Mechanical Unfolding of Spectrin Repeats Induces Water-Molecule Ordering

Journal Pre-proof Mechanical Unfolding of Spectrin Repeats Induces Water-Molecule Ordering Sarah Jacqueline Moe, Alessandro Cembran PII:

S0006-3495(20)30027-8

DOI:

https://doi.org/10.1016/j.bpj.2020.01.005

Reference:

BPJ 10253

To appear in:

Biophysical Journal

Received Date: 15 August 2019 Accepted Date: 2 January 2020

Please cite this article as: Moe SJ, Cembran A, Mechanical Unfolding of Spectrin Repeats Induces Water-Molecule Ordering, Biophysical Journal (2020), doi: https://doi.org/10.1016/j.bpj.2020.01.005. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Biophysical Society.

Mechanical Unfolding of Spectrin Repeats Induces Water-Molecule Ordering

Sarah Jacqueline Moe and Alessandro Cembran*

Department of Chemistry and Biochemistry, University of Minnesota Duluth, Duluth, Minnesota

* Correspondence: [email protected]

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Abstract Mechanical processes are involved at many stages of the development of living cells, and often external forces applied to a biomolecule result in its unfolding. Although our knowledge of the unfolding mechanisms and the magnitude of the forces involved has evolved, the role that water molecules play in the mechanical unfolding of biomolecules has not yet been fully elucidated. To this end, we investigated with steered molecular dynamics simulations the mechanical unfolding of dystrophin’s spectrin repeat 1, and related the changes in the protein’s structure to the ordering of the surrounding water molecules. Our results indicate that upon mechanically-induced unfolding of the protein, the solvent molecules become more ordered and increase their average number of hydrogen bonds. In addition, the unfolded structures originating from mechanical pulling expose an increasing amount of the hydrophobic residues to the solvent molecules, and the uncoiled regions adapt a convex surface with a small radius of curvature. As a result, the solvent molecules reorganize around the protein’s small protrusions in structurally ordered waters that are characteristic of the so-called “small-molecule regime”, which allow water to maintain a high hydrogen bond count at the expense of an increased structural order. We also determined that the response of water to structural changes in the protein is localized to the specific regions of the protein that undergo unfolding. These results indicate that water plays an important role in the mechanicallyinduced unfolding of biomolecules. Our findings may prove relevant to the ever-growing interest in understanding macromolecular crowding in living cells and their effects on protein folding, and suggest that the hydration layer may be exploited as a means for short-range allosteric communication.

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Significance Many proteins in living cells are subject to mechanical forces, which often result in protein unfolding. Although the hydrophobic effect has been well characterized as being the driving force leading to protein folding, mechanical unfolding of a protein leads to an unfolded state that is distinct from that of thermal and chemical unfolding. Thus, it is important to evaluate the impact that mechanical unfolding of a biomolecule has on the surrounding solvent. Here, we investigate the structural changes of the hydration layer upon mechanical unfolding of a spectrin repeat using molecular dynamics simulations. We discovered that as the nature of the exposed surface of the protein changes, the water molecules in the hydration layer reorganize and increase their structural order.

Introduction Many biophysical processes involve mechanical forces acting on biomolecules, which produce a range of responses, among which protein unfolding is a well-documented one(1, 2). Among the proteins that are subject to mechanical unfolding, the spectrin repeat (SR) domain occupies a prominent place, as SRs are the building blocks of many structural proteins that undergo force-induced deformations(3, 4). Proteins belonging to the spectrin superfamily include α- and β-spectrin, dystrophin, utrophin, actinin, and several other proteins in the plakin and nesprin families. These proteins contribute to forming the scaffold of the cytoskeletal network(3-5), and help to connect actin, microtubules, ankyrin, and other cytoskeletal proteins, and to anchor them to the

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cytoplasmic and nuclear membranes. In erythrocytes, it has been reported that spectrin undergoes force-induced unfolding in a shear stress-dependent manner(6), thus contributing to the cell’s flexibility(7-9). The triple-helix coiled-coil motif of the SR is a structurally common domain for load-bearing proteins(10, 11), and a single structure can include anywhere between 2 to 74 repeats(3).

In the most common arrangement, the helical C-terminus of the third helix on one SR continues in the N-terminus of the first helix of the following SR, thus forming a continuous helical linker region at the interface(10, 12), giving rise to a large filament with characteristic roll, pitch, and yaw angles. In some cases(13) – such as for spectrin and actin – two SR filaments can further intertwine in an antiparallel fashion. Additionally, SR multidomains can be interrupted by disordered hinges – such as in dystrophin and utrophin – or by other domains or repeats – such as in the plakin family. Even within the same protein, SRs have low sequence identity but high sequence and structural similarity, displaying the heptad pattern characteristic of α-helical structures(10).

The mechanical unfolding of SRs has been extensively studied with both experimental(6, 14-20) and theoretical(16, 19, 21-26) approaches. These studies have shown that low forces (in the range of 25 to 80 (14, 16-18)) are required to initiate a spectrin unfolding event, and that the partial unfolding of repeat units is an important source of flexibility. Several works(19, 22, 23) have identified the linker between two contiguous SRs as the region that initially unfolds under mechanical stress, whereas 4

different viewpoints exist on whether the forced unfolding of multiple SRs is a cooperative process(17, 18). Computational studies(16, 27) have characterized the intermediates along the unfolding pathway of single SRs. These works showed that unfolding begins at the N- and C-termini and proceeds toward the center of the bundle, until the interface between the three helices is sufficiently disrupted to allow them to break apart from each other.

Although the response of SRs to external forces has been thoroughly studied, little is currently known about the interplay between spectrin unfolding and the surrounding water molecules. The hydrophobic effect is the main driving force for protein folding(28, 29), and protein stability is affected by changes in the order of the surrounding water molecules – such as in cold denaturation triggered by increased solvent ordering at low temperature(30, 31). The rotational dynamics of the hydration layer has been shown to affect proteins’ large-scale functional motions as demonstrated by neutron scattering experiments and computer simulations(32-34). Overall, there is growing evidence suggesting that water plays a central role in mediating the structure, dynamics(35), and functionality of globular proteins(36). One topic of active debate involves the molecular origins of the hydrophobic effect(28, 37, 38). The classical “iceberg” model of hydrophobic interactions, proposed by Frank and Evans(39), has suggested that water forms highly ordered structures around hydrophobic solutes as a means to maintain its hydrogen bonding network, which restricts the translational and orientational entropy of water as it reorganizes around the hydrophobe. Computational work(40) has supported the iceberg model by showing that water around methane molecules exhibits higher 5

structural order than bulk. Similarly, Teresa Head-Gordon(41) showed that hydrophobic solutes induce solvent ordering using computer simulation. Yet other theoretical studies(38, 42-44) have suggested that the iceberg model does not fully explain hydrophobic solvation, and neutron diffraction measurements(45) have suggested that water does not reorganize around hydrophobic molecules, but instead attains disordered properties that are similar to bulk. Work by David Chandler and others(4649) has shown that a weak interpretation of the iceberg model can describe the hydration of sub-nanometer hydrophobic units, in what is described as the “smallmolecule regime”. In this limit, water can rearrange around the solute to maintain 4 hydrogen bonds (H-bonds) in an enthalpically-favored process that offsets the loss of entropy. However, the model seems inadequate for extended hydrophobic surfaces, which induce water to sacrifice one H-bond, resulting in the loss of water-water interactions(50). These findings have been supported by theoretical work by Chakrabarty(51), where water was shown to have low tetrahedral order around large (>1 nm) nonpolar Lennard-Jones particles due to the average loss of one H-bond, and high tetrahedral order around small (<1 nm) particles.

It is also widely accepted(52-54) that the properties of hydrophobic hydration may be different at small and large length scales, which is attributed to the extent of hydrogen bonding, yet it remains an open question(55-57) as to whether or not proteins behave according to the small- or large-molecule regime. Proteins, unlike hard-spheres or Lennard-Jones particles, have complex surfaces exposing both hydrophilic and hydrophobic residues with heterogeneous curvature. A study on the hydration water of 6

frataxin by Vendruscolo and co-workers(56) has suggested that proteins are better described by the small-molecule regime. Similarly, Halle(57) showed that water around protein protrusions behaves according to the small-molecule regime and maintains bulklike hydrogen bonding properties. Other studies have shown that the hydration layer of proteins may display multiple regimes in terms of both dynamics(58) and structure(5961).

Because the hydration shell plays an important role in ligand binding and protein-protein interactions(42, 62-65), characterizing its structural and dynamic nature is critical to fully understand these phenomena. In the case of SRs, an important example involves the interaction of SRs with other SRs, such as in spectrin and actin, or in the second actinbinding domains of dystrophin(66-68). Understanding the structure of the hydration layer surrounding SRs may help rationalize the forces that drive association of SRs, as studies have shown that perturbations in the dynamics of this layer may extend up to 2 nm(69). Additionally, as part of their function, SRs unfold when subject to mechanical stress, and consequently the structure of the hydration layer may be required to adapt to the protein’s extension. Although the role played by water in protein folding has been recognized(28, 29, 70), studies by Karplus and Berne have shown that mechanical unfolding is different from chemical or thermal unfolding(27, 71). While recent work by Li and Walker(72, 73) has characterized the interdependence between hydrophobic hydration and mechanical unfolding of polystyrene polymers, the interplay between the heterogeneous nature presented by different amino acids and the structure of the hydration layer of a protein subject to mechanical unfolding is still unclear. Therefore, it 7

is of interest to understand how mechanical unfolding affects the structure of the hydration layer of an SR, as perturbations in this layer could be a way to mediate protein-protein interactions or cooperative unfolding of multiple adjacent SR domains.

Here, we have investigated the role of water molecules in the mechanical unfolding of spectrin repeat 1 (SR1) of human dystrophin using steered molecular dynamics (SMD) simulations. SMD is a powerful tool to understand biomolecules’ mechanical response at the atomistic level(74), which has been successfully employed to study SRs(16, 19, 23, 26, 27). We have chosen dystrophin among the many SR-containing proteins because it does not form antiparallel dimers as spectrin or actin do, thus removing a layer of complexity from the analysis. In addition, dystrophin’s central rod is believed to unfold and act as a shock absorber that dampens extension and recoil during muscle activity(5, 67). Dystrophin links actin to the dystroglycan complex embedded in the sarcolemma, and its rod domain contains 24 SRs separated by 4 flexible hinges(20, 75). Therefore, different SRs in the protein may be exposed to and interact with different environments, ranging from the membrane to the actin rod itself. Accordingly, it is critical to understand how the mechanical unfolding of SRs affects the structure of water surrounding dystrophin, as the different environments and interaction partners may be affected differently. Our working hypothesis is that mechanical unfolding of SR1 will lead to increased exposure of hydrophobic residues and to changes in the protein’s surface convexity, which will result in an increased order of the solvation layer surrounding the protein. To avoid adding too many layers of complexity, and to keep the computational cost of SR unfolding manageable, we have chosen to study one individual SR rather 8

than multimers. Specifically, we have chosen to study dystrophin’s SR1 because of the availability of its crystal structure(11). To spatially characterize the response of water to protein unfolding from the SMD simulations, we have measured several observables tracing the properties of both the protein and the water as a function of protein extension. These observables include pulling force, work, helical content, solvent accessible surface area (SASA), protein surface curvature, hydration water count, Hbonds, and tetrahedral ( ) and Steinhardt (⟨ 6⟩) water order parameters. Our results show that the response of water to protein unfolding is dictated by many factors, the most prominent of which include the nature of the exposed residues, the curvature of the protein surface, and the size of the protein chain. As the protein unfolds, we observe that the surface of the protein becomes more hydrophobic and more convex. As a response to these changes in the protein surface, the hydration layer surrounding the protein undergoes significant structural changes. Namely, as the protein unfolds there is an increase in the water-water H-bond count, and water becomes structurally more ordered as indicated by the measured order parameters. The results presented here illustrate the interplay between protein and water structure in SRs, and characterize the spatial response of the hydration layer’s structure to changes in hydrophobicity and curvature triggered by mechanical unfolding of a macromolecule, which is relevant to both understand biological phenomena as well as to understand and improve mechanical properties of materials(73).

Methods Molecular Dynamics Simulations - Equilibration 9

The starting structure of the SR1 of human dystrophin was obtained from PDB ID 3UUN(11) and the same sequence used here is summarized in Table S1 in the Supporting Material. Molecular dynamics (MD) simulations were carried out and analyzed using version 2016.3 of the GROMACS(76) molecular dynamics package. Further data analysis and plotting were performed using the R software(77), and simulation trajectories were visualized using the Visual Molecular Dynamics (VMD) program(78). The CHARMM 36m force field(79-81) was employed in our simulations along with the CHARMM-modified(82) TIP3P water model(83). One additional simulation was carried out using the TIP4P/Ew water model(84).

SR1 was protonated using standard protonation at pH 7 with aspartate and glutamate residues negatively charged, and lysine and arginine residues positively charged. The PROPKA 3.0 online tool(85) was used to define the protonation state of histidine residues, which were all set to neutral, resulting in residues 380, 392, and 446 protonated at the  , and residue 382 protonated at the  . The protein was then solvated with 24,472 TIP3P water molecules in a rhombic dodecahedron box that ensured over 1.5  buffer between the protein and the boundaries. An additional discussion concerning the use of explicit versus implicit solvent is provided in the Supporting Material. To ensure electroneutrality and an ionic strength of 150 , 81 K+ and 69 Cl- counter ions were added to the system. The solvated system consisted of 75,394 atoms and was minimized by the steepest descents method until the maximum force was less than 1000     . The system was then simulated for 1 ns in the NVT ensemble with position restraints imposed on the protein heavy atoms using a 10

force constant of 1000     . The restraints were gradually released over the course of 3  in the NPT ensemble. Once restraints were completely released, the system was further equilibrated for 100 . The LINCS algorithm was applied to constrain all covalent H-bonds(76).

Dynamics were propagated with the Leap-Frog integrator(86) and a time step of 2 . The Nosé-Hoover thermostat(87, 88) and Parrinello-Rahman barostat(89) were used for temperature (300 ) and pressure (1 !") coupling, with a time constant of 1.0 and 2.0 , respectively. Temperature coupling of the protein was performed separately from the remainder of the system. A cut-off distance of 1  was used for Lennard-Jones interactions. Long-range electrostatic interactions were calculated using the particle mesh Ewald method(90) with 0.12  grid spacing and fourth order spline interpolation. The neighbor list was updated every 40 .

Molecular Dynamics Simulations – Forced Extension After the initial equilibration as described above, SR1 was removed from the rhombic dodecahedron box and, with its principal axis of inertia aligned along the z-axis, solvated with 65,354 TIP3P water molecules in a tetragonal box with dimensions 8.9, 8.9, and 24.8  along the x, y, and z axes, respectively. To ensure electroneutrality and an ionic strength of 150 , 195 K+ and 183 Cl- counter ions were added to the system, for a total of 198,268 atoms. Equilibration in the tetragonal box followed the same scheme and used the same parameters as in the rhombic dodecahedron. One

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difference is that in the tetragonal box a semi-isotropic coupling scheme was employed for pressure, where the box was allowed to fluctuate by the same amount in x and y dimensions, while the z dimension was kept fixed at 24.8 . Another difference is that to maintain the protein properly aligned for the following pulling simulations, the alphacarbons of the N- and C- termini were kept harmonically restrained with a force constant of 1000     .

Following the final 100  NPT equilibration, the system was subjected to mechanical pulling using SMD simulations. The restraint on the N-terminus alpha-carbon was released, while the one on the C-terminus alpha-carbon was kept in place. Constant velocity (0.08 /) pulling SMD simulations were performed by applying a moving harmonic restraint (force constant 200     ) to the alpha-carbon of the Nterminus along the z-dimension, which allowed the terminus to freely fluctuate in the x-y plane. Simulations were run for 200 , resulting in a protein elongation of approximately 16 , and the trajectories were tested to ensure that the minimum image convention was not violated. Protein atomic coordinates were recorded every 5 . Every 500 , water coordinates were saved for 20 frames at a 1  interval, and water properties were averaged over the 20 frames.

Two replicate simulations were performed using the same equilibrated system with different initial velocity distributions to control the reproducibility of our results. In addition, a “reverse-pulling” simulation was carried out by restraining the alpha-carbon

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of the N-terminus and applying a force to the alpha-carbon of the C-terminus along the z-dimension using the same pulling speed, restraining force, and spring constant, as a means to evaluate whether the direction of pulling biased the unfolding process. Lastly, a replicate simulation was carried out by pulling on the N-terminus for the spectrin system solvated with the TIP4P/Ew water model to evaluate the dependence of the observed results on the water model.

Details about the methods employed for the analyses of the SASA(91, 92), protein surface curvature(93), hydration water count, H-bonds(94, 95), and for the tetrahedral(96-99) and Steinhardt water order parameters(100-103) are provided in the text of the Supporting Material.

Results and Discussion Pulling Force and Protein Structure After the initial system equilibration (see text in the Supporting Material), using SMD simulations we evaluated the effects of mechanical stress on the structure of dystrophin SR1. Although the intermediates and bottlenecks of mechanical unfolding of spectrin repeats have been well characterized(16, 19, 23, 27), the unfolding of dystrophin’s SR1 was analyzed here in order to provide the necessary context in interpreting our observations concerning the structure of water molecules (see below). Therefore, to relate changes in the solvent structure to specific unfolding events in the protein, we

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have first characterized the sequence of events involved in protein unfolding in relation to the peak forces experienced by the pulling spring.

Fig. 1A shows the peak force experienced by the pulling spring as a function of the protein’s extension. Our estimated peak force is 300  as compared with the 25  to 80  range based on experimental studies on other SRs(14, 16-18). However, our pulling rate (0.08 /) is about five orders of magnitude faster than most experiments (for example, 10' / in reference (16)). Although faster pulling rates are responsible for higher force peaks, they do not compromise the mechanistic information obtained from atomistic simulations(104). More recently, Daday and coworkers(105) have reported peak forces for SRs of the plakin domain of desmoplakin that are of comparable magnitude to ours. They also demonstrated that there is a linear correlation between the logarithm of the pulling rate and the peak force(105). The peak forces in our simulations are comparable to those obtained by Altman and coworkers(16) for chicken brain α-spectrin repeat 16 in implicit solvent and by Ortiz and coworkers for αactinin SRs 1 and 2(19).

The blue line in Fig. 1A shows that the pulling force increases up to about 8  of extension (label 4), after which it drops and fluctuates around 0 . This results in a work function (Fig. 1A, green line) that could be coarsely defined by two regimes: a first stage where the work done increases almost linearly with the elongation, and a second stage where elongation of the protein takes place at almost no cost, as shown by the

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plateau after 8 . This type of behavior has been experimentally characterized in a number of spectrin constructs by atomic force microscopy pulling experiments(14-17, 19). Fig. 1 shows the sequence of events by six representative structures, where the helices A and C unfold first starting at the termini (label 2), and then the unfolding propagates toward the center of those helices (labels 3 and 4). The greatest pulling forces are observed between labels 3 and 4, which structurally involve the unfolding of the central sections of helices A and C, until only about three helix turns are left intact on each helix. These central sections contribute to the bulk of the interface between the three helices, whereas the termini – especially the C-terminus – are involved in less interhelical contacts. A large drop in pulling force takes place over a short range between labels 4 and 5. This transition does not involve any helical unfolding (see also Fig. 1B), but rather a rearrangement of the tertiary structure that results in the almost complete disruption of the interface between the three helices – a behavior that has been characterized previously(16, 23). After the conformational transition that disrupts the interface between the three helices has taken place, further extension SR1 occurs at almost no cost, as shown by the plateau in the force after label 5 in Fig. 1A. This is because at this stage moving the pulling restraint only picks up the “slack” in the chain, and the little additional unfolding of helix B does not involve the disruption of any hydrophobic interface. Similar unfolding profiles were observed for the other three pulling simulations described in the Methods section, in terms of both force profile and the sequence of conformational events, and the results are summarized in Figs. S9-S11.

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Helical Content To quantify the degree of unfolding of the helices, we have calculated their helical content as shown in Fig. 1B (see Supporting Material for details on helical content analysis). The data support the qualitative observations based on the structures, where the helix C – the longest of the three helices – is the one that suffers the largest loss of secondary structure upon extension. Fig. 1B also underlines that in the region between labels 4 and 5 – where the largest drop in force takes place – there is no change in helical content in any of the helices. In addition, the central helix B begins to partially unfold only after the structural rearrangement brings it in line with the other two unfolded helices, such that the applied force can act toward its extension. The number of intrahelical H-bonds was also calculated (see Fig. S5 in the Supporting Material) to monitor the structure of the alpha helices, which captures the same general trends as those shown in Fig. 1B.

Solvent Accessible Surface We have shown that the greatest pulling forces arise upon the disruption of the interface between the three helices until the interface is sufficiently weakened. Further pulling readily leads to a large tertiary structural rearrangement, which essentially separates the three helices. In order to understand the molecular underpinnings of the force profile shown in Fig. 1A, we have investigated the evolution of the solvent accessible surface area (SASA) as the protein unfolds, as shown in Fig. 2A. Our data show that protein unfolding results in an increase in the total SASA by approximately 65  over the extension range we examined. Fig. 2A further separates the SASA into the contribution 16

of hydrophobic and hydrophilic moieties, where the largest contribution (about 65% of the total SASA change) originates from the increase in hydrophobic SASA. Interestingly, the hydrophobic exposed surface is greater than the hydrophilic moiety at about 8.5  of extension (label 4). In the range between labels 3 and 4, which corresponds to the highest peak forces in Fig. 1A, the hydrophilic SASA is almost constant and the hydrophobic SASA increases by about 10  . This indicates that the observed peak forces may be related to the increased exposure of the protein’s hydrophobic core to the solvent. Further clarification is shown in Fig. 2B, which separates the hydrophobic SASA into the contribution of each individual helix. Our results show that the increase in hydrophobic SASA in the range between labels 3 and 4 is mainly due to helices A and C, which are the ones that were shown to unfold in Fig. 1B. The large drop of the force observed between labels 4 and 5 (Fig. 1A) is attributed to a large increase in hydrophobic SASA, and all three helices contribute almost equally to the increased solvent exposure.

Surface Curvature The curvature of a surface has been shown to affect the orientation of water around a protein(60), the solvation free energy for creating a cavity in water(106), the intermolecular vibrations fingerprint of water(107), the water’s dynamics(108), and the water’s order parameter(51). As a result, we examined the change in the surface curvature of the protein and the corresponding change in the hydration water’s structure.

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As discussed in the Introduction, other works(46-54) have shown that the structure of water molecules around hydrophobes depends on the size of the hydrophobe itself. For example, water molecules can rearrange themselves around small hydrophobes and maintain tetrahedral coordination (small-molecule regime)(49), which results in an increased water order. However, when facing large hydrophobic surfaces, water sacrifices one H-bond (large-surface regime), and as a result the order of water molecules is reduced(50, 51). For proteins, which display more heterogeneous surfaces, it has been shown previously that the water structure is affected by the surface curvature of the protein(57, 59-61). Specifically, water molecules near convex surfaces exhibit a higher degree of order, whereas water molecules near flat and concave surfaces are less ordered.

To monitor the interplay between the surface curvature of the protein and the order of water molecules, we have calculated the average surface curvature for the protein as a function of the extension. Fig. 2C shows that the average surface curvature for the folded protein is about 0.2  , which corresponds to a concave surface. As the protein unfolds, the average curvature quickly drifts to negative values (about −1.2  for the unfolded protein) that corresponds to a convex surface. This can be explained by the fact that the folded protein presents more grooves to the solvent, which create concave regions. In contrast, the unfolding of the protein creates elongated structures (Fig. 1) that lack the ability to form grooves and present more cylindrical (convex) surfaces to the solvent. We also noticed that the curvature profile shown in Fig. 2C closely mirrors the profile of hydrophobic SASA shown in Fig. 2A (correlation 18

coefficient of −0.99). This indicates that the increased exposure of hydrophobic surface and the corresponding increase in the surface convexity take place concomitantly during the unfolding process, which may indicate a compounding effect on the ordering of water molecules.

Residue-Wise Analyses We have demonstrated so far that the surface of the protein assumes an increasingly hydrophobic character while becoming more convex upon unfolding. Yet, these descriptors are averaged over the entire protein’s surface, whereas the structural analyses shown in Fig. 1 depict an inhomogeneous transition, with regions of the protein that unfold first, while other regions are more resilient to unfolding. Consequently, the changes in the surface properties would follow suit, where the overall changes in SASA and surface curvature (Fig. 2) arise due mostly to the changes taking place in the regions of the protein that unfold. Toward gaining a finer view of these changes, we have monitored the SASA and the surface curvature at the residue level as shown in Fig. 3. For example, Fig. 3A shows the change in SASA with respect to the folded structure, where the initial SASA increase is due to the residues near the N- and C-termini, before it propagates toward more central residues. Interestingly, the increase in SASA is encompassing the whole protein as the conformational transition takes place between labels 4 and 5. In Fig. 3B a similar trend was observed concerning the surface curvature, which becomes more convex starting at the unfolding termini. This is followed by an increase in surface

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curvature toward the center of the protein, where almost the entire protein’s surface has a convex character after label 5.

Both these observations can be interpreted in terms of the sequence of structural changes (Fig. 1), where the changes in SASA and surface curvature mostly affect only the residues that unfold, but not the nearby residues. In fact, the regions of helix B that face the unfolding residues exhibit minimal to no perturbations in both descriptors in the first half of the extension profile. This indicates that the A and B helices termini are still capable of protecting helix B from solvent accessibility even after unfolding.

To identify which residues contribute most to the changes in SASA and surface curvature, we applied principal component analysis (PCA) to the data matrices shown in Fig. 3A and 3B. Briefly, this analysis identifies the contribution of the amino acids that maximize the variance of the signal in an eigenvector (i.e., a list of amino acids and their corresponding weights). Then, by projecting the data in the matrix onto this eigenvector, it is possible to monitor the change in signal (either SASA or curvature) that is described by that eigenvector. Fig. 3C shows the projection of the SASA and surface curvature data on the first eigenvectors as well as the corresponding eigenvectors in Fig. 3D. The two profiles in Fig. 3C show a remarkable similarity, which indicates that they track the same process, although they originate from different data. We also noticed that the shape of these profiles exhibits a small change at about 3 nm of extension prior to a larger change at about 8 nm of extension, where the conformational change between label 4 and 5 takes place. This trend supports the observations of the global analysis of 20

the SASA (Fig. 2A) and the curvature (Fig. 2C), which display a smaller and larger change at 3 nm and 8 nm of extension, respectively. The process that is captured by the first eigenvector of our principal component analysis is therefore the one that is responsible for the overall protein’s response to elongation. Interestingly, Fig. 3D reveals visually that the residues that contribute most to the observed changes are those forming the hydrophobic interface among the three helices. In Fig. S5A we show that the contribution of the residues to the first eigenvector of the SASA and curvature PCA are very similar, and we further highlight their similarity through a scatterplot in Fig. S14 in the Supporting Material, for which we calculated a high correlation coefficient between the two vectors (−0.88). An autocorrelation analysis of the eigenvectors (Fig. S5B) shows approximately a 3.5 residues periodicity, which corresponds to the α-helix 3.6 amino acids per turn. Aided by the schematic helix/coil representation on the right side of the plots, the same periodicity can be qualitatively identified from the change in SASA and surface curvature in both Fig. 3A and 3B.

Overall, these analyses support the notion that protein unfolding leads to an increase in both the SASA and surface convexity, where both of these two descriptors report on the same unfolding events. In addition, the residues that are most perturbed are those forming the hydrophobic interface among the three helices.

Hydration Layer Hydrogen Bonds Structure

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The behavior of H-bonds at the protein-solvent interface is particularly relevant to understanding hydrophobic hydration(49, 109). To evaluate how the changes in the structure and surface characteristics of the protein affect the distribution of neighboring water molecules, we have analyzed H-bond parameters for the water layer surrounding the protein and presented the results in Fig. 4. We have calculated the total number of water molecules in the first shell as a function of the elongation (Fig. 4A, green line), and our results indicate that as the protein unfolds, the number of water molecules in the first layer increases by almost a factor of two as compared with the folded state. This is a consequence of the protein exposing a greater surface area, which also almost doubles from the folded to the unfolded states (Fig. 2A). Yet, the ratio between the number of water molecule in the first shell and the total SASA (Fig. S6 in the Supporting Material) suggest that there are slightly less water molecules per protein surface unit as the protein unfolds. This reduction in surface density on hydrophobic surfaces is in agreement with the reported reduction in water density observed at hydrophobic interfaces(53, 106, 110). In addition, our findings are also consistent with an increase in the hydrophobicity of the surface exposed to the solvent, which is less prone to hydrogen bonding, and explains the small reduction in water surface density.

Fig. 4A describes the evolution of the total number of H-bonds per water (grey line), which includes both water-water and protein-water interactions, where only the polar atoms on the protein were considered. As the protein unfolds, the total number of Hbonds per water increases by approximately 3.23 to 3.28 H-bonds per water molecule, which is still lower than the value observed for bulk water (3.35 H-bonds per water). The 22

change in number of H-bonds per water from the folded to the unfolded conformations is statistically significant (95% CI from 0.046 to 0.072), and we refer the reader to Fig. S12 and to the discussion in the Supporting Material for additional details. These numbers are consistent with those obtained by Persson and coworkers for TIP4P-Ew water(57), where they observe that the average number of H-bonds in the first hydration layer is about 2% lower than bulk. Importantly, the profile shown in Fig. 4A closely follows the trends shown by the SASA and curvature data (Fig. 2 and 3). In particular, we notice that the largest increase in total H-bonds per water takes place between labels 4 and 5, which marks the large protein conformational change resulting in increased SASA and convex nature of the denatured protein surface. In addition, there is another small transition that takes place around 3 nm of extension, as found for both SASA and curvature. These observations suggest that the H-bond structure in hydration layer is directly responding to the changes in the protein’s structure and surface characteristics.

Fig. 4B shows a distinct contribution of protein-water and water-water H-bonds. As the protein unfolds, we notice that the average number of protein-water H-bonds for each water molecule in the first shell decreases by about 12% (green line). In contrast, the water-water H-bond average (Fig. 4B, grey line) is the mirror image of the protein-water trend with an increase of about 6%. Notably, the same two-step trend observed here confirms that the changes in the H-bond network reflect structural changes in the protein. It is important to notice that the H-bond data presented in Fig. 4A and 4B are normalized per water molecule, which explains the observed reduction in the protein23

water H-bonds. Fig. S7 in the Supporting Material shows that the number of total protein-water H-bonds increases as the protein unfolds, which is attributed to water forming H-bonds with the amide groups being exposed upon the unfolding of the helices. The same figure shows that, as the protein unfolds, the greatest contribution to the change in the total water H-bonds comes from the water-water H-bonds because of the corresponding increase in the number of water molecules in the first hydration shell (Fig. 4A).

Overall, the water-normalized data (Fig. 4A and 4B) show that unfolding of the protein leads to a reduction of the average number of hydrogen bonds between water and protein per water molecule. This is consistent with the notion that protein unfolding leads to an increase in hydrophobic SASA, where hydrophobic surfaces preclude a larger part of the first hydration shell water molecules from making H-bonds with the protein in the unfolded state. Concomitantly, as the surface becomes more hydrophobic, it also becomes increasingly convex (Fig. 2B and 3C). In other words, the unraveling of the alpha helices exposes a peptide chain that has a smaller curvature radius than the folded protein, which allows water molecules to increase their structural order around the increasingly hydrophobic surface. This behavior of water molecules around convex surfaces has been reported previously(50, 59, 60), where water molecules are allowed to maintain water-water H-bonds, which is not the case around flatter or concave hydrophobic surfaces. It is thus the smaller curvature of the unfolded chains – when compared to the folded protein – that allows water to form more water-water H-bonds, even when facing an increasingly hydrophobic surface. 24

The observed trends described above are further supported by the results shown in Fig. 4C, where the water H-bonds distribution around the fully folded (grey) and unfolded protein (blue), and for bulk water (orange) are shown. As the protein unfolds, the peak at 3 H-bonds per water decreases, with a corresponding increase in the peak at 4 Hbonds per water. Overall, the H-bonds distribution of bulk water is more similar to that of hydration water surrounding the unfolded protein than the folded protein. This result may seem counterintuitive, given the fact that the unfolded protein displays an increasingly hydrophobic surface to the solvent. However, the unfolded protein exposes a surface that – even if more hydrophobic – shows an increased surface convexity, which allows water molecules surrounding the small protein protrusions to maintain their H-bond network by increasing their structural order.

Water Order Parameters Although H-bonds are a useful and chemically intuitive parameter to measure water structural order, other more sophisticated metrics have been developed to measure the relative orientation of water molecules(96, 97, 100-102). As a complementary approach for the H-bonds, we have also calculated the tetrahedral order parameter  for the first hydration layer, and the Steinhardt local order parameter ⟨ ' ⟩ for the second hydration layer (see Supporting Material). Fig. 5A shows that both order parameters increase as the protein unfolds, which indicates that the water surrounding the protein becomes structurally more ordered.

25

Specifically, the water  increases from about 0.515 for the folded to 0.530 for the unfolded state of the protein (the 95% CI corresponds to an increase of 0.013 to 0.017). These observed values are lower than the  for bulk water TIP3P, (herein calculated as 0.557, in close agreement with the value reported in reference (111)), which supports our H-bonds analyses. Taken together, these results suggest that the first hydration layer has a lower average number of H-bonds per water than the bulk and the layer in closer proximity to the protein is overall less structured than bulk water.

For the second hydration layer we calculated a ⟨ ' ⟩ = 0.315 for the folded state, which increases to 0.375 in the unfolded state (the 95% CI corresponds to an increase of 0.056 to 0.060). When comparing these numbers to the ⟨ 6⟩ of the same number of TIP3P bulk waters (⟨ ' ⟩ = 0.316), the Steinhardt parameter displayed a higher order for the water than the tetrahedral order. For example, the Steinhardt order parameter in the unfolded state is greater than that for bulk water. This observed difference is attributed to the fact that the Steinhardt order parameter is calculated for the second hydration layer, whereas the tetrahedral order is calculated for the first hydration layer, and other studies(111, 112) have shown that the second hydration layer displays a maximum in the order parameter. Toward further clarification, we have calculated  for different hydration layers up to 1.0 nm away from the protein (Fig. S8 in the Supporting Material). The results show that for both the folded and unfolded structures of the protein, the bulk water limit is approached within 0.7 nm from the protein’s surface, which is in agreement with the reported behavior of water molecules around an extended hydrophobic surface(50) as well as around the small protein HP-36(112). Notably, we 26

observed that the second hydration layer indeed displays a peak in the order parameter with a slightly larger value for the unfolded state than that of bulk water. This indeed supports our interpretation of the larger value observed for the Steinhardt parameter in the second layer. Fig. 5A also shows that the order parameter trends closely mimic those displayed by the H-bonds analyses (Fig. 4A and 4B), as well as those displayed by the SASA and the surface curvature (Fig. 2A and 2C). This suggests that the water structural ordering accompanies the H-bond redistribution, and that both are triggered by the increased hydrophobicity and surface convexity of the protein.

We have further investigated how the unfolding of the individual helices affects the ordering of water molecules by plotting  for the hydration layer surround each helix as shown in Fig. 5B (additional details about the statistical significance of the observed changes are provided in the Supporting Material and Fig. S13). The results show that the largest change in water order affects helix C, which takes place in the earlier stages of protein unfolding. This change in  is followed by a change in the order of water molecules surrounding helix A. In addition, a change in the order of water molecules surrounding helix B is observed only when the conformational transition at labels 4 and 5 takes place. We compared these trends with the per-helix change in hydrophobic SASA as shown in Fig. 2B, which shows that the changes in water order closely mimic the trends in hydrophobic SASA. This suggests that the water’s response to protein unfolding is a well localized property that can be traced back to individual secondary structure motifs of the protein, rather than being a distributed response over the entire 27

the protein’s surface. Although this concept has already been pioneered by Rossky(59, 60), what is of interest here is to recognize the ability of water molecules to adapt to the changes of the structure and of the surface curvature of the protein.

To determine the level of structural resolution of the water’s response to protein unfolding, we have mapped the  value for the hydration water surrounding individual residues and the results are shown in Fig. 5C. In this figure, some residues for the folded state are colored white to indicate that there was no water molecule in their vicinity. Although the data are relatively scattered, it is possible to appreciate that ordering of the water starts at the N- and C-termini of the protein and then progresses toward the center, and the largest changes take place in the conformational transition between labels 4 and 5. In particular, the order of the water molecules surrounding helix B and the parts of helices A and C that are farther away for the N- and C-termini increases only after the large conformational change occurs. Such observed behavior closely mimics the corresponding changes in the SASA and in the surface curvature (Fig. 3A and 3B). This further supports our working hypothesis that exposure of hydrophobic surfaces and increased surface convexity lead to the ordering of water molecules. Moreover, comparison of Fig. 5C with Fig. 3A and 3B shows that the change in water order around the more hydrophobic and convex surface of the unfolding protein has a considerable local characteristic. This stems from the fact that the ordering of water – within some level of noise – follows clear boundaries (Fig. 5C), which are defined by the surface hydrophobicity and the convex curvature of the unfolded protein (Fig. 3A and 3B). As we have described above, the perturbation in the order of water 28

molecules extends about 0.7 nm away from the protein’s surface. This range of perturbation is consistent with the results shown in Fig. 5C, where the blurred region between different domains of ordered water molecules along the protein’s surface spans one or two residues at most.

To identify the residues that were mostly affected by the change in the order of water molecules, we used the same statistical analysis as applied to both the SASA and surface curvature (Fig. 3A and 3B) for significant comparison by applying principal component analysis to the results shown in Fig. 5C. Fig. 5D reports both a structural representation of the residue weights for the first eigenvector, and the projection of the data in Fig. 5C along the first eigenvector. These results show that the residues that best describe the variance in water order in Fig. 5C are those that form the interface between the three helices. A more detailed comparison between the water order eigenvector and the SASA and surface curvature eigenvectors is presented in Fig. S5C and S5D, which displays great similarity between all three eigenvectors. In addition, plotting the per-residue  on the first eigenvector shows a two-steps trend that is very reminiscent of the two-step behavior shown by the SASA and by the surface curvature in Fig. 3C.

Overall, the order parameters analyses of water molecules, taken at various structural resolutions, show that as the protein unfolds, the water molecules surrounding the protein become more ordered. Both the per-residues analysis and the principal components comparison with SASA and surface curvature show that the change in 29

water molecules order are highly correlated with the increase in the surface hydrophobicity and convex curvature of the protein, indicating that changes in the two protein surface descriptors could be used to estimate the changes in the solvent structure. We have further shown that the response of water molecules to the changing surface characteristics upon protein unfolding is localized, where the water order is significantly affected within a radius of about 0.7 nm from the residues that undergo structural changes. This is a relatively shorter range than that was previously reported(113), where perturbations on the water dynamics surrounding the annexin B12 protein were found significant up to 1 nm from the protein with ODNP-enhanced NMR experiments and MD simulations. It is conceivable, however, that perturbations of the structural order of water molecules and of their dynamics may follow two slightly different decays, with the former being more short-ranged than the latter. Although some of the outcomes described above may have been expected based on the current knowledge of the hydrophobic core of a protein and of the ordering effect that hydrophobic surfaces have on water, to our knowledge there are currently no atomistic studies that have tested these hypotheses for the mechanical unfolding of a protein, and investigated the extent of the ordering effect. In particular, because most of the current studies of water structure have been performed on folded or thermally unfolded proteins, it was unclear how the worm-like structure of the mechanically unfolded protein and its surface curvature would have impacted the order of water. Our calculations showed that the surface curvature of the mechanically unfolded protein is sufficiently small to be compatible with the small-curvature regime in water, which

30

allows water molecules to maintain their H-bond network at the expenses of lower entropy. Our results depict a process in which the protein and the surrounding solvent change together as the first is mechanically unfolded. We expect this finding to be of particular relevance in crowded environments such as living cells, where the protein concentration is such that biomolecules may be, in average, just a few hydration layers apart (see calculations and discussion in the Supporting Material). In these conditions, the changes in the water order of the hydration layers that we have shown taking place upon unfolding could affect nearby proteins. In turn, structural changes in nearby proteins could affect the propensity of the protein to mechanically unfold. We speculate that in crowded media this may facilitate cooperative response to mechanical stress in proteins that are located in proximity of the unfolding protein. Specifically for SRs, which are the constituents of a number of proteins serving a scaffolding role, we expect that the perturbations in the water structure could be sensed by their many interaction partners throughout the cytosol and near the cell membrane. For example, dystrophin is known to bind to actin through its N-terminal actin binding domain 1, but it is also involved in non-specific electrostatic interactions with actin through a patch of basic SRs ranging from SR11 to SR17(67). In this configuration, many of the dystrophin’s SRs will be found in close proximity of actin, which could sense their unfolding upon mechanical stress. While the results based on water structure here presented build a compelling case, they do not take into consideration the dynamics of water, and they do not quantify the enthalpy/entropy compensation that is likely taking place in the hydrations

31

layers as a result of protein unfolding. These points are currently under investigation in our laboratory, which we plan to discuss in a forthcoming manuscript.

Conclusions Using all-atom computer simulations, we have shown that the hydration layer surrounding a protein (dystrophin’s spectrin repeat 1 in this case) responds to the mechanical unfolding of this protein by changing its hydrogen bonding network and its overall structure. Our data show that in the folded state of SR1, the protein surface exposed to water molecules is mostly hydrophilic and has, on average, a slightly concave radius of surface curvature. The hydration layer surrounding the folded protein is characterized by a lower degree of order than that in bulk water, which is measured by its lower number of hydrogen bonds per water and its lower order parameters.

As the protein unfolds, however, the exposed surfaces become increasingly hydrophobic and more convex. Because of the change in the characteristics of the exposed surface of SR1, the hydration layer becomes more ordered, as shown by its increasing number of hydrogen bonds per water, as well as by the increase in the order parameters of water molecules. These observations are attributed to the mechanicallyinduced unfolding of the protein chains, which are stretched out in the solvent and form surfaces of very small radius of curvature. Around these protrusions, water molecules can maintain their H-bond network by increasing their structural order, in accordance with the small-molecule regime(49). Our results also indicate that such arrangement is

32

impeded in the folded structure, which offers more extended surfaces to water molecules that – although less hydrophobic – still hamper the formation of a full bulk hydrogen bond network(57). These results are supported by the relationship between a residue-wise analysis of the surface hydrophobicity and curvature of the protein to a residue-wise analysis of the degree of order in the hydration layer. The regions of the protein that unfold first (i.e., the termini) expose the hydrophobic surfaces of small convex curvature, which leads to a local increase in the water molecules order in the hydration layer immediately surrounding these areas.

Overall, our calculations demonstrate that the water in the hydration layer of SR1 responds to changes in the structural conformation upon unfolding by reorganizing its structure. These changes are local (i.e., short-range), and they take place on a fast timescale.

Our results are of significant relevance to our collective understanding of how mechanically-induced protein unfolding may be affected by restraints imposed on the ability of the surrounding water molecules to reorganize (or reorder) such as in crowded environments or nearby the membrane. Importantly, the hydration layer perturbations caused by mechanical unfolding could be sensed by nearby proteins and exploited as a short-range water-mediated form of allostery. Although our experimental setup does not allow an answer for this question, it is conceivable that the local perturbations in the hydration layer caused by the unfolding of a region of the protein may help to promote

33

the unfolding of the nearby amino acids. In addition, our results may help in a rational design of novel material with mechanical properties tuned with the solvent response.

34

Author Contributions: S. J. M. performed and analyzed the MD simulations. S. J. M. and A. C. designed the research and wrote the manuscript.

Acknowledgments: This work was supported in part by the National Science Foundation grant No. MCB1616854 to A. C. The authors acknowledge the Minnesota Supercomputing Institute (MSI) at the University of Minnesota for providing resources that contributed to the research results reported within this paper. URL: http://www.msi.umn.edu.

Supporting Material: Supporting Methods, supporting Results and Discussion, fifteen additional figures, and two additional tables are available in the Supporting Material.

Supporting Citations: References(114-127) appear in the Supporting Material.

35

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Figure Legends:

Figure 1: Mechanical unfolding of SR1. (A) Pulling force (grey line) and running average (blue line) as a function of the protein’s elongation. The work, calculated by integrating the pulling force, is shown as a green line (right axis). (B) Evolution of the helical content of the three helices of spectrin as a function of the protein’s elongation, represented both as raw data (shaded areas) and running average. In both panels, selected structures along the unfolding profile (positions are indicated by arrows) are shown. For ease of referencing, grey vertical lines corresponding to each structure are traced on all panels, labeled with increasing numbers from 1 to 6.

Figure 2: Solvent accessible surface area and residue curvature analyses. (A) SR1 SASA as a function of the protein elongation. The total SASA (scale to the left) is reported alongside with the hydrophobic and hydrophilic components (scale to the right). (B) Individual helix contribution to the hydrophobic SASA. (C) SR1 average residue curvature as a function of the elongation. In all panels, grey vertical lines mark the structures reported in Figure 1.

Figure 3: Residue-wise analysis of the SASA and of residue curvature. (A) Residuewise change in SASA with respect to the fully folded structure as a function of the protein elongation. (B) Residue curvature as a function of the elongation. (C) Projection on the first eigenvector of the ΔSASA data in panel (A) and of the residue curvature in panel (B), see text for details. (D) Contribution of every residue to the first eigenvector 51

mapped onto the structure for both ΔSASA and residue curvature. In panels A-C, grey vertical lines mark the structures reported in Figure 1.

Figure 4: Hydrogen bond analyses. (A) Total number of water molecules within the first solvation shell of SR1 (green, left axis), and average number of total hydrogen bonds per water (grey, right axis) as a function of the protein elongation. (B) Average number of protein-water hydrogen bonds per water (green, left axis), and average number of water-water hydrogen bonds per water (grey, right axis) as a function of the protein elongation. (C) Density distribution of the number of hydrogen bonds per water for the folded SR1 (grey), fully unfolded SR1 (cyan), and bulk water (orange); vertical bars represent the 95% CI of the mean. In panels A-B, grey vertical lines mark the structures reported in Figure 1.

Figure 5: Water order parameters. (A) Tetrahedral order parameter (green, left axis) and Steinhardt Local ⟨ 6⟩ (grey, right axis) as a function of the protein elongation. (B) Tetrahedral order parameter averaged for the water surrounding every individual helix. (C) Residue-wise tetrahedral order as a function of the protein elongation (white color indicates that there was no water surrounding that residue). (D) Contribution of every residue to the first eigenvector mapped onto the structure and projection on the first eigenvector of the tetrahedral order data in panel (C), see text for details. In all panels, grey vertical lines mark the structures reported in Figure 1.

52