Effect of O-Linked Glycosylation on the Equilibrium Structural

Subscriber access provided by The University of Liverpool

Article

Effect of O-linked Glycosylation on the Equilibrium Structural Ensemble of Intrinsically Disordered Polypeptides Gül H. Zerze, and Jeetain Mittal J. Phys. Chem. B, Just Accepted Manuscript • DOI: 10.1021/acs.jpcb.5b10022 • Publication Date (Web): 30 Nov 2015 Downloaded from http://pubs.acs.org on December 5, 2015

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

The Journal of Physical Chemistry B is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 31

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

The Journal of Physical Chemistry

Effect of O-linked Glycosylation on the Equilibrium Structural Ensemble of Intrinsically Disordered Polypeptides G¨ul H. Zerze and Jeetain Mittal∗ Department of Chemical and Biomolecular Engineering, Lehigh University, Bethlehem, PA E-mail: [email protected]

Abstract Glycosylation is one of the most common post-translational modifications (PTMs), which provides a large proteome diversity. Previous work on glycosylation of globular proteins have revealed remarkable effects of glycosylation on protein function, altering the folding stability and structure and/or altering the protein surface which affects their binding characteristics. Intrinsically disordered proteins (IDPs) or intrinsically disordered regions (IDRs) of large proteins are also frequently glycosylated, yet how glycosylation affects their function remain to be elucidated. An important open question is if glycosylation affect IDP structure or binding characteristics or both? In this work, we particularly address the structural effects of O-linked glycosylation by investigating glycosylated and unglycosylated forms of two different IDPs, tau174−183 and human islet amyloid polypeptide (hIAPP) by all-atom explicit solvent simulations. We simulate these IDPs in aqueous solution for O-linked glycosylated and unglycosylated forms by employing two modern all-atom force fields for which glycan parameters are ∗

To whom correspondence should be addressed

1

ACS Paragon Plus Environment


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

also available. We find that O-linked glycosylation only has a modest effect on equilibrium structural ensembles of IDPs, for the cases studied here, which suggests that the functional role of glycosylation may be primarily exerted by modulation of the protein binding characteristics rather than structure.

Introduction Post-translational modifications (PTMs), such as the formation of disulfide bridges, acetylation, amidation, methylation, phosphorylation and glycosylation, are ubiquitous in eukaryotic cells. 1 PTMs can regulate protein function by introducing functional groups on protein surface that can provide recognition sites for binding to their target molecules. 2 Alternatively, PTMs can also regulate the protein function by modulating folding/misfolding mechanism and stability. 3–5 Glycosylation is one of the most common PTM which provides the largest proteome diversity compared to other PTMs, as glycosylation incorporates diverse selection of sugars, branching and length of glycan chains as well as glycosidic linkages. 6 Previous experimental work on glycosylation of globular proteins have indicated that glycosylation can affect folding of a protein in terms of its structure, dynamics and stability. 7–14 N-linked glycosylation which occurs cotranslationally have been reported to prevent misfolding and aggregation as well as stabilize the folded structure of the protein. 15 Using a coarse-grained simulation model, Shental-Bechor and Levy explained the higher stability of N-glycosylated proteins in terms of unfolded state destabilization due to the elimination of the residual secondary structure in the presence of N-linked glycans. 16,17 Moreover, simulation studies on N-linked glycosylated short peptides have highlighted the importance of steric crowding, specific hydrogen-bonding, hydrophobic stacking. 18,19 Though, our current understanding of O-linked glycosylation is limited compared to that of N-linked glycosylation, previous studies have revealed important functional roles of O-glycans in protein folding, glycoprotein-protein interactions, protein aggregation, 20,21 intercellular signalling 22 and flexible peptide linker conformations. 23 2


Page 2 of 31

Page 3 of 31

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) of large proteins are important class of proteins as they make up a significant fraction of eukaryotic proteins. 24 Due to the flexible nature of IDP structure, these proteins can more readily be exposed to the PTMs. 24–27 Larger focus in the literature has been directed to the PTMs of IDPs and IDRs which are associated with specific disease conditions. Phosphorylation of several IDPs including tau, 28,29 disordered region of Cx43, 30 p53 31 and CREB KID 32,33 proteins have been shown to carry functional and disease relevant effects. Several IDPs are also known to be O-linked glycosylated including amylin, 34 tau 35–37 and amyloid precursor protein. 37,38 However, our understanding of how glycosylation affects the physical properties of IDPs is limited compared to the globular proteins. In principle, glycosylation can modulate functional properties of IDPs by imparting structural changes and/or by introducing functional groups on protein(s) that can change their binding affinity. In this paper, we specifically focus on the first question, i.e., what are the changes caused by O-linked glycosylation in the IDP structural ensemble? To address this question faithfully, we perform replica exchange molecular dynamics simulations of glycosylated and unglycosylated tau174−183 fragment as well as full-length human islet amyloid polypeptide (hIAPP). Our simulation data for both peptides indicate that size and transient sampling of residue-level secondary structures are only affected modestly in the presence of O-linked glycosylation. Based on these results, we hypothesize that the functional role of O-linked glycosylation on IDPs is primarily in terms of changing their binding characteristics rather than monomeric structural properties.

Model and Simulation Methods To investigate the effects of glycosylation on IDP structure, we select two different IDPs – a 10-residue fragment of tau protein, tau174−183 and 37-residue human islet amyloid polypeptide (hIAPP). Using GROMACS-4.5.6, 39,40 we perform replica-exchange molecular dynam-

3



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ics (REMD) 41 simulations to sample the heterogenous ensembles of these IDPs. 42–46 The enhanced sampling in REMD is achieved by periodic exchanges with high temperature replicas, which can overcome barriers in the potential energy landscape. Swaps between adjacent temperature replicas are periodically attempted, and acceptance of exchange is based on a Metropolis criterion, which ensures Boltzmann distribution at each simulation temperature. We adjust replica temperatures, initially based on geometric spacing between 300 K and highest temperature of interest, to obtain uniform acceptance probability (of approximately 20%) between all adjacent replica pairs. 47 Tau174−183 and hIAPP monomers are solvated in a truncated octahedron box with 3.8 nm and 6.6 nm spaced faces, respectively, and ions are added to neutralize the system charges. Electrostatic interactions are calculated using the particle-mesh Ewald method 48 with a real space cutoff of 0.9 nm. A 1.2 nm cutoff is used for the van der Waals interactions. System are propagated using stochastic Langevin dynamics with a friction of 1 ps−1 . Amber ff03* (Amber ff03 49 with modified Ψ potential 50 ) and Charmm36 51 are two modern force fields for protein simulations for which carbohydrate parameters GLYCAM06j 52 and Charmm36-carbohydrates, 53–55 respectively, are also available. We note that recent protein force fields in conjunction with TIP4P/2005 (or TIP4P-Ew or TIP4P-D) water model may be more suitable 56–58 for IDP simulations but their integration with available carbohydrate parameters has not been validated. Nonetheless, the protein force fields used here can capture accurate secondary structure balance, 59 solution properties of short disordered peptides, 50 mutational effects on peptide folding stability, 60 etc. We perform our simulations for each unglycosylated and glycosylated peptide by employing both the force fields along with the TIP3P water model. 61 For Amber03* simulations, we generate initial coordinates and topology using AmberTools 62 and convert these to the GROMACS compatible coordinates and topology using ACPYPE. 63 For Charmm36 simulations, we implement the necessary monosaccharides and glycosylated amino acids in the GROMACS version of the Charmm36 force field.

4


Page 4 of 31

Page 5 of 31

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Twenty four replicas within a temperature range of 300-545 K and forty replicas in a temperature range of 300-500 K are used for tau174−183 and hIAPP peptides, respectively. Exchanges between adjacent replicas are attempted every 1 ps. Each tau or hIAPP peptide is simulated for 100 ns per replica and 150 ns (at least) per replica, respectively. All the replicas in each simulation are initiated from extended coil structures. We check the convergence and equilibration time by measuring the radius of gyration (Rg ) and end-to-end (E2E) distance of the peptides with respect to time of 300 K replica and also show their distributions for two equal non-overlapping blocks after equilibration time (Figures S1 and S2, for tau174−183 and hIAPP, respectively). We also calculate dihedral angle ω, the angle of right-handed rotation around C-N bond (Xaa-Pro), for all proline residues of tau peptides for both force fields and for both unglycosylated and glycosylated forms (Figure S3). As all our simulations start from trans configurations for all prolines and we observe trans-cis isomerization only rarely during our simulations (1 or 2 replicas), our results are not significantly affected by the presence of proline cis configurations. While cis isomers of Xaa-Pro bonds might be an important component of the biologically relevant conformational fluctuations of IDPs, disordered and ordered proteins have similar occurrence percentages of cis isomers of Xaa-Pro peptide bond (∼5-10%), on average. 64 Therefore, the use of these classical protein force fields should reasonably be reflecting cis/trans isomerization of Xaa-Pro peptide bond for IDPs, too. Though, our timescales might be short to observe statistically significant number of cis/trans isomerization events, it is known that O-glycosylation does not particularly affect cis/trans occurrences, at least for prolines following glycosylation sites. 64,65 Structural clustering analysis is performed based on the gromos method. 66

5



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 ACS Paragon Plus Environment

Page 6 of 31

Amber03* P(Rg)

6 5 4 3 2 1 0

0.6

0.8

1

6 5 4 3 2 1 0

Rg [nm]

Charmm36

0.6

0.8

1

Rg [nm] 1 0.8

1

P(E2E)

P(E2E)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


P(Rg)

Page 7 of 31

0.5

0.6 0.4 0.2

0 0

1

2

0 0

3

E2E [nm]

1

2

3

E2E [nm]

Figure 2: Radius of gyration (Rg ) and end-to-end (E2E) distance distributions of unmodified (black) and O-GlcNAcylated (red) tau for both Amber03*/GLYCAM (left) and Charmm36 (right) protein and glycan force fields. Errors are the blocked standard errors calculated from the standard deviation among the block averages by dividing data into 10 equal nonoverlapping blocks. Snapshots represent typical configurations sampled in subpopulations indicated by arrows (green residues illustrate attached glycans). were previously used by Zondlo and coworkers. 36 Sequences of selected fragment both in the absence and in the presence of O-GlcNAcylation are illustrated in Figure 1, where glycans are represented with the Consortium for Functional Glycomics (CFG) notation. 76 Equilibrium ensembles of tau174−183 peptides, which will be referred shortly as tau hereafter, are obtained from REMD simulation and further analyzed both in the absence and presence of a type of O-linked glycosylation, O-GlcNAcylation. As a measure of characteristic chain dimensions, we calculate the distributions of radius of gyration (Rg ) and end-to-end (E2E) distance from unmodified and O-GlcNAcylated ensembles of tau as shown in Figure 2. Both force fields (Amber03* with GLYCAM06j and Charmm36) yield very similar distance distributions showing peak population around similar values of Rg (∼0.8 nm) and E2E distance (∼2.5 nm) for unglycosylated ensembles. For Amber03* force field, the distance distributions for the O-GlcNAcylated tau peptide are essentially unchanged from the unglycosylated form, thereby suggesting no effect of glycosy7



fraction residue

Amber03*

Charmm36

0.8

0.8

0.6

0.6

0.4

0.4

0.2

0.2

0 Coil Bend Turn

0 Coil Bend Turn

Turn

Bend

Coil

Amber03* 0.9 0.6 0.3 0 0.9 0.6 0.3 0 0.2 0.1

Coil Bend Coil

0

0.9 0.6 0.3 0 0.9 0.6 0.3 0 0.2

Turn

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

0.1 0

THR-2 PRO-3 PRO-4 ALA-5 PRO-6 LYS-7 THR-8 PRO-9

Charmm36 Charmm36

THR-2 PRO-3 PRO-4 ALA-5 PRO-6 LYS-7 THR-8 PRO-9

Figure 3: DSSP-based 77 secondary structures of unmodified (black) and O-GlcNAcylated (red) tau with Amber03* and Charmm36 force field both for total fractions of secondary structure elements (top) and per-residue secondary structure propensities (bottom). Errors are the blocked standard errors calculated from the standard deviation among the block averages by dividing data into 10 equal non-overlapping blocks. Glycosylation sites are given in underlined bold font. lation on peptide dimensions. However, unglycosylated tau ensemble with Charmm36 force field has an additional peak around a smaller Rg (∼0.5 nm) and E2E distance (∼0.9 nm), which disappears from the glycosylated peptide distributions. The third most populated structural cluster of unglycosylated tau (Figure S4, row three, column three) shows typical structures corresponding to this region. Number of studies have previously suggested that heterogenous ensembles of IDPs can transiently sample functionally important partially structured conformations. 78–80 As a direct measure of structure formation, we calculate the populations of common secondary 8


Page 8 of 31

Page 9 of 31

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


structure elements in unmodified and O-GlcNAcylated ensembles of tau using the DSSP algorithm. 77 Top row of Figure 3 shows average fraction of particular structures for both force fields. As expected for a 10-residue peptide, with five proline residues, coil-like states (based on DSSP definition, for which ppII helices are also counted in “coil” configurations) are populated mostly for both the force fields and insignificant fractions of α and β structures are found. All three DSSP defined secondary structure elements, coil, bend and turn, fractions are also very similar for both the force fields. Additionally both force fields show little differences between unglycosylated and glycosylated forms of the peptide. To further elaborate the picture, we also show per-residue secondary structure fractions in Figure 3 (bottom) for both the force fields. At the residue-level, Amber03* simulations yield little differences between unglycosylated and glycosylated tau, with the largest change being a ∼15% increase in the “bend” propensity in one of the glycosylated threonines (THR-8). Dominant clusters of unglycosylated and glycosylated peptides with Amber03* force field also exhibit very similar structural features (Figure S4, top) which are further evidences of unchanged structural properties of tau with O-GlcNAcylation. For Charmm36, while all residues are mostly found in coil-like configurations (similar to Amber03*), PRO-6 and LYS7 residues of unglycosylated tau show ∼15% turn propensity, which is significantly decreased in the O-GlcNAcylated form of the peptide. The third most persistent structural cluster of unglycosylated tau (Figure S4, row three, column three) shows a relatively compact population, in which the residues PRO-6 and LYS-7 are in the turn structure. Residues PRO-6 and LYS-7 in the unglycosylated tau ensemble with Amber03* have ∼7% turn fraction, which also decreases in the O-glycosylated tau. However, this decrease is more prominent in the case of Charmm36 force field, as the unglycosylated tau has higher turn fraction in this force field as compared to the Amber03*. In addition to the DSSP based secondary structures, we also calculate secondary structures based on the (φ, ψ) angles of each residue in the Ramachandran map, which will allow us to assign ppII helices separately. We classify the (φ, ψ) space as, αR : −160◦ < φ < −20◦

9




Page 10 of 31

Page 11 of 31

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


longest possible block of a particular secondary structure based on (φ,ψ) sampling. Figure 4 shows SS-maps of ppII structure for both the force fields; α and β are shown in SI Figures S6 (Amber03*) and S7 (Charmm36), as α and β structures are much less prominent for this peptide. x- and y-axes indicate the length of the secondary structure block and the residue interval of that block, respectively. To interpret the data on these maps, we can consider the following example. There is a 5-residue-long light blue block on ppII map of unglycosylated tau peptide for Amber03*, and an arrow points a typical structure involving the secondary structure (ppII) in that particular block (opaque region of the snapshot). This light blue block indicates that there is 5-residue-long (x-axis) ppII helix between residues 2 and 6 (yaxis) with an approximate propensity of 0.15-0.2 (color code). If there is any common residue in different blocks of same length, propensity will add up for that particular residue index. As we use the same (φ, ψ)-based description of α (αR ), β and ppII structures as above, the sum of propensities over x-axis for each residue (indicated on y-axis) corresponds residual propensity of the same structure (Figure S5). By comparing unglycosylated and glycosylated tau peptide SS-maps (Figure 4), one can observe that most features are conserved for both the force fields, which is a further evidence that glycosylation has relatively little effect on the structural properties of this peptide. Next, we study the unglycosylated and O-glycosylated forms of a longer hIAPP peptide to further identify the structural changes induced by Oglycosylation.

hIAPP In addition to a short tau fragment, we also perform simulations of a 37-residue peptide, human amylin, which functions as a synergistic partner of insulin. 82 In its monomeric state, hIAPP is normally a soluble protein and can be classified as an IDP. 83 Pancreatic islet amyloids with hIAPP as the major protein component characterize type II diatebetes, 84 however. hIAPP has several potential O-linked glycosylation sites. Among them, THR6 and THR-9 are known to have O-linked glycans. 85,86 Literature data has not shown a 11



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Figure 5: Radius of gyration (Rg ) and end-to-end (E2E) distance distributions of unmodified (black) and O-Glycosylated (red) ensembles of hIAPP with Amber03*/GLYCAM (left) and Charmm36 (right) force fields. Errors are the blocked standard errors calculated from the standard deviation among the block averages by dividing data into 10 equal non-overlapping blocks. clear association between hIAPP glycosylation and type II diabetes so far. But as 50% of circulating hIAPP is found to be glycosylated, 86,87 there might be an associated functional role. We simulate O-glycosylated hIAPP with the core of its known O-linked glycans, 85 as previous studies have shown that primary conformational effects of glycosylation comes from the core of glycans. 10,88 First, we calculate the distributions of Rg and E2E distance in unglycosylated and glycosylated forms of hIAPP as shown in Figure 5 both for Amber03* and Charmm36 force fields. The average Rg of glycosylated hIAPP monomer (based on protein backbone atoms, 0.92 nm and 1.22 nm, respectively for Amber03* and Charmm36) are similar to that of unglycosylated hIAPP monomer (0.91 nm and 1.20 nm, respectively for Amber03* and Charmm36). The Rg and E2E distributions are also quite similar for the Amber03* force field but these are slightly different for the Charmm36 force field, especially for short E2E distances. Similar to the tau peptide (Figure 2), we find that this short E2E distance population is reduced in

12


Page 12 of 31

(a)

0.4 0.3 0.2 0.1 0

Amber03*

0.4 0.3 0.2 0.1 0

Charmm36

Turn

Bend `-bridge `-sheet

Coil

(b)

3(10)-helix _-helix

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


fraction residue

Page 13 of 31

0.9 0.6 0.3 0 0.4 0.2 0 0.2

Coil

Amber03* 5

5

10

10

15

15

20

20

25

25

Charmm36 30

30

35

35

0.1 0 0.9 0.6 0.3 0 0.6 0.4 0.2 0 0.4

0.9 0.6 0.3 0 0.4 0.2 0 0.2

5

10

15

20

25

30

35

5

10

15

20

25

30

35

5

10

15

20

25

30

35

5

10

15

20

25

30

35

5

10

15

20

25

30

35

5

10

15

20

25

30

35

5

10

15

20

25

30

35

0.1 5

10

15

20

25

30

35

5

10

15

20

25

30

35

5

10

15

20

25

30

35

0.2 0 0.3 0.2 0.1 0

_-helix 310helix

Turn

Bend

`-sheet `-bridge

0 0.9 0.6 0.3 0 0.6 0.4 0.2 0 0.4 0.2

5

10

5

10

15

20

25

30

35

15

20

25

30

35

0 0.3 0.2 0.1 0

Residue number

Residue number

Figure 6: DSSP-based 77 secondary structures of unmodified (black) and O-Glycosylated (red) hIAPP with Amber03* and Charmm36 force field both for total fractions of secondary structure elements (a) and per-residue secondary structure propensities (b). Errors are the blocked standard errors calculated from the standard deviation among the block averages dividing data into 10 equal non-overlapping blocks. Glycosylation sites are indicated with red dashed lines in per-residue plots. the glycosylated peptide for the Charmm36 force field. Next, we calculate the propensities of DSSP-defined secondary structure elements in the equilibrium ensembles of unmodified hIAPP and O-Glycosylated hIAPP. Figure 6a shows average fraction of particular structures for both the force fields. Similar to tau peptide, again for both force fields in either form of the peptide (unglycosylated/glycosylated), coil-like structures (coil/bend/turn) are the most dominant type of DSSP based secondary structures, as expected for an intrinsically disordered peptide. However, unlike tau, hIAPP has significant helical and β-sheet fractions for Amber03* and Charmm36 force fields, respec13



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

tively. In the presence of glycosylation, these total helical and β sheet fractions, respectively for Amber03* and Charmm36, are observed to decrease in favor of coil-like structures. To check if these changes are localized nearby glycosylation sites, we show residue-based secondary structure propensities in Figure 6b. With Amber03* force field, α-helical structures are populated in two regions of the unglycosylated form of the peptide: N-terminal region, residues 6-16 and C-terminal region, residues 22-30. α-helical propensity in the N-terminal region of hIAPP, which also covers the glycosylated residues of the peptide, is significantly decreased in the presence of glycosylation. For this peptide, α-helical propensity in a certain region, residues 20-29, has a particular importance as several studies have emphasized that formation of α-helical structures may serve as an important step preceding the formation of amyloid fibrils. 89–93 However, we do not observe a significant change due to glycosylation in this amyloidogenic region (residues 20-29), suggesting that early events in the aggregation process (which are dependent on interactions between α-helical structures) may not be affected. At the same time, there still might be a change in the aggregation propensity of these peptides in the presence of glycans, something that need to be addressed in future. In addition to the DSSP based secondary structures, Figure S10 shows fractions sampled in αR , β, ppII and αL regions (classified as described in the section above) per-residue. (φ, ψ) fractions of unglycosylated and O-glycosylated hIAPP for Amber03* (Figure S10, left) are very similar except for changes in the αR fraction observed in N-terminal region. There is an overall decrease in αR fraction in a region close to the O-linked glycans (residues 7-10) as a local effect of glycosylation, which is consistent with DSSP based data. With the Charmm36 protein/carbohydrate model, DSSP based secondary structure assignment of hIAPP show that there is significant β-sheet propensity in addition to the coil-like structures for the unglycosylated peptide (Figure 6). β-sheet fraction is affected only slightly in the presence of glycosylation, with a decrease in certain small regions, specifically 12-15 and 27-32, while the fractions of other secondary structures remain very similar. (φ-ψ) based structures (Figure S10-right) also yield very similar fractions, both in unglycosylated and glycosylated forms

14


Page 14 of 31

Page 15 of 31




1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

difficult to make conclusions about the role of O-linked glycosylation in this particular case. We do note that β-sheet structures are known to be over-stabilized in the Charmm36 force field. 94

Discussion and Conclusions Due to the intrinsic diversity of monosaccharides and glycosylation patterns, glycosylation is an effective way to increase proteome diversity after translation. Because of their flexible nature, IDPs have larger access to O-linked glycosylation, which can be associated with their function or disease relevant mechanism like amyloidosis or aggregation. As known from globular proteins, glycosylation can modulate functional properties of proteins by altering (i) protein structure or (ii) their binding mechanisms. In this work, we particularly address the first aspect for O-linked glycosylation. Specifically, we investigate O-glycosylated and unglycosylated tau174−183 fragment and hIAPP in aqueous solution via replica exchange molecular dynamics simulations employing two state-of-the-art all-atom protein and carbohydrate force fields. For tau fragment, we find no significant difference between unglycosylated and glycosylated ensembles with Amber03* force field, while a small population of compact structures, which disappears in glycosylated ensemble, is present in the Charmm36 simulations. Previous work has shown that N-linked glycosylation can increase the size unfolded proteins, which can be as high as 10%, 16,17 whereas we found insignificant size increase with O-linked glycosylation for the cases studied here.We also compute the contact maps of both unglycosylated and glycosylated ensembles, in which the entry for each pair of residues (i, j) represents the fraction of time that at least one heavy (i.e. non-hydrogen) atom of backbone from residue i and one from residue j are within 0.8 nm of each other, averaged over the ensemble. Contact maps also show that high propensity interactions of glycans with protein residues are only local (see Figure S13). We also perform simulations of unglycosylated and O-glycosylated full-length, 37-residue

16


Page 16 of 31

Page 17 of 31

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


hIAPP. DSSP based secondary structure fractions plots for both force fields indicate that there is a modest decrease in relevant structures (α-helices for Amber03* and β-sheet for Charmm36) in favor of increased coil propensity especially nearby O-glycosylated residues. We find that residual secondary structure sampling, specifically α-helices in N-terminal region, are affected to the largest extent with Amber03* without affecting the size of the peptide. (φ, ψ) fraction plots show that both for Amber03* and Charmm36, αR fraction of residues nearby O-glycosylation sites slightly decreases in the glycosylated ensemble, which is consistent with loss of α-helices in N-terminal region for Amber03* force field. It is also important to note that Charmm36 may have a bias towards β-sheet structure which may yield overstabilized β-structures 94 which can explain the reason why Amber03* and Charmm36 force fields yield different secondary structure characteristics for the same peptide. However, the major focus of this work is to understand structural effects of glycosylation on IDPs, and in this respect, both force fields yield highly similar outcomes: the structural effect of Olinked glycosylation is relatively modest for the peptides that we study here. Contact maps of glycosylated ensembles (Figure S16, below diagonal) reveal that high propensity contacts of glycan residues are mostly short range with residues adjacent to the glycosylated residue in the primary sequence. The moderate propensity contacts of glycans in a longer range in Amber03* case is likely to be natural consequence of protein itself being compact in the ensemble. Similarly, for Charmm36 force field, a moderate propensity contacts of glycans in region 25-32 is likely to be a consequence of the peptide having β-hairpin structures, rather than being specific to certain protein-carbohydrate pairs. As evident from DSSP and SSmap plots, this region (25-32) corresponds to a complimentary strand of β-hairpins formed, hence, it naturally forms contacts with residues 6-15, which includes glycosylated residues, as well. PTMs, for example phosphorylation, might have dramatic structural effects on IDPs like inducing folding as reported recently by Forman-Kay and coworkers. 95 Here, we find that only modest structural changes are introduced by O-linked glycosylation; in some cases we

17



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

find a small decrease in secondary structure propensity due to glycosylation or slight increase in disorder. However, the effect of PTMs could be highly context dependent, for example, the work by Ganguly and Chen has reported that phosphorylation of KID protein has shown only marginal changes in average structure, especially helicity, 33 as opposed to the induced folding (by phosphorylation) of 4E-BP2 protein of the other study. 95 Yet, the underlying conformational substates in phosphorylated KID protein have been reported to possibly affect its binding and folding upon binding significantly in the same study by Ganguly and Chen. 33 In a similar respect, our results highlight that O-linked glycosylation does not cause a significant secondary structure change at least for disordered peptides that we study, which might indicate that the function modulating effects of glycosylation on IDPs could be more relevant with the binding characteristic changes of the IDPs.

Acknowledgement We acknowledge support from the U.S. Department of Energy, Office of Basic Energy Science, Division of Material Sciences and Engineering under Award (DE-SC0013979). Use of the high-performance computing capabilities of the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by the National Science Foundation (NSF) grant no. TG-MCB-120014, is gratefully acknowledged.

Supporting Information Available Distributions Rg and E2E distance distributions for two blocks, most populated clusters of unglycosylated and glycosylated tau ensembles and hIAPP for both force fields are available. Per-residue secondary structure propensities of glycosylated hIAPP for Charmm36 force fields based on (φ-ψ) sampling and contact maps are also available. This material is available free of charge via the Internet at http://pubs.acs.org/.

18


Page 18 of 31

Page 19 of 31

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


References (1) Walsh, C. Posttranslational modification of proteins: Expanding nature’s inventory; Roberts and Company Publishers: Englewood, Colorado, 2006. (2) Lim, W.; Mayer, B.; Pawson, T. Cell Signaling: Principles and mechanisms; Garland Science, Taylor & Francis: New York, New York, 2014. (3) Rudd, P. M.; Wormald, M. R.; Stanfield, R. L.; Huang, M.; Mattsson, N.; Speir, J. A.; DiGennaro, J. A.; Fetrow, J. S.; Dwek, R. A.; Wilson, I. A. Roles for glycosylation of cell surface receptors involved in cellular immune recognition. J. Mol. Biol. 1999, 293, 351–366. (4) Seitz, O. Glycopeptide synthesis and the effects of glycosylation on protein structure and activity. ChemBioChem 2000, 1, 214–246. (5) Helenius, A.; Aebi, M. Intracellular functions of N-linked glycans. Science 2001, 291, 2364–2369. (6) Varki, A.; Cummings, R. D.; Esko, J. D.; Freeze, H. H.; Stanley, P.; Bertozzi, C. R.; Hart, G. W.; Etzler, M. E. Essentials of glycobiology; Cold Spring Harbor Laboratory Press: Cold Spring Harbor, New York, 2009. (7) Rudd, P. M.; Joao, H. C.; Coghill, E.; Fiten, P.; Saunders, M. R.; Opdenakker, G.; Dwek, R. A. Glycoforms modify the dynamic stability and functional activity of an enzyme. Biochemistry 1994, 33, 17–22. (8) O’Connor, S. E.; Imperiali, B. Modulation of protein structure and function by asparagine-linked glycosylation. Chem. Biol. 1996, 3, 803–812. (9) Wormald, M. R.; Dwek, R. A. Glycoproteins: glycan presentation and protein-fold stability. Structure 1999, 7, R155–R160.

19



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(10) Hanson, S. R.; Culyba, E. K.; Hsu, T.-L.; Wong, C.-H.; Kelly, J. W.; Powers, E. T. The core trisaccharide of an N-linked glycoprotein intrinsically accelerates folding and enhances stability. Proc. Nat. Acad. Sci. U.S.A. 2009, 106, 3131–3136. (11) Price, J. L.; Shental-Bechor, D.; Dhar, A.; Turner, M. J.; Powers, E. T.; Gruebele, M.; Levy, Y.; Kelly, J. W. Context-dependent effects of asparagine glycosylation on Pin WW folding kinetics and thermodynamics. J. Am. Chem. Soc. 2010, 132, 15359–15367. (12) Chen, M. M.; Bartlett, A. I.; Nerenberg, P. S.; Friel, C. T.; Hackenberger, C. P.; Stultz, C. M.; Radford, S. E.; Imperiali, B. Perturbing the folding energy landscape of the bacterial immunity protein Im7 by site-specific N-linked glycosylation. Proc. Nat. Acad. Sci. U.S.A. 2010, 107, 22528–22533. (13) Culyba, E. K.; Price, J. L.; Hanson, S. R.; Dhar, A.; Wong, C.-H.; Gruebele, M.; Powers, E. T.; Kelly, J. W. Protein native-state stabilization by placing aromatic side chains in N-glycosylated reverse turns. Science 2011, 331, 571–575. (14) Price, J. L.; Culyba, E. K.; Chen, W.; Murray, A. N.; Hanson, S. R.; Wong, C.-H.; Powers, E. T.; Kelly, J. W. N-glycosylation of enhanced aromatic sequons to increase glycoprotein stability. Pept. Sci. 2012, 98, 195–211. (15) Helenius, A.; Aebi, M. Roles of N-linked glycans in the endoplasmic reticulum. Annu. Rev. Biochem. 2004, 73, 1019–1049. (16) Shental-Bechor, D.; Levy, Y. Effect of glycosylation on protein folding: a close look at thermodynamic stabilization. Proc. Nat. Acad. Sci. U.S.A. 2008, 105, 8256–8261. (17) Shental-Bechor, D.; Levy, Y. Folding of glycoproteins: toward understanding the biophysics of the glycosylation code. Curr. Opin. Struc. Biol. 2009, 19, 524–533. (18) Ellis, C. R.; Maiti, B.; Noid, W. G. Specific and nonspecific effects of glycosylation. J. Am. Chem. Soc. 2012, 134, 8184–8193. 20


Page 20 of 31

Page 21 of 31

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(19) Ellis, C. R.; Noid, W. G. Deciphering the glycosylation code. J. Phys. Chem. B 2014, 118, 11462–11469. (20) Steen, P. V. d.; Rudd, P. M.; Dwek, R. A.; Opdenakker, G. Concepts and principles of O-linked glycosylation. Crit. Rev. Biochem. Mol. Biol. 1998, 33, 151–208. (21) Vasudevan, D.; Haltiwanger, R. S. Novel roles for O-linked glycans in protein folding. Glycoconjugate J. 2014, 31, 417–426. (22) Luther, K. B.; Haltiwanger, R. S. Role of unusual O-glycans in intercellular signaling. Int. J. Biochem. Cell Biol. 2009, 41, 1011–1024. (23) Johnson, Q. R.; Lindsay, R. J.; Raval, S. R.; Dobbs, J. S.; Nellas, R. B.; Shen, T. Effects of branched O-Glycosylation on a semiflexible peptide linker. J. Phys. Chem. B 2014, 118, 2050–2057. (24) Babu, M. M.; van der Lee, R.; de Groot, N. S.; Gsponer, J. Intrinsically disordered proteins: regulation and disease. Curr. Opin. Struc. Biol. 2011, 21, 432–440. (25) Wright, P. E.; Dyson, H. J. Linking folding and binding. Curr. Opin. Struc. Biol. 2009, 19, 31–38. (26) Xie, H.; Vucetic, S.; Iakoucheva, L. M.; Oldfield, C. J.; Dunker, A. K.; Obradovic, Z.; Uversky, V. N. Functional anthology of intrinsic disorder. 3. Ligands, post-translational modifications, and diseases associated with intrinsically disordered proteins. J. Proteome Res. 2007, 6, 1917–1932. (27) van der Lee, R.; Buljan, M.; Lang, B.; Weatheritt, R. J.; Daughdrill, G. W.; Dunker, A. K.; Fuxreiter, M.; Gough, J.; Gsponer, J.; Jones, D. T.; et al., Classification of intrinsically disordered regions and proteins. Chem. Rev. 2014, 114, 6589–6631. (28) Schneider, A.; Biernat, J.; Von Bergen, M.; Mandelkow, E.; Mandelkow, E.-M. Phosphorylation that detaches tau protein from microtubules (Ser262, Ser214) also protects 21



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

it against aggregation into Alzheimer paired helical filaments. Biochemistry 1999, 38, 3549–3558. (29) Amniai, L.; Barbier, P.; Sillen, A.; Wieruszeski, J.-M.; Peyrot, V.; Lippens, G.; Landrieu, I. Alzheimer disease specific phosphoepitopes of Tau interfere with assembly of tubulin but not binding to microtubules. FASEB J. 2009, 23, 1146–1152. (30) Grosely, R.; Kopanic, J. L.; Nabors, S.; Kieken, F.; Spagnol, G.; Al-Mugotir, M.; Zach, S.; Sorgen, P. L. Effects of phosphorylation on the structure and backbone dynamics of the intrinsically disordered connexin43 C-terminal domain. J. Biol. Chem. 2013, 288, 24857–24870. (31) Kruse, J.-P.; Gu, W. Modes of p53 regulation. Cell 2009, 137, 609–622. (32) Mayr, B.; Montminy, M. Transcriptional regulation by the phosphorylation-dependent factor CREB. Nat. Rev. Mol. Cell Biol. 2001, 2, 599–609. (33) Ganguly, D.; Chen, J. Atomistic details of the disordered states of KID and pKID. Implications in coupled binding and folding. J. Am. Chem. Soc. 2009, 131, 5214–5223. (34) Makimattila, S.; Fineman, M.; Yki-Jarvinen, H. Deficiency of total and nonglycosylated amylin in plasma characterizes subjects with impaired glucose tolerance and type 2 diabetes 1. J. Clin. Endocrinol. Metab. 2000, 85, 2822–2827. (35) Wang, J.-Z.; Grundke-Iqbal, I.; Iqbal, K. Glycosylation of microtubule–associated protein tau: An abnormal posttranslational modification in Alzheimer’s disease. Nat. Med. 1996, 2, 871–875. (36) Brister, M. A.; Pandey, A. K.; Bielska, A. A.; Zondlo, N. J. OGlcNAcylation and phosphorylation have opposing structural effects in tau: Phosphothreonine induces particular conformational order. J. Am. Chem. Soc. 2014, 136, 3803–3816.

22


Page 22 of 31

Page 23 of 31

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(37) Schedin-Weiss, S.; Winblad, B.; Tjernberg, L. O. The role of protein glycosylation in Alzheimer disease. FEBS J. 2014, 281, 46–62. (38) Perdivara, I.; Petrovich, R.; Allinquant, B.; Deterding, L. J.; Tomer, K. B.; Przybylski, M. Elucidation of O-glycosylation structures of the β-amyloid precursor protein by liquid chromatography- mass spectrometry using electron transfer dissociation and collision induced dissociation. J. Proteome Res. 2008, 8, 631–642. (39) Berendsen, H. J.; van der Spoel, D.; van Drunen, R. GROMACS: A message-passing parallel molecular dynamics implementation. Comput. Phys. Commun. 1995, 91, 43– 56. (40) Hess, B.; Kutzner, C.; Van Der Spoel, D.; Lindahl, E. GROMACS 4: Algorithms for highly efficient, load-balanced, and scalable molecular simulation. J. Chem. Theory Comput. 2008, 4, 435–447. (41) Sugita, Y.; Okamoto, Y. Replica-exchange molecular dynamics method for protein folding. Chem. Phys. Lett. 1999, 314, 141–151. (42) Wu, K.-P.; Weinstock, D. S.; Narayanan, C.; Levy, R. M.; Baum, J. Structural reorganization of α-synuclein at low pH observed by NMR and REMD simulations. J. Mol. Biol. 2009, 391, 784–796. (43) Reddy, A. S.; Wang, L.; Singh, S.; Ling, Y. L.; Buchanan, L.; Zanni, M. T.; Skinner, J. L.; De Pablo, J. J. Stable and metastable states of human amylin in solution. Biophys. J. 2010, 99, 2208–2216. (44) Sgourakis, N. G.; Merced-Serrano, M.; Boutsidis, C.; Drineas, P.; Du, Z.; Wang, C.; Garcia, A. E. Atomic-level characterization of the ensemble of the Aβ (1–42) monomer in water using unbiased molecular dynamics simulations and spectral algorithms. J. Mol. Biol. 2011, 405, 570–583.

23



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(45) Zhang, W.; Ganguly, D.; Chen, J. Residual structures, conformational fluctuations, and electrostatic interactions in the synergistic folding of two intrinsically disordered proteins. PLoS Comput. Biol. 2012, 8, e1002353. (46) Wu, C.; Shea, J.-E. Structural similarities and differences between amyloidogenic and non-amyloidogenic islet amyloid polypeptide (IAPP) sequences and implications for the dual physiological and pathological activities of these peptides. PLoS Comput. Biol. 2013, 9, e1003211. (47) Prakash, M. K.; Barducci, A.; Parrinello, M. Replica temperatures for uniform exchange and efficient roundtrip times in explicit solvent parallel tempering simulations. J. Chem. Theory Comput. 2011, 7, 2025–2027. (48) Essmann, U.; Perera, L.; Berkowitz, M. L.; Darden, T.; Lee, H.; Pedersen, L. G. A smooth particle mesh Ewald method. J. Chem. Phys. 1995, 103, 8577–8593. (49) Duan, Y.; Wu, C.; Chowdhury, S.; Lee, M. C.; Xiong, G.; Zhang, W.; Yang, R.; Cieplak, P.; Luo, R.; Lee, T. A point-charge force field for molecular mechanics simulations of proteins based on condensed-phase quantum mechanical calculations. J. Comput. Chem. 2003, 24, 1999–2012. (50) Best, R. B.; Hummer, G. Optimized molecular dynamics force fields applied to the helix- coil transition of polypeptides. J. Phys. Chem. B 2009, 113, 9004–9015. (51) Best, R. B.; Zhu, X.; Shim, J.; Lopes, P. E.; Mittal, J.; Feig, M.; MacKerell Jr, A. D. Optimization of the additive CHARMM all-atom protein force field targeting improved sampling of the backbone φ, ψ and side-chain χ1 and χ2 dihedral angles. J. Chem. Theory Comput. 2012, 8, 3257–3273. (52) Kirschner, K. N.; Yongye, A. B.; Tschampel, S. M.; Gonz´alez-Outeiri˜ no, J.; Daniels, C. R.; Foley, B. L.; Woods, R. J. GLYCAM06: A generalizable biomolecular force field. Carbohydrates. J. Comput. Chem. 2008, 29, 622–655. 24


Page 24 of 31

Page 25 of 31

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(53) Guvench, O.; Greene, S. N.; Kamath, G.; Brady, J. W.; Venable, R. M.; Pastor, R. W.; Mackerell, A. D. Additive empirical force field for hexopyranose monosaccharides. J. Comput. Chem. 2008, 29, 2543–2564. (54) Guvench, O.; Hatcher, E.; Venable, R. M.; Pastor, R. W.; MacKerell Jr, A. D. CHARMM additive all-atom force field for glycosidic linkages between hexopyranoses. J. Chem. Theory Comput. 2009, 5, 2353–2370. (55) Guvench, O.; Mallajosyula, S. S.; Raman, E. P.; Hatcher, E.; Vanommeslaeghe, K.; Foster, T. J.; Jamison, F. W.; MacKerell Jr, A. D. CHARMM additive all-atom force field for carbohydrate derivatives and its utility in polysaccharide and carbohydrate– protein modeling. J. Chem. Theory Comput. 2011, 7, 3162–3180. (56) Best, R. B.; Zheng, W.; Mittal, J. Balanced protein–water interactions improve properties of disordered proteins and non-specific protein association. J. Chem. Theory Comput. 2014, 10, 5113–5124. (57) Nerenberg, P. S.; Jo, B.; So, C.; Tripathy, A.; Head-Gordon, T. Optimizing solute– water van der waals interactions to reproduce solvation free energies. J.Phys. Chem. B 2012, 116, 4524–4534. (58) Piana, S.; Donchev, A. G.; Robustelli, P.; Shaw, D. E. Water dispersion interactions strongly influence simulated structural properties of disordered protein states. J. Phys. Chem. B 2015, 119, 5113–5123. (59) Best, R. B.; Mittal, J. Balance between α and β structures in ab initio protein folding. J. Phys. Chem. B 2010, 114, 8790–8798. (60) Zerze, G. H.; Uz, B.; Mittal, J. Folding thermodynamics of β-hairpins studied by replicaexchange molecular dynamics simulations. Proteins: Struct., Funct., Bioinf. 2015, 83, 1307–1315.

25



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(61) Jorgensen, W. L.; Chandrasekhar, J.; Madura, J. D.; Impey, R. W.; Klein, M. L. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 1983, 79, 926. (62) Case, D.; Babin, V.; Berryman, J.; Betz, R.; Cai, Q.; Cerutti, D.; Cheatham III, T.; Darden, T.; Duke, R.; Gohlke, H.; et al., Amber14, University of California: San Francisco, CA, 2012. (63) da Silva, A. W. S.; Vranken, W. F. ACPYPE-Antechamber python parser interface. BMC Res. Notes 2012, 5, 367. (64) Theillet, F.-X.; Kalmar, L.; Tompa, P.; Han, K.-H.; Selenko, P.; Dunker, A. K.; Daughdrill, G. W.; Uversky, V. N. The alphabet of intrinsic disorder: I. Act like a Pro: On the abundance and roles of proline residues in intrinsically disordered proteins. Intrinsically Disord. Proteins 2013, 1, e24360. (65) Pao, Y.-L.; Wormarld, M. R.; Dwek, R. A.; Lellouch, A. C. Effect of SerineOGlycosylation onCis-TransProline Isomerization. Biochem. Biophys. Res. Commun. 1996, 219, 157–162. (66) Daura, X.; Gademann, K.; Jaun, B.; Seebach, D.; van Gunsteren, W. F.; Mark, A. E. Peptide folding: when simulation meets experiment. Angew. Chem., Int. Ed. 1999, 38, 236–240. (67) Gustke, N.; Trinczek, B.; Biernat, J.; Mandelkow, E.-M.; Mandelkow, E. Domains of tau protein and interactions with microtubules. Biochemistry 1994, 33, 9511–9522. (68) Mukrasch, M. D.; Bibow, S.; Korukottu, J.; Jeganathan, S.; Biernat, J.; Griesinger, C.; Mandelkow, E.; Zweckstetter, M. Structural polymorphism of 441-residue tau at single residue resolution. PLoS Biol. 2009, 7, 399.

26


Page 26 of 31

Page 27 of 31

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(69) Goedert, M.; Spillantini, M. G.; Davies, S. W. Filamentous nerve cell inclusions in neurodegenerative diseases. Curr. Opin. Neurobiol. 1998, 8, 619–632. (70) Wang, J.-Z.; Xia, Y.-Y.; Grundke-Iqbal, I.; Iqbal, K. Abnormal hyperphosphorylation of tau: sites, regulation, and molecular mechanism of neurofibrillary degeneration. J. Alzheimer’s Dis. 2013, 33, S123–S139. (71) Arnold, C. S.; Johnson, G. V.; Cole, R. N.; Dong, D. L.-Y.; Lee, M.; Hart, G. W. The microtubule-associated protein tau is extensively modified with O-linked Nacetylglucosamine. J. Biol. Chem. 1996, 271, 28741–28744. (72) Robertson, L. A.; Moya, K. L.; Breen, K. C. The potential role of tau protein Oglycosylation in Alzheimer’s disease. J. Alzheimer’s Dis. 2004, 6, 489–495. (73) Liu, F.; Iqbal, K.; Grundke-Iqbal, I.; Hart, G. W.; Gong, C.-X. O-GlcNAcylation regulates phosphorylation of tau: a mechanism involved in Alzheimer’s disease. Proc. Nat. Acad. Sci. U.S.A. 2004, 101, 10804–10809. (74) Zeidan, Q.; Hart, G. W. The intersections between O-GlcNAcylation and phosphorylation: implications for multiple signaling pathways. J. Cell Sci. 2010, 123, 13–22. (75) Smet-Nocca, C.; Broncel, M.; Wieruszeski, J.-M.; Tokarski, C.; Hanoulle, X.; Leroy, A.; Landrieu, I.; Rolando, C.; Lippens, G.; Hackenberger, C. P. Identification of O-GlcNAc sites within peptides of the Tau protein and their impact on phosphorylation. Mol. BioSyst. 2011, 7, 1420–1429. (76) Varki, A.; Cummings, R. D.; Esko, J. D.; Freeze, H. H.; Stanley, P.; Marth, J. D.; Bertozzi, C. R.; Hart, G. W.; Etzler, M. E. Symbol nomenclature for glycan representation. Proteomics 2009, 9, 5398–5399. (77) Kabsch, W.; Sander, C. Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. Biopolymers 1983, 22, 2577–2637. 27



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 28 of 31

(78) Mittag, T.; Forman-Kay, J. D. Atomic-level characterization of disordered protein ensembles. Curr. Opin. Struc. Biol. 2007, 17, 3–14. (79) Jensen, M. R.; Markwick, P. R.; Meier, S.; Griesinger, C.; Zweckstetter, M.; Grzesiek, S.; Bernado, P.; Blackledge, M. Quantitative determination of the conformational properties of partially folded and intrinsically disordered proteins using NMR dipolar couplings. Structure 2009, 17, 1169–1185. (80) Eliezer, D. Biophysical characterization of intrinsically disordered proteins. Curr. Opin. Struc. Biol. 2009, 19, 23–30. (81) Best, R. B.; Buchete, N.-V.; Hummer, G. Are current molecular dynamics force fields too helical? Biophys. J. 2008, 95, L07–L09. (82) Cooper, G. J.; Day, A. J.; Willis, A. C.; Roberts, A. N.; Reid, K. B.; Leighton, B. Amylin and the amylin gene: structure, function and relationship to islet amyloid and to diabetes mellitus. Biochim. Biophys. Acta, Mol. Cell Res. 1989, 1014, 247–258. (83) Jaikaran, E. T.; Higham, C. E.; Serpell, L. C.; Zurdo, J.; Gross, M.; Clark, A.; Fraser, P. E. Identification of a novel human islet amyloid polypeptide β-sheet domain and factors influencing fibrillogenesis. J. Mol. Biol. 2001, 308, 515–525. (84) Cao, P.; Marek, P.; Noor, H.; Patsalo, V.; Tu, L.-H.; Wang, H.; Abedini, A.; Raleigh, D. P. Islet amyloid: From fundamental biophysics to mechanisms of cytotoxicity. FEBS Lett. 2013, 587, 1106–1118. (85) Mark, F.;

Joy, K.;

Amy, P.;

Judy, R. Glycosylated amylins. WO Patents,

WO1997035600 A1, October 2, 1997. (86) Montane,

J.;

Klimek-Abercrombie,

A.;

Potter,

K.;

Westwell-Roper,

C.;

Bruce Verchere, C. Metabolic stress, IAPP and islet amyloid. Diabetes, Obes. Metab. 2012, 14, 68–77. 28


Page 29 of 31

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(87) Percy, A.; Trainor, D.; Rittenhouse, J.; Phelps, J.; Koda, J. Development of sensitive immunoassays to detect amylin and amylin-like peptides in unextracted plasma. Clin. Chem. 1996, 42, 576–585. (88) O’Connor, S. E.; Pohlmann, J.; Imperiali, B.; Saskiawan, I.; Yamamoto, K. Probing the effect of the outer saccharide residues of N-linked glycans on peptide conformation. J. Am. Chem. Soc. 2001, 123, 6187–6188. (89) Abedini, A.; Raleigh, D. P. A critical assessment of the role of helical intermediates in amyloid formation by natively unfolded proteins and polypeptides. Protein Eng. Des. Sel. 2009, 22, 453–459. (90) Abedini, A.; Raleigh, D. P. A role for helical intermediates in amyloid formation by natively unfolded polypeptides? Phys. Biol. 2009, 6, 015005. (91) Williamson, J. A.; Loria, J. P.; Miranker, A. D. Helix stabilization precedes aqueous and bilayer-catalyzed fiber formation in islet amyloid polypeptide. J. Mol. Biol. 2009, 393, 383–396. (92) Miller, C.; Zerze, G. H.; Mittal, J. Molecular simulations indicate marked differences in the structure of amylin mutants, correlated with known aggregation propensity. J. Phys. Chem. B 2013, 117, 16066–16075. (93) Miller, C.; Zerze, G. H.; Mittal, J. Correction to Molecular simulations indicate marked differences in the structure of amylin mutants, correlated with known aggregation propensity. J. Phys. Chem. B 2014, 118, 8914–8915. (94) Best, R. B.; Mittal, J.; Feig, M.; MacKerell Jr, A. D. Inclusion of many-body effects in the additive CHARMM protein CMAP potential results in enhanced cooperativity of α-helix and β-hairpin formation. Biophys. J. 2012, 103, 1045–1051.

29



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(95) Bah, A.; Vernon, R. M.; Siddiqui, Z.; Krzeminski, M.; Muhandiram, R.; Zhao, C.; Sonenberg, N.; Kay, L. E.; Forman-Kay, J. D. Folding of an intrinsically disordered protein by phosphorylation as a regulatory switch. Nature 2015, 519, 106–109.

30


Page 30 of 31

Page 31 of 31



Effect of O-Linked Glycosylation on the Equilibrium Structural

Recommend Documents