# The dynamics of free and phosphopeptide-bound Grb2-SH2 reveals two dynamically independent subdomains and an encounter complex with fuzzy interactions

## Abstract

The growth factor receptor-bound protein 2 (Grb2) is a key factor in the regulation of cell survival, proliferation, differentiation, and metabolism. In its structure, the central Src homology 2 (SH2) domain is flanked by two Src homology 3 (SH3). SH2 is the most important domain in the recognition of phosphotyrosines. Here, we present the first dynamical characterization of Grb2-SH2 domain in the free state and in the presence of phosphopeptide EpYINSQV at multiple timescales, which revealed valuable information to the understanding of phophotyrosine sensing mechanism. Grb2-SH2 presented two dynamically independent subdomains, subdomain I involved in pY recognition and subdomain II is the pY + 2 specificity pocket. Under semi-saturated concentrations of pY-pep we observed fuzzy interactions, which led to chemical exchange observed by NMR. This information was used to describe the encounter complex. The association with pY-pep is dynamic, involving fuzzy interactions and multiple conformations of pY-pep with negative and hydrophobic residues, creating an electrostatic-potential that drives the binding of pY-pep. The recognition face is wider than the binding site, with many residues beyond the central SH2 binding site participating in the association complex, which contribute to explain previously reported capability of Grb2 to recognize remote pY.

## Introduction

Cell survival, control, proliferation, differentiation, and metabolism are mediated by a variety of well-orchestrated series of events. In this context, the growth factor receptor-bound protein 2 (Grb2) has demonstrated to be a key factor in regulating many cellular events. Grb2 is not an enzyme, instead, its multiple domains and flexible linkers provide the ability to bind to multiple partners in the cell. Grb2 is a pivotal intermediate in the communication between the cell-surface and downstream signaling1. Recently, Grb2 has been reported to have equilibrium between monomeric and dimeric states, which is critical for the activation and regulation of the Ras/mitogen-activated protein kinases (MAPKs) pathway2. The plasticity of Grb2 is essential for its biological function. It is widely known that the deregulation of MAPK pathway leads to many diseases, including cancer and developmental defects3,4,5,6.

Grb2 is composed of a central Src homology 2 (SH2) domain flanked by two Src homology 3 (SH3), a N- and C-terminus. The SH3 domain is well-known to recognize proline-rich sequences with the PxxP motif, while SH2 is the most important domain in the recognition of phosphotyrosines (pY)7,8,9. The SH2 has approximately 100 amino acid residues in globular modules with a well-conserved structure of a central antiparallel β-sheet flanked on each side by an α-helix. A remarkable point in the SH2 domains is the presence of two distinct binding pockets for the phosphopeptide recognition, where the pocket I (site I) is responsible for the pY binding to two conserved residues, RβB5 (R186) and HβD4 (H107), and the pocket II (site II) for the pY + 1, pY + 2 or even pY + 3 recognition8,10. Site II accounts for the specificity of the interaction. The phosphopeptide binds to SH2 as an extended linear conformation at the domain surface that spans from one α-helix to the other. An exception for this linear conformation is the interaction with the SH2 domain of Grb2, in which the W121 (site II) is a barrier, hindering the pY + 3 interaction. Grb2-SH2 preferentially selects pY + 2 asparagine sequences11,12.

Grb2-SH2 domain is able to form a domain-swapped dimer13,14,15,16, in which both α-helix 3 (α3) and part of the loop are involved in a major conformational change. The α3 opens and associates with the adjacent subunit of the dimer. The domain-swapped dimer is able to bind phosphopeptides with different affinities when compared to the monomeric state, sometimes with higher affinity and others with lower affinitiy14,15, contributing as another degree of freedom for Grb2 plasticity and ability of regulation. The biological role of the swapped domain is not well-known and there is no description of a cellular event with the participation of the swapped Grb2 dimer. The only structure available of the full-length Grb2 is not swapped17.

Here we present the first description of the dynamics of Grb2-SH2 domain. We verified that the Grb2-SH2 domain presents two dynamically independent subdomains, one of them in fast exchange regime (subdomain I) and other in intermediate exchange (subdomain II). The thermodynamic profile for a two-state conformational equilibrium of subdomain II in intermediate exchange regime was evaluated. We also evaluated the influence of Grb2-SH2 dynamics in the recognition of endothelial growth factor receptor (EGFR) derived phosphopeptide EpYINSQV (pY-pep) in a saturated and semi-saturated concentration. We characterized a recognition mechanism that involves the formation of an encounter complex as “binding intermediates”. Lastly, we demonstrated that the association of pY-pep to Grb2-SH2 is fuzzy and dynamic, which is essential for the molecular recognition of phosphotyrosines, where many residues beyond the central Grb2-SH2 binding site participates.

## Results

Our main purpose is the measurement of the dynamic properties of Grb2-SH2 domain and its role in the binding of pY-pep. This is the first description of the dynamics of Grb2-SH2 domain in the presence and absence of phosphopeptide. We chose the EGFR derived phosphopeptide EpYINSQV (pY-pep) because it leads to the dissociation of the Grb2, as described by Yuzawa et col. (2001)18. We measured the 15N nuclear spin relaxation parameters R1, R2 and 1H-15N-heteronuclear NOE (Figure S1), which showed that Grb2-SH2 domain is mostly rigid, displaying only a few residues involved in thermal motion (pico- to nanosecond timescale). They are mainly in the loop between α2 and β5. The most evident feature was the presence of an increased value of the R2/R1 ratio (Fig. 1A) in two regions: the first involving residues in α2, loop α2/β5 and β5, and the second in the loop β8/α3 and α3. We assigned 19 (BMRB ID 27,781) and calculated the structure of the Grb2-SH2 domain at pH 7.0 (PDB_id 6VK2) using CS-Rosetta20 with the ambiguously and unambiguously assigned NOEs derived from Aria/CNS (Figure S2, Table S1). A detailed description of the structure calculation is in the supplementary material.

These regions are in conformational exchange, and to get more insights into the dynamics we measured the 15N CPMG-RD at four temperatures and two fields (Figures S3, S4, S5, and S6). The CPMG-RD data (Fig. 1A) confirmed the observation of conformational exchange (increased R2/R1 ratio, Fig. 1B). The residues in the first region are at the site I, the phosphotyrosine (pY) recognition site and the residues in the second region are at the site II, the pY + 2 recognition site (Fig. 2A).

The analysis of the CPMG-RD curves showed that the residues in conformational exchange at site I are in fast exchange regime, while the residues at site II are in intermediate exchange regime (Figures S3, S4, S5, and S6). Although they belong to the same domain, they are dynamically independent. Grb2-SH2 has two dynamically independent subdomains: subdomain I (Fig. 2A, residues in green) for the residues in fast exchange involved in recognition site I, and subdomain II (Fig. 2A, residues in pink) for the residues in intermediate exchange involved in the recognition site II.

For the dynamic characterization of subdomain I, we looked for residues with no dispersion, but displaying R2eff above exchange-free R2eff∞. The most likely value R2eff∞ is represented by the dotted line in Figs. 1B and 2B, which represents an expected average value of R2eff for residue without exchange contribution21. The typical plot of 15N CPMG data observed for fast exchange regimes is where all the points in a flat profile are above the dotted line, meaning that much larger values of νCPMG would be necessary to refocus the exchange contribution to R2eff∞ (Fig. 2B). For details, see Figures S3, S4, S5, and S6.

As subdomain II presents residues in intermediate exchange regime, it was possible to characterize its thermodynamic profile for a two-state conformational equilibrium. We fitted the 15N CPMG-RD experiments at multiple temperatures using the Bloch-McConnell equation, which describes the evolution of the magnetization in a two-state exchange22,23. The Table S1 shows that the two-state exchange regime describes well the dynamics of subdomain II. To evaluate the quality of fitting and validity of the two-state exchange model we compared the statistical parameters (χ2 and degrees of freedom, DF) of individual fits for each residue, global fit at each temperature, and the global fit at all temperatures in two situations: (1) without any constrains; and (2) imposing Arrhenius linearity for the transition state and van’t Hoff’ linearity for the equilibrium between major and minor conformational states24. Since both global and individual fittings, χ2 < DF (global) and Σχ2 < ΣDF (individual), the global fitting is consistent with the two-state models. A more detailed description of the analysis is in the supplementary information.

The residues K124, F125, Y134, R136, and T138 presented a good 15N CPMG-RD profile. Because of the low number of residues in intermediate conformational exchange at subdomain II (Figures S3, S4, S5, and S6), there was a poor convergence of the population of the minor state (pB) for the global fitting at each temperature. Conversely, the global fitting at all temperatures and especially the constrained global fitting enabled a good convergence of pB. We obtained a good convergence for exchange constant (kex) in all situations. Figure 2C summarizes how to obtain the free energy landscape of a protein from the parameters obtained for the RD profiles. We used van´t Hoff equation to fit pB as a function of temperature and obtain the thermodynamics of equilibrium, and Eyring equation to fit kAB/kBA as a function of temperature to obtain the thermodynamics of the transition. These data enabled to obtain the thermodynamic parameters (∆G, ∆H, and ∆S) for the equilibrium and transition state (Fig. 3).

Figure 3A shows the pB and Fig. 3B the kex for global fitting at all temperatures without and with constraints. The increase in temperature led to a small decrease in pB and an increase in kex. This behavior reflected in the thermodynamic profile, which is observed in Fig. 3C.

The minor state (Fig. 3C) is enthalpically favorable and entropically unfavorable at 298 K. This is typical behavior of a conformational fluctuation involving the exposure of hydrophobic residues to the solvent24. Knowing that the conformational exchange involving loop β8/α3 and α3 may be associated with the observation, in several crystal structures, of a domain swap involving α3, which opens to interact with the adjacent subunit to form the swapped dimer13,14,15,16. The question that remains is whether the minor state is dimeric or monomeric. To answer this question, we acquired the 15N-CPMG-RD profiles at 278 K in a lower concentration (120 µM, ~ 2.5 × diluted). These profiles did not have significant changes (Figure S7), meaning that there was not the concentration-dependence expected for an oligomer. We concluded that the observed conformational exchange does not reflect a dimerization of the minor state nor domain swapping. Instead, the minor state is a result of conformational fluctuations of α3 in the monomeric state and related to the pY + 2 recognition.

To get insights on the structural changes at the minor state, we analyzed the differences in the chemical shifts (Δϖ) between the major and minor conformational states and compared with predicted values for the random coil25 and the intrinsically disordered domain (Prosecco26 and Poulsen27, Fig. 3D). The observed Δϖ´s are small when compared to the expected values for the unfolding/disordering of α3. The minor state is probably a result of the repositioning of α3, exposing hydrophobic residues to the solvent.

To correlate the dynamics with the phosphotyrosine sensing mechanism, we measured the effect of pY-pep binding on the Grb2-SH2 structure and dynamics. We analyzed the chemical shift perturbation (CSP) upon pY-pep binding (Fig. 4A). There were significant perturbations throughout the protein. When we looked at the most prominent CSPs at Grb2-SH2 structure (Fig. 4B), we verified the correlation with the peptide binding. Based on all the information available on PDB for complexes between Grb2-SH2 and different phosphopeptides, we calculated the atomistic probability density for the phosphopeptides bound to Grb2-SH2. The green mesh at Fig. 4B shows that the highest probability density is at positions pY, pY + 1, and pY + 2, in agreement with the CSP. Many of the perturbed residues are directly facing the atomic probability density of the phosphopeptides (green mesh), at subdomain I, E89 in the loop β5/β6, the same regions observed in the calculated structure as open (Figure S2D), R86 that directly binds to pY, and S96. At subdomain II, L111 of the β-hairpin β7/β8 (the highest CSP) and Q144 also bind directly to the phosphopeptide. In contrast, the probability density map of the backbone of the bound structures in the PDB is closed (Figure S2D). Residue F62, N129, and R136 are on the opposite face. It is noteworthy that in the full-length Grb2 the F62 and R136 are facing the dimerization interface. It was previously reported18 that the binding of pY-pep leads to the dissociation of the dimeric Grb2. The binding of pY-pep also affected residues at α3 (N129 and T138). L111 and T138 were the ones with the highest CSP.

Next, we measured the 15N CPMG-RD for a saturated concentration of pY-pep (6 mM) (Fig. 4C, S8, and S9). At this condition, most of the conformational exchange observed for subdomains I and II is quenched. This is typical of a conformational selection mechanism of binding.

We also measured the 15N CPMG-RD for a semi-saturated concentration of pY-pep (2.1 mM) (Fig. 5). We took advantage of the chosen experimental conditions at 20 mM inorganic phosphate and 200 mM NaCl. The inorganic phosphate competes with the pY-pep for the binding to R86 while the NaCl shields electrostatic interactions. At this condition the pY-pep binds with millimolar affinity, enabling the observation by NMR of “binding intermediates” in the process of molecular recognition. We observed, in the presence of a semi-saturated concentration of pY-pep, that residues acquired relaxation dispersion (Fig. 5A). Interestingly, these residues are at the same surface of the recognition site as shown in Fig. 5C. It is noteworthy that the residues that took part in exchange processes are uniquely at the pY-pep molecular recognition face. In the context of the full-length Grb2, this surface is exposed to the solvent, not involved in inter-domain or inter-subunit contacts.

We proposed a mechanism for pY-pep molecular recognition that involves the formation of an encounter complex as “binding intermediates” in the process (Fig. 5D). The recognition surface of the encounter complex is wider than that of the stabilized complex. Fuzzy interactions of pY-pep led to an uncertainty of the position of the pY-pep at the encounter complex that generates a chemical exchange that could be observed by NMR. In this mechanism, the residues that gained exchange are those involved in the tethering of pY-pep (or pY-pep´s) in the encounter complex. It is interesting to observe that some of these residues are negatively charged (E72, E89, D10), which were surrounding the positively charged R86 at site I, the responsible for the direct binding to the phosphate of phosphotyrosine. Hydrophobic residues also were found in the encounter complex (I65, A68, L84, F108, L111, and V122). It is noteworthy that L111 showed the highest CSP, no conformational exchange in the free state and gained relaxation dispersion in the presence of semi-saturated concentrations of pY-pep (Figure S10 and S11). Ross & Subramanian28 described the importance of hydrophobic surfaces in the formation of encounter complexes, with the first step of mutual penetration of hydration layers causing solvent disorder followed by further short-range interactions.

To better understand the dynamics of Grb2-SH2 domain and the mobility of pY-pep relative to the domain, we run 1 µs molecular dynamics simulations (MD) for the free domain and complexed with the pY-pep. By analyzing the root mean square fluctuation (RMSF, Fig. 6A), we observed four main conformational flexible regions, the N- and C-terminal residues, the loop β5/β6, and the hairpin β7/β8, both in the presence and absence of pY-pep (Fig. 6A). The conformational flexibility in these regions could not be observed in the nuclear spin relaxation parameters (Figure S2), which reflect the thermal flexibility in a timescale smaller than the overall rotational correlation time (τc, sub-τc dynamics). Based on the R2/R1 ratio, we estimated τc to be ~ 6.5 ns. The motions observed in the MD simulations are probably related to supra-τc dynamics (tenths of ns to  µs), which could not be observed either by 15N nuclear spin relaxation parameters or 15N CPMG-RD. Supra-τc dynamics are described to regulate the “on” rates in the molecular recognition process29.

In the complex, there was a slight increase in supra-τc flexibility for loop β5/β6 and hairpin β7/β8, and the C-terminal loop between residues 140 and 150. There was also a decrease in supra-τc flexibility for residues in α2, loop α2/β5, and loop β6/β7. This observation corroborates with the CSP results observed upon the addition of pY-pep (Fig. 4A,B), for which these regions presented significant CSP values. Highlighting that L111 in the hairpin β7/β8, and N143 and Q144 in the C-terminal loop are very important residues for the binding and L111 is part of the encounter complex (Figure S10 and S11), demonstrating the importance of these regions to the recognition of pY-pep and the complex formation. This behavior of increased flexibility of Grb2-SH2 in the presence of pY-pep was corroborated by the analysis of the root mean square deviation (RMSD) relative to the starting structures (Figure S12A). In the presence of pY-pep there is a wider fluctuation of RMSD around its average value when compared with the free domain. We also observed a stability point for the values of RSMD after ~ 500 ns for the free Grb2-SH2 domain, while for the pY-pep bound domain this stability point was observed since the beginning of the simulation.

The MD simulations helped describe the position and mobility of pY-pep relative to the domain. As expected, positions pY, pY + 1, and pY + 2 were well determined, presenting a high atomistic probability density at these positions (Fig. 6B). In contrast, the positions pY + 3, pY + 4, and pY + 5 showed high mobility and low atomistic probability density. This behavior agrees with the expected specificity mapping for Grb2-SH230, with no participation of pY + 3. It is remarkable that even though R86( +)/pY(-) interaction is present along with all the MD simulation, the backbone position varies significantly for all peptide, even at the postions pY and pY + 1, showing the presence of multiple conformations of the peptide at the recognition face (Fig. 6B).

To describe the supra-τc motions, we analyzed the trajectories of the MD simulations using principal component analysis (PCA). The two main principal-components (PC1 and PC2) showed an oscillation among different conformational sub-states along the simulation time (Figure S12B). For the free domain, we observed a convergence toward a stabilized conformation both in PC1 and PC2 after ~ 400 ns of simulation (2 to 3 for PC1 and 0 to − 2 for PC2 in Figure S12B). We must be careful before attributing a convergent structure for the free domain, because, with longer simulation time it could be reverted, representing a lower-frequency oscillation. For the complex, we observed no stability point, both in PC1 and PC2, without a convergence, agreeing with the gained supra-τc flexibility that denotes a higher frequency oscillation of possible conformational sub-states of the protein. The plot PC2 versus PC1 (Fig. 6C) showed the interconversion among different conformational sub-states. For both free and complexed Grb2-SH2 domain, we observed different interconverting conformational sub-states. Interestingly, the conformational sub-state with PC1 in the range between −1.5 and 1 and with PC2 between 0 and 3 are common between the free and complexed domain. It is important to note that this sub-state is the starting point for the MD simulation of Grb2-SH2 and the ending point for the complexed protein. It is worth mentioning that the starting point was the crystal structure from PDB_id 1BMB31 striped of the complexed peptide. The PCA was done with the two MD simulations concatenated in the same trajectory file, which enabled the direct comparison of the eigenvectors PC1 and PC2 for both free and complexed MD simulations.

The structural extent of supra-τc conformational dynamics is depicted in Fig. 6D. Note that loop β5/β6 and the hairpin β7/β8 presented the main structural changes responsible for PC1 and PC2. Those are the regions with the highest RMSF and higher flexibility in the presence of pY-pep. The extent of structural change in the presence of pY-pep was more pronounced than for the free domain. This could also be observed for the C-terminal loop, containing the residues N143 and Q144. Remarkably, these are the same regions for which we observed the open-to-close conformational transition in the calculated structure (Figure S2C).

## Discussion

Here we present the dynamical behavior of Grb2-SH2 domain and its relationship with the molecular recognition of phosphopeptides. We showed that this domain behaves as two dynamically independent subdomains, suggesting a correlation with previously described properties of Grb2-SH2. There are many reports on the dynamics of SH2 domains. However, a full characterization of an SH2 domain in the milli-to-microsecond timescale was not available. Many of the contributions correlate backbone dynamics in the pico-to-nanosecond timescale with the binding of phosphopeptide recognition32,33,34,35,36,37. In the present manuscript we described the dynamical behavior in multiple timescales, but with an emphasis on the conformational exchange (milli-to-microseconds), which is the timescale related to molecular recognition (koff).

The dynamical data showed that subdomain I is involved in microsecond dynamics while subdomain II in millisecond dynamics, suggesting independence in the association of the pY recognition (subdomain I) and pY + 2 recognition (subdomain II). We proposed that the dynamics at subdomain II involves a minor conformational change that exposes hydrophobic residues to the solvent. We present here the first dynamical characterization of Grb2-SH2, revealing a torsion/reorientation mechanism of α3, an important conformational state for the binding specificity of pY + 2 and allosteric events.

Our data showed that pY-pep recognition occurred by conformational selection, in which a conformational state is stabilized. The phosphopeptide association is specific for the exposed-face of the full-length Grb2, the recognition-face (Fig. 5C). Before the formation of a stabilized-complex, an encounter complex was formed involving negatively charged and hydrophobic residues, creating an electrostatic potential that drives the association of the phosphotyrosine (pY) to R86 (Figure S14A). This fact suggests that the association can be driven by Coulombic and hydrophobic interactions. The observation of an encounter complex led to the conclusion that the recognition face is wide, with fuzzy interactions with the phosphopeptide. There are still many unanswered questions regarding the phosphopeptide recognition by SH2 domain. One of the most intriguing is regarding the recognition of remote phosphotyrosines38. This is biologically relevant for proteins with multiple phosphorylations. This manuscript did not fully explain this effect, but the wide recognition interface and the fuzzy interaction with the phosphopeptide point toward a possible mechanism of how remote phosphotyrosines are sensed by SH2 domain.

The high-resolution structure of the free-state (PBD_id 6VK2) enabled the characterization of an open conformation, in which β5/β6 and C-terminal loops undergo an open-to-close conformational transition upon binding of phosphopeptides. These loops, along with the hairpin β7/β8, are far apart, demonstrating that the recognition surface is wide. The structural changes are in agreement with CSP and dynamic description of the free and bound-states, and the presence of “binding intermediates” in the encounter complex.

The PCA of the MD simulations showed that there are different conformational sub-states for the free and complexed domain, where the pY-pep can assume multiple conformations since the position pY presented the highest atomistic probability density, followed by pY + 1 and pY + 2, and the conformations at positions pY + 3 to pY + 5 were very diverse. Interestingly, the presence of pY-pep increased the extent of conformational transitions among the different sub-states. In agreement with our experimental results, Lindfors et al. (2012)39 used spin-labeled phosphopeptides to probe the interaction with SH2. The peptide assumes multiple orientations at the interacting surface. The electrostatic interactions involving charged patches of the protein resulted in an ensemble of rapidly exchanging orientations, suggesting a dynamic encounter state. This behavior shows that high-affinity binding can be dynamic and that residues outside the central SH2 binding site are also important for the Src-FAK interaction39.

The formation of the dynamic association and encounter complexes is a millisecond timescale event and involved the quenching of the dynamics of subdomain I and subdomain II. The MD simulations pinpointed important motions probably in a faster supra-τc dynamics, which involves mainly three regions of the protein: loop β5/β6 at subdomain I, and hairpin β7/β8 and the C-terminal loop, both at subdomain II. Multiple timescale dynamics are pivotal for recognition events. It is noteworthy that the slow µs-ms dynamics is related to the “off” rates, while the supra-τc dynamics (tenths of ns to µs) to the “on” rates in a molecular recognition process29. The wide and dynamic character of the recognition face is also evidenced by the MD simulation. There is a good correspondence between the contact map of Grb2-SH2 (Figure S13) and pY-pep and the CSP. All the regions mapped by CSP and CPMG relaxation dispersion were observed in the MD-simulation.

Our data also showed that the association of pY-pep to the recognition-face led to chemical shift changes in the opposite face, such as F62 and R136 that are involved in dimeric contacts in the full-length Grb2. The F62 is at subdomain I and R136 at subdomain II. This observation is suggestive of an allosteric event triggered by pY-pep association, which is in agreement with the fact that the association of pY-pep leads to the monomerization of full-length Grb218. The monomer–dimer equilibrium of Grb2 is biologically relevant and pivotal for the regulation of signal transduction pathways 3,4,5,6. The Grb2 dimer interacts with the fibroblast growth factor receptor 2 (FGFR2) which in turn activates the Ras/MAPK pathway, while its monomeric form is inhibitory for the signaling. Ras/MAPK is important and widely studied via related to a variety of cancer and development defects2,3. Further studies are necessary for a better understanding of the mechanism of monomerization. Plasticity is a major feature of an adaptor protein such as Grb2. The present manuscript detailed many of the residues involved in the dynamic of the free and bound states of the Grb2-SH2 domain, which is the basis for future studies of the plasticity of Grb2.

The dynamics of subdomain II, showed the exposure of hydrophobic surfaces with the repositioning/reorientation of α3. The possibility of this dynamics to contribute to the domain swap was considered, once the α3 is the helix involved in the swapping mechanism13,14,15,16. However, our results showed that the observed dynamics is not involved in the swapping mechanism. Domain swap for Grb2-SH2 domain occurs in a different timescale (minutes/hours) from the observed α3 dynamics (ms) and the swapped dimer can be separated in a gel-filtration column. Moreover, we showed that Grb2-SH2 is monomeric in the major and minor states. The biological role of the domain swap in the Grb2-SH2 is not fully understood and further studies are necessary. Grb2-SH2 domain-swap would add another degree of freedom for Grb2 plasticity and could be important, but it was never observed in the full-length Grb2.

In conclusion, we propose a mechanism of phosphotyrosine recognition by Grb2-SH2 domain, which involves a wide recognition face and a dynamic association of the phosphopeptide. We verified the formation of an encounter complex as “binding intermediates” involving the exposed face of the SH2 domain of the full-length Grb2. This is biologically relevant for an adaptor protein, such as Grb2, since it potentially increases the scope of interaction. In agreement with this conclusion, it has been reported that Grb2 is able to sense remote phosphotyrosines. Huang et cols (2017) showed that the binding affinity for the linker of activation of T-cells (LAT) and Grb2 depends on the phosphorylation of remote tyrosine sites38. This capacity could be conferred by the dimeric stated of full-length Grb2, but also by the wide and dynamic character of SH2 domain to recognize phosphopeptides.

## Materials and methods

### Protein expression and purification

The SH2 domain – 6 × histidine tagged (Grb2-SH2)—was expressed and purified as previously described by Sanches et al. (2019)19. Chemical shifts are deposited in the Biomagnetic Resonance Bank (www.bmrb.wisc.edu) under accession number 27781.

### NMR spectroscopy

All NMR samples of Grb2-SH2 was in 20 mM sodium phosphate buffer, 200 mM NaCl, pH 7.0, 10% D2O. NMR spectra were acquired at 25 ºC on Bruker Avance III 600 MHz, Avance III 800 MHz and Avance IIIHD 900 MHz, equipped with 15N/13C/1H triple-resonance probes (Bruker TXI). NMR spectra were processed with NMRPipe40 and analyzed using CCPNmr Analysis software41. The detailed experimental setup for all NMR experiments are in Table S3.

### Structure calculation

Distance restrains were derived from 15N-NOESY-HSQC and aliphatic and aromatic 13C-NOESY-HSQC collected at an AVANCE III HD 900 MHz, for aromatics and aliphatics. The 3D-NOESY-HSQCs were obtained using non-uniform sampling (NUS, 50%) with multidimensional Poisson Gap scheduling. NMRPipe and iterative soft threshold (hmsIST) fast reconstruction of NMR data were used for processing42 (Table S3). We run TALOS-N43 for backbone chemical shift-based dihedral angle prediction. The predicted backbone dihedral angles ϕ and ψ of the residues involved in secondary structure were used as a restraint for structural calculations.

Structure calculation of the Grb2-SH2 was performed iteratively using ARIA 2.1 program, version 2.344,45 combined with CNS version 1.246, using 15N-NOESY-HSQC and aliphatic and aromatic 13C-NOESY-HSQCs datasets as the source of distance restraints. The CCPN/Aria interface was used41.

The converged structure using Aria/CNS generated an ensemble of well-converged structures (Figure S1A) that was generated from 697 unambiguous and 277 ambiguous distance restraints. Next, the structural calculation proceeded using Chemical-Shift Rosetta (CS-Rosetta, ROSETTACOMMON Version 3.7 run at NMRBOX47. All the intra-residue NOEs were removed in CS-Rosetta calculation. The sequential, medium, and long-range distance restraints generated using Aria/CNS were then converted to the Rosetta format and used as distance restraints. 13C, 15N, and 1H NMR chemical shifts were used as inputs (BMRB 2778119 for fragment picking, along with 479 NOE-based distance restraints. 66,317 structures generated by the standard CS-ROSETTA protocol. The 20 lowest energy structures were deposited in the protein data bank (PDB id 6VK2).

The structural ensemble was visualized and analyzed with PyMOL. Quality validation was Protein Structure Validation Software suite (PSVS) (https://montelionelab.chem.rpi.edu/PSVS/) and Molprobity (https://molprobity.biochem.duke.edu/)49.

### Nuclear spin relaxation parameters

15N backbone amide relaxation parameters (15N R1, 15N R2 and 1H-15N heteronuclear Nuclear Overhauser effect—NOE) were measured for a 15N labeled Grb2-SH2 (300 µM, in 20 mM sodium phosphate buffer, 200 mM NaCl, 10% D2O, pH 7.0) using Avance III HD 800 (18.8 T, operating at 800.4 MHz) at 25 °C. R1 was measured with delays ranging from 0.05 to 1 s. R2 was measured with delays varying from 17 to 170 ms. The experimental error was evaluated from the signal-to-noise ratio of the spectra. The 1H-15N NOE was acquired with or without proton saturation for 6.0 s. Details of the NMR experiments are in Table S3. The R1 and R2 values were obtained using the relaxation module of CcpNmr Analysis 41. The 1H-15N heteronuclear NOE values were determined using the intensity saturation spectra/intensity without the saturation spectra ratio.

### 15N Relaxation dispersion measurements

15N Carr–Purcell–Meiboom–Gill relaxation dispersion (CPMG-RD) profiles for a 15N labeled Grb2-SH2 (300 µM, in 20 mM sodium phosphate buffer, 200 mM NaCl, 10% D2O, pH 7.0) were recorded in Bruker Avance III 600 (14.09 T, operating at 600.03 MHz) and Avance III 800 (18.8 T, operating at 800.4 MHz) at four temperatures (278, 283, 290 and 298 K) using the constant relaxation time of Trelax = 30 ms (15N CPMG relaxation compensation49. R2effCPMG) were calculated from peak intensities (I) in a series of two-dimensional (2D) 1H-15N correlation spectra recorded in an interleaved way at different CPMG frequencies νCPMG, (ranging from 66.7 to 1,000 s-1) using the following equation: $$R_{2}^{{eff}} \left( {\nu _{{CPMG}} } \right) = ~ - {\raise0.7ex\hbox{1} \!\mathord{\left/ {\vphantom {1 {T_{{relax}} }}}\right.\kern-\nulldelimiterspace} \!\lower0.7ex\hbox{{T_{{relax}} }}}\ln \left( {{\raise0.7ex\hbox{I} \!\mathord{\left/ {\vphantom {I {I_{o} }}}\right.\kern-\nulldelimiterspace} \!\lower0.7ex\hbox{{I_{o} }}}} \right)$$, where I is the signal intensity in the spectra collected at Trelax = 30 ms and I0 is the signal intensity in the reference spectrum recorded at Trelax = 0. The experimental error in R2eff rates were estimated signal to noise ratio for each resonance $$\Delta R_{2}^{{eff}} \left( {\nu _{{CPMG}} } \right) = ~{\raise0.7ex\hbox{1} \!\mathord{\left/ {\vphantom {1 {T_{{relax}} }}}\right.\kern-\nulldelimiterspace} \!\lower0.7ex\hbox{{T_{{relax}} }}}\left( {{\raise0.7ex\hbox{1} \!\mathord{\left/ {\vphantom {1 {(SIGNAL/NOISE)}}}\right.\kern-\nulldelimiterspace} \!\lower0.7ex\hbox{{(SIGNAL/NOISE)}}}} \right)$$.

### Amide chemical shift temperature coefficient

Amide 1HN chemical shift temperature coefficient of Grb2-SH2 (300 µM, in 20 mM sodium phosphate buffer, 200 mM NaCl, 10% D2O, pH 7.0) was measured in the presence and absence of the pY-pep. A series of two-dimensional 15N/1H HSQC spectra at 278, 283, 290 and 298 K was acquired (Bruker Avance III HD 800 18.8 T, operating at 800.4 MHz). The water chemical shift was referenced using 3-(trimethylsilyl)propane-1-sulfonic acid (DSS). Each spectrum was referenced to the water signal at each temperature. They were processed using NMRPipe and analyzed using CcpNmr Analysis. The amide chemical shift values (δHN) of all residues at different temperatures were plotted as function of the temperature, and the slope (dδHN/dT) of every curve was plotted for each Grb2-SH2 residue.

### Phosphopeptide binding

The binding of the phosphopeptide EpYINSQV (sequence from the Epidermal Growth Factor receptor, pY-pep18 to Grb2-SH2 (300 µM, in 20 mM sodium phosphate buffer, 200 mM NaCl, 10% D2O, pH 7.0, 298 K) was evaluated by chemical shift perturbation (CSP) using the 15N-HSQC spectra with and without pY-pep. CSP values were calculated using the equation $$CSP=\sqrt{{0.5\left({\Delta \delta }_{H}\right)}^{2}+{0.5\left({\Delta \delta }_{N}/10\right)}^{2}}$$.

### Construction of the probability map

We created a map of the weighted atomic density using the function VOLMAP in Visual Molecular Dynamics (VMD)50 software. The atomistic probability map was calculated (i) over an ensemble containing all Grb2-SH2 complexed with phosphopeptides available at the protein data bank (RSCB PDB), except the domain-swapped Grb2-SH2 dimers and (ii) an ensemble of 100 structures collected at each 10.000 frames of the molecular dynamics simulation of Gbr2-SH2 and of Grb2-SH2 complexed with the docked pY-pep.

### Computational simulations of the free and pY-pep bound Grb2-SH2 domain

The structure of the Grb2-SH2 domain used for computer simulations was downloaded from PDB website under access code 1BMB31. The phosphopeptide and water molecules in the crystal structure were removed. The domain and pY-pep were prepared using AutoDockTools program51 for molecular docking simulations, merging non-polar hydrogen atoms and adding atom types. The pY-pep rigid root was generated automatically, setting all possible rotatable bonds defined as active by torsions. The protonation states of ionizable residues of the protein were defined according to PROPKA software52 from PDB2PQR webserver53, considering pH 7.0. The molecular docking calculations were performed by using AutoDock Vina54, applying a total of 16 exhaustiveness. The coordinates of the center of the conformational search box at the protein binding site were defined according to the CSP results and the atomic probability density map generated from Grb2-SH2 crystal structures complexed with phosphopeptides available in PDB website. The box dimensions were 30 × 26 × 26 Å on the three coordinate axes.

Molecular dynamics (MD) simulations were performed in GROMACS version 5.0.155 using the AMBER99SB-IDLN force field56 for modeling the Grb2-SH2 domain and pY-pep. TIP3P57 was used as water model. The starting position of the pY-pep for the MD simulations was obtained from the molecular docking calculations. The structures of the free protein (PDB-ID 1BMB) and complexed with pY-pep (from AutoDock Vina) were each placed in the center of a 66 Å cubic box solvated by a solution of 200 mM NaCl in water, and the protonation state of ionizable residues was determined by PROPKA results, considering a pH 7.0. The periodic boundary conditions and NPT ensemble were used in all simulations, keeping the systems at 298 K and 1.0 bar using Nose–Hoover thermostat ($$\tau_{T}$$ = 2.0 ps) and Parrinello-Rahman barostat ($$\tau_{P}$$ = 2.0 ps and compressibility = 4.5 × 10–5 bar-1). A 12 Å cut-off point for the Lennard–Jones and Coulomb potentials was used. The long-range electrostatic interactions were calculated using the particle mesh Ewald (PME) algorithm. The simulations were performed using a time step of 2.0 fs and all covalent bonds involving hydrogen atoms were constrained to their equilibrium distance. A conjugate gradient minimization algorithm was utilized to relax the superposition of atoms generated in the box construction process. Energy minimizations were carried out with steepest descent integrator and conjugate gradient algorithm, using 500 kJ mol-1 nm-1 as maximum force criterion. At the end of preparation, 1.0 μs MD simulation of the free and pY-pep bound Grb2-SH2 were performed for data acquisition. Following dynamics, the trajectories of free and pY-pep bound domain were firstly concatenated individually and analyzed according to root mean square deviation (RMSD) of backbone atoms and root mean square fluctuation (RMSF) with respect of the C atoms of the protein. A total of 100 equally spaced frames over MD simulation time containing only pY-pep structural information were extracted for the evaluation of mobility of the phosphopeptide and for the also construction of the atomic probability density map as mentioned in the previous section. After individual analysis of each simulation, the trajectories for the free and pY-pep bound protein excluding the initial 1.0 ns were concatenated in a single file, and this new trajectory was used to the Principal Component Analysis (PCA). This aspect is important because ensures the same eigenvectors (PC1 and PC2) for both MD simulations, enabling us to directly compare the occurrence of conformational sub-states. The average structure used as a reference in the PCA calculations was obtained from the first 9.0 ns. The values of PC1 and PC2 were calculated considering the respective portions of simulation time for the free and complexed protein. For a visual inspection of motions related to the principal components, 30 frames containing Grbs2-SH2 structural information were extracted from PC1 and PC2 in the simulation time ranges correspondent to the free and pY-pep bound protein. The structural representations were prepared using PyMol58.

## Acession numbers

The atomic coordinates, experimental restraints and chemical shift assignments are available at the Protein Data Bank (PDBID 6VK2) and Biomagnetic Resonance Data Bank (BMRB ID 27781).

## Abbreviations

Grb2:

Growth factor receptor-bound protein 2

SH2:

Src homology 2

MAPK:

Mitogen activated protein kinase

NMR:

Nuclear magnetic resonance

CPMG:

Carr–Purcell–Meiboom–Gill pulse train

CSP:

Chemical shift perturbation

RMSD:

Root mean square deviation

RMSF:

Root mean square fluctuation

## References

1. 1.

Tari, A. M. & Lopez-Berestein, G. GRB2: a pivotal protein in signal transduction. Semin. Oncol. 28, 142–147 (2001).

2. 2.

Ahmed, Z. et al. Grb2 monomer–dimer equilibrium determines normal versus oncogenic function. Nat. Commun. 6, 7354 (2015).

3. 3.

Lin, C.-C. et al. Inhibition of basal FGF receptor signaling by dimeric Grb2. Cell 149, 1514–1524 (2012).

4. 4.

Ornitz, D. M. & Itoh, N. The fibroblast growth factor signaling pathway. Wiley Interdiscip. Rev. Dev. Biol. 4, 215–266 (2015).

5. 5.

Dhillon, A. S., Hagan, S., Rath, O. & Kolch, W. MAP kinase signalling pathways in cancer. Oncogene 26, 3279–3290 (2007).

6. 6.

Molina, J. R. & Adjei, A. A. The Ras/Raf/MAPK pathway. J. Thorac. Oncol. 1, 7–9 (2006).

7. 7.

Rozakis-Adcock, M., Fernley, R., Wade, J., Pawson, T. & Bowtell, D. The SH2 and SH3 domains of mammalian Grb2 couple the EGF receptor to the Ras activator mSos1. Nature 363, 83–85 (1993).

8. 8.

Machida, K. & Mayer, B. J. The SH2 domain: versatile signaling module and pharmaceutical target. Biochim. Biophys. Acta Proteins Proteomics 1747, 1–25 (2005).

9. 9.

Lowenstein, E. J. et al. The SH2 and SH3 domain-containing protein GRB2 links receptor tyrosine kinases to ras signaling. Cell 70, 431–442 (1992).

10. 10.

Vidal, M., Gigoux, V. & Garbay, C. SH2 and SH3 domains as targets for anti-proliferative agents. Crit. Rev. Oncol. Hematol. 40, 175–186 (2001).

11. 11.

Ijaz, M. et al. The role of Grb2 in cancer and peptides as Grb2 antagonists. Protein Pept. Lett. 24, 1084–1095 (2018).

12. 12.

Marengere, L. E. M. et al. SH2 domain specificity and activity modified by a single residue. Nature 369, 502–505 (1994).

13. 13.

Papaioannou, D., Geibel, S., Kunze, M. B. A., Kay, C. W. M. & Waksman, G. Structural and biophysical investigation of the interaction of a mutant Grb2 SH2 domain (W121G) with its cognate phosphopeptide. Protein Sci. 25, 627–637 (2016).

14. 14.

Benfield, A. P., Whiddon, B. B., Clements, J. H. & Martin, S. F. Structural and energetic aspects of Grb2-SH2 domain-swapping. Arch. Biochem. Biophys. 462, 47–53 (2007).

15. 15.

Hosoe, Y. et al. Structural and functional properties of Grb2 SH2 dimer in CD28 binding. Biophys. Physicobiol. 16, 80–88 (2019).

16. 16.

Nioche, P. et al. Crystal structures of the SH2 domain of Grb2: highlight on the binding of a new high-affinity inhibitor. J. Mol. Biol. 315, 1167–1177 (2002).

17. 17.

Senior, M. M. et al. The three-dimensional solution structure of the Src homology domain-2 of the growth factor receptor-bound protein-2. J. Biomol. NMR 11, 153–164 (1998).

18. 18.

Yuzawa, S. et al. Solution structure of Grb2 reveals extensive flexibility necessary for target recognition. J. Mol. Biol. 306, 527–537 (2001).

19. 19.

Sanches, K., Caruso, ÍP., Almeida, F. C. L. & Melo, F. A. NMR assignment of free 1H, 15N and 13C-Grb2-SH2 domain. Biomol. NMR Assign. https://doi.org/10.1007/s12104-019-09894-x (2019).

20. 20.

Shen, Y. et al. Consistent blind protein structure generation from NMR chemical shift data. Proc. Natl. Acad. Sci. U. S. A. 105, 4685–4690 (2008).

21. 21.

Morando, M. A., Barbosa, G. M., Cruz-Oliveira, C., Da Poian, A. T. & Almeida, F. C. L. Dynamics of zika virus capsid protein in solution: the properties and exposure of the hydrophobic cleft are controlled by the α-helix 1 sequence. Biochemistry 58, 2488–2498 (2019).

22. 22.

McConnell, H. M. Reaction rates by nuclear magnetic resonance. J. Chem. Phys. 28, 430–431 (1958).

23. 23.

Carver, J. & Richards, R. A general two-site solution for the chemical exchange produced dependence of T2 upon the carr-Purcell pulse separation. J. Magn. Reson. 6, 89–105 (1972).

24. 24.

Machado, L. E. S. F. et al. Conformational dynamics of a cysteine-stabilized plant defensin reveals an evolutionary mechanism to expose hydrophobic residues. Biochemistry 57, 5797–5806 (2018).

25. 25.

Schwarzinger, S. et al. Sequence-dependent correction of random coil NMR chemical shifts. J. Am. Chem. Soc. 123, 2970–2978 (2001).

26. 26.

Sanz-Hernández, M. & De Simone, A. The PROSECCO server for chemical shift predictions in ordered and disordered proteins. J. Biomol. NMR 69, 147–156 (2017).

27. 27.

Kjaergaard, M., Brander, S. & Poulsen, F. M. Random coil chemical shift for intrinsically disordered proteins: effects of temperature and pH. J. Biomol. NMR 49, 139–149 (2011).

28. 28.

Ross, P. D. & Subramanian, S. Thermodynamics of protein association reactions: forces contributing to stability. Biochemistry 20, 3096–3102 (1981).

29. 29.

Ban, D. et al. Kinetics of conformational sampling in ubiquitin. Angew. Chem. Int. Ed. 50, 11437–11440 (2011).

30. 30.

Liu Bernard, A., Engelmann Brett, W. & Nash Piers, D. The language of SH2 domain interactions defines phosphotyrosine-mediated signal transduction. FEBS Lett. 586, 2597–2605 (2012).

31. 31.

Zurini, M. et al. Structural and conformational requirements for high-affinity binding to the SH2 domain of Grb2 1. J. Med. Chem. 42, 971–980 (2002).

32. 32.

Momin, M., Xin, Y. & Hamelberg, D. Allosteric fine-tuning of the binding pocket dynamics in the ITK SH2 domain by a distal molecular switch: an atomistic perspective. J. Phys. Chem. B 121, 6131–6138 (2017).

33. 33.

Farrow, N. A. et al. Backbone dynamics of a free and a phosphopeptide-complexed Src homology 2 domain studied by 15N NMR relaxation. Biochemistry 33, 5984–6003 (1994).

34. 34.

Kay, L. E., Muhandiram, D. R., Farrow, N. A., Aubin, Y. & Forman-Kay, J. D. Correlation between dynamics and high affinity binding in an SH2 domain interaction. Biochemistry 35, 361–368 (1996).

35. 35.

Huculeci, R. et al. Dynamically coupled residues within the SH2 domain of FYN are key to unlocking its activity. Structure 24, 1947–1959 (2016).

36. 36.

Finerty, P. J., Mittermaier, A. K., Muhandiram, R., Kay, L. E. & Forman-Kay, J. D. NMR dynamics-derived insights into the binding properties of a peptide interacting with an SH2 domain. Biochemistry 44, 694–703 (2005).

37. 37.

Pascal, S. M., Singer, A. U., Yamazaki, T., Kay, L. E. & Forman-Kay, J. D. Structural and dynamic characterization of an SH2 domain-phosphopeptide complex by NMR approaches. Biochem. Soc. Trans. 23, 729–733 (1995).

38. 38.

Huang, W. Y. C., Ditlev, J. A., Chiang, H.-K., Rosen, M. K. & Groves, J. T. Allosteric modulation of Grb2 recruitment to the intrinsically disordered scaffold protein, LAT, by remote site phosphorylation. J. Am. Chem. Soc. 139, 18009–18015 (2017).

39. 39.

Lindfors, H. E., Drijfhout, J. W. & Ubbink, M. The Src SH2 domain interacts dynamically with the focal adhesion kinase binding site as demonstrated by paramagnetic NMR spectroscopy. IUBMB Life 64, 538–544 (2012).

40. 40.

Delaglio, F. et al. Nmrpipe—a multidimensional spectral processing system based on unix pipes. J. Biomol. Nmr 6, 277–293 (1995).

41. 41.

Vranken, W. F. et al. The CCPN data model for NMR spectroscopy: development of a software pipeline. Proteins 59, 687–696 (2005).

42. 42.

Hyberts, S. G., Milbradt, A. G., Wagner, A. B., Arthanari, H. & Wagner, G. Application of iterative soft thresholding for fast reconstruction of NMR data non-uniformly sampled with multidimensional Poisson gap scheduling. J. Biomol. NMR 52, 315–327 (2012).

43. 43.

Shen, Y. & Bax, A. Protein backbone and sidechain torsion angles predicted from NMR chemical shifts using artificial neural networks. J. Biomol. NMR 56, 227–241 (2013).

44. 44.

Rieping, W. et al. ARIA2: automated NOE assignment and data integration in NMR structure calculation. Bioinformatics 23, 381–382 (2007).

45. 45.

Linge, J. P., O’Donoghue, S. I. & Nilges, M. Automated assignment of ambiguous nuclear overhauser effects with ARIA. Methods Enzymol. 339, 71–90 (2001).

46. 46.

Brunger, A. T. et al. Crystallography & NMR system: a new software suite for macromolecular structure determination. Acta Crystallogr. Sect. D-Biol. Crystallogr. 54, 905–921 (1998).

47. 47.

Maciejewski, M. W. et al. NMRbox: a resource for biomolecular NMR computation. Biophys. J. 112, 1529–1534 (2017).

48. 48.

Chen, V. B. et al. MolProbity: all-atom structure validation for macromolecular crystallography. Acta Crystallogr. D Biol. Crystallogr. 66, 12–21 (2010).

49. 49.

Loria, J. P., Rance, M. & Iii, A. G. P. A Relaxation-Compensated Carr–Purcell–Meiboom–Gill sequence for characterizing chemical exchange by NMR spectroscopy. Analysis 2331–2332 (1999).

50. 50.

Humphrey, W., Dalke, A. & Schulten, K. VMD: visual molecular dynamics. J. Mol. Graph. 14(33–8), 27–28 (1996).

51. 51.

Sanner, M. F. Python: a programming language for software integration and development. J. Mol. Graph. Model. 17, 57–61 (1999).

52. 52.

Olsson, M. H. M., Søndergaard, C. R., Rostkowski, M. & Jensen, J. H. PROPKA3: consistent treatment of internal and surface residues in empirical pK a predictions BT. J. Chem. Theory Comput. 7, 525–537 (2011).

53. 53.

Dolinsky, T. J., Nielsen, J. E., McCammon, J. A. & Baker, N. A. PDB2PQR: An automated pipeline for the setup of Poisson-Boltzmann electrostatics calculations. Nucleic Acids Res. 32, W665–W667 (2004).

54. 54.

Trott, O. & Olson, A. J. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J. Comput. Chem. 31, 455–461 (2009).

55. 55.

Pronk, S. et al. GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit. Bioinformatics 29, 845–854 (2013).

56. 56.

Lindorff-Larsen, K. et al. Improved side-chain torsion potentials for the Amber ff99SB protein force field. Proteins Struct. Funct. Bioinforma. 78, 1950–1958 (2010).

57. 57.

Jorgensen, W. L., Chandrasekhar, J., Madura, J. D., Impey, R. W. & Klein, M. L. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 79, 926–935 (1983).

58. 58.

DeLano, W. Pymol: An open-source molecular graphics tool. CCP4 Newsl. Protein Crystallogr. (2002).

## Acknowledgments

We thank the National Center of Nuclear Magnetic Resonance (CNRMN, UFRJ, Rio de Janeiro-Brazil) and the Mutiuser Center of Molecular Inovation (CMIB, UNESP, São José do Rio Preto, Brazil) for the NMR spectra acquisition, and NMRbox (National Center for Biomolecular NMR Data Processing and Analysis, a Biomedical Technology Research Resource—BTRR). We thank Professor John Ladbury for kindly providing the plasmid of Grb2-SH2. We also thank Prof. Dmitry Korzhnev for discussion of the results and Prof. Ana Paula Valente for the paper review and suggestions. The work was supported by FAPERJ grants 215141, 210361, 239229, and 204432, CNPq Grants 309564/2017-4 and 457773/2014-6 awarded to FCLA. FAPESP Grants (2014/17630-0, 2017/20642-8), CNPq Grant 442951/2014-0 and UNESP-PROPG grants (09/2017, 12/2017) awarded to FAM. We also thank INBEB-INCT for funding. KS is funded by CNPq scholarship and IPC is funded by a postdoctoral fellowship by FAPERJ. The authors declare no conflict of interest.

## Author information

Authors

### Contributions

K.S. contributed with the sample preparation, experimental design, resonance assignments, N.M.R. data collection, data analysis and structure calculation. I.P.C. contributed with experimental design, N.M.R. data collection and molecular dynamics simulation. F.A.M. is a biophysist that contributed with data analysis and funding. F.C.L.A. is a structural biologist and N.M.R. spectroscopist, which contributed with the structure and dynamics, data analysis, experimental design and funding. The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.

### Corresponding authors

Correspondence to Fabio C. L. Almeida or Fernando A. Melo.

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Sanches, K., Caruso, I.P., Almeida, F.C.L. et al. The dynamics of free and phosphopeptide-bound Grb2-SH2 reveals two dynamically independent subdomains and an encounter complex with fuzzy interactions. Sci Rep 10, 13040 (2020). https://doi.org/10.1038/s41598-020-70034-w

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