Biased Agonist TRV027 Determinants in AT1R by Molecular

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Computational Biochemistry

Biased Agonist TRV027 Determinants in AT1R by Molecular Dynamics Simulations Silvestre Modestia, Matheus Malta de Sa, Eric Auger, Gustavo Henrique Goulart Trossini, José Eduardo Krieger, and Carlota Oliviera Rangel-Yagui J. Chem. Inf. Model., Just Accepted Manuscript • Publication Date (Web): 22 Jan 2019 Downloaded from http://pubs.acs.org on January 22, 2019

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Journal of Chemical Information and Modeling

Biased Agonist TRV027 Determinants in AT1R by Molecular Dynamics Simulations AUTHOR NAMES (Silvestre Massimo Modestia1, Matheus Malta de Sá2, Eric Auger2, Gustavo Henrique Goulart Trossini3, José Eduardo Krieger2, Carlota de Oliveira Rangel-Yagui1). AUTHOR

ADDRESS

(1Department

of

Biochemical

and

Pharmaceutical

Technology, School of Pharmaceutical Sciences, University of São Paulo, Av. Prof. Lineu Prestes, 580, 05508-900, São Paulo, SP, Brazil.

2Laboratory

of

Genetics and Molecular Cardiology, Heart Institute, University of São Paulo Medical School, Av. Dr. Enéas de Carvalho Aguiar, 44, 05403-900 São Paulo, SP, Brazil.

3Department

of Pharmacy, School of Pharmaceutical Sciences,

University of São Paulo, Av. Prof. Lineu Prestes, 580, 05508-900, São Paulo, SP, Brazil).

ABSTRACT

Functional selectivity is a phenomenon observed in G protein coupledreceptors (GPCR) in which intermediate active states conformations are stabilized

ACS Paragon Plus Environment

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by mutations or ligand binding, resulting in different sets of signaling pathways. Peptides capable of selectively activating β-arrestin, known as biased agonists, have already been characterized in vivo, and could correspond to a new therapeutic approach for cardiovascular diseases treatment. Despite biased agonism potential, the mechanism involved in selective signaling remains unclear. In this work, molecular dynamics simulations were employed to compare the conformational profile of AT1R crystal bond to angiotensin II (AngII), bond to the biased ligand TRV027 and in the apo form. Our results show that both ligands induce changes near the NPxxY motif in TM7 that are related to receptor activation. However, the biased ligand does not cause the rotamer toggle alternative positioning and displays an exclusive hydrogen bond pattern. Our work sheds light into biased agonism mechanism and will help future design of novel biased agonist for AT1R.

INTRODUCTION

The angiotensin II type 1 receptor (AT1R), a G protein-coupled receptor (GPCR), is part of the renin-angiotensin-aldosterone system (RAAS) responsible for blood pressure regulation and electrolytes homeostasis. One therapeutic approach for hypertension, which is the result of RAAS overstimulation, consists


2

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in the complete blockage of AT1R signaling by potent antagonists, known as sartans. Despite arterial pressure reduction, AT1R blocking results in negative inotropism and cardiomyocytes viability, leading to heart failure progression.1

GPCRs signaling is not limited to G protein-coupling and parallel or even distinct signals can also occur. The most general of these are mediated by βarrestins that bind to activated receptors to desensitize G protein signaling, promote

receptor

internalization

and

activate

distinct

signal

transduction

cascades.2,3,4 For AT1R, G-protein activation is detrimental, resulting in increased arterial pressure, while β-arrestin mediated response increases cell survival and inotropism.

5

Selective activation of an exclusive pathway of a GPCR can be achieved by mutation of key amino acids in the receptor or using certain ligands, this phenomenon is known as functional selectivity or biased signaling. Biased ligand are agonists when assaying some receptor functions, but they are antagonists or even inverse agonists when assaying other receptor functions.6,7 TRV027 (SarArg-Val-Tyr-Ile-His-Pro-D-Ala-OH) is a biased Ang II analog that stimulates β-


3


arrestin recruitment and activates several kinase pathways.

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8

While sartans cause

a reduction in arterial mean pressure by blockage of G protein dependent pathway, TRV027 also increases cardiomyocyte contractility via β-arrestin pathway. Recently, it was demonstrated that selective β-arrestin 1 activation causes acute catecholamine secretion through coupling with the transient receptor potential cation channel subfamily C3, which may have contributed for TRV027 failure in phase II clinical trial for acute heart failure treatment.

9,10

Biased agonism has

also been described for other GPCRs and may open up new strategies for exploiting drug selectivity at an unprecedented level by drugging unique receptor conformational states.

11,12

Complex GPCR-associated phenomena such as constitutive activity, inverse agonism and biased agonism can be explained by receptor flexibility. The most accepted hypothesis is that GPCRs exists in an ensemble of conformations and each set of conformations can be associated with different activated states. Thus, biased ligands cause a shift in the equilibrium between states by stabilizing specific receptor conformations, resulting in receptor modulation.


13

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Despite biased agonism being widely accepted because of the stabilization of specific receptor conformations, the events leading to a biased AT1R conformation are still not described. Recently, AT1R structure bound to an antagonist was solved by lipid phase crystallography, presenting a great opportunity for ligand-binding interaction studies.14,15 In this sense, molecular dynamics (MD) simulations have been extensively applied to monitor transitions between different conformational states and to account for receptor flexibility.16 Previous AT1R ligand binding studies depended on homology models based on the structure of other GPCRs.17,18,19,20,21 Here we report the binding mode of biased agonist TRV027 using AT1R crystal and molecular dynamics simulation. Topological shifts in the receptor induced by ligand interactions and activation markers are also discussed.


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METHODS

Crystal Refinement and numbering scheme

AT1R crystal structure complexed with the antagonist ZD7155 was retrieved from the Protein Data Bank (PDB entry: 4YAY, resolution 2.9 Å).14 The MODELLER v. 9.07 software was used to build the following missing residues: 1-16 (N-terminal), 173-176 extracellular loop (ECL 1), 186-189 (ECL2), 225-234 intracellular loop (ICL 3) and 318-359 (C-terminal). Ramachandran plot analysis of the resulting model were made with RamPage.

22,23

All AT1R residues are

presented following two numbering schemes. The first one is based on the residue position in AT1R sequence, while the second one corresponds to the BallesterosWeinstein numbering scheme.

24

Molecular Dynamics Simulations

All MD simulation were performed using the GROMACS package v 5.0.6 with the CHARMM36 lipid force field.25,26,27 The receptor was inserted in a


6

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palmitoyl-oleoyl-phosphatidylcholine (POPC) lipid bilayer using the Inflate_GRO script as described elsewhere.28 Simulations were carried out in explicit solvent with the TIP3P water model and counter-ions (Cl- and Na+) were added at 0.15 M to keep the system neutral.29 Each system consisted of the receptor, 282 POPC molecules, 16,373 water molecules and 203 ions in a 10 x 10 x 10 nm simulation box. The leap-frog algorithm was used to integrate Newton’s equations of motion. The Verlet cut-off scheme was employed, along with a short-range electrostatic and van der Waals cut-off radii of 1.2 nm, the latter switched at 1.0 nm. Particle Mesh Ewald (PME) method was used to calculate long-range electrostatic forces.30 All bonds were constrained with the LINCS algorithm and allowing a time step of 2 fs in all simulations.

31

After minimization with steepest

descent algorithm, an initial equilibration phase under the NVT ensemble was performed for 2 ns, restraining the position of all heavy atoms of the receptor and the lipid bilayer, allowing ions and water molecules to move freely and solvate the protein and the charged head groups of the lipids. A second equilibration phase was conducted in the NPT ensemble for 10 ns, restraining


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only the heavy atoms of the protein. Such a long equilibration phase is necessary to allow lipid molecules to properly accommodate around the protein.32

MD production runs were performed with the same initial configuration but with random seeds to generate different initial velocities. Ten individual simulations of 200 ns each were performed, totaling 2 µs of simulation time. Running multiple simulations allows the system to explore different regions of the configurational space, improving sampling. Moreover, using multiple short trajectories instead of one long submicrosecond run prevents the system from undergoing transitions to nonadditive conformational states or persisting too long in high free energy regions, which would lead to a misrepresentation of the relevant population frequencies.33 During equilibration and production phases, semi-isotropic pressure coupling was applied to keep the lipid bilayer in the lamellar phase. Periodic boundary conditions were applied, and the Berendsen thermostat was used in the equilibration phases, with τT = 1 ps, while the Nosé-Hoover thermostat was used for the production run with τT = 0.5 ps, both having 310 K as reference


8

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temperature.

34,35,36

The Parrinello-Rahman barostat was used for NPT and

production phases in order to keep pressure at 1 bar, with τP = 2 ps.37

After reaching the stability of the MD simulation, the 10 trajectories were concatenated and the Jarvis-Patrick clustering method was used, having a RootMean-Square-Deviation (RMSD) cutoff value of 0.3 nm and considering carbons-α only. Clusters with the highest number of frames were selected and the most representative structure of each one of these clusters was used for docking studies.38

Trajectory Analysis

MD trajectories output were saved every 50 ps and converted to .xtc files for analysis. To investigate system stability, root mean square deviation (RMSD) and root mean square fluctuation (RMSF) of the protein backbone were calculated with g_rms and g_rmsf, respectively, for all the MD simulations. The presence of H-bonds during the simulations was evaluated with the g_hbond tool in


9


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GROMACS using the default cutoff angle value of 30° and a cutoff radius of 0.35 nm.39 Data regarding distances and dihedral angles were calculated with the g_dist, g_angle, g_spatial, and g_mindist tools, respectively, within GROMACS. Secondary structure overtime was assessed with the do_dssp module that uses the dictionary of secondary structure (DSSP).

40

Relevant interatomic distances

for receptor activation were measured for all the MD simulations and structural representations and visual inspections were made in PyMOL package.41,42

Molecular Docking

Ligand-protein docking studies were performed in GOLD version 5.2, using the flexible docking protocol.43 To validate GoldScore function, ZD7155 was redocked in the binding pocket of AT1R crystal (Supporting Info). A cubic box with 18 Å of lattice having His2566.51 as its center was defined for the docking runs.14 Criteria for pose selection were based on the literature as follows: (i) ligand-carboxylate terminal (COOH) interacting with ε-nitrogen from Lys1995.42; (ii) ligand-Arg2 guanidinium group interacting with Asp2787.29/Asp2817.32 side chain;


10

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(iii) ligand-Val3 positioned towards the binding site; (iv) ligand-Tyr4 hydroxyl group oriented towards Asn1113.35 side chain; (v) vertical positioning (N-terminal towards extracellular side and, consequently, C-terminal towards intracellular).41,44,45 Since ligand TRV027 differs from AngII by two residues, a sarcosine in position 1 and a D-Ala in position 8, therefore, the same criteria were used to select TRV027 poses.

Molecular Dynamics Simulations of the Ligand-Receptor Complexes

The five ligand-receptor complexes obtained from molecular docking were equilibrated and submitted to MD simulations following the same protocol described previously, totaling 2 µs. The parameters for sarcosine (N-methylglycine) were

obtained

from

the

CHARMM

General

Force

Field

(Cgenff).46

After

equilibration steps, a 3 ns simulated annealing (SA) protocol was applied to the systems (Table 1), followed by MD production runs. Due to disruption of the POPC bilayer at high temperatures, only the ligands and the receptor were


11


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subjected to the simulated annealing protocol, while keeping the POPC bilayer, counter-ions and water molecules at 310 K.32

Table 1. Simulated annealing temperature protocol.

Time (ps)

0

200

400

500

600

700

800

900

1000

1200

Temperature (K)

310

600

700

800

700

600

500

450

400

310

RESULTS AND DISCUSSION

Structure Preparation

Prior to molecular dynamics simulations, Ramachandran plot analysis of the complete AT1R model were conducted for assessing model quality (Figure 1). Accordingly, 96.6% of AT1R residues were in the “most favored” region, while the remaining 3.4% of the residues were in the “allowed” region. The whole receptor structure was kept rigid during refinement and, as a result of that,


12

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angular tension was created in residues following missing segments, which explains Asp17N-terminal and Thr190ECL2 occupying glycine allowed regions.

Figure 1. Ramachandran plot analysis of AT1R model. Residues are concentrated in the characteristic α-helix (-60 > Φ > -120 e -60 > Ψ > -120) and β-sheet regions (-60 > Φ > -120 e 60 > Ψ > -160).

The complete receptor (Figure 2) was embedded in a pre-equilibrated POPC bilayer with a lipid per area value of 0.63, similar to other CHARMM36 simulations and experimental data.47


13


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Figure 2. AT1R model after crystal refinement and lipid bilayer insertion. C-terminal loop region is shown in an extended conformation (cartoon representation). At left, AT1R domains division according to the 4YAY crystal structure: TMD transmembrane domain, ICL – intracellular loop, ECL – extracellular loop.14

Molecular dynamics simulation of the Apo receptor

To study AT1R in the apo form we conducted 10 simulations of 200 ns (2 µs in total) with the complete receptor starting conformation in the classic inactive state.14,48 Root mean square deviation analysis (RMSD) of non-hydrogen atoms showed that the receptor has reached conformational stability after 100 ns (Figure


14

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3). Nonetheless, when both N- and C-terminals were disregarded in this analysis, a significant decrease in RMSD was observed and conformational stability was reached at 40 ns in all simulations (Supporting info). Despite the great conformational freedom observed, in all simulations the C-terminal assumed a coiled conformation and anchored itself in the membrane. The residues responsible for the anchoring were Pro322C-terminal, Lys323C-terminal, Leu337C-terminal, Tyr339C-terminal,

Arg340C-terminal,

Pro341C-terminal,

Lys351C-terminal,

Pro354C-terminal,

Cys355C-terminal, Glu357C-terminal and Glu359C-terminal, similar to those described in the literature.

38

Since the main interactions and phenomena leading to the

receptor activation in the time scale employed here does not involve these regions, an interval spanning 40 ns was analyzed for conformational stability and served as input for the remaining analysis.


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Figure 3. Graphic representation of the Root Mean Square Deviation (RMSD) of AT1R heavy atoms with respect to the initial structure. A significant decrease in receptor flexibility is observed when the N- and C-terminal loops are disregarded (red) when compared to the whole receptor (black).


16

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Figure 4. Graphic representation of the Root Mean Square Fluctuation (RMSF) of concatenated AT1R molecular dynamics simulations, totaling 2 µs. Great flexibility is observed in N- (atoms 1-424) and C-terminal (atoms 5287-5918) regions, followed by intracellular loops (ICL). ECL2 drop in RMSF indicates the β-sheet position.

We analyzed the flexibility of each receptor domain (Figure 4) separately and observed that the intracellular loops (ICL 1-3) were more flexible than the extracellular counterparts (Figure 4). This decreased mobility/flexibility can be explained by the shorter length of the chains, the presence of the β-sheet secondary structure on the ECL2, and the presence of disulfide bonds (Cys18N-


17


terminal-Cys274ECL3

Page 18 of 48

and Cys1013.25-Cys180ECL2) connecting the N-terminal to ECL3,

and the ECL2 to TM3, respectively, restraining the movement of the extracellular portions of the TM. The absence of a ligand during MDs allows small fluctuations in TMs distances and residues side-chain positioning, resulting in a compression of the binding site cavity volume (data not shown). Because of this reduction in the volume of binding site cavity, conformers with insufficient volume for the ligand accommodation were excluded from the analysis.

After this initial structural analysis, all ten MD simulations (from 40-200ns) were concatenated and submitted to Jarvis-Patrick clustering method, resulting in 192 clusters. To balance receptor conformational sampling and computational cost, five clusters with the highest number of conformations were selected. The most representative conformer from each of these five clusters was used for the molecular docking studies.

Molecular Docking


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As mentioned earlier, several studies based on homology models and experimental techniques have been performed in order to explore and explain the binding mode of ligands in the AT1R.

17,19,20,21,41

Based on these studies and

the antagonist positioning in the crystal structure, poses containing the ligand in a non-vertical orientation, with the N-terminal pointing towards the extracellular side and C-terminal towards the intracellular side, were ignored despite their scoring function result. Regardless of the different conformations of the receptor used for the initial docking, all the resulting selected poses had the ligand-Val3 pointing towards the receptor binding site.

To ensure that differences in docking poses interactions were not the result of binding site compression during MD, AngII and TRV027 were also docked in the refined crystal structure

using the same docking protocol. The choice for

conducting molecular docking studies in structures retrieved from MD simulation instead of only the initial crystal structure considered the receptor conformational imprint imposed by the presence of an antagonist in the binding site. As the behavior of the AT1R varies accordingly to the stimuli, we opted for docking the


19


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ligands in the receptor without any ligand relaxed by MD simulations, minimizing the possible conformational changes induced by the presence of an antagonist. Resulting poses displayed similar interactions and positioning inside the cavity, because of that, we have opted to keep the original five poses (Figure 5, Figure 6) for the complex MD simulations.


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Figure 5. Molecular docking poses for angiotensin II-AT1R conformers selected from MD simulations (1-5) displayed as cavities (magenta, pymol cutoff value of -5). (A) Example of overlapping between AngII and AT1R (outside the cavity). Sticks and cartoon representation.


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Figure 6. Molecular docking poses for TRV027-AT1R conformers selected from MD simulations (1-5) displayed as cavities (green, pymol cutoff value of -5). Sticks and cartoon representation.


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Molecular dynamics simulations of the ligand-receptor complexes

One of the limitations of the molecular docking procedure is its inability to simultaneously compute the conformational changes of both ligand and receptor during the molecular recognition process. In order to overcome initial structural constraints and better accommodate ligands in the binding site, allowing them to possibly get out entrapping regions of local minimum of energy, simulated annealing (SA) runs were conducted prior to production MD runs. After this phase, we observed the formation of the characteristic saline bridge between AT1RLys1995.42 and AngII-COOH as well as the AT1R-Asp2787.29/Asp2817.32 and AngIIArg2 interaction, described in the literature as being important for the ligandreceptor recognition process. The last frame from each of the five SA runs were simulated in duplicates of 200 ns each, totaling 2 µs per system. For practical reasons, we describe the binding events for structure 2 only because it displayed the highest number of interactions described in the methods section. However,


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other analysis are averages of all parallel simulations and can be found in Supplementary Information section.

Figure 7. Ligand-receptor interactions during molecular dynamics simulation. AngIIAT1R after simulated annealing (A) and final MD frame (B). TRV027-AT1R after simulated annealing (C) and final MD frame (D). Hydrophobic cavity is partially showed (Phe772.53, Leu1123.36, Trp2536.48, Ile2887.39, Tyr2927.43). Sticks and cartoon representation.


24

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After the production MD runs, we observed that the N-terminal moiety of AngII forms a saline bridge with Asp2636.58 carboxylate (TM6), while the AngIIAsp1-COOH interacts with Arg23N-terminal, as found experimentally elsewhere.49 Differently from AngII, the presence of a methyl group in TRV027-Sar1 reduces the possibility of interactions with some of the ECL3 residues, such as the Asp2636.58 (Figure 7). In fact, the H-bonds in TRV027 residues from Sar1 to Tyr4 are less frequent than AngII (data not shown). This reduced number of hydrogen bonds contributes to the alternative positioning of the biased ligand in the cavity, and plays a role in the higher affinity of sarcosine based super agonists. Nonetheless, hydrogen bonds between TRV027-Sar1 and Asp2817.32 were observed, as well as TRV027-Arg2 interaction with Asp2817.32 in a similar way to AngII.

For both AngII and TRV027, the Pro7 is responsible for a backbone turn, restricting the position of the last residue. AngII-Pro7 interacts with Arg167ECL2 and AngII-Phe8 side chain is turned to the hydrophobic pocket (Phe772.53,


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Val1083.32, Leu1123.36, Trp2536.48, Ile2887.39, Ala2917.42 and Tyr2927.43). The residue Trp2536.48 is part of the CWxP motif (Val2466.41

Ile2546.49), mainly

composed of hydrophobic residues. Trp2536.48 is described as a “rotamer toggle” that initiates the TM6 residues rearrange related to receptor activation. This behavior was described for rhodopsin and the type 2 β-adrenergic receptor.50 We have observed that Trp2536.48 is oriented towards TM5, but once in contact with AngII-Phe8, Trp2536.48 shifts from vertical, in contact with the binding cavity, to a perpendicular orientation relative to the z-axis, leaning towards Leu1123.36 and Phe2045.47, located in TM4 and TM5, respectively. Both in apo and TRV027AT1R complex, Trp2536.48 side chains is oriented towards the hydrophobic cavity, suggesting that the bulky benzyl moiety in AngII-Phe8, absent in TRV027, could be responsible for the changes in the rotamer toggle conformation. In fact, other β-arrestin biased ligands such as SI ([Sar1,Ile8]Ang II), SII ([Sar1,Ile4,Ile8]AngII) and TRV23 ([Sar1,Lys5,Ala8]AngII) do share the small moiety in position 8 and could theoretically have similar results.

51

However, removal of position 8 in Ang1-

7 results in a weak biased agonist with a two-fold decrease in binding affinity


26

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and β-arrestin activation compared to AngII.

52

The absence of a bulky group in

TRV027 also allows a deeper positioning of

D-Ala8

Arg167ECL2

TRV027-COOH

less

frequent

but

stabilizing

rendering interactions with interactions

with

Lys1995.42, so the reduced β-arrestin activation in Ang1-7 could be the result of the hindrance of this interaction.

While the C-terminal of AngII establishes a stable saline bridge with Arg167ECL2, the side chain of AngII-Phe8 contacts Trp2536.48. The salt bridge between AngII-COOH and Lys1995.42, which was formed during the simulated annealing, is not preserved during production run. This event is accompanied by a separation of the extracellular portion of transmembrane domains, having the distance between Leu1614.42 and Lys1995.42 α-carbons changing from 11.0 Å to 15.3 Å in the first and last frame, respectively. However, the saline bridge between TRV027-COOH and Lys1995.42 is maintained along the simulation. We cannot assign this distance increment exclusively to the breakage of the salt bridge between AngII-COOH and Lys1995.42-NH2. Saline bridges are the combination of the two strongest interatomic interactions found in proteins, namely ionic


27


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interaction and hydrogen bond, but the increment in distance of TMs may involve other residues. Data from literature shows that Lys1995.42 mutation drastically decreases ligand affinity, but without affecting receptor activation.53 Thus, we hypothesized that the saline bridge breakage could be a normal event in AT1R agonist activation mechanism, while the maintenance of TRV027-COOH-NH2Lys1995.42 hydrogen bond keeping the receptor from leaving an intermediate active state, could be related to the biased agonist mechanism of action.

Using the do_dssp gromacs module we sampled the receptor average secondary structure over time. For the TMs, two main events were observed, one refers to a disturbance in α -helix angles and hydrogen bonds causing a helicity breakage, and the other refers to turns or kinks in TMs α-helixes. To assure that secondary structure changes observed in holo simulations resulted from binding site occupancy by the ligands, a new simulated annealing step was conducted with the last frame of the apo system (Figure 8). In fact, a disruption in all transmembrane segments was observed in the first nanosecond of the SA protocol. However, as the temperature decrease, secondary structure was


28

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promptly restored, indicating that differences observed were the result of ligand presence.

Figure 8. Secondary structure overtime of the apo receptor simulation displaying domains division. (A) Production molecular dynamics, (B) Simulated annealing using last frame from apo simulation.


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The apo receptor displays a stable α-helix turn in residues Leu1614.42 and Phe2045.47 localized in TM4 and TM5, respectively (Figure 8). It is worth mentioning that these turns are also present in the 4YAY crystal, but they are not constant in the holo systems (Figure 9). Leu1614.42 side chain is oriented towards the lipid bilayer, but Phe2045.47 is part of the hydrophobic pocket located just below sartans binding site, in fact, mutations in this residue leads to reduced binding affinity.54 The interval between Tyr2927.43-Asn298

7.49

presents a small

helicity fluctuations in the apo simulations, however holo systems displayed a clear helicity breakage. Cabana and collaborators used a homology model of AT1R and observed differences in the RMSD of a similar region (Ile2887.39Asn2957.46) when comparing apo and holo systems (AT1R-AngII and AT1R-SI), suggesting a greater flexibility in this region.21 This segment partially includes the NPxxY (Asn2987.49 -Tyr3027.53) motif, which plays a key role in receptor conformational changes induced by agonists). Mutations in Tyr2927.43 hinders G protein signaling and ligand binding. Similarly, mutations in Phe2937.44 and


30

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Asn2947.45

also

prevent

receptor

activation

and

G-protein

signaling,

respectively.55,56


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Figure 9. Secondary structure overtime of the holo receptor simulations. (A) AngIIAT1R simulations. (B) TRV027-AT1R simulations. Red arrows indicate helicity breaks (Residues Tyr2927.43-Asn2987.49) and turn regions (Residues Asn461.50, Leu702.46-Ala712.47 and Thr802.56-Leu812.57).


32

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MD simulations of AngII-AT1R also resulted in turns in Leu702.46-Ala712.47 segment, which belongs to the LALAD (Leu702.46-Asp742.50) portion in TM2. Numerous studies have already demonstrated the importance of Asp742.50 in G protein-dependent

receptor

activation.57,58

Accordingly,

mutagenesis

studies

suggests that agonist binding breaks Asn1113.35-Asn2957.46 hydrogen bond, allowing Asn2957.46/Tyr2927.43 to establish a hydrogen bond with Asp742.50.59,60,61 In fact, single or double mutations in Asp742.50 and Tyr2927.43 cause ligand binding and IP3 production impairment, indicating that they play a key role in receptor activation. The Asn1113.35-Asn2957.46 hydrogen bond is present in the crystal, but it is replaced by a stable Asp742.50-Asn2957.46 hydrogen bond in the apo simulations. Other molecular modeling studies suggests that the active receptor have a hydrogen bond network involving Asn461.50, Asp742.50 and Asn2957.46.20 Our results show a distinct hydrogen bond pattern for Asp742.50 in each system (Figure 10). While the Asn1113.35-Asn2957.46 hydrogen bond is present in the crystal, it is replaced by a stable Asp742.50-Asn2957.46 hydrogen bond in the apo simulations. The high stability of Asp742.50-Asn2957.46 and lack of other interactions


33


Page 34 of 48

suggest that TM2 is less flexible on the apo system. Turns or small helicity breaks are also observed in Asn461.50-Ile501.54 region on both holo systems, suggesting that changes in these regions could be associated with the different hydrogen bond pattern. In fact, Asp742.50 from AngII-AT1R system displayed interaction with Asn1113.35, Asn2957.46 and specially Asn461.50, which is believed to

participate

in

AT1R

activation.

Finally,

TRV027

system

displayed

an

intermediate behavior between both systems. The mutant N46D is constitutively active to the β-arrestin pathway, indicating that a shift to a negative charge and reduction in hydrogen bond donor capacity reduction leads to a biased receptor. However, suppression of interactions in N46G mutant leads to an inactive receptor.

21

Thus, the reduced number of Asn461.50-Asp742.50 hydrogen bonds

observed in TRV027 system suggests an Asp742.50 interaction pattern like the N46D mutant. The increased frequency in Asp742.50-Asn2957.46 hydrogen bond, like the apo system, reinforces the hypothesis that the biased ligand TRV027 would partially activate the receptor keep the receptor in an intermediate active state.


34

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Figure 10. Hydrogen bond patterns. (A) 4YAY crystal displaying the characteristic inactive Asn1113.35-Asn2957.46 hydrogen bond. (B) Apo receptor showing the stable Asp742.50-Asn2957.46 interaction. (C) AngII-AT1R system, showing the Asn461.50Asp742.50 with the helicity break in LALAD region and Asp742.50-Asn2957.46 hydrogen bonds. (D) TRV027-AT1R system showing the different positioning of Asp742.50 reducing the Asn461.50 hydrogen bond frequency. (E) Hydrogen bond frequency (2µs per system).


35


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The E/DRY is one of the most conserved motifs in Class A GPCR and is located in the intracellular portion of TM3. The R

3.50

is responsible for an

interaction network that includes the adjacent E/D3.49 and often the residue in position 6.30, which is called ionic lock. The ionic lock is a common GPCR activation marker present in rhodopsin and α1/β adrenergic receptors.

62,63

In the

inactive state, a hydrogen bond between R3.50 from the E/DRY motif and Asp/Glu6.30 keeps the TM3 and TM6 closer in a “locked position”, limiting G protein interaction with the intracellular portion of the receptor.64 When active, this salt bridge is broken and R3.50 interacts with D/R3.49. Despite the constitutively active mutant AT1R-DRY/AAY suggesting the existence of such mechanism for AT1R, the salt bridge interaction would not be possible in human AT1R because it lacks an acidic residue at the position 6.30.12 Nevertheless, we observed the rapid formation of a salt bridge between R1263.50 with the adjacent residue R2366.31. Not only this interaction is stable in a nanosecond scale, but it can also break, having Arg1263.50 interacting with Asp1253.49 (Figure 11), in an ionic lock fashion. The immediate shift of these hydrogen bonds accompanied by the


36

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distribution of minimum distances between residues reinforces the hypothesis of the ionic lock as a genuine feature of AT1R.


37


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Figure 11. Side chains minimum distance overtime of the residues pair Asp1253.49Arg1263.50 and Arg1263.49-Asp2366.31. (A) possible ionic lock interactions in “closed” (left) and “opened” (right) states. (B) Apo receptor simulation, showing the shift of interaction from an opened to a closed state. (C) AngII-AT1R and (D) TRV027AT1R displaying an opened ionic-lock.

CONCLUSION

Here we investigated AT1R under three different conditions to propose TRV027 biased ligand determinants. Our results show that TRV027 assumes a deeper positioning in the binding site and it also does not cause a rotamer toggle conformational rearrangement. We also observed that Asp742.50 hydrogen bond pattern and secondary structure analysis were able to identify exclusive events for each system. Collectively our data suggest that biased activation shares events from both full agonism and inactive state, but the frequency that these events occur is key to differentiate them. These finds can hopefully assist drug design efforts aiming for AT1R. Our computational results also suggest the existence of an ionic lock in AT1R, indicating the need for further BRET/FRET based experiments to test this hypothesis.


38

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AUTHOR INFORMATION Corresponding Author Carlota de Oliveira Rangel-Yagui: [email protected] Phone: +55 11 3091-2478

Author Contributions The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.

Funding Sources This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.

Notes The authors declare no competing financial interest.

ACKNOWLEDGMENT


39


Page 40 of 48

Research developed with HPC resources provided by the Information Technology Superintendence of the University of São Paulo.

ABBREVIATIONS (AT1R), angiotensin II type 1 receptor; (DSSP) dictionary of secondary structure; (ECL) extracellular loop; (GPCR), G protein-coupled receptor; (ICL) extracellular loop;

(MD)

molecular

phosphocholine; methylglycine;

dynamics;

(RAAS), (SA)

(POPC)

1-Palmitoyl-2-oleoyl-SN-glycero-3-

renin-angiotensin-aldosterone

simulated

annealing;

(TM)

system;

transmembrane;

(Sar)

N-

(TIP3P)

transferable intermolecular potential with 3 points.

Supporting Info In the supporting information we present the redocking results. We also make available the RMSD and DSSP from all other parallel simulations for each system.

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For Table of Contents

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Understanding biased agonism determinants in AT1R by molecular dynamics simulations Silvestre Massimo Modestia, Matheus Malta de Sá, Eric Auger, Gustavo Henrique Goulart Trossini, José Eduardo Krieger and Carlota de Oliveira Rangel-Yagui


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Biased Agonist TRV027 Determinants in AT1R by Molecular

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