Exploring structural and thermodynamic stabilities of human prion protein pathogenic mutants D202N, E211Q and Q217R

Journal of Structural Biology 178 (2012) 225–232

Contents lists available at SciVerse ScienceDirect

Journal of Structural Biology journal homepage: www.elsevier.com/locate/yjsbi

Exploring structural and thermodynamic stabilities of human prion protein pathogenic mutants D202N, E211Q and Q217R Jingjing Guo a, Hui Ren b, Lulu Ning a, Huanxiang Liu a,b,⇑, Xiaojun Yao a,⇑ a b

State Key Laboratory of Applied Organic Chemistry and Department of Chemistry, Lanzhou University, Lanzhou 730000, China School of Pharmacy, Lanzhou University, Lanzhou 730000, China

a r t i c l e

i n f o

Article history: Received 11 October 2011 Received in revised form 23 March 2012 Accepted 26 March 2012 Available online 3 April 2012 Keywords: Familial prion diseases Molecular dynamics simulation Prion protein (PrP) D202N/E211Q/Q217R mutants MM–GBSA method

a b s t r a c t The central event in the pathogenesis of prion protein (PrP) is a profound conformational change from its a-helical (PrPC) to its b-sheet-rich isoform (PrPSc). Many single amino acid mutations of PrP are associated with familial prion diseases, such as D202N, E211Q, and Q217R mutations located at the third native a-helix of human PrP. In order to explore the underlying structural and dynamic effects of these mutations, we performed all-atom molecular dynamics (MD) simulations for the wild-type (WT) PrP and its mutants. The obtained results indicate that these amino acid substitutions have subtle effects on the protein structures, but show large changes of the overall electrostatic potential distributions. We can infer that the changes of PrP electrostatic surface due to the studied mutations may influence the intermolecular interactions during the aggregation process. In addition, the mutations also affect the thermodynamic stabilities of PrP. Ó 2012 Elsevier Inc. All rights reserved.

1. Introduction Aggregation of aberrant proteins leads to the formation of dense plaques and fibers known as amyloid. Prion diseases are the only known infectious amyloid diseases, which are characterized by depositions of misfolded prion protein (PrPSc) in various regions of brain depending on diseases. All known prion diseases, collectively called transmissible spongiform encephalopathies (TSEs), are manifested as infectious, genetic, or sporadic disorders (Prusiner, 2001; Ross and Poirier, 2004), and are untreatable and fatal. Structurally, cellular form of prion protein (PrPC) is composed of an unstructured N-terminal part (residues 23–124), a compact C-terminal globular domain (residues 125–231), and two signal peptides (residues 1–23 and 232–253) (Zahn et al., 2000). The post-translational conversion of prion protein (PrP) from its cellular form (PrPC) to its pathogenic scrapie form (PrPSc), is a key event at the origin of prion diseases (Prusiner et al., 1983). The amino acid sequences of PrPC and PrPSc are identical in chemical composition but differ only in their conformations (Stahl and Prusiner, 1991; Stahl et al., 1993; Riesner, 2003). PrPC is predominantly a-helical in structure, whereas PrPSc has a high b-sheet content (Pan et al., 1993). This secondary structural transition from a-helix to b-sheet in PrP is the fundamental event underlying prion ⇑ Corresponding authors at: School of Pharmacy, Lanzhou University, Lanzhou 730000, China (H. Liu). Fax: +86 931 891 2582. E-mail addresses: [email protected] (H. Liu), [email protected] (X. Yao). 1047-8477/$ - see front matter Ó 2012 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jsb.2012.03.009

diseases. However, the molecular basis of this conversion is currently far from being clear and remains an intriguing puzzle waiting to be solved (Cobb and Surewicz, 2009; Pandeya et al., 2010). It is known that the replacement of some amino acids in prion protein will induce its conformation transition from PrPC to PrPSc (Collinge, 2001; Mead, 2006; van der Kamp and Daggett, 2009). Human familial prion diseases are associated with about 40 point mutations of the gene coding for the prion protein (PrP), and most of these mutations are located in the globular domain of the protein (van der Kamp and Daggett, 2009; Rossetti et al., 2011). Hence, most of researches concentrated on the globular domain while the flexible N-terminal region was considered to have a negligible effect on the structure of the C-terminal core (Riek et al., 1997; Zahn et al., 2000). The globular domain (Fig. 1) contains three a-helices (H1, H2, H3) and a very short anti-parallel b-sheet (S1, S2), with a single disulfide bond (between residues Cys179 and Cys214) bridging H2 and H3. The conserved H3 region of PrP plays a critical role in its folding and stability (Gallo et al., 2005), and many of pathogenic mutations are located on this part. Here, we focus on three disease-related polar mutations of this region: D202N (Piccardo et al., 1998), E211Q (Peoc’h et al., 2000) and Q217R (Hsiao et al., 1992) mutations. To disclose the unknown mechanism of three mutations resulting in the human familial prion diseases, molecular dynamics (MD) simulations on the wild-type (WT) PrP and its mutants as well as the structural and energy analysis were performed.

226

J. Guo et al. / Journal of Structural Biology 178 (2012) 225–232

2.3. MD trajectory analysis To explore the mechanism of how the studied mutations cause the conversion from PrPC to PrPSc, the obtained MD trajectories were analyzed from the structural and energy perspectives. In this study, root-mean-square deviations (RMSDs) of Ca atoms were calculated for the globular domain (residues 128–225) by omitting three N- and C-terminal residues from the initial structure to evaluate the structural fluctuation and the equilibrium of MD trajectories. The dictionary of secondary structure of proteins (DSSP) program developed by Kabsch and Sander (1983) was used to assign secondary structures. Solvent-accessible surface areas (SASAs) of the whole protein were calculated using VMD (Humphrey et al., 1996), and electrostatic potentials were analyzed using the programs UHBD (Madura et al., 1995) and PyMOL (Delano, 2002). The formation of a salt bridge (SB) is considered if the distance between the center of mass of the oxygen atom in the acidic side chain and center of mass of the nitrogen atom in the basic side chain is within 4.0 Å by using the Salt Bridges plugin of VMD (Humphrey et al., 1996). Thermodynamic functions were calculated using MM–GBSA method for WT and mutated PrP based on the snapshots generated from the last 15-ns MD simulations. Fig.1. NMR structure of the globular domain of WT HuPrP (PDB ID: 1HJN), residues 125–228. Secondary structure elements in the C-terminal globular domain are labeled, and the mutated residues studied in this work are shown as sticks.

2. Methods 2.1. Structure preparation The initial 3D structure of wild type (WT) human PrP was taken from the Protein Data Bank (PDB ID: 1HJN) obtained by NMR at pH 7.0 (Calzolai and Zahn, 2003), which contains the C-terminal globular structure of PrP (residues 125–228). The starting structures of mutants D202N, E211Q, and Q217R were obtained by mutating the corresponding residues using Discovery Studio (Accelry Inc, 2009) because there are no their experimental structures until now. 2.2. Molecular dynamics simulations Molecular dynamics simulations were performed using AMBER 10 software package (Case et al., 2008) and AMBER ff03 force field (Duan et al., 2003; Lee and Duan, 2004) with explicit TIP3P (Jorgensen et al., 1983) water, periodic boundary conditions, particle mesh Ewald electrostatics, and a timestep of 2 fs. Na+ ions were added to keep the neutral of the system. The basic residues (Arg and Lys) were protonated, whereas the acidic residues (His, Asp, and Glu) were deprotonated to reflect ionization conditions at pH 7. Among the four histidines in WT PrP (125–228), H140, H155, and H177 are exposed on the surface, but H187 is partially buried and forms a single intramolecular H-bond, which involves H187Ne and R156 backbone carbonyl. By protonating all the histidine residues in the epsilon position (Ne) only at pH 7, the structure turned out to reproduce accurately the experimental NMR structures of human PrP (Rossetti et al., 2011). Therefore, in our simulations at neutral pH, the histidines were mono-protonated using HIE form with hydrogen on the epsilon nitrogen. Based on the prepared four systems, we then minimized each system energetically using a steepest decent method followed by conjugate gradient method, and then warmed up the systems from 0 to 310 K. All equilibration and subsequent MD stages were carried out in the isothermal isobaric (NPT) ensemble at 310 K using a Berendsen barostat (Berendsen et al., 1984) with a target pressure of 1 bar and a pressure coupling constant of 2.0 ps. In all, three separate 50 ns simulations for wild type PrP and each mutant were performed at neutral pH and physiological temperature (310 K), using different atomic velocities.

2.4. MM–GBSA calculation Computational methods that combine molecular mechanics energy and implicit solvation models, such as Molecular Mechanics/ Poisson Boltzmann Surface Area (MM–PBSA) and Molecular Mechanics/Generalized Born Surface Area (MM–GBSA), have been successfully applied in free energy calculations (Hou et al., 2011a). The MM–GBSA method also has been used in the estimation of the total energy difference between wild type protein and the mutant built from the wild type fold (Le Gac et al., 2003; Zoete and Meuwly, 2006). Here, we also used MM–GBSA approach to investigate the effects of D202 N, E211Q and Q217R mutations on the thermodynamic stability of PrP globular domain. In MM–GBSA method, the free energy of the studied protein is estimated as follows:

G ¼ Egas þ Gsol  TS

ð1Þ

Egas ¼ Eint þ Eele þ Evdw

ð2Þ

Gpolar ¼ Eele þ Gsol

ð3Þ

Gsol ¼ Gsol Gsol

np

polar

¼ cSAS

polar

þ Gsol

np

ð4Þ ð5Þ

where Egas is the gas-phase energy; Eint is the internal energy; Eele and Evdw are the Coulomb and van der Waals energies, respectively. Gsol is the solvation free energy and can be decomposed into polar and nonpolar contributions. Gsol_polar is the polar solvation contribution calculated by solving GB equation. Gsol_np is the nonpolar solvation contribution and was estimated by the solvent accessible surface area (SAS) determined using a water probe radius of 1.4 Å. In MM–GBSA calculation, the solute dielectric constant (ein) is a key parameter for the calculation of electrostatic energy. By considering the polarity of the studied protein and the results of reference (Hou et al., 2011a,b), here, we set the solute dielectric constant as 2.0. T and S are the temperature and the total conformational entropy of protein, respectively. The normal-mode analysis was performed here to evaluate the conformational entropy change (TDS) upon mutations using the nmode program in AMBER 10.0 (Case et al., 2008). In the MM–GBSA approach, the entropy term is broken down into the contributions of translational, rotational, and vibrational entropies.

J. Guo et al. / Journal of Structural Biology 178 (2012) 225–232

227

3. Results 3.1. The overall structural properties

Fig.2. Structural characteristics calculated by MD simulations. (a) Ca RMSD from the starting structure of the globular domain (residues 128–225) for all mutants from MD simulations. A windowed average (250 ps) of the WT simulations is shown for reference as a solid black line. (b) Average Ca RMSFs over the last 20 ns simulations for each PrP as a function of residue number. (c) Ca RMSFs over the last 20 ns simulations as a function of residue number. Average RMSF of the WT simulations is shown as a gray line for reference. The N- and C-terminal residues have higher RMSF values, and three terminal residues of each are omitted here.

Root-mean-square deviations of Ca atom (Ca RMSDs) of the globular domain (residues 128–225) for most simulations are fairly small, fluctuating around 2 Å (Fig. 2a). In the last 20 ns simulations, the RMSDs of the D202N and E211Q mutants are mostly less than 2.5 Å, while for WT PrP and Q217R mutant more than 25% trajectory has RMSD values larger than 2.5 Å (shown in Table S1 Supplementary Material). We also find the Q217R mutant has a higher average RMSD value than WT PrP and has only 2.27% trajectory with RMSDs of less than 2.0 Å. Hence, the Q217R mutant may have a bigger conformational change than another two mutants compared with WT PrP. Ca root-mean-square fluctuations (RMSFs) from starting structures fluctuate in a very similar manner for all runs (Fig. 2b and c). For the core domain (van der Kamp and Daggett, 2010) (residues 174–188 and 200–219), the RMSF values are very small, which suggests the corresponding H2 and H3 regions are stable. However, the three polar amino acid substitutions at H3 helix cause the core domain (174–184 and 200–219) more flexible. Residues of the three loops (S1-H1 loop, S2-H2 loop and H2H3 loop) and S1 region have relatively high RMSF values, so these regions are flexible. Unexpectedly, the WT PrP has higher RMSF values in the S1-H1, S2-H2 and H2-H3 loops, suggesting that WT PrP is more flexible at the three turns than mutants (Fig. 2b). Salt bridges (SBs) play an important role in stabilizing both secondary and tertiary aspects of PrPC. Hence, disruption of even a small proportion of salt bridges is sufficient to substantially destabilize the folded conformation, possibly accelerating or enabling the transition to PrPSc in the right conditions. Polar mutations may disrupt the native SB networks (Rossetti et al., 2011). Here, we only considered seven SBs (Fig. 3) near the mutated region. They were distributed in H1 helix, and H2-H3 region (H2-H3 loop and H3 helix) (Rossetti et al., 2011). Two salt bridges R156-E196 and E146-K204 play a role in the tertiary structure of the globular domain. In our simulations, these two SBs show a similar manner for the WT and mutated PrPs. Two stable SBs in WT PrP, D202R156 and E211-R208, abolished resulted from the polar mutations, D202N and E211Q, respectively. Our results also suggest mutations make SBs within H3 helix weaker, which is consistent with the results reported in the previous researches (Guest et al., 2010; Rossetti et al., 2011). The partial or the complete loss of the SBs in mutated PrPs may lead to the destabilization of PrP in H3 region. Studies have shown that there is no known chemical difference between the normal cellular form (PrPC) and the abnormal form of the prion protein (PrPSc) (Stahl and Prusiner, 1991; Stahl et al., 1993), and their difference appears to be a conformational change: a predominantly a-helical structure to the abnormal form with a high b-sheet content (Pan et al., 1993). However, our MD simulations show that the secondary-structure elements are largely preserved in all mutated structures in the 50-ns timescale (Fig. 4 and Figure S1 in Supplementary Material). The contents of b-sheet have a weak growth in mutated PrPs except Q217R, but the contents of helix are not down and even up (Table 1). Although mutations made the core domain of human PrP more flexible, MD-simulated mutated structures proposed no obvious structural changes. Therefore from the structural perspective, it is difficult to understand how mutations cause the conformational transitions from PrPC to PrPSc.

3.2. Thermodynamic properties The changes in the energies upon mutations were studied via DG = Gmut  GWT. Gmut and GWT is the energy of the mutated and WT PrP, respectively.

At the molecular level, the misfolding of PrP is a physico-chemical process, with the propensity to misfold determined by the

228

J. Guo et al. / Journal of Structural Biology 178 (2012) 225–232

Fig.3. Selected salt bridges involving H1, H2 and H3 helices are plotted over simulation time for all runs.

free-energy difference between folded and misfolded states and the magnitude of the energy barrier separating them (Guest et al., 2010). The most rigorous MD-based approaches to estimate thermodynamic properties of proteins include free energy perturbation and thermodynamic integration methods. However, they are computationally intensive, needing long convergence time compared with the MM–GBSA approach. Therefore, we performed MM–GBSA calculations for the WT PrP and its three mutants to further investigate the effects of mutations on the thermodynamic properties of the PrP monomer. The results of free energy calculations were shown in Table 2. As can be seen, the entropy of PrP increased by introducing amino acid substitutions. However, for D202N and E211Q mutants, their enthalpy can partially offset the changes from entropy, and their total energy suggests these two mutants are less stable than the WT PrP. However, our results indicate the Q217R mutant has higher thermodynamic stability than the WT. The previous calorimetric data (Liemann and Glockshuber, 1999) does not support it. This inconsistency may be due to several factors: the difference of PrP sequences (human PrP (125–228) vs. murine PrP (121–131)), the effects of urea, and so on. In addition, from the Table 2, it can be seen that the free energy difference between Q217R mutant and WT PrP lies in the difference of polar contributions (DGpolar, summation of Eele and Gsol_polar). As we know, to evaluate electrostatic energy (or called polar contribution) accurately is still a challenge (Warshel et al., 2006; Roca et al., 2007; Kukic and Nielsen, 2010). Thus, this inaccuracy of energy calculation may also contribute the inconsistency

of results from our study and experimental report (Liemann and Glockshuber, 1999). Although our result of Q217R mutant is different with that of Liemann and Glockshuber, the basic conclusion is the same: the destabilization of PrPC is not a general mechanism underlying the formation of PrPSc. It is known that hydrophobic and electrostatic interactions are very important for protein folding and the aggregation of misfolded proteins. Hence, more detailed analysis was based on the solvation and electrostatic energies, which play key roles in stabilizing secondary and tertiary structural elements of prion protein, and also contribute to aggregation of misfolded prion proteins. The prion protein has a large number of charged residues on the protein surface, for example, WT PrP has 15 positively and 14 negatively charged residues. Therefore, electrostatic interactions are very important for the stability of PrP (Zuegg and Gready, 1999). The D202N and E211Q mutations alter the polar charge side chains from a carboxyl group (R–COO) to an amide group (R–CONH2), while the Q217R mutation introduces an arginine with positive charge. On the one hand, as Fig. 3 shows, D202N and E211Q mutations weaken the native salt-bridge interactions, and disturb the stable core structure (H2 and H3). On the other hand, the disruption of the native electrostatic distribution on the protein surface may affect their interactions with solvation or other molecules. Fig. 5 shows the solvent accessible surfaces (SASs) of WT and mutated PrPs, which are colored by electrostatic potential on the surface. As can be seen, the SASs at all mutated regions show more positive

229

J. Guo et al. / Journal of Structural Biology 178 (2012) 225–232

Fig.4. Graphical representation of secondary structure analysis for the mutant PrP based on the DSSP algorithm. Here, we labeled a turn by ‘‘T’’, an antiparallel beta-sheet by ‘‘B’’, a parallel beta-sheet by ‘‘b’’, a pi-helix by ‘‘I’’, a 310-helix by ‘‘G’’, an a-helix by ‘‘H’’, and a coil by ‘‘C’’.

Table 1 The average values for the properties of the MD trajectories from 30 ns to 50 ns for different strains of PrP. Run

WT

D202 N

E211Q

Q217R

1 2 3 Average 1 2 3 Average 1 2 3 Average 1 2 3 Average

Secondary structure content Helix (%)

Sheet (%)

52.77 56.32 51.31 53.47 55.00 58.34 57.95 57.10 56.25 57.53 57.45 57.08 58.47 56.51 55.20 56.73

3.96 3.67 5.30 4.31 3.88 6.56 8.66 6.37 4.54 4.84 5.48 4.95 3.75 5.28 3.80 4.28

charge (blue areas) compared with the WT. This electrostatic redistribution may influence intermolecular recognition, and contribute to the inducing interactions between PrPSc and PrPC, or the aggregation of PrPSc.

Ca RMSD(Å)

SASA (Å2)

2.42 1.91 2.52 2.28 2.37 1.98 1.83 2.06 2.06 2.00 2.21 2.09 2.54 2.32 2.26 2.37

6975.82 7030.50 7206.15 7070.82 7201.83 7312.90 7230.65 7248.46 7170.51 7094.69 7255.86 7173.69 7390.03 7127.98 7315.06 7277.69

Polar contribution (Gpolar) to the free energy of PrP involves Eele and Gsol_polar. In vacuum, Eele of mutated PrP is larger than that of WT PrP, which also indicates the mutants themselves are instable. The overall polar contribution (summation of Eele and Gsol_polar) in

230

J. Guo et al. / Journal of Structural Biology 178 (2012) 225–232

Table 2 The thermodynamic functions of three mutants, D202 N, E211Q and Q217R, with respect to WT PrP. (kcal/mol).

DEele DEvdw DEint DEgas DGsol_np DGsol_polar DGsol DGpolar DH TDS DGtot

D202 N

E211Q

Q217R

0.91 5.26 9.89 16.05 1.45 2.10 3.55 3.00 19.60 6.57 13.03

11.20 1.44 7.24 17.00 1.08 0.46 1.53 11.66 18.54 4.73 13.81

20.22 5.32 2.95 22.59 1.83 37.87 36.05 17.65 13.45 9.01 22.46

DG = Gmut  GWT, the energy difference; Egas = Eele + Evdw + Eint; Gsol = Gsol_np + Gsol_polar; Gpolar = Eele + Gsol_polar; Gtot = Egas + Gsol.

Fig.5. Solvent accessible surfaces of WT and mutated PrPs after simulations, which are colored by electrostatic potential on the surface. Red and blue correspond to negative and positive electrostatic potentials, respectively. On the right, corresponding mutated residues are shown as sticks with the WT PrP shown as cartoon.

WT PrP are larger than that in D202N and E211Q variants, while smaller than that in Q217R variant. The results are consistent with the polarity of mutated residues: the stronger polarity, the larger Gpolar values. 4. Discussion 4.1. The influence of pathogenic mutations on the structure of PrP Single-amino-acid substitutions, such as the M/V129 isoforms and pathogenic mutations identified in inherited prion diseases, influence a person’s susceptibility to developing the diseases. Structural comparison between WT and mutated PrPs is an important step in understanding how mutated PrPs may contribute to prion disease mechanisms. To understand the functions of proteins at a molecular level, it is often necessary to determine their threedimensional structures. However, only a few crystal structures of

prion mutants have been determined at present, and the underlying mechanism of many pathogenic mutations is still unclear. Molecular dynamics simulation is an effective tool to study the misfolding of PrP and the effect of pathogenic mutations (van der Kamp and Daggett, 2011). Recently, many MD studies have been launched on this problem, such as G131V, S132I, A133V, D178N, V180I, T183A, H187R, F198S, E200K, V203I, V210I, Q212P mutations, etc. (Levy and Becker, 2002; De Simone et al., 2005; Zhang et al., 2006; Bamdad and Naderimanesh, 2007; Chebaro and Derreumaux, 2009; Chen et al., 2010; Hosszu et al., 2010; Rossetti et al., 2010; van der Kamp and Daggett, 2010; Behmard et al., 2011; Guo et al., 2012). Generally, mutations decrease the stability of PrP, but few of them have obvious influence on the secondary structures, such as G131V (Chen et al., 2010) which causes the elongation of native b-sheet. From previous researches, we can see that different mutants undergo different misfolding pathways and have different pathogenesis. In our present work, we performed MD simulations to investigate the dynamical and thermodynamics behavior of the globular domain of WT and the D202N, E211Q, Q217R mutants of PrP. Our results indicate different amino acid substitutions have some subtle effects on the structural features of PrP. Firstly, although H2 and H3 are very stable, the mutations made the residues 174–184 and 200–215 more flexible compared to WT PrP (Fig. 2b). Secondly, the contents of b-sheet did not increase obviously in mutated PrPs as expected (Fig. 4 and Table 1). Thirdly, SBs within the H3 helix are more stable in the WT PrP than in the mutants (Fig. 3). The aggregation of PrPSc could be affected by many different factors involving not only the intrinsic nature of proteins but also the environmental factors. In particular, the protein stability and solubility affected by solvent distribution around protein would determine the propensity to aggregate from monomer (Chong et al., 2011). In this regard, although solvation free energy might not be a distinctive factor to affect aggregation kinetics, it can certainly influence aggregation process. Solvation energy can be divided into two parts: polar (Gsol_polar) and nonpolar (Gsol_np) contributions. Nonpolar solvation term corresponds to the total SASA. Hence the higher Gsol_np values of D202N, E211Q and Q217R mutants suggest their larger SASAs compared with WT PrP, which is in agreement with the SASA values in Table 1. It also suggests mutations make the structure of PrP more exposed. The higher value of Gsol indicates the weaker interaction between solvent and PrP, and the stronger hydrophobicity of the protein structure. Therefore, contrary to Q217R mutant, the D202N and E211Q mutants are more hydrophobic and may be more prone to undergo self-assembly than WT PrP. Like in many protein systems, electrostatic effects make significant contributions to the energy of various states and take two forms: self electrostatic energy of the native protein and polar solvation energy. It is expected that electrostatic effects generally favor the well-solvated monomeric PrPC over more hydrophobic amyloid PrPSc. The formation of PrPSc may be caused by the disruption of native salt bridges and transfer of some charged groups to an environment of low permittivity. It has been found that changes in the charge state of a mutant protein are related to its tendency to form aggregates (Chiti et al., 2003), and the aggregation propensity of a polypeptide chain is inversely correlated with its net charge (Chiti et al., 2002). Hence, polar mutations may affect the kinetics of amyloid formation. Generally speaking, the core of a PrPSc amyloid is in favor of a low dielectric, hydrophobic environment (Guest et al., 2010). For the three studied mutants in our work, they are all charged, and the electrostatic potential changes at the corresponding mutated point (Fig. 5). However, we observed two different results for the solvation energies: the D202N and E211Q mutants have weaker

J. Guo et al. / Journal of Structural Biology 178 (2012) 225–232

interaction with solvation than WT PrP while the Q217R mutant is on the contrary. Hence, the lower dielectric environments and new electrostatic redistributions of PrP mutants may be favorable for the formation of amyloid by PrPSc, and Q217R mutant may undergo different misfolding mechanism with E211Q and D202N mutants. 4.2. The limitation of the initial structures and simulation conditions (a) The absence of unstructured N-terminal domain: as shown in previous reported work (Li et al., 2009), the C-terminal domain organization depends on the length of N-terminal tail present and these two domains have a charge complementarity. The net attraction between the N-terminal tail and C-terminal structure may be sufficient to collapse or condense the tail onto the surface of the structured domain, resulting in a kind of ‘‘molten shell’’. Further exploration of this phenomenon, by molecular dynamics simulation or other tools, may provide insightful understanding. Here, because of the absence of the long unstructured N-term segment, the implications for the full-length protein in vitro in our findings must be taken with great caution. It is possible that the unstructured PrP segment might alter the structure and the stability of the protein in a rather drastic way. (b) The conversion of PrPC to PrPSc is a template-directed process (Li et al., 2009), hence, the induction of PrPSc on PrPC may be an essential condition for the conversion. In our work, we only detected effects of the mutation on monomeric PrP, while lack of template, the C-terminal structure may be insufficient to form a misfolded state, videlicet PrPSc. (c) Simulation time was not long enough. Molecular dynamics (MD) is an invaluable in silico tool with which to study protein folding. In fact, it takes about a day to simulate a nanosecond for the studied protein. Unfortunately, proteins fold on microsecond timescale. Therefore, atomistic simulations of protein folding have the potential to be a great complement to experimental studies, but have been severely limited by the time scales accessible with current computer hardware and algorithms (Pande et al., 2003). Our simulations of 50 ns on mutants may not achieve an objective state of mutants. In addition, the choice of force field and initial structure for MD simulation also are important factors. To further explore the conversion between PrPC and PrPSc or the formation of amyloid by misfolded PrPs, experimental and theoretical studies are all valid approaches. But we should pay attention to the roles of the unstructured N-terminal domain and the template for the conversion. 5. Conclusions By performing all-atom MD simulations, we have investigated the atomic-level structural variations for WT PrP and PrP with disease-related polar mutations to understand the molecular origin for their misfolding pathways. The globular domain is fairly conserved between WT and mutants, and the changes of the secondary structures and local fluctuations are very small upon mutations. In addition, mutations also affect the thermodynamic properties of PrP. It is noteworthy that the electrostatic distributions at the variant surfaces are different from WT prion protein especially around the mutated residues, and this may contribute to intermolecular signaling, and further affect the conversion from PrPC to PrPSc and aggregation of PrPSc. Our work shows that the realistic atomistic simulations can provide insights into the effects of disease-related mutations on structure and thermodynamics of PrP, which in turn adds to our

231

understanding of how these mutations cause the conversion of PrPC to PrPSc and then bring to prion diseases. Acknowledgments This work was supported by the National Natural Science Foundation of China (Grants No.: 20905033 and 21103075). We would like to thank the Gansu Computing Center for providing the computing resources. References Accelry Inc. Discovery Studio version 2.5.5, 2009. SanDiego, CA. Bamdad, K., Naderimanesh, H., 2007. Contribution of a putative salt bridge and backbone dynamics in the structural instability of human prion protein upon R208H mutation. Biochem. Biophys. Res. Commun. 364, 719–724. Behmard, E., Abdolmaleki, P., Asadabadi, E.B., Jahandideh, S., 2011. Prevalent mutations of human prion protein: a molecular modeling and molecular dynamics study. J. Biomol. Struct. Dyn. 29, 379–389. Berendsen, H.J.C., Postma, J.P.M., Van Gunsteren, W.F., DiNola, A., Haak, J.R., 1984. Molecular dynamics with coupling to an external bath. J. Chem. Phys. 81, 3684– 3690. Calzolai, L., Zahn, R., 2003. Influence of pH on NMR Structure and Stability of the Human Prion Protein Globular Domain. J. Biol. Chem. 278, 35592–35596. Case, D., Darden, T., Cheatham III, T., Simmerling, C., Wang, J., et al., 2008. AMBER 10. University of California, San Francisco. Chebaro, Y., Derreumaux, P., 2009. The conversion of helix H2 to b-sheet is accelerated in the monomer and dimer of the prion protein upon T183A mutation. J Phys. Chem. B 113, 6942–6948. Chen, W., van der Kamp, M.W., Daggett, V., 2010. Diverse effects on the native bsheet of the human prion protein due to disease-associated mutations. Biochemistry 49, 9874–9881. Chiti, F., Calamai, M., Taddei, N., Stefani, M., Ramponi, G., et al., 2002. Studies of the aggregation of mutant proteins in vitro provide insights into the genetics of amyloid diseases. Proc. Natl. Acad. Sci. USA 99, 16419–16426. Chiti, F., Stefani, M., Taddei, N., Ramponi, G., Dobson, C.M., 2003. Rationalization of the effects of mutations on peptide andprotein aggregation rates. Nature 424, 805–808. Chong, S.-H., Lee, C., Kang, G., Park, M., Ham, S., 2011. Structural and thermodynamic investigations on the aggregation and folding of acylphosphatase by molecular dynamics simulations and solvation free energy analysis. J. Am. Chem. Soc. 133, 7075–7083. Cobb, N.J., Surewicz, W.K., 2009. Prion diseases and their biochemical mechanisms. Biochemistry 48, 2574–2585. Collinge, J., 2001. Prion diseases of humans and animals: their causes and molecular basis. Annu. Rev. Neurosci. 24, 519–550. De Simone, A., Dodson, G.G., Verma, C.S., Zagari, A., Fraternali, F., 2005. Prion and water: tight and dynamical hydration sites have a key role in structural stability. Proc. Natl. Acad. Sci. USA 102, 7535–7540. Delano, W., 2002. The PyMOL Molecular Graphics System. DeLano Scientific: San Carlos; CA. Duan, Y., Wu, C., Chowdhury, S., Lee, M., Xiong, G., et al., 2003. A point-charge force field for molecular mechanics simulations of proteins based on condensed-phase quantum mechanical calculations. J. Comput. Chem. 24, 1999–2012. Gallo, M., Paludi, D., Cicero, D., Chiovitti, K., Millo, E., et al., 2005. Identification of a conserved N-capping box important for the structural autonomy of the prion alpha 3-helix: the disease associated D202N mutation destabilizes the helical conformation. Int. J. Immunopathol. Pharmacol. 18, 95–112. Guest, W.C., Cashman, N.R., Plotkin, S.S., 2010. Electrostatics in the stability and misfolding of the prion protein: salt bridges, self energy, and solvation. Biochem. Cell Biol. 88, 371–381. Guo, J., Ning, L., Ren, H., Liu, H., Yao, X., 2012. Influence of the pathogenic mutations T188K/R/A on the structural stability and misfolding of human prion protein: insight from molecular dynamics simulations. BBA-Gen. Subjects 1820, 116– 123. Hosszu, L.L.P., Tattum, M.H., Jones, S., Trevitt, C.R., Wells, M.A., et al., 2010. The H187R mutation of the human prion protein induces conversion of recombinant prion protein to the PrPSc-like form. Biochemistry 49, 8729–8738. Hou, T., Wang, J., Li, Y., Wang, W., 2011a. Assessing the performance of the MM/ PBSA and MM/GBSA methods. 1. The accuracy of binding free energy calculations based on molecular dynamics simulations. J. Chem. Inf. Model. 51, 69–82. Hou, T., Wang, J., Li, Y., Wang, W., 2011b. Assessing the performance of the molecular mechanics/Poisson Boltzmann surface area and molecular mechanics/generalized Born surface area methods. II. The accuracy of ranking poses generated from docking. J. Comput. Chem. 32, 866–877. Hsiao, K., Dlouhy, S.R., Farlow, M.R., Cass, C., Da Costa, M., et al., 1992. Mutant prion proteins in Gerstmann–Straussler–Scheinker disease with neurofibrillary tangles. Nat. Genet. 1, 68–71. Humphrey, W., Dalke, A., Schulten, K., 1996. VMD: visual molecular dynamics. J. Mol. Graph. 14, 33–38.

232

J. Guo et al. / Journal of Structural Biology 178 (2012) 225–232

Jorgensen, W.L., Chandrasekhar, J., Madura, J.D., Impey, R.W., Klein, M.L., 1983. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 79, 926–935. Kabsch, W., Sander, C., 1983. Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. Biopolymers 22, 2577–2637. Kukic, P., Nielsen, J.E., 2010. Electrostatics in proteins and protein-ligand complexes. Future Med. Chem. 2, 647–666. Le Gac, G.é., Dupradeau, F.-Y., Mura, C., Jacolot, S., Scotet, V., et al., 2003. Phenotypic expression of the C282Y/Q283P compound heterozygosity in HFE and molecular modeling of the Q283P mutation effect. Blood Cell. Mol. Dis. 30, 231–237. Lee, M., Duan, Y., 2004. Distinguish protein decoys by using a scoring function based on a new AMBER force field, short molecular dynamics simulations, and the generalized born solvent model. Proteins: Struct. Funct. Bioinform. 55, 620– 634. Levy, Y., Becker, O.M., 2002. Conformational polymorphism of wild-type and mutant prion proteins: energy landscape analysis. Proteins: Struct. Funct. Bioinform. 47, 458–468. Li, L., Guest, W., Huang, A., Plotkin, S.S., Cashman, N.R., 2009. Immunological mimicry of PrPC–PrPSc interactions: antibody-induced PrP misfolding. Protein Eng. Des. Sel. 22, 523–529. Liemann, S., Glockshuber, R., 1999. Influence of amino acid substitutions related to inherited human prion diseases on the thermodynamic stability of the cellular prion protein. Biochemistry 38, 3258–3267. Madura, J.D., Briggs, J.M., Wade, R.C., Davis, M.E., Luty, B.A., et al., 1995. Electrostatics and diffusion of molecules in solution: simulations with the University of Houston Brownian Dynamics program. Comput. Phys. Commun. 91, 57–95. Mead, S., 2006. Prion disease genetics. Eur. J. Hum. Genet. 14, 273–281. Pan, K.M., Baldwin, M., Nguyen, J., Gasset, M., Serban, A., et al., 1993. Conversion of alpha-helices into beta-sheets features in the formation of the scrapie prion proteins. Proc. Natl. Acad. Sci. USA 90, 10962–10966. Pande, V.S., Baker, I., Chapman, J., Elmer, S.P., Khaliq, S., et al., 2003. Atomistic protein folding simulations on the submillisecond time scale using worldwide distributed computing. Biopolymers 68, 91–109. Pandeya, D.R., Acharya, N.K., Hong, S.T., 2010. Review: the prion and its Potentiality. Biomed. Res. 21, 111–125. Peoc’h, K., Manivet, P., Beaudry, P., Attane, F., Besson, G., et al., 2000. Identification of three novel mutations (E196K, V203I, E211Q) in the prion protein gene (PRNP) in inherited prion diseases with Creutzfeldt–Jakob disease phenotype. Hum. Mutat. 15, 482. Piccardo, P., Dlouhy, S.R., Lievens, P.M.J., Young, K., Bird, T.D., et al., 1998. Phenotypic variability of Gerstmann–Straussler–Scheinker disease is associated with prion protein heterogeneity. J. Neuropathol. Exp. Neurol. 57, 979–988.

Prusiner, S., 2001. Shattuck lecture–neurodegenerative diseases and prions. New Engl. J. Med. 344, 1516–1526. Prusiner, S.B., McKinley, M.P., Bowman, K.A., Bolton, D.C., Bendheim, P.E., et al., 1983. Scrapie prions aggregate to form amyloid-like birefringent rods. Cell 35, 349–358. Riek, R., Hornemann, S., Wider, G., Glockshuber, R., Wuthrich, K., 1997. NMR characterization of the full-length recombinant murine prion protein, mPrP(23– 231). FEBS Lett. 413, 282–288. Riesner, D., 2003. Biochemistry and structure of PrPC and PrPSc. Br. Med. Bull. 66, 21–33. Roca, M., Messer, B., Warshel, A., 2007. Electrostatic contributions to protein stability and folding energy. FEBS Lett. 581, 2065–2071. Ross, C.A., Poirier, M.A., 2004. Protein aggregation and neurodegenerative disease. Nat. Med. 10, 10–17. Rossetti, G., Cong, X., Caliandro, R., Legname, G., Carloni, P., 2011. Common structural traits across pathogenic mutants of the human prion protein and their implications for familial prion diseases. J. Mol. Biol. 411, 700–712. Rossetti, G., Giachin, G., Legname, G., Carloni, P., 2010. Structural facets of diseaselinked human prion protein mutants: a molecular dynamic study. Proteins: Struct. Funct. Bioinform. 78, 3270–3280. Stahl, N., Baldwin, M.A., Teplow, D.B., Hood, L., Gibson, B.W., et al., 1993. Structural studies of the scrapie prion protein using mass spectrometry and amino acid sequencing. Biochemistry 32, 1991–2002. Stahl, N., Prusiner, S.B., 1991. Prions and prion proteins. FASEB J. 5, 2799–2807. van der Kamp, M., Daggett, V., 2011. Molecular dynamics as an approach to study prion protein misfolding and the effect of pathogenic mutations. Top. Curr. Chem. 305, 169–197. van der Kamp, M.W., Daggett, V., 2009. The consequences of pathogenic mutations to the human prion protein. Protein Eng. Des. Sel. 22, 461–468. van der Kamp, M.W., Daggett, V., 2010. Pathogenic mutations in the hydrophobic core of the human prion protein can promote structural instability and misfolding. J. Mol. Biol. 404, 732–748. Warshel, A., Sharma, P.K., Kato, M., Parson, W.W., 2006. Modeling electrostatic effects in proteins. BBA-Proteins Proteom. 1764, 1647–1676. Zahn, R., Liu, A., Lührs, T., Riek, R., von Schroetter, C., et al., 2000. NMR solution structure of the human prion protein. Proc. Natl. Acad. Sci. USA 97, 145–150. Zhang, Y., Dai, L., Iwamoto, M., Ouyang, Z., 2006. Molecular dynamics study on the conformational transition of prion induced by the point mutation: F198S. Thin Solid Films 499, 224–228. Zoete, V., Meuwly, M., 2006. Importance of individual side chains for the stability of a protein fold: computational alanine scanning of the insulin monomer. J. Comput. Chem. 27, 1843–1857. Zuegg, J., Gready, J., 1999. Molecular dynamics simulations of human prion protein: importance of correct treatment of electrostatic interactions. Biochemistry 38, 13862–13876.