J Biol Inorg Chem (2014) 19:635–645 DOI 10.1007/s00775-014-1132-7
ORIGINAL PAPER
Copper-induced structural propensities of the amyloidogenic region of human prion protein Caterina Migliorini • Adalgisa Sinicropi Henryk Kozlowski • Marek Luczkowski Daniela Valensin
• •
Received: 17 November 2013 / Accepted: 2 April 2014 / Published online: 16 April 2014 Ó SBIC 2014
Abstract Transmissible spongiform encephalopathies are associated with the misfolding of the cellular Prion Protein (PrPC) to an abnormal protein isoform, called scrapie prion protein (PrPSc). The structural rearrangement of the fragment of N-terminal domain of the protein spanning residues 91–127 is critical for the observed structural transition. The amyloidogenic domain of the protein encloses two copper-binding sites corresponding to His-96 and His-111 residues that act as anchors for metal ion binding. Previous studies have shown that Cu(II) sequestration by both sites may modulate the peptide’s tendency to aggregation as it inflicts the hairpin-like structure that stabilizes the transition states leading to b-sheet formation. On the other hand, since both His sites differ in their ability to Cu(II) sequestration, with His-111 as a preferred binding site, we found it interesting to test the role of Cu(II) coordination to this single site on the structural properties of amyloidogenic domain. The obtained results reveal that copper binding to His-111 site imposes precise backbone bending and weakens the natural tendency of apo peptide to b-sheet formation. Keywords Prion protein Copper His-111 Amyloidogenic region b-Sheet
Responsible Editors: Lucia Banci and Claudio Luchinat C. Migliorini A. Sinicropi D. Valensin (&) Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Via A. Moro, 53100 Siena, Italy e-mail:
[email protected] H. Kozlowski M. Luczkowski Faculty of Chemistry, University of Wroclaw, F. Joliot-Curie 14, 50-383 Wrocław, Poland
Introduction Understanding the generic mechanism underlining neurodegenerative diseases represents nowadays an increasingly growing issue in medical and biological research. Neurodegenerative diseases damage central nervous system of many mammals species and their pathogenesis has been associated with proteins misfolding and proteinaceous aggregates accumulating in neuronal cells. Transmissible spongiform encephalopathies (TSE), belonging to these fatal neuronal disorders, include scrapie in goats and sheep, chronic wasting disease in deer and elk, mad cow diseases and Creutzfeldt–Jakob disease (CJD), Gerstmann–Stra¨ussler–Scheinker syndrome, fatal familial insomnia and kuru in humans. The infectious agent of TSE is mainly constituted by a misfolded form of the prion protein (PrP) [1]. The normal cellular prion protein (PrPC) is a membrane-anchored glycoprotein expressed in many cells type, but mainly present in healthy neuronal cells [2]. The abnormal isoform of the prion protein, also known as scrapie prion protein (PrPSc), is highly insoluble, is protease resistant and readily forms aggregates (plaques) in brain cells that have been associated with the induction of neuron apoptosis and with the development of neurodegeneration processes [3, 4]. Unlike PrPC, PrPSc is rich in b-sheet structures which seem to have an essential role in amyloid aggregation processes. The knowledge of this conformational transition is essential to understand the development of the diseases [5–11]. PrPC is characterized by a predominantly a-helical C-terminal domain and an unstructured N-terminal domain able to coordinate up to six copper ions. Even if the specific function of PrPC is still debate matter, it has been widely demonstrated that it plays a relevant role in copper homeostasis or in copper-based enzymatic activity [12–20].
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By now, it is well established that four copper-binding sites are offered by the octarepeat region (residues 60–91) which is composed, in the human sequence (hPrP), of four identical PHGGGWGQ units, with the histidine of each repeats being the primary Cu(II) anchoring site [21–28]. Moreover, the hPrP91-127 region immediately outside the repeat fragments (also known as amyloidogenic PrP region) offers two independent Cu(II) binding sites, each associated with a histidine residue, His-96 and His-111, respectively [21, 26, 28–42]. Although there is no general consensus, most of the results obtained so far indicate His111 as the favourite, even not exclusive, Cu(II) binding site [26, 28, 30, 31, 33–36, 41, 42]. The species, predominant at pH around 7, has a 3N1O donor set with Cu(II) bound to His-111 imidazolic nitrogen and to the deprotonated main chain nitrogens of Lys-110 and His-111. An oxygen atom, from a water molecule or carbonyl group, completes the copper coordination sphere. The structural features of the copper-binding sites within the N-terminal region of PrP have been extensively investigated using molecular dynamics (MD) simulations as well [43–55]. Most of these studies were focused on Cu(II) interactions to the octarepeat region while very few reports are centered on the role played by the metal binding within the amyloidogenic PrP region. The interest to study copper interaction with the peptide fragment encompassing His-96 and His-111 is mainly due to the role played by the region 106–126 in prion propagation. In fact, the peptide homologous to residues 106–126 of hPrP possesses molecular, physiochemical and biological characteristics similar to PrPSc and it has been found that the hydrophobic core sequence following His111 is essential to express neurotoxic properties [56–59]. In addition, previous CD investigations suggested that Cu(II) binding to His-96 and His-111 residues induces bsheet formation in the unstructured PrP amyloidogenic region [31]. MD simulations performed on Cu(II)-hPrP96111 show the high propensity of the peptide to form bsheet structure elements as well [54, 55]. However, these investigations were conducted by considering Cu(II) bound to His-96 and His-111 imidazole nitrogens only, and the effects of the long hydrophobic tail were not taken into account [54, 55]. In this work, we have combined spectroscopic and MD simulations to explore the role of Cu(II) (if any) in the
structural transition process of the PrP fragment encompassing the 91–127 region. We mainly focused on the 3N1O binding modes occurring at His-111, which represents the major metal anchoring site. The data collected show the aptitude of hPrP91-127 to go through different structural conformations according to the absence or presence of Cu(II).
Materials and methods Peptide synthesis hPrP91-127, hPrP91-115, H96A hPrP91-115 and H111A hPrP91-115 PrP fragments (Scheme 1) were synthesized on an Activotec Activo-P11 automated peptide synthesizer, with Fmoc-protected amino acids using Fmoc chemistry. Rink-amide resin was used as the solid support so that the resulting peptides would be amidated at the C-terminus. The N-terminus was acetylated with a solution of 1 M acetic anhydride, and 0.4 M diisopropylethylamine in N,Ndimethylformamide (DMF). Cleavage from the resin was performed for 90 min in a 90 % trifluoroethanol (TFA) solution containing 5 % thioanisole, 2 % anisole, and 3 % ethanedithiol as free radical scavengers. After precipitation with cold ether, the peptides were redissolved in water and lyophilized to obtain a fluffy offwhite powder. The solid was redissolved in 10 % acetic acid and purified by reversed phase HPLC on a Varian Prostar HPLC with a preparative C18 column (Varian Pursuit XRs C 18) with a semi-linear gradient of 0.1 % TFA in water to 0.1 % TFA in 9:1 CH3CN/H2O over 45 min. The identity of the peptides was verified by electrospray ionization (ESI) mass spectrometry. Circular dichroism (CD) spectroscopy CD spectra were acquired on a Jasco spectropolarimeter 810 J at 298 K. A cell with a 0.1-cm path length was used for spectra recorded between 190 and 250 nm with sampling points every 1 nm. Four scans were collected for every sample with scan speed of 50 nm/min and bandwidth of 1 nm. Baseline spectra were subtracted from each spectrum and data were smoothed with the Savitzky–Golay method. Data were processed using Origin 5.0 spread
hPrP91-127
Ac-QGGGTHSQWNKPSKPKTNMKHMAGAAAAGAVVGGLGG-NH2
hPrP91-115
Ac-QGGGTHSQWNKPSKPKTNMKHMAGA-NH2
H96A hPrP91-115
Ac-QGGGTASQWNKPSKPKTNMKHMAGA-NH2
H111A hPrP91-115
Ac-QGGGTHSQWNKPSKPKTNMKHMAGA-NH2
Scheme 1 Amino acid sequence of the investigated PrP fragments. His and Ala substituted positions are shown in bold
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sheet/graph package. The direct CD measurements (h, in millidegrees) were converted to mean residue molar ellipticity, using the relationship mean residue De = h/ (33,000 9 c 9 l 9 number of residue). Fourier transform infrared (FT-IR) spectroscopy FT-IR spectra were acquired on Agilent Cary 630 machine using attenuated total reflectance ATR FT-IR technique. Two microliter drops of all peptide solutions were cast on the crystal and left to air-dry slowly at ambient conditions to form hydrated thin films. IR spectra were obtained at a resolution of 4 cm-1, utilizing the diamond ATR (5 Bounce ZnSe ATR and DialPath/TumblIR). The IR spectra were gathered within the mid-IR range (ca. 4,000–800 cm-1) with 128 co-added scans at a spectral resolution of 4 cm-1. All spectra are shown in the absorption mode after smoothing with the Savitzky–Golay algorithm.
Scheme 2 Model used to obtain the atomic charges (shown on the top of each atoms)
Computational methods Molecular dynamics simulations were carried out on five different initial conformations of hPrP91-127 randomly generated by Dynamics Algorithm for Nmr Applications (DYANA), a program used for three-dimensional structural definition of proteins and nucleic acids [60]. DYANA performs simulated annealing (SA) by molecular dynamics in torsion angle space and uses a fast recursive algorithm to integrate the equations of motions. The simulations were performed with 300 random starting structures of hPrP91127 and 10,000 steps of SA, without any additional structural restraints. Five selected molecules (conventionally named Mol1, Mol2, Mol3, Mol4 and Mol5) were chosen among a set of 30 randomly generated structures to well represent the conformational variability of the originated conformation set. The Cu(II) bound molecules were generated from these five molecules (Mol1, Mol2, Mol3, Mol4 and Mol5) by imposing a 0.2 nm fixed distance between copper and imidazolic nitrogen (N1) of His-111 and Lys-110 and His-111 deprotonated amide nitrogen atoms. A molecule of water was added to complete the metal coordination sphere. This Cu(II) donor set (3N1O) was chosen on the basis of previous experimental evidences [21, 26, 30, 41, 42]. On these ten selected hPrP91-127 molecular conformations, we performed an energy minimization followed by a molecular dynamics (MD) simulation, using the 4.5.1. version of the GROeningen MAchine for Chemicals Simulation (GROMACS) molecular dynamics package with the OPLS-AA/L (all atom) force field [61–65]. The structures were soaked in a triclinic box of singlepoint charge (SPC) water molecules and simulated using
periodic boundary conditions. The ionized state of the residues was set to be consistent with neutral pH and all simulations were performed in presence of a number of Clcounterions to balance the positive charge of the peptide. The systems were brought to the temperature of 298 K through three steps MD runs of 10 ps each, in which the temperature was progressively raised. Subsequently, MD simulations of 100 ns at constant temperature (T = 298 K) were performed on each structures, both on free hPrP91127 and Cu(II)-hPrP91-127 peptides resulting in the total collection of 10 MD trajectories. Electrostatic interactions were taken into account using the particle mesh Ewald (PME) method. Atomic charges for the copper-binding region were derived using the model in Scheme 2 which includes the metal ion, His-111 and Lys-110 residues and the coordinated water molecule. Geometry optimization was carried out at the B3LYP/6-31G** level of theory. Frequency calculations on the optimized structures have been performed at the same level to check that the stationary points were true energy minima. To be consistent with the original parameterization of the OPLS force field, the CHELPG charge-calculation method at the B3LYP/6-31G* ˚. level was employed. The copper radius was set to 2.0 A The computed charges used in the MD simulations are shown in Scheme 2. All calculations were carried out using Gaussian 03 package [66]. The force constants for Cu(II)peptide bonds were taken from Ref. [50], while additional missing parameters were taken from Ref. [67]. For the free hPrP91-127 peptides, no restraints were used, while for the Cu(II)-hPrP91-127 systems, distance restraints between the metal ion and its coordinating atoms
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were imposed in GROMACS. The LINCS algorithm was used to constraint bond lengths. The secondary structures were calculated using DSSP algorithm, a standard method for assigning the secondary structure to the amino acids of a protein [68].
Results Spectroscopic measurements CD and FT-IR analysis of the investigated apo and metal bound PrP fragments was performed on freshly prepared samples at physiological pH and room temperatures. The CD spectra recorded in water at physiological pH are shown in Fig. 1. All the spectra are characterized by a strong negative absorption band centered around 198 nm, typical of disordered conformations. The presence of equimolar Cu(II) concentrations in solution results in reduction of the signal at 198 nm for all the investigated systems (Fig. 1, dashed lines). In addition, with the
Fig. 1 CD spectra of apo (solid line) and Cu(II) bound (dashed line) forms of a hPrP91-127; b hPrP91-115; c H96A hPrP91-115 and d H111A hPrP91-115. All the spectra were collected at physiological
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exception of H111A hPrP91-115 sample, copper binding causes considerable changes of the spectrum shape in the region from 210 to 230 nm. To better understand the role played by copper in the structural transitions of the investigated PrP fragments, we also performed FT-IR spectra. The amide I region of apo hPrP91-127 (Fig. 2a, solid line) shows two bands centered at 1,656 and 1,627 cm-1 and a weak shoulder at 1,695 cm-1. On the other hand, hPrP91-115 (Fig. 2b, solid line) exhibits just a single band centered at 1,656 cm-1. The adsorption peaks in the amide I band, are generally assigned as: 1,653 ± 4 cm-1 to helix, 1,645 ± 4 cm-1 to random coil, 1,625 ± 5 cm-1 and 1,675 ± 5 cm-1 to bsheet, 1,663 ± 4 cm-1 to b-turn [69]. By considering that frequencies overlap from a-helix and disordered structures usually occur in H2O buffer [69–71] and taking into account the results obtained by CD, we assigned the 1,656 cm-1 band to random coil rather than a-helix. On the contrary, the absorption peak at 1,627 cm-1, corresponding to the presence of b-sheet conformations, is considered the hallmark of cross b-sheet structure formation [70, 72–76].
pH and room temperature. The molar concentrations are 0.10 and 0.09 mM for the peptides and Cu(II), respectively
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Fig. 2 FT-IR spectra of apo (solid line) and Cu(II) bound (dashed line) forms of a hPrP91-127; b hPrP91-115. All the spectra were collected at physiological pH and room temperature. The molar concentrations are 2.0 and 1.8 mM for the peptides and Cu(II), respectively
Upon Cu(II) addition, no changes are observed for hPrP91-115 (Fig. 2b, dashed line), while a slight increase of the band at 1,656 cm-1 and a slight decrease of the band at 1,627 cm-1 are detected for hPrP91-127 (Fig. 2a, dashed line) suggesting a small reduction of b-sheet content. Computational investigations To better rationalize the peptide conformational changes occurring in water, molecular dynamic simulation of hPrP91-127 and its corresponding copper(II) complex [with Cu(II) bound to His-111 site] were carried out. As
reported in ‘‘Materials and methods’’, five different random conformations were used as starting points, for both the apo and metal bound hPrP91-127. As shown in Fig. 3, the starting molecules for free and bound systems are similar to each other. The main differences are observed on the backbone region containing the metal binding site. To consider the entity of conformational drift of the molecules, a root-mean-square deviation (RMSD) was applied, using the starting structures as a reference (Fig. 4). The rising of the obtained RMSD values indicates that all structures have moved away from their initial conformations. Moreover, the stabilization of these values correlates with the formation of a compact conformation in all the
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Fig. 3 Starting conformation used for MD simulations of apo and copper bound hPrP91-127. Cu(II) is shown as a black sphere. Figure was created with MOLMOL 2K.1.0
A
0.25
B
0.2 Mol1
0.15
Mol2
0.1
Mol3 Mol4
0.05
Mol5
0
RMSD (Å)
0.2
RMSD (Å)
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Mol1
0.15
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Mol3 Mol4
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Mol5
0 0
10 20 30 40 50 60 70 80 90 100
Time (ns)
0
10 20 30 40 50 60 70 80 90 100
Time (ns)
Fig. 4 RMSD of a apo and b Cu(II) bound structures
considered molecules. As expected, apo hPrP91-127 molecules showed a slightly more fluctuating trend than Cu(II)-hPrP91-127 complexes, where the metal constrains allow to get earlier a stable conformation. However, all the studied systems appear to be equilibrated after 50 ns. Secondary structure determination was performed with DSSP on apo and Cu(II) bound molecules, with the aim to observe if metal coordination has some influence on the three-dimensional arrangement of hPrP91-127. The obtained data are reported in Fig. 5a (apo), b (Cu(II)), where each residue is indicated with a progressive number from 1 (Gln-91) to 37 (Gly-127). As indicated in Fig. 5a, four of the five simulated apo systems show the occurrence of b-sheet structure. This is also evident from the plot of the last four snapshots of the MD trajectories for these molecules (Fig. 6). In particular, the data collected for Mol1 show the appearance of 2–3 bsheet strands (Figs. 5a, 6) which include amino acids in regions 107–111, 115–118 and 121–124. The b-sheet fragment encompassing residues close to His-111 assumes
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a stable conformation after 70 ns, while the other two strands are stable throughout the simulation. Mol2 has two stable anti-parallel b-sheet fragments (Figs. 5a, 6); the first involves residues from Asn-108 to Ala-113, the second those from Ala-117 to Ala-120 which in some cases extends up to Leu-125. Mol3 shows the largest b-sheet arrangements (Figs. 5a, 6) which appear in the simulation after 50 ns and includes residues from Lys-110 to Ala-115 and residues from Ala-118 to Leu-125. Moreover, after 70 ns, additional b-sheet regions encompassing residues in the N-terminal part of the peptide come out. In detail, these two b-sheet strands appear quite steady and include residues from Gly-93 to Thr-95 and from Ser-97 to Pro-102. Mol4 shows the presence of two short b-sheet fragments encompassing residues 118–120 and 124–127. On the other hand, Mol5 reveals a completely random coil conformation with any appearances of secondary structure elements along the whole trajectory. Secondary structure determination with DSSP was performed also for the analogs Cu(II)-complexes molecules
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Fig. 5 Secondary structure evolutions as function of time. a apo hPrP91-127 and b Cu(II) bound hPrP91-127. The assignments of secondary structure were made with DSSP
and the results are reported in Fig. 5b. As easily observed, Cu(II) coordination has a strong impact on the b-sheet content. In particular Mol1 and Mol2 are completely devoid of any stable structural elements, as also shown by looking at the last MD snapshots (Fig. 7). During the first 70 ns of the trajectory, Mol3 appears to possess a disordered conformation similar to Mol1 and Mol2, but it shows a short b-sheet fragment encompassing residues 116–117 and 122–123 at the end of the simulation. A different behavior is observed for Mol4, which exhibits a b-sheet fragment close to His-111. A stable anti-parallel b-sheet appears along the trajectory and involves residues just preceding and following His-111: Thr-107-Met-109 and Met-112-Gly-114, respectively. The residues involved are in the proximity of the Cu(II)-binding site as shown in Fig. 7. The last investigated molecule, Mol5, has an overall disordered arrangement with the sporadic and minimal appearance of some secondary structure elements within 112-115 region alternatively assuming an a- or 310 helix structure.
Discussion It is well accepted that the key event associated with prion diseases is the conversion of PrPC into the misfolded form, PrPSc. Compared to PrPC, PrPSc has a much higher content of b-structure as shown by models obtained by electron microscopy and spectroscopic studies [77–80].
Identifying the factors able to influence PrPC conformation might provide new insights to understand the prion propagation. In this regard, previous MD investigations showed that pH, ionic strength, temperature and single point mutations strongly affect the stability fold of the C-terminal globular domain and cause structural modifications of the N-terminal domain of hPrP [5, 81–87]. As obtained by most of the above-mentioned investigations, our MD data performed on five initial random conformations of hPrP91-127 strongly support its propensity to assume a b-sheet conformation. In particular, our findings (Figs. 5a, 6) indicate that b-sheet elements engage residues close to His-111 and residues belonging to the C-terminal hydrophobic tail of the peptide. Four out of five molecules are characterized by stable and steady b-sheet fragments. Their early appearance and their stability over time point out a strong propensity of the peptide to assume this definite secondary structure arrangement. Our MD findings are in agreement with FT-IR spectra reported in Fig. 2, which indicate the occurrence of b-sheet only for the hPrP91-127 peptide, thus supporting the key role played by the hydrophobic domain in PrP misfolding. On the other hand, the absence of b-sheet structure observed from CD analysis (Fig. 1) is probably due to the fact that structural rearrangements of secondary structure of model peptides, in particular b-sheet formation, are strongly concentration dependent. Due to method limitations, the results of CD studies may not clearly reflect the tendencies predicted by MD calculations and
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Fig. 6 Last four snapshots (70, 80, 90 and 100 ns from the left to the right) of the MD trajectories of the five apo hPrP91-127 molecules. Figure was created with MOLMOL 2K.1.0
experimentally proved by FT-IR studies. As a matter of fact, peptide solutions used in FT-IR studies differ in concentration more than one order of magnitude from those used in CD experiments. Although previous evidences relate PrPC to copper metabolism and oxidative stress, the exact role of copper in TSEs is still not known [12, 14, 15, 18–20, 88–91]. One of the hypothesis is that copper binding to PrP amyloidogenic region might induce protein misfolding [31, 54, 55]. The characterization of Cu(II) binding to the amyloidogenic PrP region has been widely investigated using a huge number of techniques [21, 26, 28–42]. The existence of two independent Cu(II) binding sites, centered around His-96 and His-111, respectively, has been demonstrated, although His-111 seems to be the preferred binding site [26, 28, 30, 31, 33–36, 41, 42]. The metal binding modes are very similar with a {Nim, 2N-, O} donor set for both His-96 and His-111 sites. On the other hand, very little is known about the structural rearrangement of the amyloidogenic PrP region upon Cu(II) binding. As shown by the CD spectra (Fig. 1), Cu(II) binding to hPrP91-127 causes structural modifications of the peptide
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backbone in agreement with what previously observed for shorter PrP fragments [31, 92]. The similar behavior detected for hPrP91-127 and its shorter derivative (hPrP91-115) indicate that the causes of these changes are not dependent on the hydrophobic tail (region 115–127). On the other hand, the differences observed for H111A substituted peptide (H111A hPrP91-115) strongly support that structural modifications of the peptide main chain occur only when Cu(II) is bound to the His-111 site. The observed CD modifications, in agreement with previous investigations [92], suggest that Cu(II) induces a rigid backbone conformation of the residues involved in metal interaction rather than an increasing b-sheet content [31]. Contrarily to CD, FT-IR experiments performed on Cu(II)-complexes point out a different behavior of hPrP91127 and hPrP91-115 (Fig. 2). The former shows the presence of both random coil and b-sheet features, while a completely disordered conformation is observed for the latter. In addition, the binding to the cupric ion results in slight changes of hPrP91-127 spectra only. In particular, our data suggest that the metal bound form has a lower bsheet content compared to the apo form. The presence of the intermolecular b-sheet interactions was also previously observed for hPrP86-147, showing similar IR spectra, which, in addition to the random coil band, exhibit a smaller component at 1,623 cm-1 and a weak shoulder around 1,690 cm-1 [93]. FT-IR data clearly indicate that Cu(II) binding to the unstructured amyloidogenic region of hPrP (hPrP91-127) does not induce b-sheet formation. On the other hand, CD spectra reported in Fig. 1 are very similar to the ones previously obtained for Cu(II)-hPrP91-115 complexes, whose behavior was interpreted as an increase of b-sheet content of the peptide caused by copper binding [31]. However, as shown in Fig. 2, FT-IR measurements point out that hPrP91-115 has a disordered conformation which is totally retained upon Cu(II) coordination. These findings strongly suggest that secondary structure rearrangements, induced by Cu(II), have to be interpreted with caution if only CD data are considered. In fact the changes observed in the far UV can be due to either secondary structure alterations or induction of charge transfer bands from the peptide to the cupric ion. For these reasons, the combined use of CD and FT-IR is preferred to evaluate the change of the secondary structure of copper bound systems. Similar to FT-IR, the comparison of MD simulations of the free molecules with their corresponding metal complexes clearly point out the role played by Cu(II) in the structural rearrangement of hPrP91-127. Apo and Cu(II) bound states of Mol1, Mol2 and Mol3 show a completely different behavior (Fig. 5). A loss of secondary structure elements is observed in Cu(II)-complexes, as shown by the last four MD snapshots (Figs. 6, 7). In particular, both Cu(II)-Mol1 and Cu(II)-Mol2 assume random coil
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Fig. 7 Last four snapshots (70, 80, 90 and 100 ns from the left to the right) of the MD trajectories of Cu(II)-hPrP91127 molecules. Cu(II) is shown as a green sphere. Figure was created with MOLMOL 2K.1.0. The last snapshot (100 ns) of Mol 1 contains a small 310 helix which is hard to detect in Fig. 5b because of its low content
conformations, exhibiting clear divergences from their analogous apo states. Cu(II)-Mol3 shows only two short bsheet strands which appear after 70 ns of simulations and involve residues exclusively belonging to the peptide C-terminal region, Ala-116-Ala-117 and Val-122- Gly123, respectively. The comparison of secondary structure evolutions of MD trajectories of Cu(II)-hPrP91-127 and their corresponding apo systems (Fig. 5) allowed us to identify the conformational changes related to metal binding. The absence of any stable structural elements observed in the Cu(II) complexes suggests that copper does not promote b-sheet structuring of the peptide, but it rather causes the loss of b-sheet elements present in their related apo systems. This behavior might be explained by hypothesizing that His-111 plays a key role in b-sheet formations and that Cu(II) coordination to His-111 site prevents the b-sheet arrangements by imposing precise backbone bending, driven by both the metal geometry and the formation of chelating rings. Previous MD simulations on Cu(II)-hPrP96-111 complex supported the stabilization of antiparallel b-sheet
structures stabilized by the formation of several hydrogen bonds [54, 55]. However, such data were obtained considering Cu(II) bound to His-96 and His-111 imidazole nitrogens only, which, approaching together, yield to the formation of b-hairpin structure. As shown by previous investigations, this binding mode might occur at low Cu(II) occupancy [34], even if successive potentiometric titrations pointed out that metal anchoring to His-111 with the subsequent coordination to backbone nitrogens occurs in the presence of substoichiometry copper concentrations as well [35].
Conclusion The structural rearrangement of the fragment of N-terminal domain of the prion protein, spanning residues 91–127, is critical for the transition of cellular form of the prion protein PrPC into its scrapie counterpart PrPSc. Interestingly, the amyloidogenic domain of the protein encloses two copper-binding sites corresponding to the His-96 and
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His-111 residues that act as anchors for metal ion binding. Previous studies employing molecular dynamics have shown that Cu(II) sequestration by both sites may modulate the peptide tendency to aggregation. Cu(II) bridging propagates the hairpin-like structure that stabilizes the transition states leading to b-sheet formation. Since both His sites differ in their ability to Cu(II) sequestration, with His-111 as a preferred binding site, we found it interesting to test the role of Cu(II) coordination to the single site on the structural properties of amyloidogenic domain. The obtained results reveal that copper binding to His-111 site, imposing precise backbone bending, weakens the natural tendency of the apo peptide to form b-sheet. Acknowledgments We thank PRIN (Programmi di Ricerca di Rilevante Interesse Nazionale) (2010M2JARJ_004), CIRMMP (Consorzio Interuniversitario Risonanze Magnetiche di Metalloproteine Paramagnetiche), CIRCMSB (Consorzio Interuniversitario di Ricerca in Chimica dei Metalli nei Sistemi Biologici) and National Science Center (NCN 2011/01/B/ST5/03936) for financial support. We acknowledge the CINECA Awards No. HP10CQ1AYP, 2010, for the availability of high-performance computing resources and support.
References 1. Soto C, Castilla J (2004) Nat Med 10(Suppl):S63–S70 2. Kretzschmar HA, Prusiner SB, Stowring LE, DeArmond SJ (1986) Am J Pathol 122:1–5 3. Prusiner SB (1998) Proc Natl Acad Sci 95(25):13363–13383 4. Prusiner SB (2001) N Engl J Med 344:1516–1526 5. Van der Kamp MW, Daggett V (2010) Biophys J 99(7):2289–2298 6. Pan KM, Baldwin M, Prusiner SB (1993) Proc Natl Acad Sci USA 90(23):10962–10966 7. Jackson GS, Hill SF, Collinge J (1999) Biochim Biophys Acta 1431(1):1–13 8. Grande-Aztatzi R, Rivillas-Acevedo L, Quintanar L, Vela A (2013) J Phys Chem B 117(3):789–799 9. Prusiner SB (1982) Science 216(4545):136–140 10. Prusiner SB (1991) Science 252(5012):1515–1522 11. Prusiner SB (1997) Science 278(5336):245–255 12. Brown DR, Qin K, Herms JW, Madlung A, Manson J, Strome R, Fraser PE, Kruck TA, von Bohlen A, Schulz-Schaeffer W, Giese A, Westaway D, Kretzschmar H (1997) Nature 390(6661):684–687 13. Kozlowski H, Luczkowski M, Remelli M, Valensin D (2012) Coord Chem Rev 256(19–20):2129–2141 14. Jackson GS, Murray I, Hosszu LLP, Gibbs N, Waltho JP, Clarke AR, Collinge J (2001) Proc Natl Acad Sci USA 98(15):8531–8535 15. Gaggelli E, Kozlowski H, Valensin D, Valensin G (2006) Chem Rev 106(6):1995–2044 16. Lehmann S (2002) Curr Opin Chem Biol 6(2):187–192 17. Brown DR, Kozlowski H (2004) Dalton Trans (13):1907–1917 18. Kozlowski H, Janicka-Klos A, Brasun J, Gaggelli E, Valensin D, Valensin G (2009) Coord Chem Rev 253(21–22):2665–2685 19. Millhauser GL (2004) Acc Chem Res 37(2):79–85 20. Emwas AHM, Al-Talla ZA, Guo X, Al-Ghamdi S, Al-Masri HT (2013) Magn Reson Chem 51:255–268 21. Migliorini C, Porciatti E, Luczkowski M, Valensin D (2012) Coord Chem Rev 256(1–2):352–368
123
J Biol Inorg Chem (2014) 19:635–645 22. Burns CS, Aronoff-Spencer E, Dunham CM, Lario P, Avdievich NI, Antholine WE, Olmstead MM, Vrielink A, Gerfen GJ, Peisach J, Scott WG, Millhauser GL (2002) Biochemistry 41(12):3991–4001 23. Valensin D, Luczkowski M, Mancini FM, Legowska A, Gaggelli E, Valensin G, Rolka K, Kozlowski H (2004) Dalton Trans 7(9):1284–1293 24. Garnett AP, Viles JH (2003) J Biol Chem 278(9):6795–6802 25. Chattopadhyay M, Walter ED, Newell DJ, Jackson PJ, AronoffSpencer E, Peisach J, Gerfen GJ, Bennett B, Antholine WE, Millhauser GL (2005) J Am Chem Soc 127(36):12647–12656 26. Kozlowski H, Luczkowski M, Remelli M (2010) Dalton Trans 39:6371–6385 27. Walter ED, Chattopadhyay M, Millhauser GL (2006) Biochemistry 45(43):13083–13092 28. Arena G, La Mendola D, Pappalardo G, Sovago I, Rizzarelli E (2012) Coord Chem Rev 256(19–20):2202–2218 29. Wells MA, Jelinska C, Hosszu LL, Craven CJ, Clarke AR, Collinge J, Waltho JP, Jackson GS (2006) Biochem J 400(3):501–510 30. Gralka E, Valensin D, Porciatti E, Gajda C, Gaggelli E, Valensin G, Kamysz W, Nadolny R, Guerrini R, Bacco D, Remelli M, Kozlowski H (2008) Dalton Trans 38:5207–5219 31. Jones CE, Abdelraheim SR, Brown DR, Viles JH (2004) J Biol Chem 279(31):32018–32027 32. Wells MA, Jackson GS, Jones S, Hosszu LL, Craven CJ, Clarke AR, Collinge J, Waltho JP (2006) Biochem J 399(3):435–444 33. Berti F, Gaggelli E, Guerrini R, Janicka A, Kozlowski H, Legowska A, Miecznikowska H, Migliorini C, Pogni R, Remelli M, Rolka K, Valensin D, Valensin G (2007) Chem Eur J 13(7):1991–2001 34. Klewpatinond M, Viles JH (2007) Biochem J 404(3):393–402 35. Remelli M, Valensin D, Bacco D, Gralka E, Guerrini R, Migliorini C, Kozlowski H (2009) N J Chem 33(11):2300–2310 } K, Nagy Z, Pappalardo G, Di Natale G, Sanna D, Micera G, 36. Osz Rizzarelli E, So´va´go´ I (2007) Chem Eur J 13(25):7129–7143 37. Walter ED, Stevens DJ, Spevacek AR, Visconte MP, Dei Rossi A, Millhauser GL (2009) Curr Protein Pept Sci 10(5):529–535 38. Burns CS, Aronoff-Spencer E, Legname G, Prusiner SB, Antholine WE, Gerfen GJ, Peisach J, Millhauser GL (2003) Biochemistry 42(22):6794–6803 39. Shearer J, Soh P (2007) Inorg Chem 46:710–719 40. Shearer J, Soh P, Lentz S (2008) J Inorg Biochem 102:2103–2113 41. Rivillas-Acevedo L, Grande-Aztatzi R, Lomeli I, Garcia JE, Barrios E, Teloxa S, Vela A, Quintanar L (2011) 50:1956–1972 42. Remelli M, Valensin D, Toso L, Gralka E, Guerrini R, Marzola E, Kozłowski H (2012) Metallomics 4(8):794–806 43. Sovago I, Kallay C, Varnagy K (2012) Coord Chem Rev 256(19–20):2225–2233 44. Furlan S, La Penna G (2012) Coord Chem Rev 256(19–20):2234–2244 45. Mentler M, Weiss A, Grantner K, Del Pino P, Deluca D, Fiori S, Renner C, Klaucke WM, Moroder L, Bertsch U, Kretzschmar HA, Tavan P, Parak FG (2005) Eur Biophys J 34:97–112 46. Furlan S, La Penna G, Guerrieri F, Morante S, Rossi GC (2007) J Biol Inorg Chem 12:571–583 47. Marino T, Russo N, Toscano M (2007) J Phys Chem B 111(3):635–640 48. Pushie MJ, Rauk A (2003) J Biol Inorg Chem 8:53–65 49. Riihima¨ki ES, Martı´nez JM, Kloo L (2007) J Phys Chem B 111(35):10529–10537 50. Pushie MJ, Vogel HJ (2007) Biophys J 93(11):3762–3774 51. Pushie MJ, Vogel HJ (2008) Biophys J 95(11):5084–5091 52. Riihima¨ki ES, Martı´nez JM, Kloo L (2008) Phys Chem Chem Phys 10(18):2488–2495
J Biol Inorg Chem (2014) 19:635–645 53. Valensin G, Molteni E, Valensin D, Taraszkiewicz M, Kozlowski H (2009) J Phys Chem B 113(11):3277–3279 54. Pushie MJ, Vogel HJ (2009) J Toxicol Environ Health A 72(17–18):1040–1059 55. Pushie MJ, Rauk A, Jirik FR, Vogel HJ (2009) Biometals 22(1):159–175 56. Jobling MF, Stewart LR, White AR, McLean C, Friedhuber A, Maher F, Beyreuther K, Masters CL, Barrow CJ, Collins SJ, Cappai R (1999) J Neurochem 73(4):1557–1565 57. Selvaggini C, De Gioia L, Cantu` L, Ghibaudi E, Diomede L, Passerini F, Forloni G, Bugiani O, Tagliavini F, Salmona M (1993) Biochem Biophys Res Commun 194(3):1380–1386 58. De Gioia L, Selvaggini C, Ghibaudi E, Diomede L, Bugiani O, Forloni G, Tagliavini F, Salmona M (1994) J Biol Chem 269(11):7859–7862 59. Walsh P, Neudecker P, Sharpe S (2010) J Am Chem Soc 132(22):7684–7695 60. Gu¨ntert P; Mumenthaler C; Wu¨thrich K (1997) J Mol Biol, p 273 61. Lindahl E, Hess B, van der Spoel D (2001) J Mol Model 7:306–317 62. van der Spoel D, Lindahl E, Hess B, Mark AE, Berendsen HJ (2005) J Comput Chem 26(16):1701–1718 63. Jorgensen WL, Maxwell DS, Tirado-Rives J (1996) J Am Chem Soc 118(45):11225–11236 64. Kaminski GA, Friesner RA (2001) J Phys Chem B 105(28):6474–6487 65. Jorgensen WL, Tirado-Rives J (1988) J Am Chem Soc 110(6):1657–1667 66. Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA, Cheeseman JR, Montgomery JA, Vreven JrT, Kudin KN, Burant JC, Millam JM, Iyengar SS, Tomasi J, Barone V, Mennucci B, Cossi M, Scalmani G, Rega N, Petersson GA, Nakatsuji H, Hada M, Ehara M, Toyota K, Fukuda R, Hasegawa J, Ishida M, Nakajima T, Honda Y, Kitao O, Nakai H, Klene M, Li X, Knox JE, Hratchian HP, Cross JB, Bakken V, Adamo C, Jaramillo J, Gomperts R, Stratmann RE, Yazyev O, Austin AJ, Cammi R, Pomelli C, Ochterski JW, Ayala PY, Morokuma K, Voth GA, Salvador P, Dannenberg JJ, Zakrzewski VG, Dapprich S, Daniels AD, Strain MC, Farkas O, Malick DK, Rabuck AD, Raghavachari K, Foresman JB, Ortiz JV, Cui Q, Baboul AG, Clifford S, Cioslowski J, Stefanov BB, G Liu, Liashenko A, Piskorz P, Komaromi I, Martin RL, Fox DJ, Keith T, Al-Laham MA, Peng CY, Nanayakkara A, Challacombe M, Gill MPW, Johnson B, Chen W, Wong MW, Gonzalez C, Pople JA (2004) Gaussian 03, Revision D.02, Gaussian, Inc., Wallingford CT 67. Rajapandian V, Hakkim V, Subramanian V (2010) J Phys Chem B 114(25):8474–8486 68. Kabasch W, Sander C (1983) Biopolymers 22:2577–2637 69. Byler DM, Susi H (1986) Biopolymers 25:469–487 70. Uversky VN (2014) Front Biosci (Landmark Ed) 19:181–258
645 71. Jiang T, Zhou GR, Zhang YH, Sun PC, Du QM, Zhou P (2012) RSC Adv 2:9106–9113 72. Bouchard M, Zurdo J, Nettleton EJ, Dobson CM, Robinson CV (2000) Protein Sci 9:1960–1967 73. Botelho HM, Leal SS, Cardoso I, Yanamandra K, MorozovaRoche LA, Fritz G, Gomes CM (2012) J Biol Chem 287(50):42233–42242 74. Shivu B, Seshadri S, Li J, Oberg KA, Uversky VN, Fink AL (2013) Biochemistry 52(31):5176–5183 75. He C, Han Y, Zhu L, Deng M, Wang Y (2013) J Phys Chem B 117(36):10475–10483 76. Pivato M, De Franceschi G, Tosatto L, Frare E, Kumar D, Aioanei D, Brucale M, Tessari I, Bisaglia M, Samori B, de Laureto PP, Bubacco L (2012) PLoS ONE 7(12):e50027 77. Govaerts C, Wille H, Prusiner SB, Cohen FE (2004) Natl Acad Sci USA 101(22):8342–8347 78. Lu X, Wintrode PL, Surewicz WK (2007) Proc Natl Acad Sci USA 104(5):1510–1515 79. Cobb NJ, So¨nnichsen FD, McHaourab H, Surewicz WK (2007) Proc Natl Acad Sci USA 104(48):18946–18951 80. DeMarco ML, Daggett V (2004) Proc Natl Acad Sci USA 100(8):2293–2298 81. Ji HF, Zhang HY (2010) Trends Biochem Sci 35(3):129–134 82. Campos SRR, Machuquiero M, Baptista AM (2010) J Phys Chem B 114(39):12692–12700 83. Xu Z, Lazim R, Mei Y, Zhang D (2012) Chem Phys Lett 539–540:239–244 84. Thukral L, Daidone I, Smith JC (2011) PLoS Comput Biol 7(9):e1002137 85. Saracino GAA, Villa A, Moro G, Cosentino U, Salmona M (2009) Proteins 75(4):964–976 86. Gu W, Wang T, Zhu J, Shi Y, Liu H (2003) Biophys Chem 104(1):79–94 87. Rossetti G, Cong X, Caliandro R, Legname G, Carloni P (2011) J Mol Biol 411(3):700–712 88. Opazo C, Barrı´a MI, Ruiz FH, Inestrosa NC (2003) Biometals 16(1):91–98 89. Ruiz FH, Silva E, Inestrosa NC (2000) Biochem Biophys Res Commun 269(2):491–495 90. Varela-Nallar L, Toledo EM, Chaco´n MA, Inestrosa NC (2006) Biol Res 39(1):39–44 91. Varela-Nallar L, Gonza´lez A (2006) Inestrosa NC. Curr Pharm Des 12(20):2587–2595 92. Di Natale G, Grasso G, Impellizzeri G, La Mendola D, Micera G, Mihala N, Nagy Z, Osz K, Pappalardo G, Rigo´ V, Rizzarelli E, Sanna D, So´va´go´ I (2005) Inorg Chem 44(20):7214–7225 93. Natalello A, Prokorov VV, Tagliavini F, Morbin M, Forloni G, Beeg M, Manzoni C, Colombo L, Gobbi M, Salmona M, Doglia SM (2008) J Mol Biol 381(5):1349–1361
123