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Sulfated Glycosaminoglycans Exploit the Conformational Plasticity of Bone Morphogenetic Protein‑2 (BMP-2) and Alter the Interaction Profile with Its Receptor Vera Hintze,*,†,∥ Sergey A. Samsonov,‡,∥ Massimiliano Anselmi,‡ Stephanie Moeller,§ Jana Becher,§ Matthias Schnabelrauch,§ Dieter Scharnweber,† and M. Teresa Pisabarro*,‡ †

Institute of Materials Science, Max Bergmann Center of Biomaterials, TU Dresden, Budapester Strasse 27, 01069 Dresden, Germany Structural Bioinformatics, BIOTEC TU Dresden, Tatzberg 47-51, 01307 Dresden, Germany § Biomaterials Department, INNOVENT e.V., Prüssingstrasse 27 B, 07745 Jena, Germany ‡

S Supporting Information *

ABSTRACT: Sulfated glycosaminoglycans (GAGs) can direct cellular processes by interacting with proteins of the extracellular matrix (ECM). In this study we characterize the interaction profiles of chemically sulfated hyaluronan (HA) and chondroitin sulfate (CS) derivatives with bone morphogenetic protein-2 (BMP-2) and investigate their relevance for complex formation with the receptor BMPR-IA. These goals were addressed by surface plasmon resonance (SPR) and ELISA in combination with molecular modeling and dynamics simulation. We found not only the interaction of BMP-2 with GAGs to be dependent on the type and sulfation of GAGs but also BMP-2/GAG/BMPR-IA complex formation. The conformational plasticity of the BMP-2 Ntermini plays a key role in the structural and thermodynamic characteristics of the BMP-2/GAG/BMPR-IA system. Hence we propose a model that provides direct insights into the importance of the structural and dynamical properties of the BMP-2/ BMPR-IA system for its regulation by sulfated GAGs, in which structural asymmetry plays a key role.

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This has been demonstrated for BMP-2,5 which has also been shown to induce osteoblast proliferation and differentiation in vitro,6 stressing its vital role for bone regeneration. BMP-2 functions through oligomerizing its high and low affinity serine kinase receptors (e.g., BMPR-IA and BMPR-IIB, respectively).7,8 Gel filtration experiments revealed that dimeric BMP-2 provides two binding epitopes for two identical BMPRIA receptor chains (i.e., 1:2 complex).9 The composition of the complete functional system might therefore likely be a heterohexameric complex formed by dimeric BMP-2, two BMPR-IA and two BMPR-IIB receptor chains.10 However, this is not fully elucidated to date. It has been shown that heparin potentiates the in vivo ectopic bone formation induced by BMP-2 in mice.11 In addition, there

INTRODUCTION Glycosaminoglycans (GAGs) represent a class of linear anionic polysaccharides consisting of repetitive disaccharide units, which are often sulfated. Sulfation pattern, monosaccharide composition, and type of glycosidic linkage contribute to a great variety of GAGs occurring in nature. They are important constituents of the extracellular matrix (ECM) interacting and modulating the function of proteins such as cytokines and growth factors like BMPs.1 BMPs are members of the transforming growth factor-β (TGF-β) superfamily2 and are synthesized as precursor proteins, processed to the mature protein and secreted as dimers.3 They are heparin binding proteins, as they were purified from demineralized bone by using their affinity to heparin-sepharose columns.4,5 BMPs are divided into subgroups based on the primary amino acid sequence in the mature regions of the molecule.3 Individual proteins of this family are sufficient alone to induce bone formation in vivo. © 2014 American Chemical Society

Received: May 12, 2014 Revised: June 26, 2014 Published: July 16, 2014 3083

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Table 1. Analytical Data of Used GAG Derivatives GAG

D.S.a

sulfate group distributionb

HA HALM sHA1 sHA1Δ6s sHA3 CS sCS3

1.0 1.4 2.9 0.8 3.1

6 4, 2′, 3′, 42′, 43′, 2′3′ 462′, 463′, 62′3′ 4, 6 462′, 463′, 62′3′

modeled GAGc

Mn [g mol−1]d,e

Mw [g mol−1]d,e

PDf

HA6 HA4, HA3′, HA43′ HA463′ CS4, CS6, CS46 CS463′

1,019,600 (394,900) 28,200 (81,100) 11,200 (46,900) 38,900 (67,000) 11,700 (28,900) 16,600 (39,800) 17,700 (28,500)

1,174,900 (1,894,700) 48,300 (187,000) 26,600 (102,700) 56,300 (135,500) 20,900 (47,700) 20,600 (62,100) 19,900 (41,500)

4.8 2.3 2.2 2.0 1.6 1.6 1.5

a D.S.: average number of sulfate groups per disaccharide repeating unit of HA and CS, respectively. bVariants of possible sulfate group distributions within the disaccharide repeating unit of HA and CS based on 13C NMR spectroscopic data (numbering refers to the one given in Chart 1, whereby different variants of substituent distributions are separated by a comma). cModeled tetrameric GAGs. d,eMn, Mw: Number-average and weightaverage molecular weight determined by GPC with LLS and RI detection (in brackets); fPD: Polydispersity index (PD = Mw/Mn), calculated from values obtained by RI detection.

Our results show that GAGs interact with BMP-2 and thereby alter its BMPR-IA receptor interaction profile in a sulfation-dependent manner. Based on our analysis, we propose a model that explains the experimentally observed interaction characteristics of the BMP-2/GAG/BMPR-IA system. This model considers the conformational plasticity of the BMP-2 Ntermini, which is key for the GAG interaction profile and responsible for the asymmetry in receptor recognition observed experimentally, and it suggests a potential mechanism underlying the signaling properties of the BMP-2/GAG/BMPR-IA system. This information might be of particular value when including GAG derivatives in the engineering of biomaterials to be used for tissue regeneration.

is strong evidence for a stimulatory role of endogenous heparan sulfate (HS), another high-sulfated GAG, in BMP-signaling in Drosophila and Xenopus embryos.12−14 Thus, GAGs are key regulators of bone formation and remodeling.15−17 Therefore, the molecular characterization of the interaction between BMPs and GAGs is of great interest for regenerative medicine. In vitro data obtained so far, however, have been inconsistent about the effect of GAGs on BMP-2 signaling even within one single cell type, which might be in part due to different sources and formulations but also different concentrations of the GAGs employed.18−20 The reasons named responsible for the either stimulatory or inhibitory effect of GAGs on BMP-2 signaling also vary from inhibiting19 or accelerating18 endocytosis of BMP-2, prolonging its half-life and reducing its interaction with the antagonist noggin11 to suggestions that heparin suppresses BMP-2-receptor binding.21 Mutagenesis studies have pointed toward the N-terminal region of BMP-2, which is rich in positively charged residues, as a potential heparin binding site.22 The structures of BMP-2 and complexes with its receptors have been experimentally solved at high resolution by X-ray crystallography.23,24 The N-terminal region is unfortunately not resolved in any of these structures, probably due to its high conformational flexibility, which may cause structural disorder. The characterization of the interaction between BMP-2 and GAGs at atomic level, however, is important for the design of innovative biomaterials in bone tissue engineering. These interactions cannot be properly addressed without considering the possible conformations adopted by the protein’s N-termini. In this study we combined ELISA and SPR experimental approaches with molecular docking and dynamics simulation techniques to dissect the molecular recognition properties of BMP-2 toward chemically sulfated hyaluronan (HA) and chondroitin sulfate (CS) derivatives. Though lacking N-sulfated glucosamine or iduronate residues, the latter represent readily available, simplified mimetic structures of naturally sulfated GAGs, e.g., high-sulfated heparin and heparan sulfate. In comparison to these native counterparts, they are distinguished by a defined monosaccharide composition, sulfation degree, and sulfate distribution within the disaccharide repeating unit and along the polymer chain providing a model system to characterize the interaction with BMP-2. We studied their interactions in the context of their impact on the recognition of BMP-2 by its high affinity receptor BMPR-IA. For this, we characterized the conformational properties of the N-termini of BMP-2 using replica exchange molecular dynamics (REMD) simulations.

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MATERIALS AND METHODS

Materials. Hyaluronan (HA; from Streptococcus, Mw = 1.1 × 106 g mol−1) was purchased from Aqua Biochem (Dessau, Germany) and chondroitin sulfate (CS, porcine trachea; a mixture of 70% chondroitin-4-sulfate and 30% chondroitin-6-sulfate) from Kraeber (Ellerbek, Germany). Sulfating agents SO3-dimethylformamide (DMF) complex (purum, ≥ 97%, active SO3 ≥ 48%) and SO3pyridine complex (pract. ≥ 45% SO3), as well as solvents used were purchased from Fluka Chemie, (Buchs, Switzerland). Recombinant human BMP-2 (355-BM-010/CF), as well as monoclonal, mouse antihuman BMP-2 (MAB3551), biotinylated, monoclonal, mouse antihuman BMP-2 (BAM3552) antibodies, and recombinant human BMP-2 receptor-IA/Fc chimera (BMPR-IA; 315-BR-100/CF; a disulfide linked homodimer containing two complete extracellular domains) were obtained from R&D Systems (Wiesbaden-Nordenstadt, Germany). The Series S Sensor Chips CM3 and C1, the Amine Coupling Kit and HBS-EP (10x) were purchased from GE Healthcare Europe GmbH (Freiburg, Germany). Preparation of HA and CS Derivatives. The low molecular weight HA (HALM; molecular weight in a range that is comparable to the ones of the other sulfated GAGs), the low- and high-sulfated HA derivatives (sHA1, sHA3) as well as the high-sulfated chondroitin sulfate (sCS3) were synthesized and characterized as previously described.25−28 The synthesis of regioselectively low-sulfated HA not sulfated at the C6 position (sHA1Δ6s) was performed according to a previously reported procedure by Becher et al.29 Briefly, the primary hydroxyl group at C6 of HA was protected by regioselective benzoylation with benzoyl chloride/pyridine followed by sulfation in dry DMF with SO3-DMF (molar polymer: SO3 ratio =1:15). Subsequent removal of the benzoyl ester function in aqueous K2CO3 solution, purification by dialysis and lyophilization gave the sulfated HA derivative. Polymer Characterization. The degree of sulfation (D.S.) giving the average number of sulfate groups per disaccharide repeating unit of HA and CS was determined by estimation of the sulfur content using an automatic elemental analyzer (CHNS-932, Leco, Mönchengladbach, Germany). The sulfate group distribution within the disaccharide 3084

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repeating unit was determined using 13C NMR spectroscopy (Bruker Advance 400 MHz spectrometer). Samples were recorded in D2O at 373 K using the D2O signal at 4.75 ppm as a reference. Peak assignment was made based on the work of Hintze et al.26 Molecular weight determination was performed by gel permeation chromatography (GPC) with a double detection system consisting of a Postnova Analytics PN 3000 (15°) laser light scattering (LLS) detector and a Jasco RID-1531 refraction (RI) detector. Absolute values of numberaverage (Mn) and weight-average (Mw) molecular weights were determined using the laser light scattering (LLS) detection system. Calculation of polydispersity (PD = Mw/Mn) was performed on the basis of Mn and Mw values obtained from RI detection. GPC operating parameters can be found in Hintze et al.26 Analytical data of GAG derivatives are summarized in Table 1. Covalent Coupling of GAG to MaxiSorp 96-Well ELISA Plates. The GAGs were immobilized in each well of MAXI-SORP 96well microtiter plates from Thermo Fisher Scientific (Schwerte, Germany) via their reducing ends as described in Hintze et al.25 For nonspecific binding, untreated wells were incubated with 2% bovine serum albumin (BSA) in Tris-buffered saline (TBS). In the following 0, 25, 50, 100, and 200 ng/mL (0, 1.25, 2.5, 5, and 10 ng) of BMP-2 diluted in phosphate buffered saline (PBS) containing 1% BSA was then incubated with the prepared surfaces for 16 h at 4 °C for binding to reach equilibrium. The supernatants were then removed and stored at −80 °C for further analysis by Sandwich-ELISA and BioLISA. Enzyme Linked Immunosorbent Assay (ELISA) and BioLISA. The amount of bound BMP-2 was determined indirectly with specific antibodies (Sandwich-ELISA) or the BMP-2 receptor (BMPR-IA; BioLISA) in supernatants containing nonbound BMP-2 recovered after incubation with immobilized GAG as described in Hintze et al.25 A calibration curve ranging from 0 ng/mL to 25 ng/mL (0−1.5 ng) in 1% BSA/PBS was prepared for BMP-2 to calculate the amount of nonbound growth factor. Data represent the mean of at least two independent experiments with each GAG analyzed in triplicate. The amount of desorbed growth factor over 8 days in PBS/1% BSA at 37 °C was determined likewise with each GAG analyzed in triplicate. Immobilization of BMP-2 and BMPR-IA on Sensor Chips. For interaction analysis of BMP-2, BMPR-IA, and GAG derivatives a BIACORE T100 instrument was used (GE Healthcare). BMP-2 was immobilized on the surface of a Series S Sensor Chip CM3 at 25 °C using the amine coupling reaction as described by the manufacturer resulting in an average of 645 RU of immobilized BMP-2 using a concentration of 2.5 μg/mL. An activated and directly deactivated flow cell was used as a reference surface without the immobilization of BMP-2. BMPR-IA was immobilized on a Series S Sensor Chip C1 at 25 °C, again using the amine coupling reaction giving values of about 220 RU of BMPR-IA for starting concentrations of 50 μg/mL. A reference surface was prepared as described above. SPR Analysis of GAG Binding to Immobilized BMP-2. HBS-EP (0.01 M Hepes (pH 7.4), 0.15 M sodium chloride, 3 mM EDTA, 0.05% surfactant P20) was used as running buffer, and the interactions were studied at 37 °C. Each GAG sample was diluted in this buffer. GAGs were injected at concentrations of 1 μM, 10 μM, and 100 μM related to the molecular weight of disaccharide units (D.U.) for 5 min at 30 μL/min, and binding levels were recorded 10 s before injection stop (values were taken from the reference subtracted sensorgrams relative to a baseline report point). Since the GAGs used differ in their chain length and sulfation degree, we chose to inject the same molar concentrations in relation to the molecular weight of D.U. rather than the total molecular weight to be able to compare the same amount of D.U. as possible binding sites. Binding levels were corrected for the latter to account for the fact that they are related to mass increase at the sensor chip surface. The injection was followed by a 10 min dissociation phase in running buffer at a flow rate of 30 μL/min. The sensor chip surface was regenerated after each sample injection with a 30 μL injection of 5 M sodium chloride in 50 mM sodium hydroxide (NaOH) followed by a 30 μL injection of 100 mM NaOH. The baseline was allowed to stabilize for at least 5 min with running buffer prior to injection of the next sample.

For ranking of binding strength, injections were made in the order sHA3, sCS3, sHA1, CS, HALM. Data represent the mean of two repetitive experiments with BMP-2 immobilized onto one surface and one experiment with BMP-2 immobilized onto another surface. In a second independent approach, in which BMP-2 was immobilized to another sensor chip surface, the order was sHA3, sHA1Δ6s. Resulting values were then normalized to the binding response of 1 μM sHA3. Data represent the mean of three independent measurements. Binding parameters were evaluated using the Biacore T100 evaluation software 2.03. SPR Analysis of BMP-2/GAG Complex Binding to Immobilized BMPR-IA. Prior to interaction analysis, the chip surface with immobilized BMPR-IA was blocked with three injections of 1% BSA, 5% sucrose in HBS-EP (700 s at 30 μL/min) followed by an injection of 0.1 M acetic acid in 5 M NaCl (120 s at 10 μL/min). Between 0.2 and 10 μM D.U. of the respective GAGs were preincubated for 60 min at RT with 20 nM BMP-2 in HBS-EP. After four start up injections, BMP-2 with and without GAG was injected for 120 s at 30 μL/min. The injection was followed by a 10 min dissociation phase in running buffer at 30 μL/min. The sensor surface was regenerated after each sample injection with a 20 μL injection of 5 M sodium chloride in 100 mM acetic acid (10 μL/min) followed by 50 μL of 20 mM hydrochloric acid (50 μL/min). The baseline was allowed to stabilize for at least 1000 s with running buffer prior to injection of the next sample. Data were double referenced by the response of the reference surface and the preceding response of HBS-EP buffer alone or 10 μM D.U. of the respective GAG in the same buffer relative to a baseline report point. Modeling and Folding of the N-termini of BMP-2. The crystal structure of the complex of BMP-2 with the ectodomains of type I (BMPR-IA) and activin type IIB (BMPR-IIB) receptors24 (PDB ID 2H62) was used for modeling the N-termini of BMP-2, which are not resolved in any of the currently available crystal structures in the Brookhaven protein databank (PDB). The first 8 residues of the protein were initially modeled as extended coil in each of the monomers. Replica exchange molecular dynamics (REMD) simulations30 were performed using Gromacs31 v.4.5 with the AMBER force field.32 In the simulations, the modeled first 8 residues of BMP-2 and also residues 9−13, which are placed in a loop characterized by high thermal disorder, were left unrestrained. The relatively low conformational mobility of residue Cys14, which is involved in a disulfide bond that gives stiffness to the so-called cysteine knot, allowed us to adequately model and simulate each N-terminus as a distinct 13 amino acids long domain. Ideal holonomic constraints were used to fix the coordinates of the rest of the protein. Twelve replicas were used with temperatures spanning from 300 to 558 K and a distribution generated with an exchange probability of 0.25 (i.e., 300, 318, 337, 357, 378, 401, 424, 448, 474, 500, 528, 558).33 Simulations for 100 ns were performed with the BMP-2 dimer alone, leading to 200 ns sampling of N-terminus conformations. A simulation of 50 ns was performed for the ternary complex composed of the BMP-2 dimer and two pairs of its type I and type II receptors. The initial configurations used for the production runs were obtained by means of 10 ns equilibration at each temperature starting from the structure with the N-termini in extended conformation. The simulations were performed in implicit solvent (GB/SA continuum solvation model)34 using a rhombic dodecahedron box with a periodic image distance of 93 Å. The initial velocities for each replica were taken randomly from Maxwellian distributions. The simulations were carried out in NVT ensemble.35 The LINCS algorithm36 was used. For Coulomb and van der Waals interactions, a twin range cutoff of 10/16 and 10 Å were used, respectively. Neighbors lists were updated every 10 fs. A time step of 2 fs was used, and exchange between replicas was attempted every 10 ps, leading to an exchange rate of about 12 per ns. Modeling and Docking of GAGs. Tetrameric GAGs HA3′, HA4, HA6, HA463′, CS4, and CS463′ were modeled in AMBER11.37 These molecules differ in the distribution of sulfate groups resembling tetramers present in the polymeric GAGs studied (Table 1). Charges were taken from the GLYCAM06 force field,38 and from literature39 for sulfates. Docking calculations were performed with Autodock 340 3085

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with a spacing grid of 0.5 Å. GAGs were treated completely flexible, whereas the optimized structures of BMP-2 in conformations nrb (nonreceptor binding), rb (receptor binding) and asym (asymmetric conformation of the BMP-2 N-termini in complex with receptor BMPR-IA) were used as rigid receptors. The Lamarckian genetic algorithm with an initial population size of 300 and a termination condition of 105 generations or 9995 × 105 energy evaluations was used. A total of 103 independent runs were performed. Spatial clustering of the 50 top docking solutions was done using the DBSCAN algorithm41 with a neighborhood search radius of 4 Å for the root-mean-square of atomic distances, while pairing up nearest atoms of the same type, and with a minimum of 5 cluster members. Complex Optimization by Molecular Dynamics (MD) and Free Energy Calculations. The complexes obtained by docking were optimized by MD with AMBER11 using ff99SB force field parameters for the proteins and GLYCAM06 for the GAGs. The complexes were solvated with TIP3P water molecules in an octahedral periodic box with a minimal distance to the periodic box border of 6 Å and neutralized by counterions. Two energy-minimization steps were carried out: 0.5 × 103 steepest descent cycles and 103 conjugate gradient cycles with harmonic force restraints on solute atoms, then 3 × 103 steepest descent cycles and 3 × 103 conjugate gradient cycles without constraints. This was followed by heating up the system from 0 to 300 K for 10 ps, a 50 ps MD equilibration run at 300 K, 106 Pa in isothermal isobaric ensemble (NPT) and a 10 ns productive MD run (NTP). The SHAKE algorithm, 2 fs time integration step, 8 Å cutoff for nonbonded interactions, and the Particle Mesh Ewald (PME) method were used. For GAGs, pyranose rings were harmonically restrained to be in 4C1 chair conformation. Free energy calculations were performed using MM-PBSA42 for 100 frames evenly distributed in the productive MD run. Statistical Analysis. The interaction of BMP-2 and GAGs (Figures 1 and 2) was evaluated using two-way ANOVA, while one-

Figure 2. Binding of BMP-2 to immobilized GAG derivatives as quantified by Sandwich ELISA with (A) capture antibodies against BMP-2 and by (B) BioLISA with BMPR-IA. Data represent the mean values of at least two independent experiments with each GAG analyzed in triplicate. Significant differences are indicated by ** (p < 0.01) and *** (p < 0.001).

Figure 1. Binding strength of GAG derivatives (1 μM, 10 μM, and 100 μM D.U.) to immobilized BMP-2 (645 RU) as determined via binding levels by SPR analysis at 37 °C. Binding data are the mean values of three independent measurements. Significant differences compared to sHA1Δ6s and sHA3 are indicated by *** (p < 0.001).

Figure 3. Release of bound BMP-2 from GAG derivatives over 8 days at 37 °C quantified by Sandwich ELISA (CA) and BioLISA (BMPRIA) in relation to the amount initially bound. Original BMP-2 concentration: 10 ng. Data are the mean values of triplicates. Significant differences (p < 0.05) for (a) compared to sHA1Δ6s and for (b) sCS3 and sHA3 compared to sHA1.

way ANOVA was used for all other sets (Figures 3 and 4). Tukey and Bonferroni posthoc tests of means comparison were applied in all cases to evaluate differences between the groups. All results are presented as mean ± SD with significant differences indicated by p < 0.05 (one asterisk), p < 0.01 and p < 0.001 (two and three asterisks).

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sugar), sHA1Δ6s, sulfated at the C2′, and C3′ positions of the acid and possibly at the C4 position but not at the C6 position of the N-acetyl-D-glucosamine), and CS (70% sulfated at the C4 position and 30% sulfated at the C6 position of the N-acetyl-D-galactosamine), and high (D.S. ∼ 3) for sHA3 and sCS3. The latter two are comparable in terms of their sulfation pattern and molecular weight (Table 1). SPR Analysis of GAGs Binding to BMP-2. The binding strength of GAG derivatives to immobilized BMP-2 (Figure 1) D-glucuronic

RESULTS Characterization of GAG Derivatives. Chart 1 gives an overview of the different GAGs used in this study, which differ in (i) the configuration of the N-acetyl-D-hexosamine ring (HA, gluco; CS, galacto), (ii) the sulfation pattern, and (iii) the D.S. values. These were low (D.S. ∼ 1) for sHA1 (exclusively sulfated at the C6 position of the N-acetyl-D-glucosamine 3086

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Figure 4. Interaction of BMP-2 with immobilized BMPR-IA (220 RU) after preincubation with different GAG derivatives. (A) Sensorgrams for the binding of 10 μM D.U. of sHA3 without (w/o) BMP-2 as well as of 20 nM BMP-2 alone or after preincubation with 0.2, 2, 5, and 10 μM D.U. of sHA3 (arrow points in the direction of increasing sHA3 concentration). (B) Binding levels of 20 nM BMP-2 alone or after preincubation with different concentrations of HALM, sHA1, and sHA3 D.U. Binding data are the average of triplicates. Significant difference compared to HALM. (C) Experimental data (solid black line), fit (dashed gray line), and components view of the fit for the interaction of BMP-2 and BMPR-IA (A + B1 = AB1 and A + B2 = AB2 model). (D) for the interaction of BMP-2 preincubated with 10 μM D.U. sHA3 and BMPR-IA (A + B = AB model).

complex was not complete with increasing concentration as opposed to all other BMP-2/GAG complexes, which explains the error bar at 100 μM D.U. sHA1Δ6s. ELISA Analysis of BMP-2 Binding to GAGs. The quantification of BMP-2 bound to GAG derivatives using capture antibodies revealed that binding is dependent on the degree of sulfation: high-sulfated GAGs interacted stronger than their lower-sulfated counterparts (Figure 2A). Sulfated HA derivatives were found to bind significantly more BMP-2 than CS derivatives of the same degree of sulfation. The low-sulfated sHA1Δ6s bound significantly more than sHA1, while binding of CS and HALM was not significantly different from the negative control (BSA). The findings could be confirmed using BMPR-IA receptor as capturing reagent (Figure 2B). However, differences between HA and CS derivatives of the same degree of sulfation were not significant. BMP-2 Release from GAGs as Determined by ELISA. BMP-2 is released differently from all GAG derivatives (Figure 3). The total release of BMP-2 over 8 days in relation to the amount initially bound exhibits a ranking as follows: sHA1 > sHA3 = sCS3 > sHA1Δ6s. Therefore, the high binding strength of sHA1Δ6s as compared to sHA1 is mainly due to the slow dissociation of complexes with BMP-2, which could be equally determined with either capture antibodies or BMPR-IA. SPR Analysis of BMP-2/GAG Interaction with Immobilized BMPR-IA. Sulfated HA derivatives affect BMP-2 binding to its receptor in a sulfation- and concentrationdependent manner (Figure 4). While neither 10 μM D.U.

Chart 1. Chemical Structures of Used GAG Derivatives

was found to depend on the degree of sulfation: high-sulfated GAGs interacted stronger than their lower-sulfated counterparts. Sulfated HA derivatives bound stronger than CS derivatives of the same degree of sulfation. This was particularly evident for the two high sulfated derivatives sHA3 and sCS3. No binding was detected for CS and HALM. The low-sulfated sHA1Δ6s, which is devoid of C6-sulfation interacted significantly stronger than its C6-sulfated counterpart sHA1. Furthermore, the regeneration of the BMP-2/sHA1Δ6s 3087

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one-to-one interaction model (A + B = AB). (Figure 4D). Obviously the transient component of the BMP-2-BMPR-IA interaction is abolished by prebound sHA3. This was also valid for sHA1, but only at the highest concentration tested. The complex stability, however, was only marginally influenced by the presence of sHA1 or sHA3 (Table 2). The kon and koff values shown in Table 2 display relative differences between the different analytes calculated with a BMP-2 concentration of 20 nM. Since the exact composition of the BMP-2/sHA complexes (i.e., number of BMP-2 molecules per GAG) and, therefore, their exact molecular weight is uncertain, KD values are not shown. Folding of the N-Termini of BMP-2. We investigated the folding of the N-termini in implicit solvent by REMD. The replica temperatures were chosen to obtain a constant probability over the whole temperature range. The obtained exchange frequencies fall in a range of 23−27%, in good agreement with the expected probability of 25%, indicating the high accuracy of temperature distribution (Supplementary Figure 1). In order to represent the accessible configurational space and to determine the most populated and stable conformations of the BMP-2 N-terminus, we computed a two-dimensional free energy landscape at 300 K and used two eigenvectors obtained from the dihedral principal component analysis performed on a set of ϕ and ψ dihedral angles of the N-terminal peptide (Figure 5).43 As expected, the N-termini are characterized by a large flexibility, given the absence of a unique most populated conformation. Among the local minima identified, we observed five most populated states corresponding to five main conformations adopted by the N-termini (numbered 1 to 5 in Figure 5). Their disposition in 3D was also analyzed in the context of the ternary complex BMP-2/BMPR-IA/BMPR-II to

HALM, sHA1, nor sHA3 alone bound to the immobilized BMPR-IA chimera, as shown for sHA3, the preincubation of BMP-2 with increasing sHA3 concentrations (0.2, 2, 5, and 10 μM D.U.) markedly reduced the growth factors association rate to the receptor (Figure 4A, Table 2) and led to significantly Table 2. Kinetic Rate Constants (kon, koff) for the Interaction of BMP-2 and BMP-2/GAG Complexes with Immobilized BMPR-IA kon [M−1 s−1]

analyte a

BMP-2

b c

BMP-2/sHA3 BMP2/sHA1

(1) (2) (1) (1)

1.9 2.3 2.6 9.2

± ± ± ±

0.8 1.4 1.3 0.7

× × × ×

koff [s−1] 7

10 108 105 106

(1) (2) (1) (1)

1.0 3.8 2.1 3.5

± ± ± ±

0.3 2.1 0.5 0.6

× × × ×

χ2 −3

10 10−1 104 103

0.76 0.04 0.41

Binding data for 20 nM BMP-2 (n = 6) were fitted to an A + B1 = AB1 and A + B2 = AB2 model, and those for b20 nM BMP-2 + 10 μM D.U. sHA3 (n = 6) and c20 nM BMP-2 + 10 μM D.U. sHA1 (n = 3) to an A + B = AB model. (1) Binding site 1 and (2) binding site 2 in the BMPR-IA chimera; analyt: binding partner in solution. The agreement of the four-parameter fitting with the experimental data is indicated with the Chi2 value (χ2). a

reduced binding levels and therefore binding strength as compared to HALM and sHA1 (Figure 4B). The latter only reduced binding levels at the two highest concentrations tested. HALM on the contrary did not influence BMP-2 binding to its receptor (Figure 4B) at any concentration. Interestingly, when BMP-2 was preincubated with 10 μM D.U. of sHA1 or any concentration of sHA3, the binding model applicable to fit the experimental data of the interaction between BMP-2 and its receptor changed from a model with two independent bindings sites (A + B1 = AB1 and A + B2 = AB2) in the homodimeric BMPR-IA chimera (Figure 4C) to a

Figure 5. Analysis of the REMD simulation of the BMP-2 N-termini with a 2D free energy landscape of their conformation (most populated: 1−5). BMP-2 dimer: yellow; N-termini: magenta; BMPR-IA: pink; BMPR-IIB: green (receptors are shown to illustrate potential steric hindrance). 3088

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consider any possibility of potential steric hindrance for receptor binding. In the most energetically favorable conformation observed (1), the N-termini form extended helicoidal structures that occupy the BMPR-IA binding site. In this conformation, the N-terminus interacts with α3 helix and the loop connecting it to strand β5 in the same subunit, and with the loop connecting strands β2 and β3 (residues 27−31) of the other subunit. In the other conformations observed (3, 4, and 5), the N-termini form well-defined α-helices. The difference between these three conformations resides essentially in the orientation of the helix axis, insomuch that they could be considered as subpopulations of a larger conformational state, as analogously observed for other growth factors of the same family (i.e., TGF-β1; PDB ID 3KFD). In these conformations (3, 4, 5), the α-helix occupies positions that might partially overlap with BMPR-IA binding site and could therefore potentially interfere with the assembling of the active ternary complex. Thus, we refer to conformations 1, 3, 4, and 5 as BMP-2nrb (nonreceptor binding). Another conformation (2) was observed in which the Ntermini adopt a helicoidal structure and pack against each other in a symmetric and antiparallel fashion over the cysteine knot connecting the two subunits. This conformation does not interfere with the binding regions of the receptors (Figure 5), and we refer to it as BMP2rb (receptor binding). Interestingly, residues 9 to 13 were observed to resemble their experimental structure (PDB ID 2H62).16 As the BMP-2 dimer consists of two BMP-2 monomers, and because we observe different behavior of the N-termini for each monomer (“receptor binding” or “non-receptor binding” conformation), we introduce the nomenclature nrb2 for that BMP-2 dimer having the two receptor binding sites blocked (BMP-2nrb2), and nrb1 for that BMP-2 dimer having one receptor binding site blocked (BMP-2nrb1). The BMP-2rb conformation (2) was taken as the starting structure for the REMD simulations of the ternary complex of the BMP-2 dimer with the receptors BMPR-IA and BMPR-IIB (i.e., BMP-2rb/BMPR-IA2/BMPR-IIB2) as it was the only conformation allowing receptor binding. In addition to the starting conformation, another one was observed in which the N-termini form helices that were not packing anymore in a symmetric fashion. One N-terminus remains in the initial position (over the cysteine knot), and the other changes its conformation and establishes contacts with the receptor BMPR-IA (Figure 6). We refer to this conformation as BMP2 asym (asymmetric receptor binding). This asymmetric orientation of the N-termini turned out to be the most stable during the simulations (data not shown). Docking of GAGs to BMP-2 and to BMP-2/BMPR-IA. Docking and MD were used to predict and analyze GAG recognition by the BMP-2 dimer. We first carried out docking calculations of tetrameric GAG derivatives with BMP-2nrb1, BMP-2nrb2, and BMP-2rb. In all cases, the docked GAGs adopted similar binding poses. Higher sulfation of GAGs leads to stronger binding (Table 3). Interestingly, we observed that HA derivatives bind stronger than CS ones of the same sulfation degree. To investigate the molecular mechanisms underlying the impact of GAGs on the biochemical function of BMP-2, the same docking and MD procedure was applied to analyze the binding of the tetrameric GAGs to the BMP-2/BMPR-IA complex. When BMP-2rb and BMP-2nrb1 are bound to BMPRIA, the GAG binding energy (ΔGGAG) is less favorable than in

Figure 6. BMP-2asym/(BMPR-IA)2/(BMPR-IIB)2 complex (folding of N-termini (magenta) simulated by REMD). The BMP-2 dimer is shown in yellow, BMPR-IA in pink, and BMPR-IIB in green.

Table 3. MM-PBSA Free Binding Energies of GAG Tetramers and BMPR-IA to the BMP-2 Dimer GAG

complex

ΔGGAG (kcal/mol)

ΔGBMPR‑IA (kcal/mol)

HA6 HA4 HA3′ HA43′ HA463′ CS6 CS4 CS46 CS463′ HA4 HA3′ HA463′ CS4 CS463′ HA4 HA3′ HA463′ CS4 CS463′

BMP-2nrb1-GAG BMP-2nrb1-GAGa BMP-2nrb1-GAG BMP-2nrb1-GAG BMP-2nrb1-GAG BMP-2nrb1-GAG BMP-2nrb1-GAG BMP-2nrb1-GAG BMP-2nrb1-GAG BMP-2nrb1-RI-GAGb BMP-2nrb1-RI-GAG BMP-2nrb1-RI-GAG BMP-2nrb1-RI-GAG BMP-2nrb1-RI-GAG BMP-2rb-GAGc BMP-2rb-GAG BMP-2rb-GAG BMP-2rb-GAG BMP-2rb-GAG BMP-2rb, nrb1-RI BMP-2rb-RI-GAG BMP-2rb-RI-GAG BMP-2rb-RI-GAG BMP-2rb-RI-GAG BMP-2rb-RI-GAG BMP-2asym-RId BMP-2asym-RI-GAG BMP-2asym-RI-GAG BMP-2asym-RI-GAG BMP-2asym-RI-GAG BMP-2asym-RI-GAG

−26.0 ± 7.2 −39.5 ± 17.2 −33.8 ± 12.3 −39.7 ± 7.4 −54.5 ± 14.0 −25.8 ± 12.5 −38.5 ± 8.1 −36.0 ± 9.2 −46.0 ± 11.0 −40.2 ± 13.1 −29.9 ± 9.0 −49.7 ± 10.5 −33.7 ± 8.0 −42.6 ± 11.1 −39.8 ± 9.5 −46.3 ± 14.1 −81.7 ± 15.4 −31.1 ± 9.2 −63.7 ± 10.4 −30.9 ± 10.2 −25.6 ± 8.9 −49.9 ± 15.2 −24.1 ± 8.3 −54.9 ± 11.6 −21.1 ± 7.1 −19.6 ± 9.1 −48.3 ± 12.7 −17.3 ± 10.1 −52.4 ± 13.6

−73.0 ± 9.9 −81.8 ± 10.4 −66.8 ± 11.5 −75.2 ± 13.1 −63.5 ± 10.1 −89.1 ± 21.9 −78.4 ± 17.8 −75.8 ± 15.0 −60.5 ± 17.0 −81.0 ± 13.7 −77.6 ± 15.2 −87.1 ± 18.2 −87.5 ± 14.1 −97.5 ± 18.4 −90.4 ± 16.5 −89.3 ± 18.4 −93.1 ± 14.8

HA4 HA3′ HA463′ CS4 CS463′ HA4 HA3′ HA463′ CS4 CS463′ a

BMP-2nrb1: BMP-2 dimer having one receptor binding site blocked. RI: BMPR-IA. cBMP-2rb: receptor binding conformation. dBMP2asym: asymmetric receptor binding conformation. b

the absence of BMPR-IA for all analyzed GAGs, and especially for those highly sulfated (Table 3) being more pronounced for the HA derivatives than for the CS ones. This is due to an electrostatic repulsion between the negatively charged GAGs and residues in BMPR-IA. 3089

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Figure 7. Schematic representation of the model proposed for BMP-2/GAG/BMPR-IA recognition. The BMP-2 dimer is shown in a yellow cartoon with the N-termini in magenta. BMPR-IA (RI) is shown in pink. A representative GAG (G) binding pose is shown in atom-colored sticks. BMP-2nrb1 and BMP-2nrb2: BMP-2 dimer having one and two receptor binding sites blocked, respectively; BMP-2rb: BMP-2 receptor binding conformation; BMP-2asym: BMP-2 asymmetric receptor binding conformation.

conformations adopted by the BMP-2 N-termini. The analysis of the energetically favorable conformations obtained shows two substantially different scenarios for receptor recognition: receptor-binding (BMP-2rb, BMP-2asym) and nonreceptor binding (BMP-2nrb1 and BMP-2nrb2) conformations. In a schematic view in Figure 7, we summarize our findings on GAG and receptor recognition by BMP-2 and highlight the crucial role of the conformational plasticity of the N-termini for the establishment of these interactions. In accordance to previously reported data on heparin binding by BMP-2, 4,21 our ELISA, BioLISA and SPR results demonstrate that BMP-2 also interacts with the chemically sulfated GAGs used in this study. GAG recognition by BMP-2 reveals preferences for GAG type, sulfation pattern, and degree as previously reported for BMP-4 and TGF-β1.25,26 In particular, for the low sulfated sHA derivative, sHA1Δ6s, which is devoid of a sulfation in the C6 position of the Nacetyl-D-glucosamine, a significantly stronger BMP-2 binding was observed than for the sHA1 variant. This could be attributed to a slower dissociation of the BMP-2/sHA1Δ6s complex in release experiments. A sulfation in the C6 position is potentially unfavorable for BMP-2/sHA1 complex formation, which is supported by our computational experiments (see Table 3). Furthermore, we found that for the same sulfation degree, HA derivatives bind stronger than their CS counterparts. These experimental results agree with observations from our computational studies. According to our MD analysis, an increase in the GAGs sulfation degree leads to more favorable interactions with BMP-2 for both BMP-2nrb1 and BMP-2rb conformations. We also predict that CS derivatives bind weaker than HA derivatives with the same sulfation degree, which suggests an important role of the N-acetylated D-hexosamine ring C4 epimer for GAG binding.

Similarly, the free energy change due to receptor binding to BMP-2rb/GAG and to BMP-2nrb1/GAG (ΔGBMPR‑IA) is less favorable than the corresponding binding to BMP-2rb and to BMP-2nrb1 for all analyzed GAGs; being also in this case more prominent for HA than for CS derivatives. In the case of GAG binding to BMP-2asym/BMPR-IA, the energy (ΔGGAG) was slightly less favorable than in case of binding to BMP-2rb/ BMPR-IA for all analyzed GAGs. For the BMP-2asym/BMPRIA/GAG tertiary complexes no significant difference in terms of ΔGGAG was found for HA and CS derivatives binding. The energy of receptor binding to BMP-2asym/GAG (ΔGBMPR‑IA) was slightly more favorable than the corresponding binding to BMP-2asym for all analyzed GAGs. In summary, our results show that the strength of GAG binding to BMP-2 and to BMP-2/BMPR-IA as well as binding of BMP-2/GAG to BMPR-IA is dependent on sulfation and GAG type.

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DISCUSSION The major goal of this study was to characterize the effect of sulfation pattern and degree of HA and CS derivatives on their interaction profile with BMP-2 applying experimental and computational approaches. Furthermore, we aimed to investigate the relevance of these interactions in terms of the capability of BMP-2 to bind its receptor BMPR-IA in the presence of these GAG derivatives. Based on our results, we propose a model that explains the observed structural, dynamic and binding properties of the BMP-2/GAG/BMPR-IA system and suggests a potential mechanism underlying its signaling properties. In order to achieve these goals, it was necessary to examine the folding properties of the N-termini of BMP-2, which were reported to be highly flexible and responsible for GAG recognition. For this, we applied REMD techniques, which allow a significantly enhanced sampling of the possible 3090

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According to our computational studies, the BMP-2nrb conformation is at equilibrium with BMP-2rb, which is less favorable (Figure 7, left) but able to bind to the receptor BMPR-IA and therefore potentially allows signaling. The conversion from BMP-2nrb to BMP-2rb is slowed down when GAGs bind to BMP-2nrb (Figure 7, left), which represents a hindrance for the conformational transition and therefore also for interaction with two BMPR-IA molecules. We observe that the higher the GAG sulfation, the stronger the interaction and, therefore, a more pronounced shift toward BMP-2nrb takes place. This is corroborated with our experimental SPR data, which point out that when the GAG derivatives are prebound to BMP-2, they significantly reduce the association rate and therefore the binding strength to the receptor in a concentration and sulfation dependent manner. These findings agree with previously reported data showing that heparin weakens BMP-2 binding to its functional receptor.18,19,21 Furthermore, Kuo et al. observed no effect of heparan sulfate on the formation of the BMP-2/BMPR-IA complex8 for BMP-2 mutants with truncated N-termini, supporting their key role in the BMP-2/BMPR-IA complex formation in the presence of GAGs. Bramono et al., however, reported a slightly increased BMP-2/BMPR-IA interaction in the presence of heparin and some heparan sulfate variants tested in coimmunoprecipiation experiments. 44 It should be taken into account that immunoprecipitation, in contrast to our SPR measurements, only addresses complex stability but not complex formation kinetics. Moreover, our SPR data demonstrate that the GAGs studied do not bind to the receptor BMPR-IA, which is in line with findings of Bramono et al. for heparin and several heparan sulfates.44 This supports our conclusion that the observed alteration of the BMP-2/BMPR-IA interaction profile by GAGs is rather due to direct interactions of the GAGs with BMP-2. In contrast, Kanzaki et al. claimed that heparin interacts with BMP-2 as well as BMPR using quartz-crystal microbalance, where both receptor types were immobilized simultaneously instead of BMPR-IA only.21 Interestingly, the kinetic data we obtained from SPR experiments for BMP-2 preincubated with sHA3 and sHA1 at high concentrations fit to a binding model in which the BMP-2 dimer recognizes only one BMPR-IA molecule, which corresponds to the BMP-2nrb1/BMPR-IA complex from our molecular modeling experiments. This differs from the signaling complex consisting of two BMPR-IA binding sites per BMP-2 dimer (corresponding to the BMP-2rb/BMPR-IA complex), which implies a structural asymmetry in the BMP-2/BMPR-IA system that could be modulated by sulfated HA derivatives. Such molecular recognition could have important functional implications affecting signaling. Consistent with these observations, our calculations provide a structural and energetic explanation for this asymmetry in the BMP-2/BMPR-IA complex and how its intrinsic structural and dynamical properties are modulated by GAGs. Our results suggest that a BMP-2 bound to the GAGs in the less favorable BMP-2rb conformation provide a symmetric complex that can bind to two BMPR-IA receptor molecules and is, therefore, biologically active. In this BMP-2rb/GAG/(BMPR-IA)2 complex, the GAG affinity is also sulfation-dependent, but it is lower than in the respective BMP-2rb/GAG complex. At the same time, the interaction of BMPR-IA with the preformed BMP-2rb/GAG complex is energetically less favorable with increasing sulfation, which would putatively lead to lower biological activity. Both

aspects are due to repulsive electrostatic interactions between a negatively charged region in BMPR-IA in close proximity to the GAG binding site and the bound GAGs. Dissociation of the GAG from the BMP-2rb/(BMPR-IA)2 complex might leave the N-termini free to sample the conformational space in a nonconcerted manner. Our folding studies of the BMP-2 N-termini in the presence of both receptors, BMPR-IA and BMPR-IIB, indicate the possibility of an asymmetric disposition of the N-termini (BMP-2asym), which corresponds to an energetically more favorable conformation in which one N-terminus establishes contacts with BMPR-IA and stabilizes the interaction (Figure 7, right). Structural asymmetry, although not frequent, has been observed in biological systems to perform specialized functions (e.g., a key element in allosteric interactions).45,46 Our computational data show that the complex BMP-2asym/ BMPR-IA is also able to bind GAGs in a sulfation-dependent manner with a slightly weaker affinity than BMP-2rb/BMPR-IA.

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CONCLUSION Based on our experimental and computational results, we conclude that sulfated GAGs lead to alterations in the molecular recognition profile of BMP-2 to its receptor BMPR-IA. We show that the conformational plasticity of the BMP-2 N-termini has a key role in the structural and thermodynamic characteristics of the BMP-2/GAG/BMPR-IA system. Moreover, we establish that the recognition of GAGs by BMP-2 and by the BMP-2/BMPR-IA complex is dependent on the GAG type, sulfation pattern and degree. The same applies to the recognition of BMPR-IA by the BMP-2/GAG complex. We provide direct insights into the importance of the structural and dynamical properties of the BMP-2/BMPR-IA system for its regulation by sulfated GAGs, in which structural asymmetry plays a key role. Our model explains the obtained kinetic experimental data and contributes to the understanding of protein−GAG interactions.

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ASSOCIATED CONTENT

S Supporting Information *

Statistics from replica exchange MD simulations for BMP-2. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Authors

*E-mail: [email protected] (V.H.). *E-mail: [email protected] (M.T.P.). Author Contributions

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

Shared first authorship due to equal contribution to this work.

Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The authors would like to thank Alina Miron, Sarah Beckmann and Heike Zimmermann for excellent technical assistance with the ELISA studies. We are thankful to Ralf Gey for its invaluable IT support and to Dr. Anja Drescher for critical 3091

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suggestions to the SPR part. This work has been financially supported by the DFG German Research Council (SFBTRR67; A2, A3, A7).

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(28) van der Smissen, A.; Hintze, V.; Scharnweber, D.; Moeller, S.; Schnabelrauch, M.; Majok, A.; Simon, J. C.; Anderegg, U. Biomaterials 2011, 32, 8938−8946. (29) Becher, J.; Möller, S.; Weiss, D.; Schiller, J.; Schnabelrauch, M. Macromol. Symp. 2010, 296, 446−452. (30) Sugita, Y.; Okamoto, Y. Chem. Phys. Lett. 1999, 314, 141−151. (31) Hess, B.; Kutzner, C.; van der Spoel, D.; Lindahl, E. J. Chem. Theory Comput. 2008, 4, 435−447. (32) Duan, Y.; Wu, C.; Chowdhury, S.; Lee, M. C.; Xiong, G.; Zhang, W.; Yang, R.; Cieplak, P.; Luo, R.; Lee, T.; Caldwell, J.; Wang, J.; Kollman, P. J. Comput. Chem. 2003, 24, 1999−2012. (33) Patriksson, A.; van der Spoel, D. Phys. Chem. Chem. Phys. 2008, 10, 2073−2077. (34) Qiu, D.; Shenkin, P. S.; Hollinger, F. P.; Still, W. C. J. Phys. Chem. A 1997, 101, 3005−3014. (35) Bussi, G.; Donadio, D.; Parrinello, M. J. Chem. Phys. 2007, 126, 014101. (36) Hess, B.; Bekker, H.; Berendsen, H. J. C.; Fraaije, J. G. E. M. J. Comput. Chem. 1997, 18, 1463−1472. (37) Case, D. A.: Darden, T. A.; Cheatham, T. E.; Simmerling, C. L.; Wang, J.; Duke, R. E.; Luo, R.; Walker, R. C.; Zhank, W.; Merz, K. M.;Roberts, B.; Wang, B.; Hayik, S.; Roitberg, A.; Seabra, G.; Kolossváry, I.; Wong, K. F.; Paesani, F.; Vanicek, J.; Liu, J.; Wu, X.; Brozell, S. R.; Steinbrecher, T.; Gohlke, H.; Cai, Q.; Ye, X.; Wang, J.; Hsieh, M. J.; Cui,G.; Roe, D. R.; Mathews, D. H.; Seetin, M. G.; Sagui, C.; Babin, T.; Luchko, T.; Gusarov, S.; Kovalenko, A.; Kollman, P. A. Amber11; University of California: San Franscisco, CA, 2010. (38) Kirschner, K. N.; Yongye, A. B.; Tschampel, S. M.; GonzalezOuteirino, J.; Daniels, C. R.; Foley, B. L.; Woods, R. J. J. Comput. Chem. 2008, 29, 622−655. (39) Huige, C. J. M.; Altona, C. J. Comput. Chem. 1995, 16, 56−79. (40) Morris, G. M.; Goodsell, D. S.; Halliday, R. S.; Huey, R.; Hart, W. E.; Belew, R. K.; Olson, A. J. J. Comput. Chem. 1998, 19, 1639− 1662. (41) Ester, M.; Kriegel, H. P.; Sander, J.; Xu, X. AAAI Press 1996, 226−231. (42) Miller, B. R.; McGee, T. D.; Swails, J. M.; Homeyer, N.; Gohlke, H.; Roitberg, A. E. J. Chem. Theory Comput. 2012, 8, 3314−3321. (43) Mu, Y.; Nguyen, P. H.; Stock, G. Proteins 2005, 58, 45−52. (44) Bramono, D. S.; Murali, S.; Rai, B.; Ling, L.; Poh, W. T.; Lim, Z. X.; Stein, G. S.; Nurcombe, V.; van Wijnen, A. J.; Cool, S. M. Bone 2012, 50, 954−964. (45) Swapna, L. S.; Srikeerthana, K.; Srinivasan, N. PLoS One 2012, 7, e36688. (46) Goodsell, D. S.; Olson, A. J. Annu. Rev. Biophys. Biomol. Struct. 2000, 29, 105−153.

REFERENCES

(1) Gandhi, N. S.; Mancera, R. L. Chem. Biol. Drug Des. 2008, 72, 455−482. (2) Celeste, A. J.; Iannazzi, J. A.; Taylor, R. C.; Hewick, R. M.; Rosen, V.; Wang, E. A.; Wozney, J. M. Proc. Natl. Acad. Sci. U. S. A. 1990, 87, 9843−9847. (3) Wozney, J. M. Mol. Reprod. Dev. 1992, 32, 160−167. (4) Ruppert, R.; Hoffmann, E.; Sebald, W. Eur. J. Biochem. 1996, 237, 295−302. (5) Wang, E. A.; Rosen, V.; Cordes, P.; Hewick, R. M.; Kriz, M. J.; Luxenberg, D. P.; Sibley, B. S.; Wozney, J. M. Proc. Natl. Acad. Sci. U. S. A. 1988, 85, 9484−9488. (6) Balemans, W.; Van Hul, W. Dev. Biol. 2002, 250, 231−250. (7) Kirsch, T.; Nickel, J.; Sebald, W. EMBO J. 2000, 19, 3314−3324. (8) Kuo, W. J.; Digman, M. A.; Lander, A. D. Mol. Biol. Cell 2010, 21, 4028−4041. (9) Kirsch, T.; Nickel, J.; Sebald, W. FEBS Lett. 2000, 468, 215−219. (10) Nickel, J.; Sebald, W.; Groppe, J. C.; Mueller, T. D. Cytokine Growth Factor Rev. 2009, 20, 367−377. (11) Zhao, B.; Katagiri, T.; Toyoda, H.; Takada, T.; Yanai, T.; Fukuda, T.; Chung, U. I.; Koike, T.; Takaoka, K.; Kamijo, R. J. Biol. Chem. 2006, 281, 23246−23253. (12) Bornemann, D. J.; Duncan, J. E.; Staatz, W.; Selleck, S.; Warrior, R. Development 2004, 131, 1927−1938. (13) Freeman, S. D.; Moore, W. M.; Guiral, E. C.; Holme, A. D.; Turnbull, J. E.; Pownall, M. E. Dev. Biol. 2008, 320, 436−445. (14) Olivares, G. H.; Carrasco, H.; Aroca, F.; Carvallo, L.; Segovia, F.; Larrain, J. Dev. Biol. 2009, 329, 338−349. (15) Mania, V. M.; Kallivokas, A. G.; Malavaki, C.; Asimakopoulou, A. P.; Kanakis, J.; Theocharis, A. D.; Klironomos, G.; Gatzounis, G.; Mouzaki, A.; Panagiotopoulos, E.; Karamanos, N. K. IUBMB Life 2009, 61, 447−452. (16) Rai, B.; Nurcombe, V.; Cool, S. M. Crit. Rev. Eukaryotic Gene Expression 2011, 21, 1−12. (17) Salbach, J.; Rachner, T. D.; Rauner, M.; Hempel, U.; Anderegg, U.; Franz, S.; Simon, J. C.; Hofbauer, L. C. J. Mol. Med. 2012, 90, 625− 635. (18) Jiao, X.; Billings, P. C.; O’Connell, M. P.; Kaplan, F. S.; Shore, E. M.; Glaser, D. L. J. Biol. Chem. 2007, 282, 1080−1086. (19) Takada, T.; Katagiri, T.; Ifuku, M.; Morimura, N.; Kobayashi, M.; Hasegawa, K.; Ogamo, A.; Kamijo, R. J. Biol. Chem. 2003, 278, 43229−43235. (20) Degat, M. C.; Dubreucq, G.; Meunier, A.; Dahri-Correia, L.; Sedel, L.; Petite, H.; Logeart-Avramoglou, D. J. Biomed Mater. Res. A 2009, 88, 174−183. (21) Kanzaki, S.; Takahashi, T.; Kanno, T.; Ariyoshi, W.; Shinmyouzu, K.; Tujisawa, T.; Nishihara, T. J. Cell Physiol. 2008, 216, 844−850. (22) Ohkawara, B.; Iemura, S.; ten Dijke, P.; Ueno, N. Curr. Biol. 2002, 12, 205−209. (23) Scheufler, C.; Sebald, W.; Hulsmeyer, M. J. Mol. Biol. 1999, 287, 103−115. (24) Weber, D.; Kotzsch, A.; Nickel, J.; Harth, S.; Seher, A.; Mueller, U.; Sebald, W.; Mueller, T. D. BMC Struct Biol. 2007, 7, 6. (25) Hintze, V.; Miron, A.; Moeller, S.; Schnabelrauch, M.; Wiesmann, H. P.; Worch, H.; Scharnweber, D. Acta Biomater. 2012, 8, 2144−2152. (26) Hintze, V.; Moeller, S.; Schnabelrauch, M.; Bierbaum, S.; Viola, M.; Worch, H.; Scharnweber, D. Biomacromolecules 2009, 10, 3290− 3297. (27) Kunze, R.; Rosler, M.; Möller, S.; Schnabelrauch, M.; Riemer, T.; Hempel, U.; Dieter, P. Glycoconjugate J. 2010, 27, 151−158. 3092

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