Skip to main content
The Journal of Biological Chemistry logoLink to The Journal of Biological Chemistry
. 2011 Jan 26;286(16):14608–14617. doi: 10.1074/jbc.M110.201954

The IL1α-S100A13 Heterotetrameric Complex Structure

A COMPONENT IN THE NON-CLASSICAL PATHWAY FOR INTERLEUKIN 1α SECRETION*

Sepuru K Mohan 1, Chin Yu 1,1
PMCID: PMC3077658  PMID: 21270123

Abstract

Interleukin 1α (IL1α) plays an important role in several key biological functions, such as angiogenesis, cell proliferation, and tumor growth in several types of cancer. IL1α is a potent cytokine that induces a wide spectrum of immunological and inflammatory activities. The biological effects of IL1α are mediated through the activation of transmembrane receptors (IL1Rs) and therefore require the release of the protein into the extracellular space. IL1α is exported through a non-classical release pathway involving the formation of a specific multiprotein complex, which includes IL1α and S100A13. Because IL1α plays an important role in cell proliferation and angiogenesis, inhibiting the formation of the IL1α-S100A13 complex would be an effective strategy to inhibit a wide range of cancers. To understand the molecular events in the IL1α release pathway, we studied the structure of the IL1α-S100A13 tetrameric complex, which is the key complex formed during the non-classical pathway of IL1α release.

Keywords: Cytokine, NMR, Protein Export, Protein Secretion, Protein Structure, Protein-Protein Interactions, Non-classical Pathway

Introduction

Interleukin 1α (IL1α) and interleukin 1β (IL1β) are prototypic members of the IL1 gene family; these proteins are well recognized for their inflammatory and angiogenic activities (14). IL1α is a potent cytokine that possesses a wide spectrum of immunological and inflammatory activities (5, 6). It is also involved in pathological processes such as restenosis and tumor formation (7, 8). IL1α is synthesized as a higher molecular weight precursor protein, pIL1α, which is cleaved by calpain or a calpain-like protease to form mature IL1α. The biological functions of IL1α are mediated by binding to transmembrane receptors and thus require the export of mature IL1α to the extracellular space (9, 10).

In general, proteins are exported via the ER-Golgi pathway with the help of a hydrophobic N-terminal sequence, which allows the protein to enter the ER-Golgi pathway (11). However, several extracellular proteins such as IL1α, IL1β, fibroblast growth factor (FGF1 and FGF2), S100A13, sphingosine kinase 1, gelectin-1, and the extra vesicular p40 fragment of Syt1 all lack N-terminal signal sequences and are exported via ER-Golgi independent non-classical routes (10, 1214). Most of these proteins are involved in several key biological functions, such as angiogenesis, cell proliferation or differentiation, and tumor growth. It was first assumed that angiogenic growth factors could be released from mechanically injured tissues to promote wound healing, a process that requires angiogenesis. Various lines of evidence demonstrated that these proteins are exported from cultured cells in the absence of cell death (15, 16). IL1α is secreted by a different pathway, which is activated by diverse forms of stress, including heat shock (15, 16) and serum starvation (17). Thus, it is important to understand and define the non-classical pathway responsible for the export of IL1α; this information may eventually help in the clinical management of inflammatory and angiogenic-dependent events. In this article we discuss the molecular interactions in the non-classical secretory pathway of interleukin 1α.

IL1α and FGF1 are structurally homologous proteins, which are exported via an ER-Golgi independent pathway (18). In both cases, a multiprotein complex forms and traverses the membrane. Unlike FGF1, IL1α release does not depend on the covalent dimerization of IL1α. Mature IL1α is exported as a monomeric, biologically active cytokine (19, 20). In this non-classical secretion pathway, FGF1 associates with S100A13 and Syt1, whereas IL1α associates with S100A13; these protein complexes then bind to copper ions before being secreted. IL1α and the Ca2+ binding protein S100A13 associate in the cytoplasm (19, 20). Apparently, both proteins are secreted together. Direct roles for S100A13 in the export of IL1α have been demonstrated by the expression of a dominant-negative S100A13 mutant that attenuates the export of IL1α (19).

S100A13 is a member of the S100 protein family. It is characterized by its specificity for diverse forms of cancer (2124). S100A13 acts as a template molecule for the non-classical secretion pathway of IL1α, FGF1 (25), and prothymosin-α (26). S100A13 has been reported to co-express with IL1α in brain tumors, demonstrating a perivascular distribution. S100A13 is a member of the family of Ca2+-binding proteins that is characterized by the absence of a classical signal peptide sequence and the presence of two EF-hand domains. S100A13 is a novel member of the S100 gene family, which encodes a highly charged carboxyl-terminal domain that could be involved in specific protein interactions. S100 proteins are characterized by two distinct EF-hand motifs that have different Ca2+ affinities (27). Maciag and co-workers (19, 20) demonstrated that S100A13 is involved in regulating the release of IL1α in response to stress, independent of the conventional ER-Golgi pathway. When S100A13 is expressed in IL1α-free cells, it is spontaneously released via a non-classical pathway at both at 37 and 42 °C; however, when it is expressed in cells with IL1α, it is released only in response to heat shock (19). An additional indication of the participation of S100A13 in the export of pro-inflammatory cytokines is its specificity for binding to anti-inflammatory drugs such as amlexanox and chromolyn (28). S100A13 appears to be the central player in the formation of this complex.

These results suggest that IL1α-S100A13 complex formation is the first step in the export of IL1α, followed by direct translocation of this protein complex across the plasma membrane. In this article, we describe the interfacial regions of the solution structures of free IL1α and the IL1α-S100A13 complex. Our results demonstrate that S100A13 acts as a template for the formation of the multiprotein complex.

EXPERIMENTAL PROCEDURES

Ingredients for Luria Broth were obtained from AMRESCO. Aprotinin, pepstatin, leupeptin, phenylmethylsulfonyl fluoride, Triton X-100, and β-mercaptoethanol were obtained from Sigma. Heparin and glutathione-Sepharose were obtained from Amersham Biosciences. 15NH4Cl, 13C-labeled glucose, and D2O were purchased from Cambridge Isotope Laboratories. All other chemicals used were of high quality analytical grade. Unless specified, all solutions were made in 25 mm sodium phosphate containing 100 mm NaCl and 2 mm CaCl2.

Expression and Purification of the IL1α and S100A13

Human IL1α cDNA encoding the recombinant protein was subcloned into a pET(20b+) expression vector. IL1α was overexpressed and purified as described by Chang et al. (29). Human S100A13 cDNA encoding the recombinant protein was subcloned into a pGEX-4T1 expression vector. S100A13 was expressed in Escherichia coli BL21(DE3). The unlabeled protein was expressed in Luria broth (LB) medium. The soluble portion of the cell lysate was loaded onto a GST-Sepharose column. Nonspecifically bound proteins were removed by washing the column with PBS. The bound GST-S100A13 protein was eluted with 10 mm glutathione and 50 mm Tris-HCl (pH 8.0). The GST-fused S100A13 protein was exchanged into PBS, and the solution was treated with 50 μg of thrombin for 10–12 h to cleave the GST fusion protein. The protein was reloaded onto a GST column to obtain pure S100A13. The S100A13 and IL1α were further purified by gel filtration on a Superdex-75 (GE Healthcare) column with 25 mm sodium phosphate (pH 6.5) containing 100 mm NaCl and 2 mm calcium chloride as the eluent. The purity of the protein was verified by SDS-PAGE, and the molecular weight was confirmed by electrospray mass spectrometry.

Preparation of Isotopically Enriched IL1α and S100A13

Uniform 15N and 15N, 13C labeling of IL1α and S100A13 was achieved by culturing the cells in M9 minimal medium containing either 15NH4Cl for single (15N) labeling or 15NH4Cl and 13C glucose for double (15N and 13C) labeling. To achieve maximal expression yields, the composition of the M9 medium was modified by the addition of a vitamin mixture. The expression host strain E. coli BL21(DE3) pLysS is a vitamin B1-deficient host; therefore, the medium was supplemented with thiamine (vitamin B1).

Isothermal Titration Calorimetry

Protein-protein binding was characterized by measuring the change in heat caused by titration of one binding partner into a solution containing the other binding partner, using a Microcal VP titration calorimeter at 25 °C. IL1α and S100A13 solutions (25 mm sodium phosphate (pH 6.5), 100 mm NaCl, and 2 mm calcium chloride) were centrifuged and degassed under vacuum before use. Titrations were performed by injecting 8-μl aliquots of protein (30 times; 0.1 mm) into 0.01 mm of the binding partner. The titration curves were corrected using buffer-protein and protein-buffer controls and analyzed using Origin software supplied by Microcal.

1H-15N HSQC2 Titration

NMR data were recorded at 25 °C on a Varian 700 MHz spectrometer equipped with a cold probe. For the two-dimensional heteronuclear experiments, the concentration of the proteins was ∼0.5 mm. All protein samples were prepared in 25 mm phosphate buffer (pH ∼ 6.5, 90% H2O, 10% D2O) containing 100 mm NaCl and 2 mm CaCl2. The 15N-labeled proteins were titrated with unlabeled protein at a 1:1 molar ratio. The weighted average of the 15N and 1H chemical shift perturbations was calculated using the equation Δδ = [(δ1H)2 + 0.2 (δ15N)2]1/2. Amide proton exchange rates were monitored by acquiring a series of 1H-15N HSQC spectra of the free protein and the protein in complex with other proteins involved in the multiprotein release complex. The spectra were processed with V-nmr and analyzed with SPARKY (30).

Three-dimensional NMR Experiments

Free IL1α resonances and the IL1α and S100A13 resonances in the IL1α-S100A13 tetrameric complex were assigned using various multidimensional NMR experiments. Assignments for the backbone 1H, 13C, and 15N resonances in the complex containing IL1α and S100A13 were obtained from three-dimensional HNCA and HNCOCA experiments (31). The side chain resonances were assigned using three-dimensional 15N-edited TOCSY-HSQC and HCCH-TOCSY data sets supplemented with CBCA(CO)NH (32) and HBHA(CO)NH (33) spectra. HNCO spectra were used to assign the carbonyl carbons (34). The aromatic resonances of IL1α and S100A13 were assigned using simultaneous 13C/15N-edited NOESY-HSQC spectra (35). Intermolecular distance restraints were derived from the three-dimensional 13C(ω2)-edited, 12C(ω3)-filtered NOESY-HSQC spectrum (36) of the 1:1 15N/13C/1H IL1α-14N/12C/1H S100A13 and 15N/13C/1H S100A13-14N/12C/1H IL1α complexes.

Structure Calculations

The free IL1α structure and structures of IL1α and S100A13 in the IL1α-S100A13 tetrameric complex were calculated iteratively with ARIA/CNS (version 2.2) using the PARALLHDG 5.3 force field in the PARALLHDG mode (37, 38). Preliminary structure calculations based on intramolecular NOE data and TALOS (39) data established that the backbone folds of IL1α and S100A13 are not substantially altered in the protein complex. Distance restraints, dihedral angles, and hydrogen bond constraints were used in the structure calculation. Interproton distance restraints for the structure calculations were derived from the 15N-separated NOESY-HSQC and 13C-separated NOESY-HSQC experiments. The quality of the calculated structures was assessed using PROCHECK (40).

Docking Studies

HADDOCK (4145) was used to dock IL1α and S100A13 in the tetrameric complex using the previously determined structures established by ARIA and intermolecular NOEs. Intermolecular distance restraints were derived from a three-dimensional 13C and 15N (F1)-filtered, 13C (F2)-edited, and 12C (F3)-filtered NOESY experiment. A scaling factor was determined by comparing the intensities of the resolved peaks with those of the corresponding peaks in the 13C-edited NOESY spectrum acquired for the IL1α-S100A13 complex. The chemical shift perturbations observed upon complex formation were used to define ambiguous interaction restraints for residues at the interface. Active residues were defined as those having both chemical shift perturbations and a relative residue accessible surface area larger than 50% for either side chain or backbone atoms as calculated by NACCESS (46). Passive residues were defined as all other surface non-accessible residues (having a relative residue accessible surface area smaller than 50% for side chain or backbone atoms). Ambiguous interaction restraints were defined between every active residue of the first protein and all active and passive residues of the second protein and vice versa. A total of 5000 rigid-body docking trials were carried out using the standard HADDOCK protocol. The 100 lowest energy solutions were used for subsequent semiflexible simulated annealing and water refinement. The 20 lowest energy structures were used to represent the structure of the complex. The structures were analyzed with PROCHECK (40).

RESULTS

In this report, we studied the solution structure of free IL1α and its interactions with S100A13 by ITC and NMR. We solved the solution structure of the IL1α-S100A13 complex, a key component in the non-classical secretion pathway of IL1α. We also studied the interaction of amlexanox with IL1α, which is known to inhibit the non-classical secretion pathway of IL1α and S100A13.

Structure of Free IL1α

The complete resonance assignments of free IL1α were deposited in the BMRB under the accession number 16379. A set of 1536 intramolecular NOEs was assigned from the three-dimensional 15N-edited NOESY-HSQC and converted into 1458 relevant distance restraints. In addition, 62 hydrogen bonds, identified from deuterium exchange experiments, were also used. Thus, a total of 1520 distance restraints were used in the final structure calculations (Table 1). Fig. 1A shows the superposition of the 20 lowest-energy structures. (The coordinates of these structures have been deposited in the Protein Data Bank as 2KKI.) The average r.m.s. deviation value for the secondary structure region was 0.38 ± 0.02 Å for the backbone atoms and 0.81 ± 0.02 Å for all heavy atoms. Analysis of the structures by PROCHECK indicated good stereochemistry for the bond angles and bond lengths and showed that 98.6% of all of the non-glycine residues fall within the allowed region of the Ramachandran plot (Table 1).

TABLE 1.

Structural statistics for the final 18 simulated annealing structures of free IL1α

Calculations
Structural statistics of free IL1α from ARIA/CNS restrained calculations
    Protein distance restraints
        Total 1458
        Intra-residue 275
        Sequential 376
        Medium range 1〈|i-j|〉 <5 278
        Long range 〈|i-j|〉 ≥5 529
        H-bond restraints 62
        Dihedral angle restraints 220

    Structural statistics for 20 structures
        Average r.m.s. deviation
            Backbone r.m.s. deviation to mean (Å) 0.58 ± 0.02 Å
            Heavy atoms r.m.s. deviation to mean (Å) 1.35 ± 0.03 Å
        Average r.m.s. deviation (structured region)
            Backbone r.m.s. deviation to mean (Å) 0.38 ± 0.02 Å
            Heavy atom r.m.s. deviation to mean (Å) 0.81 ± 0.03 Å

    Ramachandran analysis
        Residues in most favored regions 78.0%
        Residues in additional allowed regions 18.9%
        Residues in generously allowed regions 1.7%
        Residues in disallowed regions 1.4%
FIGURE 1.

FIGURE 1.

A, superposition of the backbone (N, Cα, and C′) atoms of the 20 final solution structures of free IL1α. The cyan, orange, and gray colors represent β-strand, helix, and loop regions, respectively. B, ribbon representation of the 20 final solution structures of free IL1α.

Fig. 1B shows the superposition of an ensemble of 20 structures of free IL1α. The free IL1α structure contains 13 β-strands (β1, 12–26; β2, 31–34; β3, 40–43; β4, 54–60; β5, 69–74; β6, 78–82; β7, 90–93; β8, 101–102; β9, 111–116; β10, 119–124; β11, 131–132; β12, 142–143; β13, 151–155) and one α-helix (α1, 104–109). The chemical shift index of free IL1α was calculated using the Hα, Cα, Cβ, and C′ resonances (47). The consensus chemical shift index (supplemental Fig. S1) also indicated that IL1α consists of 13 β-strands connected by turns. Although the position of the β-strands were shifted, truncated, or elongated by one or two residues, the predicted secondary structure of IL1α from the chemical shift index agreed well with the secondary structure observed in the structure. According to the crystal structure, IL1α contains 12 β-strands. The range of β-strands in the NMR structure is almost the same as in the x-ray structure. The core of this structure is a 6-stranded β-barrel that is closed at one end by another 6 β-strands to form a bowl-like structure. The main feature of the structural core is that it has nearly precise internal 3-fold symmetry. The r.m.s. deviation difference between the solution structure and the x-ray structure (48) for the backbone atoms was 1.31 Å.

IL1α-S100A13 Binding Studies

Isothermal titration calorimetry (ITC) is a useful technique for the study of protein-protein interactions (49). ITC can be used to reliably measure the binding constants and energy changes that accompany protein-protein binding. Most importantly, ITC provides information on the number of protein binding sites. We measured the binding affinities of IL1α to S100A13 and S100A13 to IL1α by ITC (Fig. 2). The binding constants are in the range of 2.15–3.23 × 10−6 m.

FIGURE 2.

FIGURE 2.

Isotherm representing the binding of S100A13 to IL1α at 25 °C. The raw data of the titration of S100A13 with IL1α are shown in the upper panel, and the lower panel shows the integrated data obtained after subtracting the heat of dilution. The titrations were performed in 25 mm sodium phosphate (pH 6.5) containing 100 mm NaCl and 2 mm calcium chloride.

Chemical shift perturbation is the most commonly used NMR method to map protein interfaces (50, 51). The cross-peaks in the 1H-15N HSQC spectrum that are perturbed upon addition of the unlabeled protein often represent the binding site(s) of the protein to the target protein. Therefore, monitoring 1H-15N chemical shift perturbations by observing the shifts in the 1H-15N HSQC spectrum provides residue-level information about the protein-protein interface. The interaction causes changes in the chemical environment of the protein interface and therefore affects the chemical shifts of the nuclei in that area. 15N chemical shift perturbation has been used in many cases to map protein-protein interactions (5052). To understand the mechanism of the IL1α non-classical secretion pathway at the molecular level, we solved the structures of free IL1α and the IL1α-S100A13 tetrameric complex, which is potentially the key complex formed in the non-classical secretion pathway of IL1α.

In the IL1α-S100A13 binary complex, we mapped IL1α binding sites on S100A13 and S100A13 binding sites on IL1α based on the chemical shift perturbations observed in the 1H-15N HSQC spectrum. 1H-15N HSQC spectra of free IL1α and free S100A13 are well dispersed, and the cross-peaks of the backbone amide protons of the 138 residues of IL1α and the 96 residues of S100A13 were unambiguously assigned. At a IL1α (15N labeled):S100A13 (unlabeled) ratio of 1:1, cross-peaks corresponding to 16 residues in IL1α (Leu40, Thr41, Gln84, Asp85, Glu86, Asp87, Val90, Leu92, Lys93, Glu94, Met95, Gly104, Ser105, Glu106, Val125, and Ala126) were perturbed upon complex formation, whereas the chemical shifts of the other residues were nearly identical to those of the free IL1α (supplemental Fig. S2A). These 16 residues possibly constitute the S100A13 binding site(s) in IL1α. The plot of the weighted average of the 15N-1H chemical shift perturbations of the residues in IL1α upon complex formation with S100A13 also shows that a maximum of 16 residues are perturbed (supplemental Fig. S2B). These residues are distributed in four regions of IL1α (Leu40–Thr41, Gln84–Met95, Gly104–Glu106, and Val125–Ala126) and are close to helix 1, loop 1, and the basic rich C-terminal region of S100A13. At a IL1α (unlabeled):S100A13 (15N labeled) ratio of 1:1, cross-peaks corresponding to 17 residues, including Glu14′, Val17′, Phe21′, Phe23′, Arg25′, Arg29′, Lys30′, Asp31′, Ser32′, Leu33′, Lys72′, Phe73′, Asn74′, Arg88′, Lys89′, Leu93′, and Ile95′ (′ indicates S100A13 residues) are peak-broadened upon complex formation, whereas the chemical shifts of the other residues are the same as those of free S100A13 (supplemental Fig. S3A). These residues might constitute the IL1α binding site(s) in S100A13. A plot of the weighted average of the 15N and 1H chemical shift perturbation of residues in S100A13 upon complex formation with IL1α shows that the S100A13 binding region is distributed in helix 1, loop 1, and the basic C-terminal region (supplemental Fig. S3B).

Comparison of the H/D exchange rates of the individual amide protons in the free and bound states confirmed the binding interfaces in the IL1α-S100A13 complex. Amide protons in proteins can readily exchange with deuterons. However, amide protons that are involved in backbone hydrogen bonds are more resistant to exchange than those in the unstructured portions of the protein (53). After mapping the interfaces using chemical shift perturbation and H-D exchange data, we focused on solving the solution structure of the IL1α-S100A13 tetrameric complex to understand the molecular interactions in more detail.

Structure of the IL1α-S100A13 Tetrameric Complex

The resonance assignments of the IL1α-S100A13 tetrameric complex were obtained using standard strategies based on triple-resonance experiments. In total, 95% of the backbone amide resonances in the 1H-15N HSQC spectrum and their α carbons were sequentially assigned based on HNCA and HN(CO)CA experiments. The backbone carbonyl carbons were assigned using the HNCO experiment. The Hα and side chain proton resonances were assigned based on three-dimensional 15N-edited TOCSY-HSQC, three-dimensional HCCH-TOCSY, and 15N-edited NOESY-HSQC experiments. The NH2 groups of Gln and Asn residues were connected to their side chain γ and β protons using an 15N-edited NOESY-HSQC.

The Structure of IL1α in the IL1α-S100A13 Complex

A set of 1596 intramolecular NOEs of IL1α were assigned from the three-dimensional 15N-edited NOESY-HSQC and converted to 1510 relevant distance restraints. In addition, 60 hydrogen bonds, identified from deuterium exchange experiments, were also used. Thus, a total of 1570 distance restraints were used in the final structure calculations (Table 2). The final representative ensemble of structures shows few molecular and constraint violations greater than 5 Å. The average r.m.s. deviation value for the secondary structure region was 0.35 ± 0.02 Å for the backbone atoms and 0.84 ± 0.03 Å for all heavy atoms. Analysis of the structures by PROCHECK indicated good stereochemistry for the bond angles and bond lengths and that 98.8% of all of the non-glycine residues fall within the allowed region of the Ramachandran plot (Table 2).

TABLE 2.

Structural statistics for the final 20 simulated annealing structures of IL1α, S100A13, and the IL1α-S100A13 tetrameric complex

Calculations
Structural statistics from ARIA/CNS restrained calculations (IL1α in the IL1α-S100A13 tetrameric complex)
    Protein distance restraints
        Total 1510
        Intra-residue 281
        Sequential 362
        Medium range 1〈|i-j|〉 <5 205
        Long range |i-j| ≥5 548
        H-bond restraints 60
        Dihedral angle restraints 220

    Structural statistics for 20 structures
        Average r.m.s. deviation
            Backbone r.m.s. deviation to mean (Å) 0.61 ± 0.02 Å
            Heavy atoms r.m.s. deviation to mean (Å) 1.45 ± 0.03 Å
        Average r.m.s. deviation (structured region)
            Backbone r.m.s. deviation to mean (Å) 0.35 ± 0.02 Å
            Heavy atom r.m.s. deviation to mean (Å) 0.84 ± 0.03 Å

    Ramachandran analysis
        Residues in most favored regions 78.5%
        Residues in additional allowed regions 18.2%
        Residues in generously allowed regions 3.1%
        Residues in disallowed regions 1.2%

Structural statistics from ARIA/CNS restrained calculations (S100A13 domain in the IL1α-S100A13 tetrameric complex)
    Protein distance restraints
        Total 1625
        Intra-residue 301
        Sequential 411
        Medium range 1〈|i-j|〉 <5 158
        Long range |i-j| ≥5 569
        H-bond restraints 48
        Dihedral angle restraints 116

    Structural statistics for 20 structures
        Average r.m.s. deviation
            Backbone r.m.s. deviation to mean (Å) 0.81 ± 0.02 Å
            Heavy atoms r.m.s. deviation to mean (Å) 1.29 ± 0.04 Å
        Average r.m.s. deviation (structured region)
            Backbone r.m.s. deviation to mean (Å) 0.38 ± 0.02 Å
            Heavy atom r.m.s. deviation to mean (Å) 0.87 ± 0.03 Å

    Ramachandran analysis
        Residues in most favored regions 77.5%
        Residues in additional allowed regions 19.5%
        Residues in generously allowed regions 2.2%
        Residues in disallowed regions 0.8%

Structural statistics from HADDOCK restrained calculations (IL1α-S100A13 tetrameric complex)
    Structural statistics for 20 structures
        Average r.m.s. deviation at backbone to mean (Å) 0.41 ± 0.03 Å
        Average r.m.s. deviation at IL1α and S100A13 interface 0.52 ± 0.05 Å
        Average r.m.s. deviation at IL1α interface 0.57 ± 0.05 Å
        Average r.m.s. deviation at S100A13 interface 0.59 ± 0.05 Å

    Ramachandran analysis
        Residues in most favored regions 76.4%
        Residues in additional allowed regions 19.5%
        Residues in generously allowed regions 2.3%
        Residues in disallowed regions 1.8%

Fig. 3A shows the superposition of an ensemble of 20 structures of the IL1α in IL1α-S100A13 complex. The IL1α structure contains 13 β-strands and one α-helix. The structure of IL1α in the complex is similar to that in the unbound state. The S100A13 binding site on IL1α is distributed over four regions. The first region is in the β3 strand, the second region is loop 6 and β7, the third region is in helix 1, and the fourth region is in loop 9. The majority of the residues in the interfacial region are highly solvent accessible. When the structures of the free (Fig. 1A) and bound (Fig. 3A) IL1α are compared, some differences are seen in the binding interface, possibly attributable to the binding of S100A13. The β3 strand, loop 6, and β7 strand of IL1α are near the C terminus of S100A13. Loop 9 is near loop 3, helix 1 is near loop 1, and loop 6 is near loop 1 and helix 1 of S100A13.

FIGURE 3.

FIGURE 3.

A, superposition of the backbone (N, Cα, and C′) atoms of the 20 final solution structures of IL1α in the IL1α-S100A13 tetrameric complex. B, ribbon representation of IL1α in the IL1α-S100A13 tetrameric complex. C, superposition of the backbone (N, Cα, and C′) atoms of the 20 final solution structures of the S100A13 dimer in the IL1α-S100A13 tetrameric complex. The two monomers are colored green and brown. D, ribbon representation of S100A13 in the IL1α-S100A13 tetrameric complex.

The Structure of S100A13 in the IL1α-S100A13 Complex

A set of 1656 intramolecular NOEs of S100A13 were assigned from the three-dimensional 15N-edited NOESY-HSQC spectrum and converted to 1625 relevant distance restraints. Additionally, 48 hydrogen bonds identified from the deuterium exchange experiments were also used. Thus, a total of 1673 distance restraints were used in the final structure calculations (Table 2). The 20 lowest energy structures of the S100A13 homodimer (Fig. 3C) complex with IL1α were used to represent the structure of the tetrameric complex. The average r.m.s. deviation value for the secondary structure region was 0.38 ± 0.02 Å for the backbone atoms and 0.87 ± 0.03 Å for all heavy atoms. Analysis of the structures by PROCHECK indicated good stereochemistry for the bond angles and bond lengths and showed that 99.2% of all of the non-glycine residues fall within the allowed region of the Ramachandran plot. Fig. 3C shows the superposition of an ensemble of 20 structures of S100A13 in the tetrameric complex with IL1α. The S100A13 structure is a homodimer, with each monomer composed of four α-helices and two β-strands, in agreement with the chemical shift indices. The IL1α binding site on S100A13 is distributed over four regions. The first region is in helix 1, the second region is in loop 1, the third region is in loop 3, and the final region is in the basic C terminus. The majority of the residues in the interfacial region are highly solvent accessible.

Structure of IL1α-S100A13 Complex

Triple resonance experiments were performed by mixing double-labeled (15N and 13C) protein with the corresponding unlabeled partner(s) to form the appropriate complexes. We assigned the IL1α and S100A13 resonances in the IL1α-S100A13 tetrameric complex. An unambiguous method for mapping biomolecular interactions is to use the intermolecular nuclear Overhauser effect (NOE) (54). The intensity of the NOE is proportional to the sixth root of the inter-proton distance (r−6). We obtained intramolecular NOEs from isotope-edited NOE spectra using 15N-edited NOESY and 13C-filtered NOESY experiments. We observed 46 intermolecular NOEs in the IL1α-S100A13 (supplemental Fig. S4) complexes by mixing a double-labeled (15N, 13C) protein with its corresponding unlabeled protein partner(s).

Calculating the structures of protein-protein complexes using intermolecular data, chemical shift perturbation data, or both has recently been highly successful when using the modeling program HADDOCK (3640). HADDOCK was used to dock the previously determined structures of IL1α and S100A13 (in IL1α-S100A13 complex) from ARIA/CNS. The structure of the binary complex of IL1α and S100A13 was calculated using 46 intermolecular NOEs obtained from the filtered NOE data of the complex. Based on the chemical shift perturbations of IL1α and S100A13 upon complex formation, ambiguous interaction restraints were defined for the residues at the interface. The active and passive residues were used to generate ambiguous interaction restraints (Table 3). A total of 5000 rigid body docking trials were carried out using the standard HADDOCK protocol with the 100 lowest energy structures used for subsequent semiflexible simulated annealing and water refinement. The 20 lowest energy structures were used to represent the structure of the complex (Fig. 4A). The average r.m.s. deviation value for the backbone is 0.41 ± 0.03. The average r.m.s. deviation at the interface between IL1α and S100A13 is 0.52 ± 0.05. The average r.m.s. deviation at the IL1α interface is 0.57 ± 0.05 Å. The average r.m.s. deviation at the S100A13 interface is 0.59 ± 0.05 Å. The complex structure was analyzed using PROCHECK (40).

TABLE 3.

List of the active and passive residues used to define the ambiguous interaction restraints for the docking of S100A13 with IL1α

IL1α-S100A13 tetrameric complex Residue
IL1α
    Active residues Gln38, Tyr39, Gln84, Asp85, Glu86, Val87, Gln88, Lys93, Glu94, Met95, Ser105, and Asn108
    Passive residues Leu40, Thr41, Leu91, Glu106, Thr107, Val125, and Ala126

S100A13
    Active residues Thr18′, Phe21′, Thr22′, Arg25′, Gln26′, Glu27′, Gly28′, Arg29′, Lys30, Glu70′, Phe73′, Lys89′, Leu93′, and Ile95
    Passive residues Glu14′, Val17′, Asp31′, Asp68′, Ser69′, Lys72
FIGURE 4.

FIGURE 4.

A, superposition of the backbone (N, Cα, and C′) atoms of the 20 final solution structures of the IL1α-S100A13 heterotetrameric complex. The green and maroon colors represent the S100A13 dimer and two IL1α monomers, respectively. B, ribbon and surface representation of the IL1α-S100A13 tetrameric complex; IL1α is shown in maroon; the two S100A13 monomers are shown in green. C, the electrostatic representation of the IL1α-S100A13 tetrameric complex shows that the binding between the two molecules is due to hydrophobic and charge-charge interactions.

Fig. 4B shows the ribbon representation of the IL1α-S100A13 tetrameric complex. S100A13 is a homodimer. In this complex, each monomer binds one IL1α molecule, and the complex appears as two symmetric units.

DISCUSSION

ITC provides direct information on the stoichiometry, binding affinity, and heat changes that occur during protein-protein binding in solution. Here, we monitored the binding affinity of IL1α to S100A13 and S100A13 to IL1α. The isotherms in Fig. 2 represent the binding between IL1α and S100A13. The binding constant between IL1α and S100A13 is rather weak (2.15–3.23 μm, Fig. 2). The titration curve representing the binding of IL1α-S100A13 saturates at a protein to ligand ratio of 1:1.

The IL1α-S100A13 Interface

A detailed summary of the intermolecular contacts between S100A13 and IL1α is shown in Fig. 5. There are 44 residues at the interface region; 25 are from S100A13, and 19 are from IL1α. The majority of the interactions between the two proteins are either hydrophobic or electrostatic. Key residues that are involved in two or more intermolecular contacts include Phe21′, Thr22′, Ala24′, Arg29′, Lys30′, Ser32′, Arg88, and Lys89′ of S100A13 and Thr41, Gln84, Asp85, Val87, Val90, Met95, Ser105, and Thr107 of IL1α. Based on these results, the contact between proteins S100A13 and IL1α is mainly the result of a combination of hydrophobic and polar interactions (Fig. 5B).

FIGURE 5.

FIGURE 5.

A, summary of the intermolecular contacts between IL1α and S100A13 in the IL1α-S100A13 complex. B, stereo view of intermolecular contacts (as indicated by dotted lines) between IL1α and S100A13 in the IL1α-S100A13 heterotetrameric complex.

In addition, 24 hydrogen bonds between the side chains and the backbone were observed. The side chain of Arg25′(NE) forms a hydrogen bond with the backbone nitrogen of Val90. There are also hydrogen bonds between Arg25′(O) and Gln88 HB1, Lys30′(O) and Leu90 HD1, Lys89′ OE1 and Ser105 HB2, and Gly104 O and Arg88′(HH2). The large interfacial region between IL1α and S100A13 (∼2652 Å) contains intermolecular salt bridges, hydrogen bonds, and hydrophobic contacts, all of which provide information for binding recognition between IL1α and S100A13.

Inhibition of IL1α-S100A13 Complex Formation

Amlexanox is a drug known to inhibit the non-classical secretion pathway of IL1α-S100A13 (20, 55). In this report, we investigated the amlexanox binding site on IL1α by titrating amlexanox with IL1α and monitoring the change in chemical shifts in the 1H-15N HSQC spectrum (Fig. 6A). Notably, the amlexanox binding site on IL1α is located in two regions. The major binding region is in the interface of the IL1α-S100A13 complex (Fig. 6, B and C). Based on the above results and previous results (S100A13-amlexanox interaction), amlexanox can inhibit formation of the IL1α-S100A13 complex.

FIGURE 6.

FIGURE 6.

A, overlay of 1H-15N HSQC spectra of IL1α (uniformly labeled with 15N) in its free state (black) and in the amlexanox-bound state (red). B, ribbon representation of IL1α; the green region indicates the amlexanox binding sites on IL1α. C, amlexanox chemical structure. D, ribbon representation of the IL1α-S100A13 tetrameric complex structure. Amlexanox binding sites on IL1α are in red; the amlexanox binding site is in the interface of the IL1α-S100A13 tetrameric complex, implying that amlexanox can inhibit formation of the tetrameric complex.

The Mechanism for the Non-classical Secretory Pathway of IL1α

In this article, we describe the solution structure of the IL1α-S100A13 heterotetrameric complex, which is the core component of the interleukin-1α non-classical secretion pathway. S100A13 plays a crucial role in the entire non-classical secretion pathway. S100A13 is a homodimer and acts as a template for binding two IL1α molecules to form the tetrameric complex. Copper also binds to S100A13 and IL1α, which is essential for the non-classical secretion pathway of both proteins (19, 56). Maciag et al. (10, 19) described how copper plays a crucial role in the non-classical secretion pathway of IL1α.

The formation of the multiprotein complex takes place in the vicinity of the cell membrane (10). The cell membrane is asymmetric, with acidic phospholipids such as phosphatidylglycerol, phosphatidylserine, and phosphatidylinositol in the inner leaflet of the cell membrane (57). Extracellular stimuli induce the flipping of acidic phospholipids to the cell surface (58) where phosphatidylserine can be detected using fluorescently tagged recombinant annexin V (59). This externalization mechanism is reversible. IL1α and S100A13 specifically bind acidic phospholipids and have been demonstrated to destabilize liposomes, which are composed of acidic phospholipids (19, 60).

Based on the present results and evidence from the literature, we propose a mechanism for the non-classical secretory pathway of IL1α. First, apo-S100A13 binds to Ca2+ ions to form halo-S100A13, which is the active conformation for tetrameric complex formation. The active S100A13 then binds to IL1α, which is the core component of the multiprotein complex. Formation of the tetrameric complex is the key step in the non-classical secretory pathway of IL1α. Later, this complex interacts with Cu2+ ions (carried by SK1) and moves close to the acidic environment of the inner leaflet of the cell membrane. A conformational change could occur in the tetrameric complex due the acidic conditions in the inner leaflet and the presence of Cu2+ ions. These partially structured states of the complex that are generated at the membrane are highly competent to traverse the membrane bilayer because the partial unfolding results in the exposure of normally hidden hydrophobic residues (61). IL1α is secreted as a monomer in an active conformation (19, 20). Under reducing conditions, such as those found outside the cell membrane, the complex dissociates.

In this article, we elucidate the interfacial regions of the proteins in the tetrameric complex, which is the core component of the interleukin-1α non-classical secretory pathway. These findings may prove useful in understanding the mechanism of the non-classical pathway of IL1α secretion at the molecular level. The biological effects of IL1α are mediated through the activation of transmembrane receptors and therefore require the release of these proteins into the extracellular space. The information provided within this article might provide clues on how to stop the formation of the multiprotein complex, which is essential for IL1α transport, thereby assisting in rational drug design for IL1α-induced angiogenesis and cell proliferation.

Acknowledgments

We thank members of the 700 MHz Nuclear Magnetic Resonance facility, Chemistry Department, National Tsing Hua University, Hsinchu, Taiwan.

*

This work was supported by National Science Council of Taiwan Grant 98-2113-M-007-018-MY2.

Inline graphic

The on-line version of this article (available at http://www.jbc.org) contains supplemental Figs. S1–S5.

The atomic coordinates and structure factors (code 2l5X) have been deposited in the Protein Data Bank, Research Collaboratory for Structural Bioinformatics, Rutgers University, New Brunswick, NJ (http://www.rcsb.org/).

2
The abbreviations used are:
HSQC
heteronuclear single quantum coherence
ITC
isothermal titration calorimetry
NOE
nuclear Overhauser effect
r.m.s.
root mean square.

REFERENCES

  • 1. Dinarello C. A. (1994) FASEB J. 8, 1314–1325 [PubMed] [Google Scholar]
  • 2. Dinarello C. A. (1998) Int. Rev. Immunol. 16, 457–499 [DOI] [PubMed] [Google Scholar]
  • 3. Maini R. N., Taylor P. C. (2000) Annu. Rev. Med. 51, 207–229 [DOI] [PubMed] [Google Scholar]
  • 4. Kawaguchi Y., Nishimagi E., Tochimoto A., Kawamoto M., Katsumata Y., Soejima M., Kanno T., Kamatani N., Hara M. (2006) Proc. Natl. Acad. Sci. U.S.A. 103, 14501–14506 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5. Dayer J. M. (2003) Rheumatology 42, Suppl. 2, ii3–ii10 [DOI] [PubMed] [Google Scholar]
  • 6. Combarros O., Llorca J., Sánchez-Juan P., Mateo I., Infante J., Rodríguez E., Sánchez-Quintana C., Berciano J. (2007) J. Neurol. 254, 115–117 [DOI] [PubMed] [Google Scholar]
  • 7. Elaraj D. M., Weinreich D. M., Varghese S., Puhlmann M., Hewitt S. M., Carroll N. M., Feldman E. D., Turner E. M., Alexander H. R. (2006) Clin. Cancer Res. 12, 1088–1096 [DOI] [PubMed] [Google Scholar]
  • 8. Bujak M., Frangogiannis N. G. (2009) Arch. Immunol. Therap. Exp. 57, 165–176 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9. Dinarello C. A. (1996) Blood 87, 2095–2147 [PubMed] [Google Scholar]
  • 10. Prudovsky I., Mandinova A., Soldi R., Bagala C., Graziani I., Landriscina M., Tarantini F., Duarte M., Bellum S., Doherty H., Maciag T. (2003) J. Cell Sci. 116, 4871–4881 [DOI] [PubMed] [Google Scholar]
  • 11. Blobel G. (2000) ChemBioChem 1, 86–102 [DOI] [PubMed] [Google Scholar]
  • 12. Nickel W. (2005) Traffic 6, 607–614 [DOI] [PubMed] [Google Scholar]
  • 13. Prudovsky I., Tarantini F., Landriscina M., Neivandt D., Soldi R., Kirov A., Small D., Kathir K. M., Rajalingam D., Kumar T. K. (2008) J. Cell. Biochem. 103, 1327–1343 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14. Soldi R., Mandinova A., Venkataraman K., Hla T., Vadas M., Pitson S., Duarte M., Graziani I., Kolev V., Kacer D., Kirov A., Maciag T., Prudovsky I. (2007) Exp. Cell Res. 313, 3308–3318 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15. Jackson A., Friedman S., Zhan X., Engleka K. A., Forough R., Maciag T. (1992) Proc. Natl. Acad. Sci. U.S.A. 89, 10691–10695 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16. Mouta Carreira C. M., Nasser S. M., di Tomaso E., Padera T. P., Boucher Y., Tomarev S. I., Jain R. K. (2001) Cancer Res. 61, 8079–8084 [PubMed] [Google Scholar]
  • 17. Shin J. T., Opalenik S. R., Wehby J. N., Mahesh V. K., Jackson A., Tarantini F., Maciag T., Thompson J. A. (1996) Biochim. Biophys. Acta 1312, 27–38 [DOI] [PubMed] [Google Scholar]
  • 18. Nickel W. (2003) Eur. J. Biochem. 270, 2109–2119 [DOI] [PubMed] [Google Scholar]
  • 19. Mandinova A., Soldi R., Graziani I., Bagala C., Bellum S., Landriscina M., Tarantini F., Prudovsky I., Maciag T. (2003) J. Cell Sci. 116, 2687–2696 [DOI] [PubMed] [Google Scholar]
  • 20. Tarantini F., Micucci I., Bellum S., Landriscina M., Garfinkel S., Prudovsky I., Maciag T. (2001) J. Biol. Chem. 276, 5147–5151 [DOI] [PubMed] [Google Scholar]
  • 21. Hayrabedyan S., Kyurkchiev S., Kehayov I. (2005) J. Rep. Immunol. 67, 87–101 [DOI] [PubMed] [Google Scholar]
  • 22. Sparvero L. J., Asafu-Adjei D., Kang R., Tang D., Amin N., Im J., Rutledge R., Lin B., Amoscato A. A., Zeh H. J., Lotze M. T. (2009) J. Translat. Med. 7, 17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23. Landriscina M., Schinzari G., Di Leonardo G., Quirino M., Cassano A., D'Argento E., Lauriola L., Scerrati M., Prudovsky I., Barone C. (2006) J. Neurooncol. 80, 251–259 [DOI] [PubMed] [Google Scholar]
  • 24. Pierce A., Barron N., Linehan R., Ryan E., O'Driscoll L., Daly C., Clynes M. (2008) Eur. J. Cancer 44, 151–159 [DOI] [PubMed] [Google Scholar]
  • 25. Landriscina M., Bagalá C., Mandinova A., Soldi R., Micucci I., Bellum S., Prudovsky I., Maciag T. (2001) J. Biol. Chem. 276, 25549–25557 [DOI] [PubMed] [Google Scholar]
  • 26. Matsunaga H., Ueda H. (2010) Cell Death Differ. 17, 1760–1772 [DOI] [PubMed] [Google Scholar]
  • 27. Bhattacharya S., Chazin W. J. (2003) Structure 11, 738–740 [DOI] [PubMed] [Google Scholar]
  • 28. Shishibori T., Oyama Y., Matsushita O., Yamashita K., Furuichi H., Okabe A., Maeta H., Hata Y., Kobayashi R. (1999) Biochem. J. 338, 583–589 [PMC free article] [PubMed] [Google Scholar]
  • 29. Chang H. K., Mohan S. K., Chin Y. (2010) Biomol. NMR Assign. 4, 59–60 [DOI] [PubMed] [Google Scholar]
  • 30. Goddard T. D., Kneller D. G. (2008) SPARKY 3, University of California, San Francisco, CA [Google Scholar]
  • 31. Grzesiek S., Bax A. (1993) J. Magn. Reson. B 102, 103–106 [Google Scholar]
  • 32. Wittekind M., Mueller L. (1993) J. Magn. Reson. B 101, 201–205 [Google Scholar]
  • 33. Grzesiek S., Bax A. (1993) J. Biomol. NMR 3, 185–204 [DOI] [PubMed] [Google Scholar]
  • 34. Kay L. E., Xu G. Y., Yamazaki G. (1994) J. Magn. Reson. A 109, 129–133 [Google Scholar]
  • 35. Pascal S. M., Muhandiram D. R., Yamazaki T., Forman-Kay J. D., Kay L. E. (1994) J. Magn. Reson. B 103, 197–201 [Google Scholar]
  • 36. Breeze A. L. (2000) Prog. Nucleic Magn. Reson. Spectrom. 36, 323–372 [Google Scholar]
  • 37. Linge J. P., O'Donoghue S. I., Nilges M. (2001) Methods Enzymol. 339, 71–90 [DOI] [PubMed] [Google Scholar]
  • 38. Rieping W., Habeck M., Bardiaux B., Bernard A., Malliavin T. E., Nilges M. (2007) Bioinformatics 23, 381–382 [DOI] [PubMed] [Google Scholar]
  • 39. Cornilescu G., Delaglio F., Bax A. (1999) J. Biomol. NMR 13, 289–302 [DOI] [PubMed] [Google Scholar]
  • 40. Laskowski R. A., Rullmannn J. A., MacArthur M. W., Kaptein R., Thornton J. M. (1996) J. Biomol. NMR 8, 477–486 [DOI] [PubMed] [Google Scholar]
  • 41. Dominguez C., Boelens R., Bonvin A. M. J. (2003) J. Am. Chem. Soc. 125, 1731–1737 [DOI] [PubMed] [Google Scholar]
  • 42. Diaz A. R., Stephenson S., Green J. M., Levdikov V. M., Wilkinson A. J., Perego M. (2008) J. Biol. Chem. 283, 2962–2972 [DOI] [PubMed] [Google Scholar]
  • 43. Williams C., Rezgui D., Prince S. N., Zaccheo O. J., Foulstone E. J., Forbes B. E., Norton R. S., Crosby J., Hassan A. B., Crump M. P. (2007) Structure 15, 1065–1078 [DOI] [PubMed] [Google Scholar]
  • 44. Ababou A., Gautel M., Pfuhl M. (2007) J. Biol. Chem. 282, 9204–9215 [DOI] [PubMed] [Google Scholar]
  • 45. De Vries S. J., Van Dijk A. D. J., Krzeminski M., Van Dijk M., Thureau A., Hsu V., Wassenaar T., Bonvin A. M. J. J. (2007) Proteins 69, 726–733 [DOI] [PubMed] [Google Scholar]
  • 46. Hubbard S. J., Thornton J. M. (1993) NACCESS, Department of Biochemistry and Molecular Biology, University College, London [Google Scholar]
  • 47. Wishart D. S., Sykes B. D. (1994) J. Biomol. NMR 4, 171–180 [DOI] [PubMed] [Google Scholar]
  • 48. Graves B. J., Hatada M. H., Hendrickson W. A., Miller J. K., Madison V. S., Satow Y. (1990) Biochemistry 29, 2679–2684 [DOI] [PubMed] [Google Scholar]
  • 49. Pierce M. M., Raman C. S., Nall B. T. (1999) Methods 19, 213–221 [DOI] [PubMed] [Google Scholar]
  • 50. Garrett D. S., Seok Y. J., Peterkofsky A., Clore G. M., Gronenborn A. M. (1997) Biochemistry 36, 4393–4398 [DOI] [PubMed] [Google Scholar]
  • 51. Hall D. A., Vander Kooi C. W., Stasik C. N., Stevens S. Y., Zuiderweg E. R., Matthews R. G. (2001) Proc. Natl. Acad. Sci. U.S.A. 98, 9521–9526 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52. Chang Y. G., Song A. X., Gao Y. G., Shi Y. H., Lin X. J., Cao X. T., Lin D. H., Hu H. Y. (2006) Protein Sci. 15, 1248–1259 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53. Wand A. J., Englander S. W. (1996) Curr. Opin. Biotechnol. 7, 403–408 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54. Piotto M., Saudek V., Sklenár V. (1992) J. Biomol. NMR 2, 661–665 [DOI] [PubMed] [Google Scholar]
  • 55. Rani S. G., Mohan S. K., Yu C. (2010) Biochemistry 49, 2585–2592 [DOI] [PubMed] [Google Scholar]
  • 56. Sivaraja V., Kumar T. K., Rajalingam D., Graziani I., Prudovsky I., Yu C. (2006) Biophys. J. 91, 1832–1843 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57. Pomorski T., Hrafnsdottir S., Devaux P. F., Van Meer G. (2001) Sem. Cell. Dev. Biol. 12, 139–148 [DOI] [PubMed] [Google Scholar]
  • 58. Bevers E. M., Comfurius P., Dekkers D. W., Zwaal R. F. (1999) Biochim. Biophys. Acta 1439, 317–330 [DOI] [PubMed] [Google Scholar]
  • 59. Fischer K., Voelkl S., Berger J., Andreesen R., Pomorski T., Mackensen A. (2006) Blood 108, 4094–4101 [DOI] [PubMed] [Google Scholar]
  • 60. Kathir K. M., Ibrahim K., Rajalingam D., Prudovsky I., Yu C., Kumar T. K. (2007) Biochim. Biophys. Acta 12, 3080–3089 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61. Ptitsyn O. B. (1995) Adv. Protein Chem. 47, 83–229 [DOI] [PubMed] [Google Scholar]

Articles from The Journal of Biological Chemistry are provided here courtesy of American Society for Biochemistry and Molecular Biology

RESOURCES