2 Eppley Institute for Research in Cancer and Allied Diseases, University of Nebraska Medical Center, Omaha, NE 68198-6805; 3 Department of Biochemistry, Kansas State University, Manhattan, KS 66506; 4 Institute of Organic Chemistry, University of Hamburg, 20146 Hamburg, Germany; 5 Faculty of Health Sciences, School of Dentistry, University of Copenhagen, Copenhagen DK-2200, Denmark; 6 Institute of Biochemistry, Medical Faculty, University of Cologne, 50931 Cologne, Germany
Received on May 19, 2003; revised on August 1, 2003; accepted on August 4, 2003
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Abstract |
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Key words: glycopeptide / NMR / O-glycosylation / substrate specificity
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Introduction |
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The primary step of O-glycosylation involves essential recognition events between the glycosyltransferase and protein substrate. A number of early studies investigated substrate specificity but achieved limited success. Initial studies were complicated by the variable expression of different GalNAc-transferases in different cell lines and the complexities of evaluating substrate specificity in vivo, where a number of distinct enzymes react with the substrate. It is now generally accepted that different GalNAc-transferases employ distinct parameters of substrate recognition; however, the mechanisms whereby the distinct enzymes undertake substrate recognition and catalytic activity are poorly understood (Clausen and Bennett, 1996; Gooley and Williams, 1994
; Elhammer et al., 1993
, 1999
). No consensus peptide-sequence motif for acceptor sites has been identified for any of the GalNAc-transferases (Lis and Sharon, 1993
; Clausen and Bennett, 1996
; Ten Hagen et al., 2003
). Although some enzymes show site-selective specificities, the same enzymes demonstrate overlapping specificities with other enzymes. Moreover, several enzymes (e.g., GalNAc-T4 and -T7) catalyze the glycosylation of some sites only after flanking serine or threonine residues have been glycosylated (Bennett et al., 1999a
,b
; Hassan et al., 2000
; Hanisch et al., 2001
). Previous studies have shown that the amino acid sequence and environment near the site of glycosylation may significantly affect enzyme activity (Nishimori et al., 1994
; Wandall et al., 1997
; Elhammer et al., 1993
, 1999
; Gerken et al., 1997
, 2002
). However, detailed structural information on the substrate parameters that determine the optimal recognition and binding by the different GalNAc-transferases is largely unknown.
The aim of this study was to define distinct conformational features of the human mucin (MUC1) peptide substrates that contribute to acceptor substrate efficiency. Synthetic peptides from the tandem repeat of the MUC1 core protein, a major site of mucin-type O-glycosylation, have been widely used for kinetic and structural studies of the transferase specificities (Nishimori et al., 1994; Liu et al., 1995
; Fontenot et al., 1995
; Wandall et al., 1997
; Hanisch et al., 1999
; Kirnarsky et al., 1998
, 2000
). Previously, based on nuclear magnetic resonance (NMR) studies of relatively short, nonglycosylated MUC1 peptides, we proposed a structural model of the acceptor substrate recognition by the transferases GalNAc-T1 and -T3 (Kirnarsky et al., 1998
). This model defined a structural motif containing extended conformations of the peptide backbone at and around the glycosylation site as one important determinant for enzymesubstrate recognition (Kirnarsky et al., 1998
; Elhammer et al., 1993
, 1999
; Gerken et al., 1997
).
In the present study, we used NMR spectroscopy and computational methods for the structural analysis of a series of glycosylated and nonglycosylated 21-residue MUC1 peptides, AHGVTSAPDTRPAPGSTAPPA (AHG21). Some peptides were monoglycosylated with a GalNAc at positions Thr5, Thr10, or Thr17. Other peptides were diglycosylated at positions Thr5 and Thr17. Structural data on differentially glycosylated AHG21 peptides, in conjunction with kinetic data from three purified recombinant transferases, GalNAc-T1, -T2, and -T4 (Wandall et al., 1997; Hanisch et al., 1999
, 2001
; Hassan et al., 2000
), allowed us to define distinct conformational propensities of the peptide backbone at the glycosylation site that we postulate serve as the primary target for the substrate recognition by these GalNAc-transferases.
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Results |
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Carbohydratepeptide and carbohydratecarbohydrate interactions
On the addition of GalNAc, several NOE cross-peaks related to sugarpeptide interactions were observed near the glycosylated threonines (Table III). All three glycosylated threonines demonstrated medium cross-peaks between the peptide backbone amide proton and the amide proton of the N-acetyl group of GalNAc. As shown previously, this is consistent with an orientation of the monosaccharide perpendicular to the peptide backbone (Kirnarsky et al., 2000). For glycosylated Thr5, the methyl group of GalNAc showed weak contact with the alpha proton of the following Ser6. No sugar contacts were detected with adjacent residues for Thr10* and Thr17*. For all glycosylated threonines, weak or very weak NOE cross-peaks were observed between the H5 proton of the sugar ring and the methyl group of the side chain of the threonine. All three glycosylated threonines showed strong to medium contacts between the methyl group of GalNAc and the H2 and H3 sugar protons. We could not detect any cumulative structural effects caused by the simultaneous addition of two GalNAc residues at AHG21 (T5, T17), but we cannot rule out the possibility that such effects result from a higher density of glycosylation.
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For the VTSA fragment, several distinct clusters were obtained using the RMSD criterion of 0.7 Å (Table IV). The most populated cluster (PBID) included about 30% of all structures and was composed of a mix of conformers of nonglycosylated and glycosylated at Thr5 peptides. Another mixed cluster (DPP/BD) contained about 15% of all structures. Two different clusters (PBDI and PPID), which represented 14% and 8% of all conformers, were populated only by structures without the sugar at the Thr5 position. Also, two distinct clusters (D/IBBP and DPBP), which represented 12% and 10% of all conformers, contained only conformers of peptides glycosylated at Thr5. A few smaller clusters (less than 5%) were not considered. Thus about half of all structures for the VTSA fragment fell in the clusters that included conformers of both nonglycosylated at Thr5 and glycosylated peptides, and another half of the structures were assigned to separate clusters with conformers of peptides either glycosylated or nonglycosylated at the Thr5 position.
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Discussion |
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Previously, based on the NMR studies of the short peptides from the MUC1 protein core, we proposed a structural model that could explain some molecular details of the initial recognition of the peptide substrates by the GalNAc-T1 and -T3. It was hypothesized that polypeptide GalNAc-transferases interact with substrates at three positions: the residue to be glycosylated and two proximal domains at N- and C-termini. The extended backbone conformation of the substrate that provided the proper orientation of the potential donors and acceptors of the hydrogen bonding was predicted to be important for the substrate efficiency (Kirnarsky et al., 1998). Although this model was based on a very limited set of structural and kinetic in vitro data for the short, nine-residue peptides, it was generally consistent with the extended acceptor substrate conformation complementing the extended binding site of the GalNAc-transferase proposed by Elhammer and co-workers based on the in vivo data analysis (Elhammer et al., 1993
, 1999
). Also, we demonstrated previously that glycosylation of the threonine residue within the VTSA region affected peptide backbone conformations of the 15-residue MUC1 protein core fragment (Kirnarsky et al., 2000
).
In the present study we determined the structural propensities of the polypeptide backbone near all sites of O-glycosylation that might be critical for the initial recognition by the distinct GalNAc-transferase and defined the influence of threonine glycosylation on the flanking serine residues within the VTSA and GSTA fragments. NMR-derived structural data on differently glycosylated 21- residue MUC1 peptides were compared with kinetic data for purified recombinant transferases GalNAc-T1, -T2, and -T4 (Wandall et al., 1997; Hassan et al., 2000
; Hanisch et al., 1999
, 2001
). These kinetic data were obtained with the 21-residue AHG21 peptide, as well as with the larger MUC1-derived substrates, TAP24 and TAP25. GalNAc-T1 and -T2 have distinct specificities for these peptides with a partial overlap (Wandall et al., 1997
). GalNAc-T4 requires prior glycosylation of the peptide substrate for activity and catalyzes glycosylation of two sites in the MUC1 peptides that are not used by other known GalNAc-transferases (Bennett et al., 1998
). The requirement for prior glycosylation of peptide substrates for activity of GalNAc-T4 (and for substrate specificity exhibited by other GalNAc-transferases) has led to the postulation of two nonmutually exclusive hypotheses: (1) Glycosylation of peptide substrates induces conformations that can be recognized by the catalytic site of an appropriate GalNAc-transferase (e.g., GalNAc-T4); or (2) glycosylated residues on peptide substrates activate novel functions for GalNAc-transferases through the "lectin domain," which is separate from the catalytic site (through allosteric means or other ways such as localizing the enzyme to the substrate). We have tested the first hypothesis (glycosylation of peptide substrates alters their conformation so that conformations are created that can be recognized by the catalytic site of an appropriate GalNAc-transferase) in the studies reported in this manuscript. Specifically, we endeavored to detect alterations in the conformational propensity of MUC1 peptides that are glycosylated at positions that enable the peptides to serve as substrates for GalNAc-T4. Our NMR data for the AHG21 glycopeptides showed that O-glycosylation influenced chemical shifts and coupling constants only for glycosylated threonines and the nearest flanking residues. Therefore we focused our analysis on structural propensities within the peptide fragments VTSA, DTR, and GSTA.
The catalytic efficiencies of different GalNAc- transferases for glycosylation of different sites on MUC1 peptides can be ranked in the following order: GalNAc-T1:Thr5>Thr17>>Ser16; GalNAc-T2: Thr17>Thr5> Ser16; and GalNAc-T4:Thr10>Ser16 and Ser6, if the peptide was previously glycosylated at any other site (Wandall et al., 1997; Hassan et al., 2000
; Hanisch et al., 2001
). The catalytic efficiencies of these transferases for specific glycosylation sites on MUC1 peptides were correlated with the structural propensities of the peptide backbone within the AHG21 peptides obtained from the NMR data. The conformational preferences for the nonglycosylated Thr5, Thr17, and Thr10 residues were ranked in the following order:Thr5:B>P; Thr17:P>B; and Thr10:D (Tables IV
VI). A comparison of the kinetic and structural data suggests that the kinetic efficiencies observed for the GalNAc-T1, -T2, and -T4 can be correlated with specific conformations for the residue to be glycosylated. Thus the extended backbone conformations assigned to the B area of the Ramachandran plot are preferable for the GalNAc-T1; polyproline IIlike conformations assigned to the P area are primarily recognized by the GalNAc-T2; and relatively folded conformations assigned to the D area of the Ramachandran plot are required for the efficient recognition and binding by the GalNAc-T4. The amino acid sequence context and the proper conformations of the flanking residues may significantly contribute to the substrate efficiency.
For GalNAc-T1, the extended backbone conformations at and around the residue to be glycosylated are consistent with previously proposed extended structural motifs for substrate recognition (Elhammer et al., 1993, 1999
; Gerken et al., 1997
; Kirnarsky et al., 1998
). The N-terminal extension and the presence of the proline residue at the g + 3 position are likely to contribute significantly to catalytic efficiency with GalNAc-T1. The ability of GalNAc-T1 to glycosylate the first threonine of the TAP25 peptides with valine substitutions (Figure 1, H and L in Hassan et al., 2000
) does not contradict this observation because these peptides have been synthesized with a biotin group at the N-terminus (Hassan et al., 2000
) that can serve structurally as an N-terminal extension. The inactivity of the GalNAc-T1 toward the Ser6, which preferably exhibits the extended (B) conformations within the VTSA fragment if the Thr5 is glycosylated, can be explained by the lack of a proline at the g + 3 position.
For GalNAc-T2, we proposed the polyproline IIlike conformation of the peptide substrate backbone at the glycosylation site as the structural determinants for the recognition and binding. These conformations were among the most populated structures of the nonglycosylated threonine within the GSTA region of the AHG21 peptides. The ability of GalNAc-T2 to glycosylate the N-terminal threonine in the TAP24 and TAP25 peptides (Hassan et al., 2000) has shown that N-terminal elongation at the glycosylation site of the substrate is not critical for GalNAc-T2 activity, in contrast to GalNAc-T1. The proline residue at position g + 3 is likely to benefit the enzyme-substrate binding affinity, however, with MUC5AC motif peptides (Tetaert et al., 2001a
,b
), GalNAc-T2 glycosylated the threonine residue without a proline at the g + 3 position. The lack of the GalNAc-T2 activity toward the serine within the VTSA region (Wandall et al., 1997
; Hanisch et al., 1999
, 2001
) may result from a combination of two factors: the relative paucity of polyproline II conformations of the serine for both glycosylated and nonglycosylated peptides and the absence of a proline residue at position g + 3. The preference for a proline residue at the g + 3 position, demonstrated by several GalNAc-transferases, may indicate the existence of a structurally (and evolutionary) conserved subsite within the active sites of these enzymes that is responsible for specific interactions with proline residues.
For substrates catalyzed by GalNAc-T4, the most preferred conformations of threonine/serine to be glycosylated were assigned to the D area on the Ramachandran plot. These conformations were abundant for the threonine residue within the DTR fragment and for the serine in the GSTA region, if the adjacent threonine was glycosylated. Both residues have been described as the effective acceptor sites for the GalNAc-T4 (Hassan et al., 2000; Hanisch et al., 2001
). For serine residues within the VTSA fragment, the D area was significantly more populated if the threonine was nonglycosylated as compared to peptides glycosylated at Thr5. Hassan and co-workers have shown, however, that GalNAc-T4 may glycosylate the serine residue within the VTSA fragment of the longer peptides, TAP24 and TAP25, if all other sites (including Thr1) were glycosylated (see Hassan et al., 2000
: Figure 1, A, G, and L). It is likely that the N-terminal extension, TAPP, especially when all threonines are glycosylated, promotes conformational changes that are beneficial for GalNAc-T4 activity.
Thus the length of the peptide substrate might affect substrate acceptability in two different ways. First, certain physicochemical parameters (volume, charge, hydrophobicity, etc.) of the amino acid residues around the glycosylation site might promote substrate recognition by providing distinct subsites that facilitate association with the catalytic site of the enzyme. Second, the length of the proximal portions of the acceptor substrate, especially to the N- terminal side of the glycosylation site, might significantly affect its structural flexibility and conformational propensities. Indeed, our NMR data on the VTSA fragment that was differently positioned within MUC1 peptides GVT9 (Kirnarsky et al., 1998), PPA15 (Kirnarsky et al., 2000
), and AHG21, showed slightly different patterns of sequential connectivities, including dNN connectivities. The PPA15 peptide, which contained two conformationally constrained prolines at the N-terminus (PPAHGVTSA), demonstrated less flexibility in the VTSA fragment (Kirnarsky et al., 2000
) than was observed for the AHG21 peptides.
Our model for enzymesubstrate specificity proposes that the relatively broad substrate specificity of polypeptide GalNAc-transferases is a result of the recognition of the distinct substrate backbone conformations rather than the specific side chains (Kirnarsky et al., 1998). It was predicted that the backbone of the central part of the acceptor substrate forms a set of hydrogen bonds with the enzyme, whose alignment is facilitated by the adjacent domains on the substrates. The amide proton of the acceptor residue may serve as a donor for hydrogen bonding with the enzyme to properly align the side chain hydroxyl moiety of the threonine/serine for glycosylation. The carbonyl oxygen of the reactive residue and several flanking residues may also be involved in hydrogen bonding with the GalNAc-transferase.
It should be noted that all three preferred conformations: the extended ß-strand-like structure, the polyproline IIlike conformation, and the inverse -turn-like conformation, demonstrate significant differences in the orientation of these proposed donor/acceptor groups for hydrogen bonding. Indeed, even though these conformations are relatively close on the Ramachandran plot, where all occupied the same upper left quadrant, the superimposition of the NC
, C
Cß and C
C' bonds of the acceptor residue, taken in B, P, D, or I conformations, show sharply different relative orientations of the NH and C'O groups. The distinct orientations are a result of 60°70° differences for the
,
angles between these conformational areas.
Glycosylation affected mutual orientation of the side chains of the flanking Thr and Ser residues that could be measured by a virtual torsional angle (i, i + 1) between vectors CßC
(i) ... C
Cß(i + 1). As can be seen from the Figure 5 side chains of the Thr5Ser6 and Ser16Thr17 oriented diametrically opposite to each other when Thr was glycosylated. The virtual torsional angle
(5,6) for the averaged structure with the nonglycosylated Thr5 was about 120°, whereas for the Thr5* it was
165°. For the pair Ser16Thr17, the virtual torsional angle
(16,17) changed from 85° for the nonglycosylated Thr17 to 165° for the Thr17*. The orientation of the side chains into diametrically opposite directions is typical for extended ß-like conformations proposed by different authors for the substrate- transferase binding (Elhammer et al., 1993
; Gerken et al., 1997
). Thus O-glycosylation of threonine promoted a ß-like structure for the flanking ThrSer residues within the MUC1 tandem repeat that might be beneficial for the subsequent glycosylation of Ser.
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In summary, the studies presented here suggest that distinct conformations of the substrate backbone contribute to specific interactions of acceptor substrates with three distinct GalNAc-transferases. The finding of different preferred conformations for the acceptor sites that are differently glycosylated by the GalNAc-T1, -T2, and -T4 supports the hypothesis that there are unique active site conformations for each member of this enzyme family.
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Materials and methods |
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where T*Thr-GalNAc, were synthesized and purified by reverse phase chromatography on preparative and analytical high-performance liquid chromatography columns in acetonitrile/0.1% aqueous trifluoroacetic acid gradients, as previously described for glycopeptides A1 to A9 (Karsten et al., 1998). The purity of the glycopeptides was confirmed by matrix-assisted laser desorption ionization mass spectrometry.
NMR spectroscopy
The NMR spectroscopy was performed as described previously (Kirnarsky et al., 1998, 2000
). Briefly, all high- resolution 1D and 2D 1H-NMR experimental data were acquired with a 11.75 T Varian UNITYplus spectrometer (Varian, Palo Alto, CA), operating at 499.96 MHz for 1H, with a 5-mm triple-resonance inverse detection probe. Using a peptide concentration of 3 mM, spectra were recorded at 10°C in 90% H2O/10% D2O and processed and analyzed using Varian software VNMR 6.1B on a Silicon Graphics Indigo2 XZ workstation. The invariant nature of NMR chemical shifts and line widths on 10-fold dilution indicated that the peptides were monomeric in solution at the 3 mM concentration used for 2D NMR analysis. Standard NMR pulse sequences were used for 2D DQF-COSY, TOCSY, NOESY, and ROESY experiments. Water peak suppression was obtained by low-power irradiation of the H2O peak during the relaxation delay (1.2 s). A total of 512 increments of 8K data points were collected for the DQF-COSY spectra, and a total of 256 increments of 4K data points were recorded for all other experiments. All data sets were obtained in hypercomplex, phase-sensitive mode.
Proton resonance assignments were confirmed by comparison of cross-peaks in a NOESY spectrum with those in a TOCSY spectrum (Wüthrich, 1986) acquired under similar experimental conditions. NOESY experiments were performed with 100, 200, and 400 ms mixing times. ROESY spectra were acquired with a mixing time of 300 ms. TOCSY spectra were recorded using MLEV-17 (Bax and Davis, 1985
) for isotropic mixing for 90 ms at a B1 field strength of 8 KHz. The H2O peak (4.91 ppm at 10°C) was used as a reference peak for chemical shift assignments. Coupling constants (3JN
) were measured directly from 1D and DQF-COSY spectra. All experiments were zero-filled to 4K data points in the t1 dimension; when necessary, spectral resolution was enhanced by Lorenzian-Gaussian apodization. A mixing time of 200 ms was used for the calculation of inter-proton upper limit distance restraints. The NOE peaks were divided into four groups with upper limits of 2.5, 3.0, 3.5, and 4.0 Å.
Structure determination protocol
All structural data were generated and visualized using the SYBYL 6.6 software package (TRIPOS Associates, St. Louis, MO). A model of the O-glycosylated Thr residue was created within SYBYL using the Amber-based Kollman force field and Glycam parameters (Woods et al., 1995; Woods and Chappelle, 2000
). 3D structures of the AHG21 peptides were generated from NMR data sets using a structure determination protocol described previously (Kirnarsky et al., 1998
, 2000
). Briefly, the FiSiNOE-3 (Shats and Sherman, 1996
) and HABAS (Güntert et al., 1989
) programs were used to define angle constraints and stereospecific assignments. These data, in conjunction with the distance constraints and coupling constants, were used as input data for the DYANA program (Güntert et al., 1997
) within SYBYL to generate 3D structures consistent with the NMR data. The standard selection of minimization levels and parameters for the DYANA program implemented within the SYBYL 6.6 were used to generate 100 structures for each peptide that were consistent with the NMR data set (distance constraints violations were less than 0.1 Å; torsion angle constraints violations were less than 5°). All DYANA-generated structures were subjected to constrained energy minimization within SYBYL using the Powell method with a maximum of 2000 minimization cycles. Calculations were performed using the Kollman "all-atom" force field, Kollman charges with distance-dependent dielectric constant, and the GLYCAM parameters for the carbohydrate moiety.
After energy minimization, the 25 best structures of each peptide were pooled together and all structures were clustered using the RMSD criterion for backbone-heavy atoms, starting from the lowest-energy structure. To evaluate conformational parameters of the amino acid residues within the cluster, averaged structures of the clusters were calculated, and each residue was compared among the clusters. To simplify comparisons, conformational angles of the averaged structures were converted to a notation based on conformational areas of the Ramachandran plot. These conformational areas were defined by clustering the protein conformations from high-resolution X-ray data (Rubinstein et al., 2001) and denoted as B, P, I, D, R, and L (Figure 2). Note that the P area of the Figure 2 includes clusters p and c that were defined in Rubinstein et al. (2001)
.
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Acknowledgements |
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Footnotes |
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Abbreviations |
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References |
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