Electrostatic Interactions between Small Molecules and Peptide Self-Assemblies. Rebekah C. Brooks, Noel Xiang An Li, Anil K. Mehta, and David G.

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1 Electrostatic Interactions between Small Molecules and Peptide Self-Assemblies Rebekah C. Brooks, Noel Xiang An Li, Anil K. Mehta, and David G. Lynn Abstract Structurally unique polymorphs of Aβ aggregates peptides resulting from amyloid precursor protein cleavage are implicated in many diseases, such as Alzheimer s disease and Huntington s disease. Small molecules such as the imaging agents Pittsburgh Compound B, Congo red, and Thioflavin T have been utilized to determine the distinct cross-β architectures of Aβ. Congeners of Aβ(16-22) were used to investigate the role of electrostatics in the binding of these imaging agents to amyloid self-assemblies by integrating molecular dynamics and experimental analysis. Molecular dynamics studies of a solvated system were performed, each containing an imaging agent and one of three different congeners of Aβ(16-22) with varied charges. These studies, in addition to corresponding in vitro experiments, provide evidence for a significant role of electrostatic interactions between Aβ aggregates and small molecules, providing a method for isolating and investigating driving forces of amyloid folding. Introduction Proteins, directed by their unique primary sequence of amino acids, specifically fold into energetically favorable conformations that allow the protein to efficiently function 2. However, misfolding does occur and can give rise to many diseases 3. Structural changes from misfolding disrupt the native mechanism of the protein 4, which potentially leads to negative effects in the cell or system, such as the down-regulation of a metabolite or a build-up of the malfunctioning protein 5. Increased protein aggregation has been found to be associated with many neurodegenerative diseases. Specifically, the pathogenesis of Alzheimer s disease (AD), Parkinson s disease (PD), Huntington s disease (HD), and amyotrophic lateral sclerosis (ALS) involves the accumulation of misfolded proteins, usually distinguishable by -sheet conformations; these structures are referred to as amyloid 6,7,8,9. In an attempt to understand self-assembling peptides, much attention has recently been directed toward research to characterize some of the dynamic structural forms of amyloid-β (Aβ), focusing on Aβ assembly in differing physical and chemical environments 10. This study investigates the influence of electrostatics in the binding of small molecule imaging agents commonly used for

2 identifying Aβ plaques. A better understanding of specific influencing interactions between imaging agents and amyloid will enable further studies for understanding the structural forms of Aβ. Although accumulation of age-related protein aggregates are found in the central nervous system (CNS) for most diagnosed cases, it has been shown that not all aggregate formations result in disease symptoms 11. Research has also shown that there are many more high-affinity binding sites for the Aβimaging agent Pittsburgh compound B (PiB) on human AD amyloid plaques compared to nonhuman primate plaques, the latter of which are known to contain copious amounts of Aβ without displaying the symptoms of AD 12. By highlighting functional differences between polypeptides differing only in secondary and tertiary structure, researchers could make connections between protein structure and disease. From these studies (what are these? In text citation here), a Figure 1: The peptide sequence, + KLVFFAE, demonstrates the selfassembly of specific oligomers 13. correlation between amyloid structure and its potential for neurotoxicity can be made. This also demonstrates the potential for using a combination of imaging agents uniquely binding to the amyloid to investigate specific structural moieties related to amyloid toxicity. In order to isolate specific moieties within a protein s structure, manipulation of truncated peptide sequences can be performed. For this method, truncated peptides selfassemble into structurally organized systems which provide information about the structure and the ability to analytically characterize the cross-β architecture related to many protein aggregates. Specifically, the peptide sequence Aβ(16-22), residues 16 to 22 of the Aβ peptide associated with AD, forms a bilayer nanotube structure when assembled in acidic conditions 13,14. The hydrophobic core is shielded within the center of the bilayer while the hydrophilic positively charged ends are exposed to the solvent. This structure has been well-characterized by NMR and Figure 2: The amyloid imaging agents CR, ThT, and PiB. CR is negatively charged, ThT is positively charged, and PiB is neutral. microscopy experiments (Figure 1) 13,12. As a seven-residue peptide, Aβ(16-22) is able to form amyloid and is soluble, which allows spectroscopic analysis to easily be performed 15. In addition, slight residue mutations drive changes in the morphology of the self-assemblies 15. This technique is extremely versatile and creates staged environments for analyzing binding energies between the self-assembled structure and small molecules, such as imaging agents.

3 Therefore, the interactions of common amyloid imaging agents, such as PiB 12, Thioflavin T (ThT) 16, and Congo red (CR) 17 (Figure 2), with defined amyloid structures, can be explored. For this study, congeners of Aβ(16-22) were designed to form a peptide nanotube and maintain a certain surface charge: positive, negative, and net neutral. In this manner, the effects of electrostatic interactions between amyloid and imaging agents were isolated. We hypothesized that electrostatics would play a significant role in the binding of the imaging agents to the amyloid. Defining the binding energies of small molecules with amyloid provides a method for isolating and investigating driving forces of amyloid folding. The aim of this research is to describe the binding energies and interactions between the self-assembled peptide structures and small molecules to investigate the role of electrostatics in the binding of these imaging agents to amyloid self-assemblies. This will provide the basis for further studies in using a combination of imaging agents with different binding propensities to determine the molecular structure of amyloids within biological systems. Figure 3: The amyloid imaging agent CR bound to Ac-KLVFFAL-NH 2. Peptide assembly is shown as a Van der Waals surface with the hydrophobic residues colored grey and the positively charged lysine residue colored blue. CR is drawn as sticks with the nitrogens blue, carbons grey, hydrogens white, oxygens red, and sulfur atoms yellow. Results and Discussion Molecular dynamics (MD) simulations provide an approach that explores relevant interactions within a specified in silico environment accomplished by imparting kinetic energy into the system and displaying the motions of the components. Because protein structure has a direct relationship with function, simulations are used to better understand and explore the relevant function of the system, to bind or repel the imaging agent. As a positive control, simulations of a well-defined system were performed. CR (Figure 2) and assemblies of the peptide sequence Ac-KLVFFAL-NH 2 were introduced to an initially neutral solvated environment. The Ac-KLVFFAL-NH 2 assembled surface is positively charged with the positively charged lysine exposed to the solvent. Oriented electron diffraction and linear Figure 4: The amyloid imaging agent ThT bound to Ac-pYLVFFAL-NH 2 (the negatively charged phosphotyrosine is shown in red).

4 dichroism were previously used to define the orientation of CR binding to the surface of Ac-KLVFFAL-NH Simulations were completed with both CR initially placed in the previously characterized binding site, CR lining the surface of the amyloid with the carbonyl backbone parallel to the nanotube s long axis 17, and placed 20 Å away from the peptide surface. When placed in the accepted binding site, CR did not move away from the surface, but did twist in its relative position (Figure 3). With CR set 20 Å away from the peptide surface and within the set 1.2 ns time frame, CR approached the surface of Ac-KLVFFAL-NH 2 and began to bind. Because these simulations highly correlated with the known outcome of previously recorded experimental binding data 17, we were able to perform further simulations with confidence that the simulations would reflect experimental analyses. Peptide Liga nd Binding Groove Transl ated A series of simulations was performed using known small-molecule amyloid imaging agents (Figure 2) combined with congeners of the truncated peptide sequence Aβ(16-22). Models of a positively charged (Ac-KLVFFAL-NH 2 ) and negatively charged (Ac-pYLVFFAL- NH 2 ) peptide were constructed and the binding of a positively charged (ThT), negatively charged (CR), or neutral (PiB) small molecule (Figure 2) was interrogated. Both peptide sequences have been previously assembled and characterized, providing data on their particular architectures and allowing us to construct models of assemblies based on these previous characterization data 18. NMR analysis shows that both the Ac-KLVFFAL- Ac- KLVFFAL -NH 2 CR ThT PiB AcpYLVFFA L-NH 2 CR ThT PiB Ac- KL(terL)F FAE-NH 2 CR ThT PiB Table 1: Results of MD simulations comparing simulations with the imaging agents initially in the known binding site versus 20 Å translated from the surface. Checks imply that binding, or surface attraction, took place while an x implies the surface attraction did not take place. and Ac-pYLVFFAL-NH 2 peptides form anti-parallel out-of-register cross-β architectures. These simulations elucidated a trend related to the electrostatic interactions of the small molecule to the peptide surface (Table 1). The small molecule bound readily to the peptide surface with the opposing charge in both the simulation where the small molecule started within the binding groove and where it translated 20 Å away from the peptide surface (Figure 3, Figure 4). When NH 2 13,12,17 the charged molecule and the surfaces were similarly charged, no binding was observed during the time course of the simulation. Unlike the charged small molecules, PiB bound to both the positively and negatively charged surfaces (Figure 5a,b).

5 To further analyze the binding trend related to the electrostatic landscapes, we modeled a previously characterized peptide surface (Ac-KL(terL)VFFAE-NH 2 ), which self-assembles into the same anti-parallel out-of-register cross-β architecture maintains a net neutral charge due to both a positive and negative charged residue exposed to the solvent 15. Although neither charged molecule was found to bind to the surface of the Ac- KL(terL)FFAE-NH 2 assemblies (Figure 5c), PiB bound effectively with the majority of its interactions between the PiB benzothiazol system and the peptide surface (Figure 5c). Together, these data highlight the importance of electrostatic interactions to binding (Table 1). When the charged small molecule approaches the similarly charged solventexposed residue on the peptide assembly, a significant repulsion overcomes the attraction of other charged residues and prevents the binding of a charged molecule to Ac- KL(terL)FFAE-NH 2. a. b. c. Figure 5: Images of MD simulations showing the binding of PiB to Ac-pYLVFFAL-NH 2 (a), Ac- KLVFFAL-NH 2 (b), and Ac-KLterLFFAE-NH 2 (c). In each image, the negatively charged residues are colored red and the positively charged residues are colored blue. To support the MD simulations, in vitro binding experiments were performed with the same peptide assemblies, Ac-KLVFFAL-NH 2, Ac-pYLVFFAL-NH 2, and Ac- KL(terL)FFAE-NH 2 (Figure 6). It has been shown that ThT displays increased fluorescence when bound to amyloid and has been used in high-throughput screening for analyzing amyloid aggregation in vitro 19. Upon binding to amyloid, a bathochromic shift in the UV-vis λ max for CR is observed and the absorbance increases in intensity. Thus, UV-vis spectroscopy was used for CR binding experiments (Figure 7) and fluorescence spectroscopy was used for ThT binding experiments (Figure 8). A significant increase in absorption of CR was observed in the presence of Ac-KLVFFAL-NH 2 nanotubes, indicating binding of CR to Ac-KLVFFAL-NH 2, but not to Ac-pYLVFFAL-NH 2 (Figure 7). When introduced to a solution of Ac-pYLVFFAL-NH 2, the absorption peak for CR is identical to the absorption peak of CR with no added peptide nanotube. Combined with the MD data, this result is attributed to the electrostatic repulsion between negatively charged CR and the negatively charged Ac-pYLVFFAL-NH 2. Conversely, binding results from the electrostatic attraction between the CR and the positively charged Ac- KLVFFAL-NH 2.

6 Absorbance Fluorescence Intensity Wavelength (nm) Figure 7: UV-vis spectra of CR binding. This shows a CR control (black), Ac-KLVFFAL-NH 2 with CR (blue), and Ac-pYLVFFAL- NH 2 with CR (red) Wavelength (nm) Figure 8: Fluorescence spectra of Thioflavin T binding. This shows ThT (green) binding to Ac- KLVFFAL-NH 2 (blue) and Ac-pYLVFFAL-NH 2 (red). Figure 8 contains the florescence emission spectra for ThT in the presence of Ac- KLVFFAL-NH 2 or Ac-pYLVFFAL-NH 2. Also reflecting the MD data, positively charged ThT only exhibited fluorescence in the presence of negatively charged AcpYLVFFAL-NH 2 and had no significant interaction with the positively charged Ac- KLVFFAL-NH 2 assemblies. Again, the electrostatic interactions between the small molecule and the peptide self-assembly are directly related to their binding energies. Conclusion These results demonstrate that the electrostatic landscape of peptide assemblies directly influences the interaction between charged small molecules and the peptide assembly surface, but has minimal effects on neutral small molecules. PiB binds similarly in each electrostatic environment, leading to the possibility that the benzothiazol system found in PiB is crucial to disease-relevant Aβ binding. As PiB binds to cross-β architecture independent of charge, it may provide a means for characterizing highly charged amyloid. The apparent electrostatic specificity between oppositely charged peptide sequences and imaging agents suggests that combining PiB with charged amyloid specific imaging agents, such as ThT and CR, may provide a method for identifying the surface charge of amyloids leading to a better understanding of the aggregate s surface. Further research should be performed on the binding specificity of a combination of imaging agents on Aβ aggregates, both in vitro and in vivo mouse studies. This approach can now be used to further investigate the distinct structure of Aβ aggregates related to disease pathogenesis. Methods

7 Molecular Dynamics Simulations were performed by first building the system s individual components, which are the peptide assemblies and the small molecules in this case. Minimizations were constrained by the hydrophobic core in MacroModel 20. The system was solvated using neutralized SPC water and an OPLS (Optimized Potentials for Liquid Simulations) force field; also, the box size was fixed in order to achieve periodic boundaries. Small molecules were then introduced to an environment, and the new system was minimized in a 1.2ns time frame at 300 K and atm using the Desmond 21 simulation package. The simulations were visualized using VMD (Visual Molecular Dynamics) 22 and the interactions that took place were analyzed by RMSD (root mean square deviation) and distance moved over time. Specific interactions such as VDW interactions and hydrogen bonding of the small molecule to the self-assembly surface were also evaluated using Maestro. Peptide Synthesis and Assembly The peptide sequences Ac-KLVFFAL-NH 2, Ac-pYLVFFAL-NH 2, and Ac- KL(terL)VFFAE-NH 2 were synthesized 17 and capped at the N- and C-termini with CH 3 CO- and NH 2 using a CEM liberty peptide synthesizer. Purification was performed using reverse phase HPLC with a 40% acetonitrile-water gradient. MALDI-MS was used to confirm the molecular weight and purity of the peptides. The 2.5 mm Ac-KLVFFAL- NH 2 and 2.0 mm Ac-pYLVFFAL-NH 2 were self-assembled in 40% MeCN and 0.1% TFA (ph 2) at 4 o C during an incubation time of 2 weeks for mature assemblies. The peptide assemblies were then titrated to ph 7 with 0.1 M NaOH in 40% MeCN. TEM images were acquired to verify homogeneous assemblies. Binding Studies UV-vis absorption spectra were recorded from 360nm to 600nm for 16 μm CR with 160 μm Ac-KLVFFAL-NH 2 and 160 μm Ac-pYLVFFAL-NH 2 at neutral ph in a 1 cm pathlength cuvette using a Jasco V-530 UV spectrophotometer. A spectrofluorometer was used to evaluate binding studies of 16 μm ThT with 160 μm Ac-KLVFFAL-NH 2 and 160 μm Ac-pYLVFFAL-NH 2. ThT was excited at 455 nm and the fluorescence was recorded from 460 to 600 nm. ThT exhibits an increase of fluorescence at 485 nm when bound to amyloid 16. Solutions containing 16 μm ThT were used in these studies. A control of ThT with no peptide assembly was performed. ThT, at a 1:10 concentration, with Ac-KLVFFAL-NH 2 and Ac-pYLVFFAL-NH 2 exhibited its signature fluorescence when accompanied by Ac-pYLVFFAL-NH 2. Acknowledgements We gratefully acknowledge Allisandra K. Mowles for synthesizing and assembling Ac- KLVFFAL-NH 2, Sha (Lisa) Li for synthesizing and assembling Ac-pYLVFFAL-NH 2, and Rolando Rengifo for his assistance and technical training. We are grateful to

8 Jeannette Taylor and Hong Yi in the Emory Robert P. Apkarian Microscopy Core for TEM advice and training. We also acknowledge Emory University s SURE program and Samford University for their support; the Division of Chemical Sciences, Geosciences, and Biosciences, Office of Basic Energy Sciences of the U.S. Department of Energy through Grant DE-ER15377 for peptide synthesis and structural analyses and acknowledge NSF and the NASA Astrobiology Program, under the NSF Center for Chemical Evolution CHE This work also benefitted from the Howard Hughes Medical Institute (HHMI). References 1. Nelson, D. L.; Cox, M. M., Principles of Biochemistry, Lehninger. Sixth Edition ed. 2. Levinthal, C., Are there pathways for protein folding?. J. Chim. Phys. 1968, 65, Jucker, M.; Walker, L. C., Self-propagation of pathogenic protein aggregates in neurodegenerative diseases. Nature 2013, 501 (7465), Uversky, V. N.; Dunker, A. K., The case for intrinsically disordered proteins playing contributory roles in molecular recognition without a stable 3D structure. F1000 biology reports 2013, 5, Jucker, M.; Walker, L. C., Self-propagation of pathogenic protein aggregates in neurodegenerative diseases. Nature 2013, 501 (7465), Ross, C. A., Poirier, M. A., Protein aggregation and neurodegenerative disease. Nature medicine 2004, 10 Suppl, S Sigurdsson, E. M.; Wisniewski, T.; Frangione, B., Infectivity of amyloid diseases. Trends in molecular medicine 2002, 8 (9), Xing, Y.; Nakamura, A.; Chiba, T.; Kogishi, K.; Matsushita, T.; Li, F.; Guo, Z.; Hosokawa, M.; Mori, M.; Higuchi, K., Transmission of mouse senile amyloidosis. Laboratory investigation; a journal of technical methods and pathology 2001, 81 (4), Liang, Y.; Lynn, D. G.; Berland, K. M., Direct observation of nucleation and growth in amyloid self-assembly. Journal of the American Chemical Society 2010, 132 (18), Childers, W. S.; Anthony, N. R.; Mehta, A. K.; Berland, K. M.; Lynn, D. G., Phase networks of cross-β peptide assemblies. Langmuir : the ACS journal of surfaces and colloids 2012, 28 (15), Levine, H., 3rd; Walker, L. C., Molecular polymorphism of Abeta in Alzheimer's disease. Neurobiology of aging 2010, 31 (4), Anil K. Mehta, R. F. R., W. Seth Childers, John D. Gehman, Lary C. Walker,; Lynn, D. G., Context Dependence of Protein Misfolding and Structural Strains in Neurodegenerative Diseases. Wiley Periodicals, Inc. Biopolymers (Pept Sci) Mehta, A. K.; Lu, K.; Childers, W. S.; Liang, Y.; Dublin, S. N.; Dong, J.; Snyder, J. P.; Pingali, S. V.; Thiyagarajan, P.; Lynn, D. G., Facial symmetry in protein selfassembly. Journal of the American Chemical Society 2008, 130 (30),

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