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* Basic Research Program, Science Applications International Corporation-Frederick, Laboratory of Experimental and Computational Biology, National Cancer Institute, Frederick, Maryland 21702; Laboratory of Experimental and Computational Biology, National Cancer Institute, Frederick, Maryland 21702; School of Computer Science, Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 69978, Israel; and Sackler Institute of Molecular Medicine, Department of Human Genetics, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv 69978, Israel
Correspondence: Address reprint requests to Ruth Nussinov, Tel.: 301-846-5579; Fax: 301-846-5598; E-mail: ruthn{at}ncifcrf.gov.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONCOMPUTATIONAL METHODSRESULTS AND DISCUSSIONCONCLUSIONS AND FUTURE WORKACKNOWLEDGEMENTSREFERENCES |
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONCOMPUTATIONAL METHODSRESULTS AND DISCUSSIONCONCLUSIONS AND FUTURE WORKACKNOWLEDGEMENTSREFERENCES |
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, 2003; Harper and Lansbury, 1997; Rochet and Lansbury, 2000; Wanker, 2000). Amyloidogenic proteins do not share sequence or structural homology. Nevertheless, x-ray diffraction data show that they have a similar semiordered cross-ß-fibril organization (Serpell, 2000). Detailed atomic information of the 3D structure of the amyloid is lacking. Since amyloid fibrils are noncrystalline and insoluble, the structure cannot be obtained by conventional methods such as x-ray crystallography and solution NMR. Although solid-state NMR and molecular simulations provide options for understanding the structures of amyloid fibrils, they are still difficult and challenging (Ma and Nussinov, 2002b; Petkova et al., 2002). There are still many open questions regarding these highly ordered amyloid fibrils. For example, what is the driving force of amyloid aggregation? In protein folding, the hydrophobic effect is usually regarded as the driving force; however, some hydrophilic peptides can also form ordered amyloids (Balbirnie et al., 2001; Reches et al., 2002). Second, which interactions stabilize the ordered structure of the amyloid fibrils? In particular, what are the roles of side-chain interactions in the formation of an amyloid fibril? Are there particular residues that play key roles in amyloid formation? Furthermore, what is the minimal size of the amyloid seed and its stability? How sensitive is amyloid formation to small sequence changes?
These challenging problems are being addressed by both experimental and computational approaches. Experiments have established that a hexamer (NFGAIL) of the human islet amyloid polypeptide (hIAPP) and even a smaller pentamer (FGAIL) are sufficient for amyloid formation (Tenidis et al., 2000). Molecular dynamics (MD) simulations indicate that the most stable conformation of the ordered aggregates of NFGAIL is an antiparallel orientation within the sheets and parallel organization between sheets (Zanuy et al., 2003). Furthermore, several fragments in the Syrian hamster prion protein (ShPrP) have been shown to form amyloids. For the AGAAAAGA fragment (Gasset et al., 1992), explicit water MD simulations of the oligomers (Ma and Nussinov, 2002a) indicate that they are stable in an antiparallel arrangement when the size is from six to eight peptides. The heptapeptide GNNQQNY derived from the yeast prion Sup-35 illustrates similar amyloid properties as the full length Sup-35 (Balbirnie et al., 2001). This heptapeptide has been well studied by MD simulations in an implicit water model with a total simulation time of 20 µs (Gsponer et al., 2003). The simulations generated an in-register parallel association of GNNQQNY ß-strands, consistent with x-ray diffraction and Fourier transform infrared (FTIR) spectroscopy. The parallel ß-sheet arrangement is favored in energy over the antiparallel due to side-chain interactions mainly from hydrogen bonds between the amide groups and the tyrosine aromatic rings 
-stacking. Recently, a parallel ß-strand structure of full length Alzheimer's ß-amyloid (Aß1–40) has been observed by solid-state NMR techniques (Petkova et al., 2002). Roughly at the same time, Ma and Nussinov (2002b) used MD simulations to examine the stabilities of different possible oligomers formed by fragments of the Aß. They independently proposed a very similar bent structure for Aß10–35 with a double layered sheet (Ma and Nussinov, 2002b; Petkova et al., 2002). Moreover, multiple long timescale MD simulations have been used to study the assembly of Aß16–22. These suggested that an 
-helical conformation may be an intermediate in the assembly. Similar results were obtained from circular dichroism by monitoring the secondary structure changes of Aß1–40 and Aß1–42 during the amyloid formation (Kirkitadze et al., 2001).
Recently, Gazit et al. (Reches et al., 2002) found that a short pentapeptide containing aromatic and charged residues (DFNKF) from human calcitonin (hCT) can form highly ordered amyloid fibrils. hCT is a 32-amino acid peptide hormone, important in the calcium-phosphorous metabolism (Arvinte et al., 1993; Zaidi et al., 2002). hCT tends to aggregate, and its amyloid depositions are associated with medullary carcinoma of the thyroid (Arvinte et al., 1993). The DFNKF fragment was chosen due to the pH effects on the fibril formation of hCT (Kanaori and Nosaka, 1995) and the proposed role of aromatic residues in the fibrillation (Azriel and Gazit, 2001; Gazit, 2002a,b). These results showed some striking features: i), Early studies generally concluded that the hydrophobic effect plays an important role in the fibril formation. Nevertheless, this hydrophilic/charged peptide can also form highly ordered amyloid fibrils. ii), Few cases were reported for amyloid formation by pentapeptide and tetrapeptide. Short fragments that can form ordered fibrils imply that amyloid formation with full-length proteins may be dominated by some specific residues/segments. The unexpected high rate of amyloid formation (E. Gazit, Tel Aviv University, 2004, personal communication) by DFNKF indicates that the nucleating seed may be relatively small, albeit stable. Very recently, solid-state NMR data on the DFNKF peptide using isotope labeling on two Phe positions have been published (Naito et al., 2004). The authors showed that a mixture of 70% antiparallel structure (the first Phe forms a hydrogen bond with Lys) and 30% other structure (the first Phe forms a hydrogen bond with Asn) can have a best fit to the solid-state NMR data. It is also interesting to point out that the authors suggested that the full length calcitonin peptide forms a mixture of antiparallel and parallel ß-sheets at acidic condition.
Unlike other larger amyloid-forming fragments, the small size of DFNKF peptide allows us to study the stability and dynamics of the potential amyloid nuclei by using computational approaches. Earlier studies (our unpublished results) have tested the stabilities of various two- and three-sheet arrangements, with parallel/antiparallel sheets and strands. After tests of 24 models with over 82 ns explicit water simulations, these studies have found that the single layer ß-sheet with parallel strands is a stable organization for the DFNKF. Furthermore, replica-exchange molecular simulations, sampling a wide range of conformational space of DFNKF oligomers at temperatures ranging from 300 K to 600 K, also showed that the parallel structure of DFNKF tetramer is the lower energy conformer (our unpublished results). Parallel organization has been suggested for an assortment of different amyloid fibrils (Balbirnie et al., 2001; Bouchard et al., 2000; Petkova et al., 2002). However, no stable antiparallel DFNKF ß-sheet structure had been found in the MD simulations. Further attempts in our group are currently ongoing to search for stable antiparallel ß-sheets using enhanced MD simulation protocols.
Currently, there are increasing indications that small oligomers are the toxic agents in amyloidogenic diseases (Hardy and Selkoe, 2002; Kayed et al., 2003). Here, we employ all-atom MD simulations to explore the stabilities and dynamics of potential small oligomer seeds of DFNKF peptides, with the size increasing from dimer to tetramer. The results show that the stabilities of parallel DFNKF oligomers increase with the number of strands. Small DFNKF oligomers such as trimer and tetramer are stable in the parallel organization for a sufficient time in the 350-K MD simulations, indicating that the seed size for the DFNKF amyloid aggregation can be quite small. The direct observation of the dynamic registration of parallel DFNKF oligomers from the out-of-register conformation in the trimer simulations implies that an extended strand may serve as a ß-sheet template, assisting in amyloid formation. Characterization of the formation of the in-register parallel structure shows that it follows a noncooperative process. Sequence variant studies including mutations and capping show that the side-chain–side-chain interactions are important in preserving the parallel DFNKF arrangements. In particular, the Asn side-chain–side-chain hydrogen bonds between two neighboring chains were found to be particularly important in retaining the parallel DFNKF integrity. The N-/C-terminal residues (Asp and Phe) as well as the backbone hydrogen bonds near the N-/C-terminus were observed to be more flexible than the residues in the interior of the strands.
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COMPUTATIONAL METHODS |
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TOPABSTRACTINTRODUCTIONCOMPUTATIONAL METHODSRESULTS AND DISCUSSIONCONCLUSIONS AND FUTURE WORKACKNOWLEDGEMENTSREFERENCES |
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). Simulations were performed using an NVT ensemble with periodic boundary conditions. The DFNKF oligomers and mutants studied here were solvated with explicit TIP3 water molecules in a cubic box. The lengths of the cubic box used for the DFNKF monomer, dimer, trimer, and tetramer simulations are 30 Å, 30 Å, 35 Å, and 40 Å, respectively. A 10-ns simulation was carried out for each system at 350 K. This simulation temperature is slightly higher than room temperature and may aid in avoiding kinetic traps and allow us to probe the stabilities and dynamics of DFNKF oligomers more quickly in the limited simulation time. The Adopted Basis Newton-Raphson (ABNR) energy minimizations were performed for all systems before the MD simulations. A 1-fs time step was used in the numerical integration. A group based distance cutoff was applied at 10 Å and 11 Å when generating the list of pairs. The force switching function was used to smooth the electrostatic potential energy, whereas the van der Waals shift function was used to smooth the van der Waals potential energy starting at 8 Å (Steinbach and Brooks, 1994). The nonbonded neighboring list was updated every 20 steps.
To probe the dynamical structure characteristics during the simulations, some quantities were computed. We calculated the C-RMSD, the residue-wise distances dij(t), the scalar product of end-to-end vectors cos(
)ij, the fraction of native contact (Qnat), the population of the ß-strand and of the -helix, the end-to-end distance, and the radius of gyration (Rg). The C-RMSDs were calculated from the minimal deviations of the C atoms of the trajectories away from the energy minimized structure with parallel organizations by superimposing the conformations. The residue-wise distances dij(t) were calculated from the distances between the C atom of residue i and the C atom of residue j at different simulation time t. The scalar product of end-to-end vectors, 
for a pair chain i and j, were calculated to monitor the relative orientations of chains i and j (Klimov and Thirumalai, 2003). When cos()ij is close to 1.0, chains i and j adopt a parallel-like organization. In contrast, when cos()ij is close to –1.0, chains i and j adopt an antiparallel-like organization. The native contacts included backbone hydrogen bonds and side-chain contacts (Rao and Caflisch, 2003). The backbone hydrogen bond was calculated based on the definition of hydrogen bonds used in STRIDE (Frishman and Argos, 1995). A native side-chain contact is considered when the distance between the geometrical center is smaller than 6.7 Å. The energy minimized structures with parallel organization were used to construct the native contacts. The fraction of native contacts was calculated as the fraction of contacts common to both the current conformation and the native structure (here, the energy minimized structures with parallel packing were used). The end-to-end distance was calculated between the nitrogen atom in the ammonium group and the carbon atom in the carboxyl group. The radius of gyration (Rg) for the oligomers and peptide was computed using all the heavy atoms (Massi et al., 2001).
To probe possible minima of the DFNKF monomer and dimer that may exist in the simulation, the free energy landscape was determined from the histogram analysis (Zhou et al., 2001) by calculating the normalized probability, P(X) = exp(–ßW(X))/Z, where X is any set of reaction coordinates. The relative free energy (or the so-called potential of mean force) can be described as W(X2) – W(X1) = –RT log(P(X2)/P(X1)). The free energy landscape was expressed as a function of various reaction coordinates including the end-to-end distance, the radius of gyration, the cos()ij, and the average of the five residue-wise distances.
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RESULTS AND DISCUSSION |
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TOPABSTRACTINTRODUCTIONCOMPUTATIONAL METHODSRESULTS AND DISCUSSIONCONCLUSIONS AND FUTURE WORKACKNOWLEDGEMENTSREFERENCES |
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Relative stability of DFNKF oligomers
It is currently accepted that amyloid fibril formation follows a nucleated assembly mechanism and proceeds via a conformational change (Jarrett et al., 1993; Jarrett and Lansbury, 1993; Lomakin et al., 1997; Serio et al., 2000; Tenidis et al., 2000). The early events in the nucleus formation involve a series of association steps. These are not favorable thermodynamically since the interstrand interactions (enthalpy) cannot compensate for the loss of the entropy after the association. Once the crucial nucleus is formed, further steps of association are thermodynamically favored. The addition of smaller monomers to the larger nucleus has a lower entropic cost, and the monomers can interact with the growing nucleus at multiple sites, resulting in rapid amyloid formation. Therefore, studying the stability and dynamics of DFNKF oligomers that are potential nuclei is essential to understand the assembly mechanism.
The time series of the C-root mean-square deviation (C-RMSD) and the fraction of native contacts (Qnat) of different sizes of DFNKF oligomers have indicated their relative stabilities (Fig. 1). The C-RMSD and the Qnat were calculated at 350 K based on the corresponding energy minimized structures because the native structures were not available. At the early stage of the simulations, all three simulated DFNKF oligomers fluctuated around their energy minimized structures with small C-RMSD and large Qnat. Subsequently, the C-RMSD increased (and Qnat decreased) in all three simulations, and they no longer came back to the energy minimized basins during the course of simulations. However, the dissociation (increase of C-RMSD and decrease of Qnat) of the three DFNKF oligomers initiated at different time stages (with different lag phases). The magnitude of the DFNKF dimer C-RMSD increased sharply after 
1.0 ns and reached the maximal value of 9.7 Å roughly at t 4.8 ns. Similarly, at t 4.8 ns, the calculated Qnat of the dimer was zero, indicating that the dimer has no native-like characteristics at this stage. Nevertheless, the dimer did not dissociate completely. A small fraction of the native contacts was observed during the rest of the simulation. In contrast to the large C-RMSD fluctuation of the dimer, the tetramer maintained its parallel integrity with remarkably low values of C-RMSD until t 6.0 ns, after which it increased gradually. For the trimer, the magnitudes of the C-RMSD and Qnat were between dimer and tetramer.
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-RMSD is lower than 2.5 Å and at the same time its Qnat is higher or equal to 0.70. Based on these two criteria, the population times of stable and parallel structures were estimated to be 1.30 ns, 3.71 ns, and 6.98 ns, for parallel DFNKF dimer, trimer, and tetramer, respectively. It can be clearly seen that the stabilities of the parallel oligomers were dramatically increased from dimer to tetramer. Overall, the DFNKF oligomers were stabilized with the increase in the number of strands. Moreover, in a 10-ns MD simulation at 300 K (data not shown), the DFNKF tetramer was found to maintain a remarkably stable parallel structure during the entire simulation. These observations suggest that even small oligomers, parallel trimer or tetramer, can act as stable seeds in prompting amyloid fibril formation. Thus, the size of the critical nucleus for enhancing amyloid fibrillization can be quite small. Previous MD simulations of the aggregation mechanism of Aß16–22 amyloid peptide in explicit water (Klimov and Thirumalai, 2003) and the GNNQQNY peptide with the implicit water model (Gsponer et al., 2003) also observed that even a small number of peptides (three) can form in-register structures. These results also support our observations that three or four peptides are stable enough to act as the nucleus for amyloid formation.
The parallel DFNKF oligomers are mainly stabilized by backbone hydrogen bonds, salt bridges, side-chain hydrogen bonds, and --interactions between neighboring chains. The interchain interactions, through which the parallel DFNKF ß-sheet is organized, will be described elsewhere in detail (Haspel et al., unpublished results). Here, we briefly discuss the roles of the more significant interchain interactions stabilizing the parallel DFNKF oligomers. We focus on how the parallel DFNKF oligomers are stabilized by these interactions as their sizes increase. The examination of how an individual interchain interaction affects the stabilities of parallel DFNKF oligomers is discussed in the sequence variation section.
Undoubtedly, backbone hydrogen bonds play an important role in organizing either the parallel or the antiparallel DFNKF ß-sheet. In addition, the side-chain/side-chain and side-chain/N- and side-chain/C-terminal interactions also play important roles in stabilizing the parallel strands (shown in Fig. 2 a). The side chain of Asp forms salt bridges with the ammonium group of the N-terminus of the neighboring chain. Similarly, the longer Lys side chain also forms salt bridges with the carboxyl group at the C-terminus of its adjacent chain. However, these salt bridge stabilizations only exist in the shortened peptides. In the full length peptide, these residues do not have the ability to form these salt bridges. Furthermore, the Asn–Asn side-chain hydrogen bond also forms between neighboring chains. These hydrogen bonding networks hold the parallel DFNKF strands together. In addition to the electrostatic interactions, the hydrophobic --stacking of the Phe aromatic rings also plays an important role in stabilizing these parallel strands. --stacking is well known to play central roles in molecular recognition and self-assembly (Shetty et al., 1996; Sun and Bernstein, 1996). Furthermore, the higher occurrence of aromatic residues in amyloid-related peptides relative to their lower occurrence in proteins (Gazit, 2002b) suggested that --stacking may play an important role in amyloid formation. In particular, in the DFNKF peptide, the aromatic residues constitute 40% of the residues of the whole chain. Similar side-chain interactions were pointed out to be very important in a previous study generating the in-register parallel packing of GNNQQNY ß-strands (Gsponer et al., 2003). ß-helices may form with different residue types; however, the aligned residues in successive ladders are consistently observed to have similar chemical properties. ß-helices have been discussed as a possible fold for amyloids (Wetzel, 2002). Although the short peptides DFNKF studied here cannot form ß-helices, nevertheless, their homotypic side-chain stacking in parallel ß-sheet are similar to ß-helices.
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Dynamics of parallel DFNKF oligomers
Knowledge of the dynamical behavior of the DFNKF oligomers is expected to provide insights into the role of individual residues in stabilizing the DFNKF oligomers. Understanding the structural fluctuation of amyloid fibrils may provide hints for designing drugs to decompose the amyloid fibril targeted at the flexible portion. Here, we probed the dynamical behavior of parallel DFNKF oligomers. Although it does not provide a complete amyloid assembly mechanism, it generates useful information toward the understanding of the amyloid assembly mechanism.
DFNKF monomer conformation and dynamics
To understand the dynamics and stability of the DFNKF oligomers, we first characterized the structure and the dynamical behavior of the DFNKF monomer. The dynamical characteristics of the DFNKF monomer are essential, especially since it serves as a reference in the understanding of the conformational changes in the oligomer simulations. To characterize the conformers of the DFNKF monomer, a 12-ns MD trajectory is generated at 350 K with the same simulation conditions used in the DFNKF oligomer simulations. To avoid the bias imposed on the initial structure, the first 2-ns trajectories were discarded with a total of 10 ns used in the analysis.
To characterize the conformation of the DFNKF monomer, the free energy landscape as a function of the end-to-end distance and the radius of gyration was calculated (Fig. 3). The energy unit is shown in RT (T = 350 K). The end-to-end distance of DFNKF was defined by the distance between the nitrogen atom of the N-terminal ammonium group and the carbon atom of the C-terminal carboxyl group. The radius of gyration was calculated using all the heavy atoms. There are two main basins in Fig. 3. The structures in basin A are the helical-turn/random coil-like states with shorter end-to-end distances and smaller radii of gyration. Those conformations own a higher helical propensity. In contrast, the structures in basin B are extended ß-strand-like states with end-to-end distances of 13 Å. In this simulation, the DFNKF visited basins A and B several times, indicating that the system has reached equilibrium. There is an energy barrier separating basins A and B. The barrier height is slightly higher than the thermal energy. Since there are two populated conformers of the DFNKF monomer that coexist in solution, the process of cross-ß-amyloid fibril formation, which finally converts the non-ß-stranded monomers to the ß-stranded conformation, may undergo a conformation change (e.g., from basin A 
B).
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)) between chains were calculated. Fig. 4 a shows the five residue-wise distances and the cross angle between chains of the DFNKF dimer as a function of simulation time. Only the homogeneous residue-pair interactions between chains (in parallel arrangement) were calculated. In this figure, the ID15-IID15 C-distance increases at t 1 ns, whereas the other residue-pair distances are kept around their in-register parallel distances until t 2.5 ns. At t 5 ns, all residue-wise distances reach their maximal values approximately at the same time. On the other hand, the DFNKF dimer rearranges to the antiparallel-like structure (see Fig. 4 b; the cos() –1); however, the structures are not in-register antiparallel arrangements. Instead, one of the chains forms a helical turn-like structure with similar structures shown in basin A (in Fig. 3). Subsequently, all residue-wise distances reach another minimum with a parallel-like association at 6.5 ns. The DFNKF dimer structure reorganizes from parallel-like to antiparallel-like structures and from antiparallel-like to parallel-like structures in an oscillatory way, but at some time periods the fraction of native contacts is very low.
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) between chains and the average homogeneous residue pair distance (the average distance of five residue pairs used in Fig. 4 a). Several basins (local minima) were characterized: (A) the parallel in-register dimer; (B) parallel dimer with a larger separation between interchain N-/N-termini; (C) parallel dimer, but the separations between the chains are larger; (D) interchain N- and C-termini residues associated with an antiparallel arrangement; (E) one chain in a helical turn-like structure associates with another partially extended chain; and (F) a structure similar to structure E, however, with a more extended strand. The helical turn-like structures identified in basins E and F are similar to the helical turn-like structure characterized in the DFNKF monomer simulations (Fig. 3). The free energy landscape can provide information regarding the DFNKF aggregation pathway and the corresponding barriers. For convenience, the energy scale is shown in RT instead of kcal/mol. These six basins can be further classified as two larger basins. Since there is no clear energy barrier between basins A, B, and C, these three basins can be classified as one basin only (denoted as basin I). Similarly, basins D, E, and F can also be classified as a single basin (denoted as basin II). Conformers within the same larger basins (I and II) can freely convert to each other at RT (T = 350 K). In this simulation, the free energy landscape suggests that the helical turn-like structure (basins E and F) can potentially convert to the parallel ß-stranded dimer (basins A and B) via an intermediate state (basin D) having an antiparallel-like arrangement at 350 K. The largest energy barrier occurs between basins I and II retarding the free interconverting dimers between basins I and II. In this barrier region, the structure adopts a perpendicular interchain arrangement (cos() 0.0 and average residue-wise distance 9 Å). The energy landscape of the DFNKF dimer was established based only on a 10-ns MD simulation at 350 K. Although it provides a protocol for the DFNKF dimer aggregation, the conformational space sampled is limited. A broad conformational sampling of the DFNKF oligomer aggregate using replica-exchange molecular dynamics (REMD) simulation, an effective conformation sampling method, is expected to provide further details of the DFNKF aggregation mechanism (Tsai et al., unpublished results).
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) between chains of the DFNKF trimer. In the early events of the simulation (t = from 0 ns to 3.0 ns), the DFNKF trimer kept its parallel in-register integrity. Subsequently, the partial DFNKF trimer structure fluctuated away from the parallel in-register arrangements indicated by the larger C-C distances. At 4.5 ns, the twist angles between chains (in Fig. 6 c) are 90° as well as the larger separations between IF19-IIF19, IIF19-IIIF19, IK18-IIK18, IIK18-IIIK18, and IID15-IIID15, which indicate that the DFNKF trimer loses its parallel integrity at this period. However, during from t 5.5 ns to t 7.0 ns, the chain-II and chain-III register back to the parallel arrangement denoted by the five smaller pairwise C-C distances as well as the calculated smaller cross angles at this time period. In contrast, the interchain structural characteristics between chain-I and chain-II fluctuate during from t 5.5 ns to t 7.0 ns, especially for the N-/C-terminal residues. By the end of the simulation, the orientation of chain-I with respect to chain-II has a larger deviation from their parallel structure.
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2.0 Å at the early stages of the simulation. From 4.1 ns to 5.6 ns, the structures of chains-II and -III were out-of-register with hydrogen bond distances away from the optimal values. Subsequently, chains-II and -III underwent an aggregation process, and all distances reached parallel in-register structures during the simulation time from 5.6 ns to 7.2 ns. After 7.2 ns, partially out-of-register structures were formed.
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5.6 ns to t 7.2 ns).
The side chain–side chain interactions between chains-II and -III within the trimer are also very interesting. Fig. 8 shows five selected side chain–side chain distances within the simulation time. They include two salt bridges near the C- and N-termini, two aromatic interactions, and one side chain–side chain hydrogen bond. For the salt bridge interactions, the average distance between all possible hydrogen bond donors (e.g., two oxygen atoms at the carboxylate group) and acceptors (e.g., three hydrogen atoms at the 
group) was used. Similar treatments were used to handle the Asn–Asn side-chain hydrogen bonds. Thus, the minimal distances for the salt bridge interactions and Asn–Asn side-chain hydrogen bond are longer than the hydrogen bond distances shown in Fig. 7. The C
-C (for the Phe residues) distances were chosen to represent the relative --interactions. The behavior of these three kinds of side-chain–side-chain interactions are remarkably different. The IIF16–IIIF16 was well packed during the simulation as evidenced by the lower C-C fluctuation. On the other hand, the IIF19–IIIF19 packing has a larger C-C fluctuation. However, the fluctuation decreased after 5.8 ns until the end of the simulation. The Asn–Asn side-chain hydrogen bond frequently broke and quickly reformed within very short time periods. In contrast to the Asn–Asn side-chain hydrogen bond behavior, the salt bridge interaction is very strong and stable once it is formed. Nevertheless, when it is broken, it takes a longer time to reform. This is clearly seen in Fig. 8 a for the IID15...IIID15 salt bridge interaction. Similar behavior, but to a lesser extent, was observed for the salt bridge at the C-terminus (Fig. 8 d). For clarity, the durations of the formation of this salt bridge are marked by circles (Fig. 8 d).
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). The intrinsic instability of N- and C-termini residue pairs in the ß-strands as well as the charged IK18-IIK18 pair may provide hints for rational drug design. Target molecules that promote the solubility of N-/C-terminal residues might decompose the cross-ß-amyloid fibril more easily.
DFNKF tetramer dynamics profile
The residue-wise distances and cos() between the chains of the DFNKF tetramer are shown in Fig. 9. To facilitate a comparison, the same scale is used as in Fig. 6 (DFNKF trimer). It is clear that the DFNKF tetramer has a smaller fluctuation as compared to the DFNKF trimer. Until t 6 ns, the entire DFNKF tetramer structure is maintained in its parallel in-register packing. After t 6 ns, the ID15-IID15, IID15-IIID15, IF19-IIF19, and IIF19-IIIF19 distances start fluctuating with larger magnitudes. Nevertheless, the association between chain-III and chain-IV was almost maintained in their parallel in-register packing during the entire simulation. Even though both chains-I and -IV are located at the edges of ß-sheet, their stabilities are different. The initial structure is not a perfect symmetry, resulting in uneven interactions of chains-I and -II. Similar results are also observed for trimer simulation. In contrast to the dimer and trimer simulations, the Lys residues in the tetramer were less flexible. However, the limited simulations do not allow us to assess whether Asn and Phe16 dominate the stability. Further simulations and mutant experiments in vitro are needed.
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-stacking between aromatic Phe residues. The effects of these interactions on the stability of nine-stranded DFNKF systems were examined by mutant studies in previous studies (our unpublished results). Here, we examined the effects of these interactions on the stability of the smaller DFNKF tetramers, with longer timescale MD simulations (10 ns). In addition to the mutant studies of the DFNKF tetramers, capping studies were used to mimic as much as possible the properties of the DFNKF tetramers when the peptides are part of the longer calcitonin sequence and at the same time to screen the salt bridge interactions of the chain termini. For the capping studies, the DFNKF tetramer was capped with a normal Nme and Ace, resulting in a blocked peptide sequence Ace-DFNKF-Nme, where Ace is acetylate and Nme is N-methylamide. In addition, three mutants, DFAKF (designed to probe the role of Asn side-chain hydrogen bond), DANKF (to examine the role of Phe16), and DFNKA (to examine the role of Phe19), were also studied. Each mutant was studied as a tetramer.
Fig. 10 shows the C-RMSD of these DFNKF mutants from their corresponding energy minimized structures with parallel organization. The results for the DFNKF are also plotted in Fig. 10 for comparison. It is clear that the C-RMSDs of all DFNKF mutants as well as the Ace-DFNKF-Nme are larger than the original DFNKF tetramer, indicating that the side-chain interactions we noted above are important and affect the stabilities of the parallel DFNKF oligomers. When the Asn was mutated to Ala, it lost its integrity quickly as evidenced by the remarkably large C-RMSD. The Asn side-chain–side-chain hydrogen bonds (discussed in the dynamics analysis above), even though easily broken, are also easy to reform, and may play an important role in maintaining the parallel DFNKF integrity. Similarly, previous studies also indicated that the glutamines can form a side-chain hydrogen bond network along the fibril axis to stabilize the parallel packing (Bevivino and Loll, 2001).
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-RMSDs of DFNKA tetramers are slightly larger than the original DFNKF tetramer, indicating that this mutant might be only slightly unstable as compared to the original DFNKF tetramer. In contrast, the C-RMSD of the DANKF tetramers is much higher than the wild-type DFNKF tetramer. The parallel integrity of the DANKF tetramers is quickly lost in the simulations. The role of salt bridge interactions are studied by blocking the termini using Ace and Nme. Here, the stronger salt bridge interactions are screened and are replaced by weaker hydrogen bonds. The C-RMSDs of Ace-DFNKF-Nme tetramers are also larger than in the original DFNKF tetramer, indicating that salt bridges do affect the stability of the DFNKF amyloid and showing that the simulations for such a short peptide may make deduction for the full length hCT. Thus, the parallel DFNKF tetramer is stabilized by these two salt bridge interactions. To conclude, the DFNKF salt bridges, side-chain–side-chain hydrogen bonds, and -stacking do contribute to keep the parallel arrangement of the DFNKF oligomers. In particular, the Asn side chain–side chain hydrogen bond plays a significant role in preserving the parallel integrity of DFNKF oligomers. These mutations, which remove specific salt bridges, hydrogen bonds, or hydrophobic interactions, may inhibit the formation of amyloid fibrils. |
CONCLUSIONS AND FUTURE WORK |
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TOPABSTRACTINTRODUCTIONCOMPUTATIONAL METHODSRESULTS AND DISCUSSIONCONCLUSIONS AND FUTURE WORKACKNOWLEDGEMENTSREFERENCES |
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; Kayed et al., 2003). These observations suggest that it is essential to study the stability and dynamics of small amyloid oligomers in detail. In this study, we have explored the stabilities and dynamics of the DFNKF oligomers, which are amyloid-forming peptides derived from the human calcitonin peptide. DFNKF oligomers with parallel arrangement were found to become more stable as the number of strands increases. The DFNKF trimer and tetramer are stable in the parallel arrangement for a sufficient time in the MD simulations, indicating that the size of the crucial nucleus seed for the DFNKF amyloid formation can be quite small. This may explain the rapid formation of the DFNKF amyloid fibrils in experiment, which to date apparently has not been observed for other amyloid peptides. The simulation results also show that the ß-strand acts as a ß-sheet template in prompting other conformers to register in parallel. The process of registration is noncooperative. In general, residues near the N-/C-termini are found to be more flexible, whereas interior residues are relatively more stable. The sequence variant studies indicate that the side chain–side chain interactions including salt bridges, hydrogen bonds, and hydrophobic interactions in the parallel DFNKF oligomers are very important. In particular, the Asn side-chain hydrogen bond was found to be crucial in stabilizing the parallel DFNKF structure.
Here, we employ conventional MD to study small DFNKF oligomers. Although it provides significant insights into the oligomers' stabilities and dynamics, due to the limitations of current computer power and simulation methods, the mechanism of amyloid fibril formation cannot be explored in detail. In an attempt to better address the conformational sampling problem, our group is currently employing a more powerful sampling method, the replica-exchange molecular dynamics (Gnanakaran and Garcia, 2003; Sugita and Okamoto, 2000), to more completely sample the conformational energy surface of the DFNKF oligomers. This should provide more detailed information of the DFNKF aggregation mechanism and energy landscape.
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ACKNOWLEDGEMENTS |
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TOPABSTRACTINTRODUCTIONCOMPUTATIONAL METHODSRESULTS AND DISCUSSIONCONCLUSIONS AND FUTURE WORKACKNOWLEDGEMENTSREFERENCES |
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Submitted on January 19, 2004; accepted for publication March 23, 2004.
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REFERENCES |
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(N-termini), and Lys–COO– (C-termini). The oxygen and nitrogen atoms on side chains forming the interchain hydrogen bonds are shown in red and blue balls, respectively. (b) Side-chain aromatic 
- and 
-angles shows that the conformations within this basin have higher ß-strand content. Representative structures of these two basins are shown along with the free energy landscape. The backbone atoms are shown as thick sticks, whereas the side-chain atoms are presented as thin sticks. The N- and C-termini are denoted by blue and green balls, respectively.
