Solid-State-NMR-Structure-Based Inhibitor Design to Achieve

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Solid-state-NMR-structure-based Inhibitor Design to Achieve Selective Inhibition of the Parallel-in-register #sheet Versus Antiparallel Iowa Mutant #-amyloid Fibrils Qinghui Cheng, and Wei Qiang J. Phys. Chem. B, Just Accepted Manuscript • Publication Date (Web): 23 May 2017 Downloaded from http://pubs.acs.org on May 25, 2017

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The Journal of Physical Chemistry

Solid-state-NMR-structure-based Inhibitor Design to Achieve Selective Inhibition of the Parallel-in-register β-sheet Versus Antiparallel Iowa Mutant β-amyloid Fibrils Qinghui Cheng1, and Wei Qiang1,* 1

Department of Chemistry, the State University of New York at Binghamton,

Binghamton, NY 13902 *

Corresponding Author:

Dr. Wei Qiang, Department of Chemistry, the State University of New York, Binghamton, NY 13902 Email: [email protected]

ACS Paragon Plus Environment


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Abstract Solid-state nuclear magnetic resonance (ssNMR) spectroscopy has been widely applied to characterize the high-resolution structures of β-amyloid (Aβ) fibrils. While these structures provide crucial molecular insights on the deposition of amyloid plaques in Alzheimer’s diseases (AD), ssNMR structures have been rarely used so far as basis for designing inhibitors. It remains a challenge because the ssNMR-based Aβ fibrils structures were usually obtained with sparsely-isotope-labeled peptides with limited experimental constraints, where the structural models, especially the side-chain coordinates showed restricted precision. However, these structural models often possess higher accuracy within the hydrophobic core regions with more well-defined experimental data, which provide potential targets for the molecular design. This work presents an ssNMR-based molecular design to achieve selective inhibition of a particular type of Aβ fibrillar structure, which was formed with the Iowa mutant of Aβ with parallel-in-register β sheet hydrophobic core. The results show that short peptides that mimic the C-terminal β strands of the fibril may have preference in binding to the parallel Aβ fibrils rather than the anti-parallel fibrils, mainly due to the differences in the high-resolution structures in the fibril elongation interfaces. The Iowa mutant Aβ fibrils are utilized in this work mainly as a model to demonstrate the feasibility of the strategy because it is relatively straightforward to distinct the parallel and antiparallel fibril structures using ssNMR. Our results suggest that it is potentially feasible to design structure-selective inhibitors and/or diagnostic agents to Aβ fibrils using ssNMR-based structural models.


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Introduction The aberrant aggregation of β-amyloid (Aβ) peptides into amyloid fibrils is considered as a clinic hallmark of Alzheimer’s disease (AD)1-3. Designing of the amyloid-specific binding agents and inhibitors has been utilized as main strategies for the diagnosis and treatment of AD4-6. However, at the current stage, the molecular design for both purposes require improvement. The abundance of amyloid plaques in AD patients’ brains correlated poorly with the progress of diseases3, 7. Developments of structurally specific binding agents may provide a potential solution to this problem. Furthermore, the therapeutics that reply on the designing of anti-amyloid inhibitors are facing major failure in phase II/III clinic tests2. The Aβ oligomers, rather than mature fibrils, are considered to possess higher levels of neurotoxicity8-12. Given the fact that these oligomers and fibrils might share similar high resolution structures with subtle atomic-level differences13, the molecular design that tends to target the specific Aβ species should also be structure-selective. The solid-state nuclear magnetic resonance (ssNMR) spectroscopy has been applied widely to determine the high-resolution structures of amyloid fibrils and/or oligomers over the past two decades14, 15. The ssNMR-based structural models of Aβ fibrils showed high levels of polymorphisms at atomic resolution16, which raises the question of whether the previous diagnostic agents and/or inhibitors are able to target different fibrillar structures with optimized efficiencies. Such problems may affect the precision of quantification of amyloid plaques in AD patients, or hinder the effects of part of anti-amyloid inhibitors. On the other hand, although the ssNMR spectroscopy has shown major success in solving the fibril structures, it remains unclear whether these structures can be utilized for molecular design. In fact, the structure-based molecular design for amyloid fibrils mainly relies on crystal structures of short segments of Aβ5. The major challenge is that the ssNMR-based high-resolution structures of Aβ fibrils are typically obtained using scattering uniformly isotope-labeled peptides (i.e. only a set of residues are isotopically labeled) with a few recent studies done on uniformly isotope-labeled peptides17-19, where only a limited



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set of structural constraints can be experimentally determined. Therefore, there are usually relatively large root-mean-square deviations (RMSDs) for the reported structures, and especially for the side-chain coordinates. For instances, the published antiparallel and parallel Iowa mutant Aβ fibril structures had all-heavy-atom side-chain RMSDs ~ 1.6 Å (for residues 15-34) and 2.2 Å (for residues 15-40) respectively20, 21, meaning that the precise positions of side chains cannot be predicted within ~ 2 Å, which might jeopardize to the molecular design. We will show in the present work that structure-based inhibitor design for Aβ fibrils may also be achieved using ssNMR-derived structural models. The peptide backbone and side-chain RMSDs for the hydrophobic core segments in the published Aβ fibril structures were usually smaller than the RMSDs for the entire molecules, which was caused by the fact that more experimental constraints were generally available in these regions. It was reasonable to design molecules that target these hydrophobic cores. These regions are always involved in the elongation of fibrils, especially in the seeded fibrillation process22-24. Here we show our strategy in an example of the Iowa mutant of Aβ (Asp23-to-Asn23) fibrils25. Most cases of AD are believed to be sporadic and occur in the aging people, but 1-2% of the disease have been linked to the existence of rare mutations in Aβ sequence, which are typically associated with the early onset familial AD (FAD)26. As one of such examples, the fibril structures formed by the Iowa mutant have been previously determined using ssNMR spectroscopy20, 21, 27, 28. It has been shown that the peptide could form fibrils with both parallel-in-register and anti-parallel β sheet core structures under different conditions. These two fibrils exhibited distinct morphologies in the transmission electron microscopy (TEM) images, where the parallel fibrils showed mainly straight and long filaments and anti-parallel fibrils were typically short and curvy20, 21. The residue-specific registries in the hydrophobic core region can be precisely determined using the PITHIRDs-CT ssNMR, which measures the interstrand distances in β sheet structures29. In addition, seeding procedures have been developed to obtain either parallel or antiparallel fibrils with considerably high homogeneity.


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Based on the published structures in Protein Databank (PDB, 2MPZ for the parallel-in-register fibril and 2LNQ for the anti-parallel fibril20, 21, i.e. Fig. 1), it was clear that the side-chain packing patterns (i.e. known as “steric zipper”) were distinct between these two fibrils. The interface of the antiparallel fibrils was relatively flat with the backbones of N- and C-terminal β strands located roughly within the same plane. This might be caused by the fact that there were additional interactions between the C-terminus and the loop region (e.g. the side-chain interactions between Lys28 Nζ and the C-terminal carboxylic group20) of the peptide to stabilize the planar stacking in the antiparallel fibrils. In parallel fibrils, on the other hand, the repulsion forces from the terminal charges will tend to destabilize the planar stacking. From the molecular design point of view, we expect that the offset in the stacking of parallel fibrils will benefit the binding of short peptides because it generates “grooves” in the elongation interfaces. In addition, the detailed configurations of “hollows” created by the steric zipper within the hydrophobic cores of parallel and anti-parallel fibrils were different. Materials and Methods Molecular Design and Docking. Table 1 shows the sequences of short peptide inhibitor candidates for the initial docking, which mimic either the N- or the C-terminal β-strand segments of Aβ fibrils. Similar strategies of molecular design have been utilized in the inhibitor design based on the crystal structures of Aβ segments5. The lengths of peptides varied from 5 to 8 residues, which considered the fact that the hydrophobic cores for the parallel and antiparallel fibrils were different20, 21

. The N- and C-termini of these inhibitor candidates were capped with acetyl and

amide groups respectively to avoid additional electrostatic interactions to the termini of fibrils, which enhanced the possibility of binding of these candidates to the fibril elongation interfaces. Docking

was

performed

(http://www.swissdock.ch/docking).

using The

the

online

pentamer


SwissDock segments

of

server either


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parallel-in-register Iowa mutant Aβ fibrils (PDB 2MPZ) or antiparallel Aβ fibrils (PDB 2LNQ) were utilized as targets. The coordinates for ligands (i.e. the candidate C-terminal and N-terminal short peptides) were generated using PyMol package. The docking returned 21 binding modes between targets and ligands with the most favorable CHARMM energies. These binding modes were visualized using the UCSF Chimera software and the candidates with high selectivity in terms of the binding to the fibril elongation interfaces of parallel versus antiparallel structures were chosen for the next step. Peptides synthesis and purification. The selected candidates from molecular docking were synthesized using routine solid-phase peptide synthesis and Fmoc chemistry. The Rink Amide Resin was utilized for these syntheses to provide C-terminal amidation, and the N-terminus was acetylated. All peptides were purified with high-performance liquid chromatography (HPLC) with reversed-phase C18 peptide column. The purity was verified using mass spectrometry. The unlabeled and selectively-isotope-labeled Iowa mutant Aβ peptides were kindly provided by the Tycko group. Seeded fibril growth. The Iowa mutant fibrils with either parallel or anti-parallel structures were prepared using the previously published seeding protocols20, 30. Briefly, the parent fibrils, which contained a mixture of both structures, were grown from ~ 100 µM freshly-dissolved Iowa mutant Aβ peptides in 10 mM sodium phosphate buffer (pH 7.4) with one-week quiescent incubation at 4oC. For the antiparallel fibrils, 1% of the parent fibrils were sonicated on ice, mixed with freshly-dissolved peptides and incubated at 4oC for one day. The solution was then filtrated through 0.45µm Nylon syringe filter twice, and a second portion of monomeric peptides were added in and stored at 4oC for no longer than 1 week. For the parallel fibrils, 10% of the parent fibrils were sonicated on ice, mixed with freshly-dissolved peptides and incubated at 4oC for 4 hours to produce the Generation 1 seeded fibrils. The same procedure was repeated for another seven cycles to obtain the homogeneous parallel fibrils (i.e. Generation 8 seeded fibrils).


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Tests of inhibitors for fibrillation kinetics using the Thioflavin-T (ThT) fluorescence assay. The seeded fibrillation kinetics for both the parallel and the anti-parallel Iowa mutant Aβ fibrils in the presence or absence of candidate inhibitors were monitored using ThT fluorescence, which was widely applied to investigate the elongation of amyloid fibrils. All fluorescence kinetic traces were recorded on a Perkin-Elmer LS55 Spectrometer at ambient temperature. The excitation and emission wavelengths were set to 435 nm and 485 nm, respectively. A set of control experiments were performed using ThT fluorescence to ensure that the inhibitor candidates did not form fibrils with a range of concentrations from 1.5 µM to 6.0 µM. For the parallel fibrils, A 20 µL aliquot of fibril solution was sonicated on ice, and diluted with 160 µL sodium phosphate buffer and mixed with 4.0 µL of 1.0 mM freshly-dissolved Aβ peptides in DMSO and 20 µL of 50 µM ThT stock solution. The inhibitor candidates were added to samples with the final concentration 1.5 µM. The measurements on antiparallel fibrils were performed similarly, except that the fibril seed solution was not sonicated but filtered using 0.45 µm Nylon syringe filter before mixing with freshly-dissolved Aβ peptides, ThT and/or inhibitor candidates. Transmission electron microscopy (TEM) imaging. Samples that were utilized for the TEM experiments and the ssNMR measurements were prepared using the following procedures: The parallel fibrils (i.e. the Generation 8 fibril after seeding) were sonicated on ice for 2 minutes and mixed with equal moles of un-sonicated antiparallel fibrils. For the control samples, 10-fold excess of freshly-dissolved Iowa mutant Aβ peptides in DMSO were then added into the mixed seeds. For samples with candidate inhibitors, the same amounts of seeds and fresh Aβ peptides were utilized, and the desired moles of inhibitors were also mixed together. The TEM samples were prepared with both 1.5 µM and 6.0 µM candidate inhibitors, while the ssNMR samples were prepared with 1.5 µM inhibitors. All TEM and ssNMR samples were incubated quiescently for one week at ambient temperature before measurements. The TEM images were recorded on a FEI Morgagni microscope and the samples were prepared with negative staining using uranyl acetate.



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13

C PITHIRDs-CT ssNMR spectroscopy and data analysis.

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13

C PITHIRDs-CT

spectroscopy has been demonstrated to provide quantitative measurements of the interstrand distances, and therefore provides a feasible approach to evaluate the selectivity of the candidate inhibitors. All ssNMR spectra were obtained on a 600 MHz Bruker spectrometer equipped with a 2.5 mm magic-angle-spinning (MAS) triple-resonance probe. The ssNMR samples were prepared using the protocol described in the previous section. After the incubation, the fibrils were pelleted down by ultracentrifugation (100,000 rpm for 30 minutes at 4ºC), followed by overnight freeze-drying. The powder was packed in MAS rotors and re-hydrated with 5.0 µL deionized water. The PITHIRDs-CT experiments were performed with 75 kHz and 55 kHz 1H and

13

C cross polarization radiofrequency (rf) fields respectively, 30 kHz

rotor-synchronized

13

C π pulses, 95 kHz 1H decoupling and 20 kHz MAS frequency.

The pulsed spin locking (PSL) acquisition was applied to enhance the signal-to-noise of spectra31. To quantify the population of parallel and antiparallel fibrils in the presence and absence of candidate inhibitors, we generated the nuclear spin models based on the published PDB coordinates for both parallel and antiparallel Iowa mutant fibrils for the

isotope-labeled

sites (i.e. Ala21-13CH3,

Val18-13CO,

Ala30-13CH3 and

Gly33-13CO). The simulation considered three adjacent Aβ strands with either parallel or antiparallel β sheet structures. The SIMPSON package was then applied to generate 13

C-13C dipolar dephasing curves for these model systems32. The

the simulated experimental

13

C signals from either the control or candidate inhibitor samples were

fit to a linear combination of simulated dephasing data for both parallel and antiparallel fibrils. The best-fit populations of parallel and antiparallel fibrils were obtained with minimum deviation between the experimental and simulated data. Results and Discussion Molecular docking of the C- and N-terminal β-strand mimics. Table 2 summarizes the percentage of interface binding of the candidate inhibitors (i.e. N-terminal and


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C-terminal β-strand mimics) to either parallel or antiparallel fibrils, because this binding mode might potentially block the elongation of fibrils. It is worth noting that we utilized pentamers as targets for docking, which were much shorter than either the parallel or antiparallel seeds in the actual experiments. Therefore, the percentage of interface binding shown in Table 1 may decrease significantly for the actual seeds, because the peptide mimics also showed considerable probabilities to bind to both the top and side surfaces of fibrils as well and these binding probabilities would increase with the longer fibril seeds (i.e. Fig. 2). Only the relative percentage of binding to parallel fibrils versus antiparallel ones may be meaningful. As shown in Table 1, the C-terminal peptide mimics have higher selectivity in binding to parallel fibrils versus antiparallel fibrils These mimics showed 28.6% - 52.4% interface binding to the parallel fibrils, and 0% - 19.0% interface binding to the antiparallel fibrils in general. The N-terminal peptide mimics, on the other hand, showed 19.0% - 61.9% and 19.0% - 42.8% interface binding to parallel and antiparallel fibrils respectively, and therefore relatively low selectivity. When exploring the detailed binding modes for individual inhibitor candidates, one could conclude that the short peptides had high tendency to bind to the top surfaces (indicated by navy blue in Fig. 2) and interfaces (green in Fig. 2) for parallel fibrils, while were more likely to bind to the side surfaces (red in Fig. 2) for antiparallel fibrils. The alignments of side chains in parallel fibrils might provide promising binding sites for the inhibitor candidates on top surfaces, while in antiparallel fibrils, the alternating arrangements of the adjacent Aβ chains formed major “grooves” on the side surfaces. Therefore, it was not surprising that the binding of short peptides showed distinct preferences to these different sites. However, the parallel fibrils showed an additional possible binding site, which was the “grooves” formed by the offset of the stacking of β sheets. Figs. 2A and 2C indicated that a considerable population of inhibitor candidates might bind to this site, which potentially block the seeded fibrillation. Such binding site was not obvious in antiparallel fibrils because the interface was relatively flat (i.e. Figs. 2B and 2D).



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It was also interesting to note that the N-terminal inhibitor candidates had enhanced binding to the antiparallel fibrils. We showed in Fig. S1 (i.e. Supporting Information) the representative binding modes for the 3 N-terminal inhibitor candidates with highest percentage of interface binding, namely N51 (QKLVF), N61 (QKLVFF) and N62 (KLVFFA). It seemed that the binding of these candidates to the loop segment of antiparallel fibril (i.e. segment that includes residues Ala21-Ala30) played important roles, and the side chains of Leu, Val and/or Phe contributed to the binding. These side chains seemed to insert into the hydrophobic pocket created by the side chains of Ala21, Asn23, Asn27 and Ala30 in the antiparallel fibril. However, these peptide mimics showed similar binding percentages to parallel fibrils as well, and therefore little selectivity. Therefore, we chose to study the C-terminal peptide mimics for their potential selectivity to inhibit the elongation of parallel fibrils. ThT fluorescence kinetic measurements on candidates C53, C61 and C62. The kinetics of the seeded fibrillation of parallel and antiparallel fibrils in the presence and absence of C-terminal peptides, monitored by ThT fluorescence, were plotted in Fig. 3. In the absence of candidate inhibitors, both parallel and antiparallel fibrils showed immediate increases of fluorescence emission, which indicated the seeded fibrillation process. In addition, the parallel fibrils grew more rapidly than the antiparallel fibrils (i.e. black traces in Fig. 3A and 3B), which could be explained by the fact that the parallel fibrils were generated using repeated seeding protocol that selected the kinetically favored filaments21, 28. The antiparallel seeds, which were not sonicated, also led to fibrillation when additional freshly-dissolved monomers were added in. Previous TEM work showed that these antiparallel fibrils had the morphology of protofilaments and were likely to represent a metastable state of fibrillation20. The kinetic traces were fit to a bi-exponential growth function in Eq. 133, 34: = + 1 − exp− t + 1 − exp− t (1) with elongation rate constants k1 and/or k2. As shown in Table 3, for some traces, the best-fit rate constants k2, which represented the slow kinetics, were much smaller than k1, and in these cases the fibrillation might only occur through the addition of


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monomeric peptides to seeds. In these cases, the fibril growth kinetics showed a single-exponential behavior, which was consistent to the previously published ThT kinetics studies on the Iowa mutant fibrils27. In other cases, there seemed to be a second mechanism of ThT fluorescence emission where the rate constants were at least one order of magnitude slower. This could either due to the multiple binding modes of the fluorescence dye to fibrils33, or the structural conversions between antiparallel and parallel fibrils20. We compared the fast kinetics rate constants k1 in this study because these were more likely to represent the direct seeding effect in our experimental setup. Table 3 suggested that the C-terminal inhibitor candidates did not have significant inhibition effects to the antiparallel fibrils, but a few of them, such as C53, C61 and C62, were likely to decelerate the elongation of parallel fibrils. Particularly, the candidates C53 (i.e. IGLMV) and C61 (i.e. AIIGLM) showed almost complete elimination of seeded fibrillation when they were added in. The addition of candidate C62 (i.e. IIGLMV) also decreased the k1 value to ~ 10% of the control sample. Overall, most of the C-terminal short peptide mimics seemed to have considerable inhibition effects to the parallel fibrils, except for C51 and C52, which did show relatively lower percentage of interface binding in Table 2. However, we emphasize that the ThT kinetic data does not necessarily correlate quantitatively to the molecular docking results, because the latter only considers the binding energy between targets and ligands in thermostable states, but not the dynamics of the fibril ends, which would play significant roles in the seeded fibrillation kinetics. Based on the ThT fluorescence results, we selected the candidates C53, C61 and C62 to continue with the TEM and ssNMR tests. TEM experiments on the morphological difference between controls and samples with inhibitors. Fig. 4 shows the TEM images of the control, which was prepared in the absence of inhibitor candidates, and samples with the inhibitors C53, C61 and C62 at 1.5 µM and 6.0 µM concentrations. Fig. 4A indicated that the control had mainly straight and long filaments that were consistent with the previously published parallel Iowa mutant Aβ fibrils21. These parallel fibrils showed characteristic rough



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boundaries and the absence of clear periodical twisting. The bulk morphology of fibrils with 1.5 µM inhibitor candidates (i.e. Figs. 4B-D) showed an increased amount of short and curvy filaments, which typically had lengths of a few hundred nanometers (e.g. indicated by the enlarged images in the insets of Figs. 4B-D). These protofilament-like morphologies have been shown in previous works as a feature for the antiparallel Iowa mutant Aβ fibrils20, 28. Therefore, the TEM results suggested that the population of antiparallel fibrils was enhanced with the addition of the inhibitor candidates, confirming the structure-selective inhibition effects to the parallel fibrils. However, it is worth mentioning that the samples shown in Figs. 4B-D were more likely to contain mixtures of both parallel and antiparallel fibrils, because the seeded fibrillation rate for parallel fibrils was at least five times faster than the antiparallel ones. In addition, it was interesting that few fibril was observed when higher concentrations of inhibition candidates were added in. Instead, there seemed to be wiggling protofibrils and/or small amorphous aggregates in the TEM images (i.e. Figs. 4E-G), which were like the morphologies observed in previous works when small-molecule inhibitors were added into fibrils35, 36. This observation suggested that these inhibitor candidates might not only be able decelerate the fibril elongation process, but also destabilize the existing fibrils or seeds when they were added in large abundance. However, the structural selectivity only seemed to occur within certain concentration range of inhibitors. It is possible that the optimized inhibitor concentrations are correlated to the actual concentrations of fibril ends in seeds, as well as the structural and dynamic features of parallel and antiparallel fibril ends. Future works will be performed to investigate such possibilities. The ssNMR PITHIRDs-CT spectroscopy and quantitative analysis of the structure-specific inhibition effects. Fig. 5 shows representative

13

C-PITHIRDs-CT

spectra for the isotope-labeled samples in the control and a sample with the inhibitor candidate C53. Additional ssNMR spectra are provided in Supporting Information. The plots of PITHIRDs dephasing as a function of the dipolar evolution time for all


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samples are displayed in Fig. 6. The plots in Fig. 6D clearly indicated that the control was qualitatively different from all samples with inhibitor candidates, with faster 13C PITHIRDs decay curves for all labeled sites. This result suggested the presence of large population of parallel-in-register β sheet fibrils in the control, which was consistent with the bulk morphology shown in the TEM image (i.e. Fig. 4A). On the other hand, all samples with inhibitor candidates (Figs. 6A-C) showed relatively slower

13

C decay for the labeled sites, which was an indication of the formation of

antiparallel β sheets. The results were also consistent with the antiparallel fibrils because the sites Ala21-CH3 and Ala30-CH3 showed slower decay comparing to Val18-CO and Gly33-CO. In the previously published structure for the antiparallel Iowa mutant Aβ fibrils, the N- and C-terminal β sheets had “i/38-i” and “i/66-i” registries, where Val18 and Gly33 were in the center of β sheets with shorter 13C-13C distances20. To quantify the structural selective inhibition effects of the candidates, we generated the nuclear spin models for the labeled sites based on the published parallel and antiparallel fibrils and simulated the

13

C PITHIRDs dephasing. The best-fit

populations of parallel structure (i.e. the parameter “P” in Fig. 7) were obtained by minimizing the deviation between experimental and simulated dephasing using: = ∑+ ,

)

, ! ∗#$ , %& ∗#'( * )

(2)

, where there were 24 experimental data points for each individual control or sample with inhibitor candidates. The experimental uncertainties - ./0 were estimated from the noises of the corresponding ssNMR spectra. As shown in Fig. 7, the control showed predominantly parallel fibrils, with P = 85 ± 3%, which was consistent with the ThT and TEM results. With the addition of all three inhibitor candidates, the percentage of parallel fibrils decreased significantly. The P values were 26 ± 4%, 35 ± 3% and 30 ± 3% for inhibitors C53, C61 and C62 respectively, meaning that the antiparallel fibrils were the main components in the mixtures. Considering that the seeded fibrillation rate for parallel fibrils was much higher than the antiparallel ones,



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we concluded that the addition of all these candidates preferentially eliminate the seeded fibrillation from the Iowa mutant fibril seeds with parallel-in-register β sheet structures. Conclusion We described here a strategy to design structure-specific inhibitors to eliminate the seeded growth of a parallel β-sheet Iowa mutant Aβ fibril, based on the high-resolution structural models from ssNMR. Although the structural models were obtained with limited experimental constraints, we were able to perform screening on 20 short peptide segments that mimic either the N- or C-terminal β-strands of the fibrils using molecular docking and ThT fluorescence kinetic measurements. The three inhibitor candidates were then tested for their structurally selective inhibition effects using TEM and ssNMR, and the selectivity was confirmed. This initial attempt of ssNMR-structure-based molecular design suggested that the structural models obtained with limited number of constraints might also be utilized as targets. We emphasize that the structural differences in the fibril elongation interfaces between the parallel and antiparallel Iowa mutant fibrils may be significant in terms of the surface flatness, which gave advantages for the selectivity. Similar strategies may be applied to the inhibitor design for 40- versus 42-residue Aβ fibrils18, 19, or different Aβ fibrils derived from AD patients with different clinic histories17, 37. Supporting Information The Supporting Information is available free of charge on the ACS Publication website, including the molecular docking results for representative N-terminal peptide mimics, supplementary ssNMR PITHIRDs-CT spectra and the plots of simulated PITHIRDs-CT decay curves using SIMPSON. Notes The authors declare no competing financial interest. Acknowledgements


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This work is supported by the start-up fund from the Research Foundation of the State University of New York, and the National Science Foundation (MRI0922815). We thank Dr. Robert Tycko for the isotope-labeled Iowa mutant Aβ peptide, as well as the usage of the transmission electron microscope. We also thank Dr. Juergen Schulte for helping to set up the PITHIRDs-CT experiments. References 1.

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Tables Table 1 Candidate peptide sequences for molecular docking.


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Sequencesa

Sequences

C51

Ac-AIIGL-NH2

N51

Ac-QKLVF-NH2

C52

Ac-IIGLM-NH2

N52

Ac-KLVFF-NH2

C53

Ac-IGLMV-NH2

N53

Ac-LVFFA-NH2

C54

Ac-GLMVG-NH2

N54

Ac-VFFAE-NH2

C61

Ac-AIIGLM-NH2

N61

Ac-QKLVFF-NH2

C62

Ac-IIGLMV-NH2

N62

Ac-KLVFFA-NH2

C63

Ac-IGLMVG-NH2

N63

Ac-LVFAAE-NH2

C71

Ac-AIIGLMV-NH2

N71

Ac-QKLVFFA-NH2

C72

Ac-IIGLMVG-NH2

N72

Ac-KLVFFAE-NH2

C81

Ac-AIIGLMVG-NH2

N81

Ac-QKLVFFAE-NH2

a

All peptides were designed with acetylated N-terminus

and amidated C-terminus.

Table 2 Percentages of interface binding modes for individual inhibitor candidates. % to

% to

% to

% to



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

parallela

antiparab

C51

28.6

4.7

C52

28.6

C53

parallel

antipara

N51

42.8

38.1

14.3

N52

33.3

19.0

38.1

0.0

N53

61.9

19.0

C54

33.3

0.0

N54

38.1

19.0

C61

33.3

14.3

N61

42.8

42.8

C62

38.1

19.0

N62

42.8

33.3

C63

38.1

4.7

N63

19.0

23.8

C71

52.4

4.7

N71

57.1

33.3

C72

47.6

19.0

N72

33.3

23.8

C81

38.1

4.7

N81

47.6

33.3

a

the number of interface bindings modes to parallel

fibrils / 21 x 100% b

the number of interface binding modes to antiparallel

fibrils / 21 x 100%

Table 3 Summary of the seeded fibrillation rate constants k1,para

k2,para

k1,anti

k2,anti


Page 20 of 31

Page 21 of 31

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(min-1)a

(min-1)

(min-1)

(min-1)

Control

0.1540 (.0019)

0.0060

0.0342 (.0027)

0.0034

C51

0.1830 (.0034)

0.0039

0.0134 (.0022)

n/a

C52

0.0912 (.0031)

0.0056

0.0224 (.0024)

n/a

C53

0.0027 (.0013)

n/ab

0.0459 (.0031)

n/a

C61

0.0024 (.0013)

n/a

0.0471 (.0035)

0.0146

C62

0.0155 (.0018)

n/a

0.0313 (.0029)

0.0067

C63

0.0596 (.0027)

0.0054

0.0254 (.0026)

0.0041

C71

0.0494 (.0025)

0.0058

0.0281 (.0026)

0.0061

C72

0.0465 (.0033)

0.0052

0.0758 (.0038)

0.0146

a

The rate constants were obtained by fitting the corresponding

ThT fluorescence kinetic curves to Eq. 1, where k1 and k2 indicated faster and slower rate constants in Eq. 1. Uncertainties from bi-exponential fitting were provided for the faster rate constants k1. b

“n/a” indicated k2

Solid-State-NMR-Structure-Based Inhibitor Design to Achieve

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