild dimer and one from the state 4 of the mutant. It is clear that the helixes involved in the interactions between the two subunits are changed from the TM1, TM2, TM3 and TM4 in the stable state of the wild dimer to TM4 and H8 in the state s4. Furthermore, a detailed comparison between CCTR5wt and the state 4 of CCR5 in Figure 7 shows that the separation of the two subunits upon the mutations accompanies to some extent rotation of the subunits, supporting for the “rolling dimer” interface model69. However, within the 1 us

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simulation time, the two subunits are not completely separated and still retain to some extent interactions with the aid of twelve residues in TM4 and H8 (vide Table 3). 3.6.3

Dynamics Features for the representative Conformations in the

Dissociation Process To gain insight into the effect of the mutation on the overall dynamics of the dimer, the PCA analysis was performed for the wild and mutant dimers, based on their 1 us aMD trajectories. It can be seen from Figure 8 that the first principle component (PC1) captures more than 70 % of all motions of the dimers, which could represent main dynamics. Thus, Figure 9 further shows the projection of the first eigenvector on the subspace, which is defined by the coordinates of the atoms of the receptor. In Figure 9, the color from red to blue corresponds to the movement from large to small. Judged from the color in Figure 9, the movement of the interface of the wild dimer is low, showing its stability. It was reported that the interfacial regions of GPCR dimer would remain stable even in sub-millisecond scale simulation time88-91. However, the interfacial region of CCR5mut presents significant fluctuations, in particular for the intercellular side of TM4 in the protomer A, the extracellular side of TM1 in the protomer B and the intercellular sides of TM1, TM3, TM4 in the protomer B. These regions are associated with the interface. The observation indicates that the mutations increase the instability of the interfacial region and trigger the dissociation of the dimer. To gain more insights into the dynamic motions of the two protomers in the CCR5 dimer, correlation and modevector analyses were further performed. Generally, we consider cross-correlations larger than 0.6 or smaller than –0.6 to be strong. It can be seen from Figure 10 that the residues between the two protomers of CCR5wt almost present positive correlations (vide upper triangle of Figure 10a), indicating that the two protomers move simultaneously along same direction. In contrast, the two protomers

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of CCR5mut significantly exhibit negative correlations, in particular for TM2A-TM2B, TM2A-TM4B, TM2A-ECL2B, TM2A-TM5B, TM4A-TM4B, TM4A-ECL2B and TM4ATM5B (vide lower triangle of Figure 10a). The negative correlations suggest that the two protomers in CCR5mut move along opposite direction, as reflected by Figure 10b. These observations further confirm that the mutations of I52V and V150A impair the formation of CCR5 dimers, providing a support for the result from Hernanz-Falcon22. 4. Conclusion Despite intense interests on the GPCR oligomers, the knowledge about their structural and functional mechanisms are still very limited due to the cellular complexity and the urgent absence of their crystal structures. Thus, many questions remain partially or completely unanswered on experiments. In this work, we combined aMD and cMD simulations coupled with PMF, PCA, correlation analysis and PSN to study the effects of dimerization and the mutations of I52V and V150A on the CCR5 homodimer, in order to address the question about the cooperativity of the ligand binding and the controversy about the dimer separation upon the mutations. ` As evidenced by the COM distance, the contact area, the binding free energy, the dynamic behavior and the PMF result, the interface involved in TM1, TM2, TM3 and TM4 is also stable for the CCR5 homodimer, exhibiting the diversity of the interfaces. The dimerization leads to the asymmetric impact on the structures of the two protomers with respect to its monomeric type, either for the overall structure or the ligand-binding pocket. The volume of the ligand-binding pocket is increased for the protomer A while an opposite trend is observed for the protomer B. Consequently, the two protomers exhibit the asymmetric binding to the maraviroc. Compared to its monomeric type, one protomer binding to the maraviroc is enhanced while the other one is weakened. On the other hand, the binding of the maraviroc would weaken the interaction strength between

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the two protomers of the dimer, further supporting the experimental findings that the ligand binding could influence the dimerization of GPCRs. The protein structure network further reveals the allosteric pathway between the two protomers to modulate the asymmetric ligand binding. Six important residues were identified to devote main contributes to the allosteric communication, including the interface residue Phe852.59, the two residues of the ligand binding pocket Trp862.60 and Tyr1083.32, Thr822.56 of the highly conserved TXP motif and the two unreported residues Leu1043.28 and Leu1073.31. Different from the PMF landscape of the wild dimer, which only exhibits one lowestenergy stable state, the dimer mutant exhibit the four lowest-energy stable states. The four states present gradual increases in the COM distance, a drop in the contact area and the interaction pairs, which are resulted from the mutation-enhanced instability of the interface and anti-correlation movement of the two subunits. The results clearly confirm that the two mutations would impair the dimerization and lead to its separation. In a whole, the results from our work first reveal the allosteric mechanism of the ligand binding between the two protomers of the CCR5 dimer and elucidate the controversial problem about the effect of the two mutations on the CCR5 dimerization. The observations could advance our understanding of the structure and function of the GPCR dimers.

ACKNOWLEDGMENTS This project is supported by the National Science Foundation of China (Grant No. 21573151) and NSAF (Grand No. U1730127). Reference 1. Rosenbaum, D. M.; Rasmussen, S. G.; Kobilka, B. K., The Structure and Function of G-ProteinCoupled Receptors. Nature 2009, 459, 356-363. 2. Khelashvili, G.; Dorff, K.; Shan, J.; Camacho-Artacho, M.; Skrabanek, L.; Vroling, B.; Bouvier, M.; Devi, L. A.; George, S. R.; Javitch, J. A., GPCR-OKB: The G Protein Coupled Receptor Oligomer Knowledge

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1-5.6. 30. 49. Kaufmann, K. W.; Lemmon, G. H.; DeLuca, S. L.; Sheehan, J. H.; Meiler, J., Practically Useful: What the Rosetta Protein Modeling Suite Can Do for You. Biochemistry 2010, 49, 2987-2998. 50. Gray, J. J.; Moughon, S.; Wang, C.; Schueler-Furman, O.; Kuhlman, B.; Rohl, C. A.; Baker, D., Protein–Protein Docking with Simultaneous Optimization of Rigid-Body Displacement and Side-Chain Conformations. J. Mol. Biol. 2003, 331, 281-299. 51. Lee, J.; Cheng, X.; Swails, J. M.; Yeom, M. S.; Eastman, P. K.; Lemkul, J. A.; Wei, S.; Buckner, J.; Jeong, J. C.; Qi, Y., Charmm-Gui Input Generator for Namd, Gromacs, Amber, Openmm, and Charmm/Openmm Simulations Using the Charmm36 Additive Force Field. J. Chem. Theory Comput. 2015, 12, 405-413. 52. Case, D.; Betz, R.; Cerutti, D.; Cheatham, T.; Darden III, T.; Duke, R.; Giese, T.; Gohlke, H.; Goetz, A.; Homeyer, N. Amber 2016; University of California, 2016. 53. Maier, J. A.; Martinez, C.; Kasavajhala, K.; Wickstrom, L.; Hauser, K. E.; Simmerling, C., Ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from Ff99SB. J. Chem. Theory Comput. 2015, 11, 3696-3713. 54. Essmann, U.; Perera, L.; Berkowitz, M. L.; Darden, T.; Lee, H.; Pedersen, L. G., A Smooth Particle Mesh Ewald Method. J. Chem. Phys. 1995, 103, 8577-8593. 55. Berendsen, H. J.; Postma, J. v.; van Gunsteren, W. F.; DiNola, A.; Haak, J., Molecular Dynamics with Coupling to an External Bath. J. Chem. Phys. 1984, 81, 3684-3690. 56. Kastner, K. W.; Izaguirre, J. A., Accelerated Molecular Dynamics Simulations of the Octopamine Receptor Using GPUs: Discovery of an Alternate Agonist‐Binding Position. Proteins: Struct., Funct., Bioinf. 2016, 84, 1480-1489. 57. McCammon, J. A.; Harvey, S. C., Dynamics of Proteins and Nucleic Acids. Cambridge University Press 1988. 58. Kannan, N.; Vishveshwara, S., Identification of Side-Chain Clusters in Protein Structures by a Graph Spectral Method1. J. Mol. Biol. 1999, 292, 441-464. 59. Zhang, X.; Yuan, Y.; Wang, L.; Guo, Y.; Li, M.; Li, C.; Pu, X., Use Multiscale Simulation to Explore the Effects of the Homodimerizations between Different Conformation States on the Activation and Allosteric Pathway for the ɥ-Opioid Receptor. Phys. Chem. Chem. Phys. 2018, 20, 13485-13496. 60. Miller III, B. R.; McGee Jr, T. D.; Swails, J. M.; Homeyer, N.; Gohlke, H.; Roitberg, A. E., Mmpbsa. Py: An Efficient Program for End-State Free Energy Calculations. J. Chem. Theory Comput. 2012, 8, 33143321. 61. Wang, J.; Morin, P.; Wang, W.; Kollman, P. A., Use of MM-PBSA in Reproducing the Binding Free Energies to Hiv-1 RT of TIBO Derivatives and Predicting the Binding Mode to HIV-1 RT of Efavirenz by Docking and MM-PBSA. J. Am. Chem. Soc. 2001, 123, 5221-5230. 62. Rastelli, G.; Degliesposti, G.; Del Rio, A.; Sgobba, M., Binding Estimation after Refinement, a New Automated Procedure for the Refinement and Rescoring of Docked Ligands in Virtual Screening. Chem. Biol. Drug Des. 2009, 73, 283-286. 63. Seeber, M.; Felline, A.; Raimondi, F.; Muff, S.; Friedman, R.; Rao, F.; Caflisch, A.; Fanelli, F., Wordom: A User ‐ Friendly Program for the Analysis of Molecular Structures, Trajectories, and Free Energy Surfaces. J. Comput. Chem. 2011, 32, 1183-1194. 64. Rovira, X.; Pin, J. P.; Giraldo, J., The Asymmetric/Symmetric Activation of GPCR Dimers as a Possible Mechanistic Rationale for Multiple Signalling Pathways. Trends Pharmacol. Sci. 2010, 31, 15-21. 65. Han, Y.; Moreira, I. S.; Urizar, E.; Weinstein, H.; Javitch, J. A., Allosteric Communication between Protomers of Dopamine Class A GPCR Dimers Modulates Activation. Nat. Chem. Biol. 2009, 5, 688-695. 66. Lane, J. R.; Donthamsetti, P.; Shonberg, J.; Draper-Joyce, C. J.; Dentry, S.; Michino, M.; Shi, L.; Lã³Pez, L.; Scammells, P. J.; Capuano, B., A New Mechanism of Allostery in a G Protein-Coupled Receptor Dimer. Nat. Chem. Biol. 2014, 10, 745-752. 67. Jin, J.; Momboisse, F.; Boncompain, G.; Koensgen, F.; Zhou, Z.; Cordeiro, N.; Arenzana-Seisdedos, F.; Perez, F.; Lagane, B.; Kellenberger, E., CCR5 Adopts Three Homodimeric Conformations That Control Cell Surface Delivery. Sci. Signal. 2018, 11, eaal2869. 68. Jonas, K. C.; Fanelli, F.; Huhtaniemi, I. T.; Hanyaloglu, A. C., Single Molecule Analysis of Functionally Asymmetric G Protein-Coupled Receptor (GPCR) Oligomers Reveals Diverse Spatial and Structural Assemblies. J. Biol. Chem. 2015, 290, 3875-3892. 69. Dijkman, P. M.; Castell, O. K.; Goddard, A. D.; Munoz-Garcia, J. C.; De Graaf, C.; Wallace, M. I.; Watts, A., Dynamic Tuneable G Protein-Coupled Receptor Monomer-Dimer Populations. Nat. Commun. 2018, 9, 1710.

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70. Palani, A.; Tagat, J. R., Discovery and Development of Small-Molecule Chemokine Coreceptor CCR5 Antagonists. J. Med. Chem. 2006, 49, 2851-2857. 71. Garciaperez, J.; Rueda, P.; Alcami, J.; Rognan, D.; Arenzanaseisdedos, F.; Lagane, B.; Kellenberger, E., An Allosteric Model of Maraviroc Binding to CC Chemokine Receptor 5 (CCR5). J. Biol. Chem. 2011, 286, 33409. 72. Watson, C.; Jenkinson, S.; Kazmierski, W.; Kenakin, T., The CCR5 Receptor-Based Mechanism of Action of 873140, a Potent Allosteric Noncompetitive HIV Entry Inhibitor. Mol. Pharmacol. 2005, 67, 1268-1282. 73. Muniz-Medina, V. M.; Jones, S.; Maglich, J. M.; Galardi, C.; Hollingsworth, R. E.; Kazmierski, W. M.; Ferris, R. G.; Edelstein, M. P.; Chiswell, K. E.; Kenakin, T. P., The Relative Activity of "Function Sparing" HIV-1 Entry Inhibitors on Viral Entry and CCR5 Internalization: Is Allosteric Functional Selectivity a Valuable Therapeutic Property? Mol. Pharmacol. 2009, 75, 490-501. 74. Li, J.; Wei, D. Q.; Wang, J. F.; Li, Y. X., A Negative Cooperativity Mechanism of Human CYP2E1 Inferred from Molecular Dynamics Simulations and Free Energy Calculations. J. Chem. Inf. Model. 2011, 51, 3217-3225. 75. Chen, F.; Liu, H.; Sun, H.; Pan, P.; Li, Y.; Li, D.; Hou, T., Assessing the Performance of the Mm/Pbsa and MM/GBSA Methods. 6. Capability to Predict Protein-Protein Binding Free Energies and Re-Rank Binding Poses Generated by Protein-Protein Docking. Phys. Chem. Chem. Phys. 2016, 18, 22129-22139. 76. Mellado, M.; Rodrã-Guez-Frade, J. M.; Maã±Es, S.; Martã-Nez-A, C., Chemokine Signaling and Functional Responses: The Role of Receptor Dimerization and TK Pathway Activation. Annu. Rev. Immunol. 2001, 19, 397-421. 77. Vila-Coro, A. J.; Mellado, M.; Ana, A. M. D.; Lucas, P.; Real, G. D.; Rodriguez-Frade, J. M., Hiv-1 Infection through the CCR5 Receptor Is Blocked by Receptor Dimerization. Proc. Natl. Acad. Sci. U. S. A. 2000, 97, 3388-3393. 78. Karolina, G.; May, L. T.; Baker, J. G.; Briddon, S. J.; Hill, S. J., Negative Cooperativity across β1Adrenoceptor Homodimers Provides Insights into the Nature of the Secondary Low-Affinity CGP 12177 β1-Adrenoceptor Binding Conformation. FASEB J. 2015, 29, 2859-2871. 79. Tateyama, M.; Abe, H.; Nakata, H.; Saito, O.; Kubo, Y., Ligand-Induced Rearrangement of the Dimeric Metabotropic Glutamate Receptor 1α. Nat. Struct. Mol. Biol. 2004, 11, 637-642. 80. Guo, W.; Shi, L.; Filizola, M.; Weinstein, H.; Javitch, J. A., Crosstalk in G Protein-Coupled Receptors: Changes at the Transmembrane Homodimer Interface Determine Activation. Proc. Natl. Acad. Sci. U. S. A. 2005, 102, 17495-17500. 81. Xue, L.; Rovira, X.; Scholler, P.; Zhao, H.; Liu, J.; Pin, J.-P.; Rondard, P., Major Ligand-Induced Rearrangement of the Heptahelical Domain Interface in a GPCR Dimer. Nat. Chem. Biol. 2015, 11, 134. 82. Lo, C. L.; Chothia, C.; Janin, J., The Atomic Structure of Protein-Protein Recognition Sites. J. Biol. Chem. 1999, 285, 16027-16030. 83. Huang, J.; Chen, S.; Zhang, J. J.; Huang, X. Y., Crystal Structure of Oligomeric β1-Adrenergic G Protein–Coupled Receptors in Ligand-Free Basal State. Nat. Struct. Mol. Biol. 2013, 20, 419-425. 84. Wu, B.; Chien, E. Y. T.; Mol, C. D.; Fenalti, G.; Liu, W.; Katritch, V.; Abagyan, R.; Brooun, A.; Wells, P.; Bi, F. C., Structures of the CXCR4 Chemokine Receptor in Complex with Small Molecule and Cyclic Peptide Antagonists. Science 2011, 330, 1066–1071. 85. Wu, H.; Wacker, D.; Katritch, V.; Mileni, M.; Han, G. W.; Vardy, E.; Liu, W.; Thompson, A. A.; Huang, X. P.; Carroll, F. I., Structure of the Human Kappa Opioid Receptor in Complex with Jdtic. Nature 2012, 485, 327-332. 86. Jones, S.; Thornton, J. M., Principles of Protein-Protein Interactions. Proc. Natl. Acad. Sci. U. S. A. 1996, 93, 13-20. 87. Basse, M. J.; Betzi, S.; Bourgeas, R.; Bouzidi, S.; Chetrit, B.; Hamon, V.; Morelli, X.; Roche, P., 2p2idb: A Structural Database Dedicated to Orthosteric Modulation of Protein–Protein Interactions. Nucleic Acids Res. 2012, 41, D824-D827. 88. Periole, X.; Huber, T.; Marrink, S. J.; Sakmar, T. P., G Protein-Coupled Receptors Self-Assemble in Dynamics Simulations of Model Bilayers. J. Am. Chem. Soc. 2007, 129, 10126-10132. 89. Periole, X.; Knepp, A. M.; Sakmar, T. P.; Marrink, S. J.; Huber, T., Structural Determinants of the Supramolecular Organization of G Protein-Coupled Receptors in Bilayers. J. Am. Chem. Soc. 2012, 134, 10959-10965. 90. Prasanna, X.; Chattopadhyay, A.; Sengupta, D., Cholesterol Modulates the Dimer Interface of the β2-Adrenergic Receptor Via Cholesterol Occupancy Sites. Biophys. J. 2014, 106, 1290-1300. 91. Ghosh, A.; Sonavane, U.; Joshi, R., Multiscale Modelling to Understand the Self-Assembly

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Mechanism of Human β2-Adrenergic Receptor in Lipid Bilayer. Comput. Biol. Chem. 2014, 48, 29-39.

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For Table of Contents use only Molecular Mechanism regarding Allosteric Modulation of Ligand Binding and the Impact of Mutations on Dimerization for CCR5 Homodimer Fuhui Zhang a, Yuan Yuanc, Minghui Xiang a, Yanzhi Guo a, Menglong Li a,Yijing Liub Xuemei Pu a,*

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Table 1. Components of binding energies (in kcal mol−1) between two protomers in the apo CCR5wt (labelled as CCR5wt) and the CCR5wt bound to the maraviroc (labelled as CCR5wt-m), derived from MM/PBSA calculation. Components

Energy (kcal mol−1) CCR5wt

CCR5wt-m

ΔEvdwa

-194.21

-150.26

ΔEeleb

1320.92

1380.97

ΔEgasc

1126.71

1230.71

ΔGnpsolvd

-1152.65

-1252.67

ΔGpsolve

-24.07

-19.13

ΔGsolvf

-1176.72

-1271.80

ΔGbindingg

-50.01

-41.09

a

Non-bonded van der walls contribution from MM force field

b

Non-bonded electrostatic energy as calculated by the MM force field

c

Total gas phase energy

d

Nonpolar contribution to the solvation free energy

e

Polar contribution to the solvation free energy calculated

f

Solvation free energy

g

Binding energy

ΔEgas = ΔEele + ΔEvdw+ ΔEint,

ΔGsolv = ΔGnpsolv + ΔGpsolv,

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ΔGbinding = ΔEgas + ΔGsolv

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Table 2. The binding energy (in kcal mol−1) between the marviroc and the receptor unit (e.g., the CCR5 monomer, the protomer A of CCR5wt, the protomer B of CCR5wt), along with the volume (Å3) of the ligand pocket for the three receptor units. Contribution

CCR5 monomer

CCR5wt protomer A

CCR5wt protomer B

ΔEvdwa

-53.0

-49.4

-31.6

ΔEeleb

-16.6

-21.8

-8.9

ΔEgasc

-69.6

-71.2

-40.5

ΔGpsolvd

33.4

28.7

22.0

ΔGnpsolve

-7.9

-6.7

-4.0

ΔGsolvf

25.5

22.0

18.0

ΔGbindingg

-44.1

-49.2

-22.5

Volume

567

650

412

a

Non-bonded van der walls contribution from MM force field

b

Non-bonded electrostatic energy as calculated by the MM force field

c

Total gas phase energy

d

Polar contribution to the solvation free energy calculated

e Nonpolar

contribution to the solvation free energy

f

Solvation free energy

g

Binding energy

ΔEgas = ΔEele + ΔEvdw+ ΔEint,

ΔGsolv = ΔGnpsolv +ΔGpsolv,

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ΔGbinding = ΔEgas + ΔGsol

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Table 3. The contact area (Å2), the number of non-bonded contacts and the interface residues for the stable states of the CCR5wt and the CCR5mut systems. properties

CCR5wt

s1

s2

s3

s4

Contact area

1577.0

823.7

731.5

658.1

347.5

The number of non- bonded

98

61

54

41

28

47

27

23

18

12

contacts The number of interface residues

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Figure 1. Changes in RMSD values of backbone atoms for the three receptors units (CCR5 monomer, protomer A and protomer B of CCR5wt dimer) along with simulation time (left) and their distribution (right). 149x59mm (300 x 300 DPI)

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Figure 2. Changes in RMSD values of the ligand binding pocket for the three receptor units (CCR5 monomer, protomer A and protomer B of CCR5wt dimer) along with simulation time (left) and their distribution (right). 146x53mm (300 x 300 DPI)

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Figure 3. Residues contributed to the dimerization. Per-residue decomposition of the binding free energy for the apo CCR5wt (a) and the CCR5wt bound to the maraviroc (c). Crucial residues contributed to the interaction between the two protomers of the apo CCR5wt (b) and the CCR5wt bound to the maraviroc (d). 160x159mm (300 x 300 DPI)

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Figure 4. Free energy landscapes of CCR5wt (left) and CCR5mut (right). The two coordinates selected are the center of mass (COM) distance between the two protomers and the RMSD value of backbone atoms of the dimer with respect to the initial structure. 147x61mm (300 x 300 DPI)

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Figure 5. The pathway with the highest frequency between the ligand-binding sites of two submits in CCR5wt. Red ball and orange ball denote the interface residue and the residue of the binding pocket, respectively.

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Figure 6. Changes of the center of mass (COM) distance and the contact area between the two protomers for the CCR5wt and CCR5mut systems.

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Figure 7. The representative conformations with the lowest energy of CCR5wt (left) and the state s4 of CCR5mut (right). 159x52mm (300 x 300 DPI)

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Figure 8. Eigenvalue contributions of principal components (PCs) to variance of the dataset. 82x37mm (300 x 300 DPI)

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Figure 9. The projection of the first principle component (PC1) colored by the length of the atomic component of the eigenvector for CCR5wt (left) and CCR5mut (right), in which the color represents the mobility (red: large; green: intermediate; blue: small). The receptor is shown in cartoon and the mutated residues (I52V and V150A) are shown in red sticks. Regions with high mobility are highlighted in red box. 160x68mm (300 x 300 DPI)

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Figure 10. Motions for residues and receptors. (a) Correlated motions between residues shown by a dynamic map of color-coded residue cross-correlations for the CCR5mut (lower triangle) and CCR5wt (upper triangle). (b) The relative displacement of the protomers of the dimer is depicted with arrows. Top is the representative structure form the stable state of CCR5wt; Bottom is the representative structure from the s4 state of CCR5mut.

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