Amyloid-Î² peptide interactions with amphiphilic ... - ACS Publications

Subscriber access provided by Kaohsiung Medical University

Amyloid-# peptide interactions with amphiphilic surfactants: electrostatic and hydrophobic effects Nicklas Österlund, Yashraj S. Kulkarni, Agata D. Misiaszek, Cecilia Wallin, Dennis M. Krüger, Qinghua Liao, Farshid Mashayekhy Rad, Jüri Jarvet, Birgit Strodel, Sebastian K.T.S. Wärmländer, Leopold L. Ilag, Shina C. L. Kamerlin, and Astrid GRÄSLUND ACS Chem. Neurosci., Just Accepted Manuscript • DOI: 10.1021/acschemneuro.8b00065 • Publication Date (Web): 23 Apr 2018 Downloaded from http://pubs.acs.org on April 24, 2018

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 15 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

ACS Chemical Neuroscience

Amyloid-β peptide interactions with amphiphilic surfactants: electrostatic and hydrophobic effects Nicklas Österlunda,b, Yashraj S. Kulkarnic, Agata D. Misiaszekc, Cecilia Wallina, Dennis M. Krügerc, Qinghua Liaoc, Farshid Mashayekhy Radb, Jüri Jarveta,d, Birgit Strodele, Sebastian K.T.S. Wärmländera, Leopold L. Ilagb, Shina C.L. Kamerlinc*, Astrid Gräslunda* a

Department of Biochemistry and Biophysics, Arrhenius Laboratories, Stockholm University, 106 91 Stockholm, Sweden. Department of Environmental Science and Analytical Chemistry, Arrhenius Laboratories, Stockholm University, 106 91 Stockholm, Sweden. c Department of Cell and Molecular Biology, Uppsala University, 751 24 Uppsala, Sweden d The National Institute of Chemical Physics and Biophysics, 12618 Tallinn, Estonia e Institute of Complex Systems: Structural Biochemistry, Forschungszentrum Jülich, 52425 Jülich, Germany

b

ABSTRACT: The amphiphilic nature of the amyloid-β (Aβ) peptide associated with Alzheimer’s disease facilitates various interactions with biomolecules such as lipids and proteins, with effects on both structure and toxicity of the peptide. Here, we investigate these peptide-amphiphile interactions by experimental and computational studies of Aβ(1-40) in the presence of surfactants with varying physico-chemical properties. Our findings indicate that electrostatic peptide-surfactant interactions are required for coclustering and structure induction in the peptide and that the strength of the interaction depends on the surfactant net charge. Both aggregation-prone peptide-rich co-clusters and stable surfactant-rich co-clusters can form. Only Aβ(1-40) monomers, but not oligomers, are inserted into surfactant micelles in this surfactant-rich state. Surfactant head group charge is suggested to be important as electrostatic peptide-surfactant interactions on the micellar surface seems to be an initiating step towards insertion. Thus, no peptide insertion or change in peptide secondary structure is observed using a non-ionic surfactant. The hydrophobic peptidesurfactant interactions instead stabilize the Aβ monomer, possibly by preventing self-interaction between the peptide core and Cterminus, thereby effectively inhibiting the peptide aggregation process. These findings give increased understanding regarding the molecular driving forces for Aβ aggregation, and the peptide interaction with amphiphilic biomolecules.

KEYWORDS: Alzheimer’s Disease, Aβ Aggregation, Surfactant interactions, Optical and NMR Spectroscopy, Mass Spectrometry, Molecular Dynamics Simulations chemical properties of different Aβ segments facilitate interactions with many classes of molecules, which in turn can modulate the peptide aggregation behavior by affecting fibril nucleation, elongation, and/or fragmentation.7 Thus, Aβ can specifically bind certain metal ions as well as many organic molecules with different effects on aggregation kinetics and end product formation.8–13 Of special significance to Aβ aggregation in vivo is the interaction with other types of amphiphiles such as polypeptides and lipids, which in addition to modulating Aβ structure and aggregation kinetics may form complex co-aggregates of various kinds.14,15 To investigate the interactions between Aβ and amphiphilic biomolecules we here employ surfactants as simple amphiphile model molecules. Surfactants carry a polar head group of varying chemical properties, typically in combination with a single non-polar hydrocarbon tail. These molecules tend to self-assemble in aqueous solution due to hydrophobic effects, where each surfactant has a characteristic concentration above which micellar structures are spontaneously formed (i.e., the critical micelle concentration: CMC)16

INTRODUCTION Formation of amyloid fibrils involves conversion of destabilized natively folded or intrinsically disordered proteins into large, stable, and highly ordered aggregates, which are in vivo often associated with disease pathology.1 In Alzheimer’s disease (AD), the disease-related amyloidogenic peptide is the 39-43 residue long amyloid-β (Aβ) peptide formed from proteolytic cleavage of the transmembrane amyloid-β precursor protein, which after release from the cell membrane spontaneously assembles into amyloid plaques found extracellularly.2 These plaques are generally considered to be relatively harmless end-products of an aggregation process that involves formation of likely more neurotoxic intermediate globular Aβ oligomers.3–5 The Aβ peptides are amphiphilic in their nature: The Nterminal region is relatively hydrophilic, while the Cterminal part contains mainly hydrophobic amino acid residues (Figure 1A). At pH 7 the average net charge of the Aβ(1-40) peptide is calculated from the pKa values of individual amino acids to be -2.7.6 The varying physico1

ACS Paragon Plus Environment

ACS Chemical Neuroscience 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

Page 2 of 15

Figure 1. Overview of the components of the model systems used in the study. A) Primary sequence of the Aβ(1-40) peptide with charged amino acid residues indicated in bold. The calculated theoretical hydrophobicity of Aβ(1-40)17 is plotted against residue number. Pink regions are very hydrophilic, yellow regions are moderately hydrophobic while orange regions are very hydrophobic. B) Structure and properties of the studied surfactants. Blue boxes indicate positively charged groups, while red boxes indicate negatively charged groups. *Data from Sigma-Aldrich.

Primarily these micelles may be considered as biomembrane mimetics. Lipid membranes have been proposed to be important interaction partners of the Aβ peptide in a biological context and membrane damage may be one of the effects causing neuronal death in the AD brain.18–20A two-step mechanism has been proposed where leakage is first induced by pore formation by oligomeric peptide channels and then precedes into amyloid formation, which disrupts the membrane by mechanical stress.21 Pore formation results in cationic-specific leakage that can be blocked by Zn2+ binding, while the amyloid induced leakage is more general and cannot be blocked by metal binding. Biomembrane surfaces may also serve as nucleation sites for aggregation in solution due to surface catalysis effects and locally increased ionic strength due to charged membrane head groups, which has been shown to be of great importance for amyloid aggregation processes.22–25 Understanding details of the Aβ-surfactant interactions under varying conditions may help understanding the chemical details of this amyloid induced membrane damage. In addition, the insight into hydrophilic and hydrophobic interactions between peptide and amphiphile could be useful in potential drug development against AD. Such interactions show how relatively simple organic compounds may compete with the self-interactions between two Aβ peptides, thereby hindering the disease related peptide selfaggregation. A previous screening study involving biophysical measurements demonstrated some aspects of how small amphiphilic molecules at sub-CMC concentrations can modulate the structural and self-association properties of the Aβ(142) peptide.26 Induction of peptide β-structure and α-helical structure by the amphiphile molecules was found to be associated with aggregation enhancement and retardation, respectively. In the present study we examine in detail how Aβ(1-

40) interacts with selected surfactants carrying non-ionic, zwitterionic and cationic head groups under different concentrations and surfactant/peptide ratios. The results are compared with those of the well-studied anionic sodium dodecyl sulfate (SDS) surfactant. SDS has a negatively charged head group and a similar length of its hydrocarbon tail as our selected surfactants (Figure 1B). Myristyl sulfobetaine (SB3-14) has a negatively charged head group derived from a sulphonate group and therefore structurally very similar to SDS. However, the presence of a positively charged tertiary amine between the negative head group and the hydrocarbon tail gives SB3-14 a molecular net charge of zero in contrast to the negatively net charged SDS molecule. Therefore SB3-14 was chosen as the zwitterionic model surfactant for this study. The shorter version, lauryl sulfobetaine (SB3-12), was also studied. For similar reasons regarding chemical similarity, cetyl trimethylammonium bromide (CTAB) was selected as the cationic model surfactant as it carries the same positively charged tertiary amine group as SB3-14. Dodecyl β-Dmaltoside (DDM), which has a large and highly polar maltoside sugar head group with no permanent charges at pH 7, was selected as a non-ionic model surfactant. Structures and properties (including CMCs) of these surfactants and the anionic SDS surfactant are shown in Figure 1B. The term CMC here means the theoretical CMC of the surfactant alone, i.e. in the absence of Aβ (Figure 1B, Supporting Table S1). Micelle concentrations (cm) are calculated from surfactant concentration (cs) and theoretical CMCs and aggregation numbers (N) according to Equation 1.

c

2


c CMC 1 N

Page 3 of 15 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


Figure 2. CD spectra obtained after titrating different surfactants to 20 µM Aβ(1-40) A) Non-ionic DDM B) zwitterionic SB3-14 and C) cationic CTAB. D-F) Spectral minima in Figures A-C versus surfactant concentration.

RESULTS AND DISCUSSION We here present a battery of biophysical results to give more clear-cut molecular information about the complex interactions between the amphiphilic Aβ peptide and other amphiphilic molecules of cellular relevance, such as biomembranes. We study peptide secondary structure induction below and above the surfactant CMCs, surfactant/peptide coclustering, as well as amyloid aggregation kinetics. In addition, we use native mass spectrometry to follow the peptidesurfactant interactions in the gas phase. We present herein newly developed soft ionization mass spectroscopy protocols where non-covalent interactions between Aβ(1-40) and micelles are preserved in the mass spectrometer from ionization to detection, as has previously been shown for other proteins.27–29 Finally, we apply molecular dynamics simulations to compare Aβ(1-40) interactions with ionic and non-ionic micelles. Here we chose to compare the well-studied anionic SDS surfactant micelle with micelles of our non-ionic model surfactant DDM. The combined results show how the Aβ aggregation and amyloid formation propensities depend on a balance between electrostatic and hydrophobic interactions between the peptide and its immediate environment.

Zwitterionic SB3-14 and cationic CTAB induce secondary structure transitions in the Aβ peptide Figure 2 shows the circular dichroism (CD) spectroscopy titrations of the DDM, SB3-14 and CTAB surfactants to 20 µM Aβ(1-40) peptide, in each case going from below to above the formal surfactant CMC. The Aβ peptide without added surfactant exhibits a mixture of random coil and lefthanded 31-helix.30 Titration with non-ionic DDM does not induce any change in Aβ secondary structure neither below nor above the CMC of DDM (Figures 2A and 2D). In contrast, addition of zwitterionic SB3-14 or cationic CTAB immediately induce clear changes in Aβ secondary structure (Figures 2B and 2C), similar to those previously reported for the Aβ-SDS interaction.31 Addition of zwitterionic SB3-14 to Aβ at concentrations below the CMC leads to a slight increase in the random coil CD signal, i.e. increased negative ellipticity at 197 nm. Addition of SB3-14 around the CMC induces a transition from a random coil/31-helix structure (spectral minimum at 197 nm)

3



Page 4 of 15

Figure 3. CD spectra of 20 µM Aβ(1-40) in A) a surfactant-free solution and B) in the presence of 1 mM DDM surfactant at varying temperatures. Solid lines are CD spectra of the Aβ peptide at increasing temperatures, while the dotted lines are CD spectra at decreasing temperatures after reaching 80 °C. C) Peptide aggregation kinetics monitored by ThT fluorescence at 37 °C under quiescent conditions in the absence and presence of DDM surfactant. D) Relative signal intensity from Aβ amide cross peaks in the 1H,15N-HSQC spectrum, normalized to the signal intensities of the peptide in absence of DDM surfactant. The red line represents the mean hydrophobicity at each residue in the peptide chain as calculated by the Abraham & Leo method.17 Stars indicate residues not detected even in a surfactant-free Aβ(1-40) sample due to spectral overlap or solvent exchange effects.

the electrostatic effects in the system. This would yield a situation dominated by hydrophobic interactions between the two hydrophobic parts of the peptide, as well as between the peptide and the hydrophobic tail of the surfactant. As the latter is hidden in the interior of the micelle, this would either promote insertion of the peptide into the micelle or induce peptide self-aggregation. CD spectroscopy is relatively insensitive to the difference in these two different β-sheet states (Supporting Figure S6C-D). However, Thioflavin T (ThT) kinetics, the established probe for kinetic amyloid formation32, reveals that increased ionic strength does promote increased amyloid formation, indicating that increased peptide self-interaction in solution is preferred over peptide insertion into the micelle at these conditions (Supporting Figures S2B,S2C) . Cationic CTAB molecules induces a large structural change in the Aβ-peptide even at low concentrations, probably due to favorable electrostatic interactions between the cationic surfactant and the anionic peptide. A mixture of βsheet and α-helical structures is initially observed, but the αhelical content increases upon increased surfactant concentration (Supporting Figure S7C), and clear minima at 208 nm and 222 nm are observed for CTAB additions above the CMC (Figure 2C) which is in agreement with the predicted spectra (Supporting Figure S6A-B). At low micelle:peptide ratios, the 222/208 nm ratio is greater than one, but the nega-

to a β-sheet structure (spectral minimum at 215 nm) (Figures 2B,2E) in agreement with theoretical spectra (Supporting Figure S6). Deconvolution of the experimental spectra also reveal a somewhat higher percentage of β-sheet at this surfactant concentration (Supporting Figure S7). An isodichroic point is observed at 210 nm, indicating a simple two-state coil-sheet transition (Figure 2B). Similar results are obtained for Aβ interactions with SB3-12, which has a shorter hydrophobic tail than SB3-14, and consequently a higher CMC (3 mM). Still, β-sheet structure is only induced upon SB3-12 additions around the surfactant CMC (Supporting Figure S1), indicating the need to form some sort of micelle-like cluster or peptide/surfactant co-cluster for structure induction to occur. Further addition of SB3-14 above the CMC and at micelle:peptide ratios greater than one increases α-helical content in Aβ, as seen by the increase of ellipticity at 208 and 222 nm (Figures 2B, 2E). The CD intensities are low compared to a typical α-helix spectrum (Supporting Figure S6AB), suggesting a mixture of different conformational species, which can also be seen by spectral deconvolution (Supporting Figure S7). A shift from this mixed β-sheet/α-helix state towards the predicted pure β-sheet spectrum is observed upon increasing the ionic strength (Supporting Figure S2A). We interpret this effect in terms of peptide charge shielding, which reduces 4


Page 5 of 15 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

ACS Chemical Neuroscience ogenous systems, such as micelle-like structures. The emission spectra of pyrene features several peaks and the ratio of the third and first vibrational bands (I3/I1) may be used as a marker for increased hydrophobic environment of the pyrene molecule.36

tive ellipticity at 208 nm increases with increasing micelle concentration. As the 208 nm minimum represents the backbone amide π-π* transition which is parallel-polarized relative to the helical axis, the signal is sensitive to changes in helical packing and arrangement.33,34 The 222/208 nm ratio may therefore be interpreted to report on changes in superhelicity due to interactions of different peptides in a peptiderich surfactant-peptide co-cluster. For increased surfactant concentrations, the interacting peptides are arguably dissolved into single monomeric helices. 1 H,15N-HSQC NMR spectra were recorded for Aβ(1-40) in the presence of SB3-14 and CTAB at concentrations above their respective CMC values (Supporting Figures S3 and S4). Neither the presence of SB3-14 or CTAB give rise to new peptide cross peaks in the amide region at these conditions. This is in contrast to the SDS case well above the CMC, where a stable micelle bound α-helical peptide has yielded a well resolved 1H,15N-HSQC spectrum different from the spectrum of the random coil peptide in solution.35 Cross peak intensities are, however, decreased for most residues. The decrease in peak intensity is also proportional to the decrease in peak volume indicating that there is no significant line broadening effect due to increased transverse relaxation in the NMR visible fraction of the peptide. This indicates exchange with an NMR invisible state such as a large peptide-surfactant co-cluster that occurs on a relatively slow time scale for NMR spectroscopy. Non-ionic DDM prevents Aβ aggregation through hydrophobic surfactant-peptide interactions Although no strong structure inducing interactions between the Aβ peptide and DDM micelles can be observed in CD spectroscopy, a temperature ramping experiment shows that the presence of DDM micelles increases the reversibility of the temperature induced peptide aggregation (Figures 3A and 3B). The addition of DDM below or above the CMC furthermore completely abolishes ThT binding and/or increase in fluorescence (Figure 3C). Also, no clear β-sheet signature expected for amyloid aggregates is seen in CD spectroscopy after 48 h of incubation at 37 °C and no fibrils could be detected using atomic force microscopy (AFM) after the before mentioned incubation period (Supporting Figures S8). These results indicate that free DDM molecules as well as DDM micelles can effectively act as chaperones and inhibit amyloid forming aggregation in solution. NMR spectroscopy data suggest that the most hydrophobic parts of the Aβ peptide are the ones that interact most strongly with the DDM surfactant. 1H,15N-HSQC amide spectra of 15N- labeled Aβ(1-40) peptide in the absence and presence of DDM are shown in Supporting Figure S5. Upon addition of DDM surfactant the 1H,15N-HSQC amide peak intensities are decreased most significantly for the hydrophobic residues in the central core and C-terminal parts of the peptide (Figure 3D). The interaction effect is most notable at high surfactant concentrations, well above the CMC, indicating that the hydrophobic core of the micelle is accessible to the peptide.

Figure 4. A) Pyrene fluorescence in the absence (empty symbols) and presence (filled symbols) of the Aβ(1-40) peptide. Pyrene fluorescence is shown for increasing amounts of CTAB, DDM and SB3-14. B) Pyrene fluorescence for Aβ/CTAB and Aβ/SB3-14 are shown in black at varying surfactant concentration. These curves are compared to red curves showing the 215/208 nm CD ratio indicating the presence of β-sheet structure. Specific intermediate states are marked by the symbols † (100 µM CTAB), and * (300 µM SB3-14) C) Amyloid aggregation kinetics for 20 µM Aβ(1-40), as monitored by ThT-fluorescence at 37 °C under quiescent conditions in absence of surfactant (black) and after addition of 1 mM SDS (brown solid), 100 µM CTAB (blue dotted (†)), 300 µM CTAB (purple dotted line), 1 mM CTAB (yellow dotted line), 100 µM SB3-14 (cyan dashed line), 300 µM SB3-14 (green dashed line (*)), and 1 mM SB3-14 (yellow dashed line).

Electrostatic interactions induce peptide-surfactant coclustering, forming aggregation-prone β-sheet structures. Pyrene fluorescence is sensitive to hydrophobic environments, and can be used to probe hydrophobic microheter-

Upon increased surfactant concentration, the I3/I1 ratio increases in a sigmoidal way for all three surfactants in solutions with or without Aβ(1-40) (Figure 4A). The emission 5



Page 6 of 15

Binding of Aβ to membrane mimicking micelles is observed in the gas phase Preservation of micellar structures in the gas phase under gentle ionization conditions was observed in titration experiments where increasing amounts of zwitterionic SB3-14 was added before mass spectrometry (MS) measurements. As can be seen in Supporting Figure S9A the signal intensity for the SB3-14 monomer is increased until reaching a value close to the solution CMC, at which point the intensity reaches a plateau. Reaching surfactant concentrations above the solution CMC also coincides with the appearance of higher molecular weight species (Supporting Figure S9B), which most probably represent surfactant cluster species. Adding Aβ to this micelle solution produces additional MS peaks not seen in the sample of only SB3-14, indicating the formation of large peptide-surfactant co-clusters (Figure 5A). Although both the zwitterionic and non-ionic surfactants form clusters as well as peptide-surfactant co-clusters which could be preserved in the mass spectrometer, a significant difference is observed upon applying collisional activation. The mean charge state in positive ionization mode of the free Aβ(1-40) peptide in 20 mM ammonium acetate solution pH 7.3, without any surfactant added, is measured to be 4.1. Addition of surfactant above the CMC lowers the MS peakintensities for all free peptide species as peptide-surfactant co-clusters of varying sizes are formed. However, the free peptide species that could be measured retain mean charge states close to 4.1 (4.2 upon addition of DDM, 3.8 upon addition of SB3-14), indicating that the free peptides retain a solvent accessibility similar to that without surfactant (Figure 5B). Increasing the collision voltage produces an increasing amount of monomeric species as peptide-surfactant clusters begin to dissociate. In the presence of DDM, most ejected free peptides have 4 or 5 charges, and the mean charge is close to that of the surfactant-free state. However, in the presence of SB3-14, the charge state of Aβ is shifted towards 2 or 3 charges (Figure 5B). This indicates that Aβ in the presence of DDM has the same amount of protonation sites exposed as in a surfactant-free solution, while interactions with SB3-14 make on average two Aβ protonation sites unavailable, perhaps because the peptide is inserted into a micellar structure. The lower charge states of the peptide in presence of SB3-14 compared to DDM might additionally be indicative of a more folded structure38, as is also seen in CD spectroscopy (Figures 2A and 2B). In the previously published NMR-derived model structure of Aβ(1-40) in an SDS micelle, the two positive residues K16 and K28 are partially buried in the interior of the micelle.39 A similar positioning and protection of the peptide inside the zwitterionic micelle is possible. In contrast, the present results suggest that the interaction of Aβ with DDM may occur on the micelle surface, as the peptide charge state is unaffected by the presence of DDM micelles. Without addition of surfactant, Aβ becomes extensively fragmented at collisional energies higher than 20 V (Supporting Figure S10A). Higher charge states generally fragment more easily due to the higher internal energy of those species40, resulting in a shift towards lower charges at higher collisional energies. Upon addition of DDM or SB3-14, lower amounts of fragmentation occur even at higher energies (Supporting Figure S10B), indicating that the surfactant

ratio end plateaus are, however, reached at different concentrations for the different surfactants, namely in the same order as their theoretical CMC values (Supporting Table S1). DDM first, SB3-14 next and CTAB last. All surfactants reach the plateau at lower concentrations than their theoretical CMC values, probably because the hydrophobic pyrene molecule facilitates formation of micelle-like structures by organizing the surfactant molecules around itself. It can also be seen that the presence of Aβ-peptide greatly induces the formation of hydrophobic clusters of CTAB, as the plateau phase is reached at a concentration of around 100 µM (Figure 4A, blue traces), which is only 10% of the theoretical CMC for CTAB. It stands to reason that the strong electrostatic attraction between positive surfactant and negative peptide would favor the formation of co-clusters. Addition of Aβ to zwitterionic SB3-14 has a small effect on clustering (Figure 4A, green traces). The formation of nonionic DDM micelles does not seem to be affected by Aβ at all (Figure 4A, purple traces). When Aβ is added to the charged surfactants, the plateau phases are reached around the concentrations where CD measurements indicate a structural change in the peptide (Figure 4B), suggesting that the formation of co-clusters is correlated to the structural changes in the peptide. The Aβ secondary structure, monitored by CD spectroscopy, moves through a transition state of increased β-sheet content at the pyrene fluorescence plateau. These structures are prone to aggregate into amyloid material, as seen in the kinetic ThT aggregation assays (Figure 4C). This was also confirmed by the increase in β-sheet content indicated by deconvolution of secondary structures from CD spectra after the incubation time (Supporting Figure S7D-E) and fibril formation in corresponding AFM images from the same samples (Supporting Figure S8). The ThT kinetics assay further shows that SB3-14 inhibits amyloid formation at concentrations below the CMC, (Figure 4C, cyan dashed trace). The higher SB3-14 concentrations that induce β-sheet conformations in the CD measurements (Figure 2B, 4C symbol *) allow Aβ to fibrillate, although at a slower rate (Figure 4C, green dashed trace) than in a surfactant-free solution (Figure 4C, black solid trace). CTAB does not affect the Aβ aggregation rates significantly (Figure 4C, blue dotted trace), while anionic SDS promotes aggregation (Figure 4C, red solid trace), which is in line with previous reports on the Aβ-SDS interaction.37 Higher concentrations of SB3-14 as well as CTAB slow down or completely abolish peptide amyloid aggregation, as probed by ThT fluorescence (Figure 4C, yellow dotted line, yellow dashed line). Upon addition of surfactant the final ThT fluorescence intensity is decreased, which might indicate a decrease in formation of ThT-binding material, and/or a decrease of ThT-binding to fibrils due to changes in morphology, and/or a change in ThT fluorescence quantum yield in the bound state. End-point CD spectra and AFM imaging show that there is no formation of β-sheet structure and/or amyloid material for any of the ThT negative conditions (Supporting Figures S7, S8).

6


Page 7 of 15 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


Figure 5. A) Mass spectra of SB3-14 above the CMC of the surfactant in absence of, and upon addition of Aβ(1-40). Arrows indicate peaks that are only observed upon the addition of peptide. B) Intensities for the different charge states of the monomeric Aβ(1-40) peptide at different collisional energies in the absence (top panel) of surfactant and after addition of DDM (middle panel) or SB3-14 (bottom panel). The mean charge of Aβ(1-40) at zero collisional energy without added surfactant is shown as a reference value in the red solid trace. Additionally, the mean peptide charge at each collisional energy and experimental condition is also shown by the red dashed line. C) Arrival time distributions for Aβ monomer (m/z=1082-1084, z = +4) with and without the addition of surfactant above CMC. The negative second derivative is shown above each peak highlighting possible fine structures in the peaks.

the peptide in the gas phase.42,43 Increased drift time indicates increased collisional cross section. However, this relationship is non-trivial and careful calibration is required to obtain exact CCS values.44,45 In this study, we assess only qualitatively how the drift time changes upon addition of surfactant. The drift time profile for the Aβ(1-40) monomer in a surfactant-free ammonium acetate solution shows two distinct distributions, one more compact with a smaller drift time, and one more extended with a longer drift time (Figure 5C). Inspection of the second derivative, commonly used for peak picking in other instrumental analysis methods46–48, suggests that the larger more extended distribution is the result of several overlapping peaks. This fine structure is probably caused by the flexibility and dynamics of the extended Aβ coil structure. Addition of DDM surfactant above CMC does not drastically change the drift times of the monomer. However, the peak width of the more extended structure is decreased. Inspection of the second derivative shows that the signal for some of the substructures are enriched compared to the others, indicating that interactions with DDM stabilizes certain specific Aβ conformations. Addition of SB3-14 further stabilizes compact forms of Aβ, but perhaps more notably induces a large conformation shift with a substantial portion of the peptide population now adopting an even more extended structure (Figure 5C). We interpret this as a structure where

stabilizes Aβ in the gas phase by peptide shielding and/or charge reduction.41 In contrast to a simple surfactant-free ammonium acetate solution where we detect multiple oligomeric peptide states, only monomeric Aβ(1-40) is observed upon addition of surfactant and collisional activation (Supporting Figure S11). This indicates that under our experimental conditions, only monomeric Aβ(1-40) is present and interacts with micelles in the soluble fraction. The increased solvation of Aβ by the surfactants is observed by mass spectrometry as an initial increase in free peptide monomer concentration upon addition of surfactant (Supporting Figure S9A), as well as a surfactant-dependent decrease of various oligomeric peptide species, especially larger oligomers (Supporting Figure S11). This might also be the reason why the random coil signal seen in the CD spectrum initially increases upon addition of small amounts of SB3-14 (Figure 2B), as the solvated oligomeric species have a somewhat more ordered structure than the monomeric Aβ. Electrostatic micelle-peptide interactions change the Aβmonomer conformation in the gas phase Traveling wave ion mobility spectrometry reports on the drift time of ions in a carrier buffer gas when exposed to an electric field. This drift time is related to the charge and the collisional cross section (CCS), and therefore structure, of 7



Page 8 of 15

porting Table S2). The top-ranked cluster representations (where the two starting α-helical structures are considered together) are shown in Figure 6. When the peptide is simulated with an initial random coil structure, it spends most of the simulation time on the micelle surface with the hydrophobic part binding to shallow hydrophobic grooves on the micelle (Figures 6A and 6B). The peptide stays largely disordered during the simulations with both types of micelles. Representative structures of micelle-bound α-helical peptides bound to DDM and SDS micelles are shown in Figures 6C and 6D, respectively. Here we observed that when starting from a helical structure, a kink in the peptide helix at residues 27-28 is formed within the first few steps of the simulation. This behavior is observed also in the “control” simulations. Stabilizing interactions of Aβ(1-40) with the DDM micelle are weaker compared to those observed between the peptide and the SDS micelles. The per-residue binding energy calculations performed using MM/GBSA highlight this difference in the intensities of peptide-micelle interactions (Figure 7). Root mean square deviation (RMSD) calculations show that the Aβ(1-40) peptide in the α-helical form interacts with SDS in a more stable conformation compared to DDM (Supporting Figure S14). The α-helical structure is largely maintained with the bend at residues 27-28 during the simulations with DDM on the µs simulation timescales used here. However, the peptide binds to the micelle in shallow hydrophobic clefts on the surface. Aβ(1-40) interactions with SDS are stronger, with the Aβ helical regions bound to deep hydrophobic grooves in the micelle. The amino acid residues S26, N27, and K28 form a link between the two α-helices, and together with the N-terminal region they are more exposed to the bulk solvent than the rest of the peptide. Despite being solvent-exposed, K28 makes strong electrostatically attractive interactions with the charged SDS head-groups, as do the other positively charged residues R5 and K16. The negatively charged Aβ residues (E3, D7, E11, E22 and D23) make strong electrostatically repulsive interactions with SDS (Figure 7B). The results show a general pattern for the peptide-micelle interactions. The charged and thus hydrophilic N-terminal Aβ region interacts with the charged head-groups of SDS and with the polar atoms of the maltose moiety of DDM, while the hydrophobic core and C-terminal region of the peptide interact with the hydrocarbon tail of the surfactant molecules. Rearrangement of the surfactant molecules according to the conformation of the peptide is often observed. The MD simulations agree with experimental findings on several points. Favorable interactions between the Aβ peptide and the DDM micelle are primarily found within the hydrophobic peptide stretches (Figure 7A), which could also be seen by NMR spectroscopy (Figure 3D). The peptide tends to move toward the DDM micelle surface when inserted into the micelle, as revealed by a comparison between Supporting Figure S13C (starting structure for MD) and Figure 6C (most relevant structure obtained from MD), giving support to the idea that the peptide is relatively surfaceexposed when interacting with DDM. The MD simulations furthermore show that the DDM micelle can rearrange itself to expose hydrophobic surfactant tails on the micelle surface towards the hydrophobic peptide segments. This exemplifies

the peptide extends along the micelle surface and maximizes the amount of favorable electrostatic interactions between the peptide and the micelle. The drift time peak for this more extended form is probably also a sum of several smaller overlapping peaks, given the shape of the second derivative. This would indicate that several slightly different peptide conformations are possible when binding to the micelle. Molecular dynamics simulations of interactions between the Aβ-monomer and micelles The experimental results presented here suggest an intricate balance between Aβ self-interaction and peptide-surfactant interactions, in both cases of electrostatic as well as hydrophobic nature. For further understanding of these interactions we have performed molecular dynamics (MD) simulations on the Aβ(1-40) peptide in the presence of DDM and SDS micelles. Two peptide starting structures were used: an αhelical structure derived from an earlier NMR study of Aβ interacting with SDS micelles (PDB ID 1BA4)49 and a random coil conformation of the peptide created by a 400 ns MD simulation at 300K in water, starting from the above cited NMR structure. Micelle-free control simulations in water were performed for both starting structures (Supporting Figure S12).

Figure 6. Top ranked cluster representations from MD simulations of A) a disordered Aβ(1-40) peptide in complex with a DDM micelle, B) a disordered Aβ(1-40) peptide in complex with an SDS micelle, C) an α-helical Aβ(1-40) peptide in complex with DDM, and D) an α-helical Aβ(1-40) peptide in complex with SDS. The Aβ-peptide is shown in purple ribbon representation, where all the amino acid residues after K16 bearing a hydrophobic sidechain are colored in yellow. The micelles are shown in surface representation, with the carbon atoms shown in white, the oxygen atoms in red and the sulfur atoms in yellow. The peptide runs from the Nterminus (left) to the C-terminus (right) in all panels. For the micelle interaction simulations, the random coil peptide starting structure was placed at the micellar surface (Supporting Figures S13A and S13D, for respectively DDM and SDS micelles). The α-helical starting structure was placed buried inside the micelle in two different ways (Supporting Figures S13B-C, S13E-F). Three independent 1 µs simulations were performed for each starting structure (Sup8


Page 9 of 15

ACS Chemical Neuroscience Surface

Helix

Peptide hydrophobicity

-30

0.5

-40

A

0

Hydrophobicity (arbitrary units)

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

Effective Binding Free Energy (kcal/mol)

1 -20

-20 -30 -40

B 0 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

Residue Number

Figure 7. Effective per residue binding free energy contributions of Aβ(1-40) in complex with A) DDM and B) SDS micelles, as estimated using the MM/GBSA method in Amber16.50,51 The “surface” binding mode refers to the simulations in which unstructured Aβ(1-40) was allowed to bind to the micelle surface. The “helix” binding mode refers to the simulations in which the α-helical form of Aβ(1-40) was buried into the micelle. The red dashed line in panel A represents the mean hydrophobicity in the peptide chain as calculated by the Abraham & Leo method.17

how hydrophobic interactions between peptide and surfactant are still possible even after micelle formation (Figure 3D) and without the peptide being inserted into the micelle. Calculations of theoretical collisional cross sections using the software IMPACT52 show that the Aβ(1-40) peptide interacting on the surface of SDS is significantly more extended than the peptide interacting on the DDM surface (Supporting Table S3), likely due to ionic peptidesurfactant head group interactions, as suggested by the ion mobility data for Aβ(1-40) in the presence of SB3-14 micelles (Figure 5C). This extended surface conformation might be an initiating step towards insertion into the micelle, similar to the carpet model proposed for the membrane interactions of some antimicrobial peptides.53 Comparing the amount of secondary structure in the peptide after the simulations indicate that Aβ in complex with the DDM micelle goes towards lower amounts of αhelix and higher amounts of coil and turn structures, compared to Aβ in complex with SDS (Supporting Table S4). The timescale of these simulations does not allow us to observe the complete transition of the peptide from α-helix to random coil. However, we observe that the peptide moves towards the disordered state, ends up on the surface of the DDM micelle (Figure 6D), and interacts weakly with the hydrophobic parts of the surfactant molecules (Figure 7A). It is thus largely exposed to the solvent, and if the simulations were continued for an infinitely long time, equilibrium would be reached and perhaps the structural change into a random coil, as seen by experimental data, could have been fully captured.

factants, the interactions are completely dominated by strong electrostatic effects which immediately create peptide-surfactant co-clusters. These co-clusters are however significantly less potent seeds for amyloid formation than the co-clusters induced by SDS. This could be because the co-clusters with cationic surfactants are electrostatically linked and represent a more amorphous state compared to the amyloid state. This state is furthermore characterized by organization of Aβ into very stable α-helical structures that are not aggregation prone, even at low surfactant concentration. This could exemplify a strategy to therapeutically disturb the neurotoxic amyloidogenic pathway, for instance by introduction of cationic peptides or other positively charged molecule as anti-amyloid agents.54,55 In the SDS case the electrostatic interactions between the negative Aβ peptide and the negative surfactant molecules are on the contrary energetically unfavorable, which could destabilize the unfolded monomeric peptides and drive them towards an ordered amyloid state where ionic groups could be hidden from the surroundings. Such cellular regions or interaction partners of high negative net charge might therefore be of special interest for AD research. We also show that this unfavorable electrostatic effect is much smaller for the zwitterionic SB3-14 surfactant and completely absent for the non-ionic DDM surfactant. Instead, favorable hydrophobic interactions between surfactant tail and the hydrophobic parts of the peptide stabilize the unfolded monomer, resulting in solvation of oligomers and slower or abolished amyloid aggregation. This type of interaction between Aβ and other cellular hydrophobic compounds, such as certain lipids, chaperones, and even non-chaperone proteins, is undoubtedly very important under normal conditions in vivo to prevent massive aggregation and resulting cell death.56,57 Blocking the selfinteraction of the hydrophobic peptide segments using small hydrophobic compounds could be also considered as a possible therapeutic strategy, especially since our results show significant effects not only on amyloid fibril formation but also on oligomers, which are considered to be the most toxic species. For the zwitterionic surfactant, the apparent competition between the hydrophobic and electrostatic effects

Concluding remarks We have shown that the aggregation behavior and the secondary structure of the Aβ peptide is heavily affected by the introduction of interacting surfactant molecules, with an apparent competition between electrostatic and hydrophobic interactions that often have opposite effects to each other in forming molecular complexes. While monomeric anionic SDS surfactants induce rapid amyloid aggregation37, positive and zwitterionic surfactants have a smaller effect on Aβ aggregation. For cationic sur9



becomes obvious, since micelle formation seems to be needed for formation of β-sheet structure and amyloid fibrils (Figures 2B, 2E, 4C, Supporting Figure S1). One explanation for this could be that the chaperone effect of the hydrophobic tails dominates below the CMC, while micelles formation hides the tails in the micellar core, thus decreasing the relative hydrophobic interactions and increasing the relative electrostatic interactions from the charged micelle surface. This electrostatic effect, perhaps together with an increased crowding effect, could then be enough to induce amyloid formation, like in the SDS case. Amyloid formation is however slower than in the surfactant-free case, as peptide interactions with the hydrophobic surfactant tails are still possible by insertion into the micelle. Our results suggest that surfactant charge is required for peptide insertion and that the interaction strength is related to the amount of net charge. Our MD simulations and experimental work propose that an initiating step for insertion is helical induction and electrostatic peptide-micelle interactions on the micelle surface. Rearrangement of the micelle and exposition of hydrophobic surfactant patches is also suggested before the more hydrophobic parts of the peptide are fully inserted into the micelle core. While Aβ(1-40) is strongly anchored in the negatively charged SDS micelle, giving rise to a completely new set of peaks in the 1H,15N-HSQC amide spectrum, the interaction with zwitterionic SB3-14 is considerably weaker. Even though our results suggest that the peptide is at least partially buried in the zwitterionic micelle, the peptide probably exchanges between the micelle phase and the solution phase, as is suggested from the mixed β-sheet/α-helix features of the CD spectrum at higher surfactant concentrations. The surfactants in this study act as important models for different ionic and hydrophobic environments affecting amyloid formation. However, a real biological membrane has many different physico-chemical properties, such as bilayer thickness, curvature and fluidity, which are not described by our models. Surface curvature, which is significantly larger in micelles compared to a typical biological membrane, has for instance been shown to affect the aggregation of amylin.58 Specific lipid composition and chemistry should also be important for interactions with the Aβ peptide.59,60 Membrane thickness has furthermore also been reported to have an effect on Aβ aggregation and toxicity.61 Such varying properties are certainly important in a real membrane environment. Our findings in this study underline how the interaction between the Aβ peptide and membrane could largely be decided by the net charge of the membrane without considering more complex aspects of cellular membranes. The results suggest that the peptide should interact more strongly with anionic prokaryotic membranes than with eukaryotic membranes, which could be a reason why the peptide has antimicrobial properties.62,63 This net charge dependence would also explain why the Aβ peptide is localized to the inner mitochondrial membrane intracellularly,64 as the inner mitochondrial membrane carries a larger negative net charge than most other eukaryotic membranes due to its prokaryotic origin.65 These negatively charged surfaces

Page 10 of 15

could therefore be considered as possible catalysts for amyloid formation.

MATERIALS AND METHODS Aβ-peptide stock solution Unlabeled and uniformly 15N-labeled lyophilized Aβ(1-40) was bought from Alexotech (Umeå, Sweden), and dissolved in NaOH as previously described.66,67 For electrospray mass spectrometric studies this method was adjusted by exchanging NaOH for volatile NH4OH. Circular dichroism spectroscopy Circular dichroism (CD) spectra were recorded on a Chirascan CD spectrometer (Applied Photophysics, UK) using a quartz cuvette with an optical path length of 2 mm. Acquisitions were made in the spectral region of 190-250 nm with a step size of 1nm and a sampling time of 4 seconds per data point. Measurements were made on samples of 20 µM Aβ(1-40) in 10 mM NaPi, pH 7.3, at 293K under quiescent conditions. Measurements were done both on freshly prepared samples and samples that had been left to incubate under quiescent conditions at 310 K in Eppendorf tubes for 48 hours. CD deconvolution and analysis CD spectra were deconvoluted using the BeStSel method.68 data was analyzed between 190 and 250 nm and Aβ peptide concentration was measured using intrinsic tyrosine absorbance (280 nm) on a NanoDrop Microvolume spectrometer (Thermo Fisher Scientific, USA). Theoretical reference CD spectra were generated for previously published NMR derived Aβ structures using pdb2cd.69 CD spectra were generated for both helical states in solution and in micelles (PDB ID: 2LFM70, 1BA449) and β-sheet states of the monomeric peptide as well as large amyloid aggregates (PDB ID: 2OTK71, 2LMQ72). Atomic Force Microscopy Solid-state atomic force microscopy (AFM) imaging was carried out by a ScanAsyst unit (Bruker Corp., USA) in tapping mode in air with a resolution of 256-256 or 1024-1024 pixels. FASTSCAN-A cantilevers (Bruker Corp., USA) were used. Samples were collected at the end after the CD experiments (above), with an incubation time of 48 hours at +37 °C without agitation, with various combinations of 10 µM Aβ(1-40) and the surfactants DDM, SB3-14, and CTAB. Each sample was diluted two times in Milli-Q water before incubation on a freshly cleaved mica surface for 20 minutes. Excess liquid was removed from the mica substrate, which was washed three times with Milli-Q water and left to air-dry in room temperature. Pyrene fluorescence assay Pyrene in ethanol was added to a final concentration of 1 µM in aqueous samples of 10 mM NaPi, pH 7.3, with and without previous addition of 20 µM Aβ(1-40). Pyrene fluorescence of the samples upon addition of surfactant was recorded at 298K using a Fluorolog-3 spectrofluorometer (Horiba Jobin-Yvon, France). The samples were kept in quartz cuvettes of 4 mm optical path length, and magnetic stirring was employed during the entire measurements. Excitation was done at 335 nm (slit width 5 nm), and emission spectra were recorded between 260 and 410 nm (slit width 2.5 nm). Thioflavin T fluorescence assay A FLUOstar Omega 96-well plate reader (BMG labtech, Germany) was used to monitor the aggregation kinetics of 20 µΜ Aβ(140) together with 40 µM of the fluorescent dye Thioflavin T (ThT) and varying surfactant concentrations in 10mM sodium phosphate buffer, pH 7.3. The sample volume was 100 µL per well, and eight replicates per experimental condition were measured. ThT was excited at 440 nm and emission was measured at 480 nm every

10 ACS Paragon Plus Environment

Page 11 of 15 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


three minutes. The well plate was incubated in the instrument at 310K under quiescent conditions.

ASSOCIATED CONTENT Supporting Information

NMR spectroscopy 1 H,15N-heteronuclear single quantum coherence (HSQC) spectroscopy was performed on 84 µM uniformly labeled 15N-Aβ(1-40) monomer in 20 mM sodium phosphate buffer (pH 7.3). Surfactants were titrated to the peptide samples, and HSQC spectra were recorded at 288K using a 700 MHz Bruker Advance spectrometer with a cryo-probe (upon addition of CTAB and DDM) or a 500 MHz Bruker Advance spectrometer with a cryo-probe (upon addition of SB3-14). The data was processed in Topspin 3.2 (Bruker, USA), and the assignment of the 1H,15N-HSQC spectrum for Aβ(1-40) is known from previous work.73 Mass and ion mobility spectrometry Mass spectra of Aβ(1-40) alone, and in complex with the surfactants, were recorded on a Synapt G2-Si high definition mass spectrometer (Waters Corporation, USA) equipped with a conventional electrospray source, operating in positive ion mode. Working parameters were: injection flow rate 10 µL/min, capillary voltage 2.5 kV, and cone voltage 40 V. The analysis was done in high-resolution mode in the 500-4000 m/z range, using an acquisition rate of 3 s/spectrum. Gas phase ion mobility was measured by activating the instrument’s traveling wave ion guide, using settings of: wave velocity 2000 m/s, wave height 35 V, trap gas 2 ml/min, helium gas 120 ml/min, and IMS gas 80 ml/min. Collision-induced dissociation (CID) experiments were performed to induce disassociation of noncovalent complexes by applying collision energy (CE) in the instruments trap compartment. Data processing was done using Proteowizard MSconvert74, UniDec75, and MZMine 2.76 Molecular Dynamics Simulations All molecular dynamics (MD) simulations performed in this work were based on the solution NMR structure of the Aβ(1-40) peptide in a water-micelle environment (PDB ID: 1BA4)35,77, in complex with SDS and DDM micelles generated using Micelle Maker.78 Multiple configurations of Aβ-micelle complexes comprising of random coil and α-helical forms of the peptide were generated manually using PyMOL version 1.7.2.1.79 All MD simulations were performed with the GPU implementation of the AMBER16 software package.80 The ff14SB81 force field was used to describe Aβ(1-40), while the SDS and DDM molecules were described using the GLYCAM_06j82 force field. All simulations were performed with explicit water molecules using NVT conditions. We performed 3 replicas of 1 µs length each per system, leading to a simulation time of 3 µs per system and 24 µs in total (see Table S2). More details of the system setup and MD simulation are included in the Supporting Information. Subsequent analyses of the MD trajectories were performed using CPPTRAJ.83 Secondary structure analysis of the MD trajectories was performed using the STRIDE algorithm.84 Effective binding free energies of the Aβ peptide to SDS or DDM micelles were calculated using the MM/GBSA per-residue decomposition scheme as implemented in AMBER16.85 Snapshots for this analysis were taken from the MD trajectories in 100 ps intervals. Parameters were taken as recommended, using the generalized Born method (model II)50, i.e. igb = 5, to estimate the polar solvation energy. The root mean square deviation (RMSD) of the backbone atoms of the Aβ peptide was calculated every 100ps using “g_rms” in GROMACS v. 4.6.586,87. Clustering was performed using the method by Daura et al.88 as implemented into GROMACS. A 2.0Å RMSD cut-off was used, based on structures sampled every 1 ns of the simulations.

The Supporting Information is available free of charge on the ACS Publications website. Additional computational methodology. Additional supporting figures: CD spectra of Aβ/SB3-12; CD spectra and ThT aggregation curves of Aβ in presence of SB3-14 at varying ionic strength; NMR spectra of Aβ in presence of surfactants; theoretically calculated CD spectra of some Aβ conformations; deconvoluted CD spectra of Aβ in presence of surfactants with calculated amounts of secondary structure elements; AFM images of Aβ in presence of surfactants after incubation; additional mass spectra of Aβ, surfactant clusters and Aβsurfactant co-clusters; top clusters of control MD simulations in water; initial starting structures of MD simulations. Supporting tables: Theoretical and experimentally obtained CMC values; overview of simulation times; calculated CCS values from MD simulation peptide structures; percentages of various secondary structure elements for MD simulation peptide structures;

AUTHOR INFORMATION Corresponding Authors * Astrid Gräslund: Mailing address: Department of Biochemistry and Biophysics, Stockholm University, SE-10691 Stockholm, Sweden. E-mail: [email protected] * Shina C.L. Kamerlin: Mailing address: Department of Cell and Molecular Biology, Uppsala University, SE-75124 Uppsala, Sweden E-mail: [email protected]

Author Contributions NÖ, LLI, and AG conceived and designed the experiments. NÖ and FMR performed the ion mobility/mass spectrometry experiments, CW performed the NMR and AFM experiments, NÖ performed the other experiments. NÖ, CW, JJ, SKTSW, LLI and AG analyzed the experimental data. YSK, QL, DMK, BS and SCLK designed the computational studies. YSK, ADM and QL performed the computational studies. YSK, ADM, QL, DMK, BS and SCLK analyzed the computational data. NÖ, YSK, SCLK and AG wrote the paper with input from the other authors. Funding This study was supported by grants from the Swedish Research Council to SCLK and AG and the Alzheimer foundation to AG. NÖ and YSK were supported by doctoral fellowships from the Sven and Lilly Lawski foundation.

Notes The authors declare no competing financial interest.

ACKNOWLEDGMENT The authors thank the Swedish National Infrastructure for Computing (SNIC) for the generous allocation of supercomputing resources.

REFERENCES (1) Knowles, T. P. J., Vendruscolo, M., and Dobson, C. M. (2015) The physical basis of protein misfolding disorders. Phys. Today 68, 36–41. (2) Haass, C., and Selkoe, D. J. (1993) Cellular processing of βamyloid precursor protein and the genesis of amyloid β-peptide. Cell.



(3) Haass, C., and Selkoe, D. J. (2007) Soluble protein oligomers in neurodegeneration: Lessons from the Alzheimer’s amyloid β-peptide. Nat. Rev. Mol. Cell Biol. (4) Selkoe, D. J., and Hardy, J. (2016) The amyloid hypothesis of Alzheimer’s disease at 25 years. EMBO Mol. Med. 8, 595–608. (5) Gong, Y., Chang, L., Viola, K. L., Lacor, P. N., Lambert, M. P., Finch, C. E., Krafft, G. A., and Klein, W. L. (2003) Alzheimer’s disease-affected brain: Presence of oligomeric Aβ ligands (ADDLs) suggests a molecular basis for reversible memory loss. Proc. Natl. Acad. Sci. 100, 10417–10422. (6) Moore, D. S. (1985) Amino acid and peptide net charges: A simple calculational procedure. Biochem. Educ. 13, 10–11. (7) Cohen, S. I. A., Linse, S., Luheshi, L. M., Hellstrand, E., White, D. A., Rajah, L., Otzen, D. E., Vendruscolo, M., Dobson, C. M., and Knowles, T. P. J. (2013) Proliferation of amyloid-β 42 aggregates occurs through a secondary nucleation mechanism. Proc. Natl. Acad. Sci. 110, 9758–9763. (8) Wallin, C., Luo, J., Jarvet, J., Wärmländer, S. K. T. S., and Gräslund, A. (2017) The Amyloid-β Peptide in Amyloid Formation Processes: Interactions with Blood Proteins and Naturally Occurring Metal Ions. Isr. J. Chem. 57, 674–685. (9) Abelein, A., Gräslund, A., and Danielsson, J. (2015) Zinc as chaperone-mimicking agent for retardation of amyloid β peptide fibril formation. Proc. Natl. Acad. Sci. 112, 5407–5412. (10) Bieschke, J., Russ, J., Friedrich, R. P., Ehrnhoefer, D. E., Wobst, H., Neugebauer, K., and Wanker, E. E. (2010) EGCG remodels mature α-synuclein and amyloid-β fibrils and reduces cellular toxicity. Proc. Natl. Acad. Sci. 107, 7710–7715. (11) Doig, A. J., and Derreumaux, P. (2015) Inhibition of protein aggregation and amyloid formation by small molecules. Curr. Opin. Struct. Biol. (12) Arosio, P., Vendruscolo, M., Dobson, C. M., and Knowles, T. P. J. (2014) Chemical kinetics for drug discovery to combat protein aggregation diseases. Trends Pharmacol. Sci. (13) Wärmländer, S., Tiiman, A., Abelein, A., Luo, J., Jarvet, J., Söderberg, K. L., Danielsson, J., and Gräslund, A. (2013) Biophysical studies of the amyloid β-peptide: Interactions with metal ions and small molecules. ChemBioChem 14, 1692–1704. (14) Luo, J., Wärmländer, S. K. T. S., Gräslund, A., and Abrahams, J. P. (2016) Cross interactions between the Alzheimer′s disease amyloidβ peptide and other amyloid proteins: a further aspect of the amyloid cascade hypothesis. J. Biol. Chem. 291, 16485-16493. (15) Stewart, K. L., and Radford, S. E. (2017) Amyloid plaques beyond Aβ: a survey of the diverse modulators of amyloid aggregation. Biophys. Rev. 9, 405-419. (16) Cross, T. A., Sharma, M., Yi, M., and Zhou, H. X. (2011) Influence of solubilizing environments on membrane protein structures. Trends Biochem. Sci. 36, 117-125. (17) Abraham, D. J., and Leo, A. J. (1987) Extension of the fragment method to calculate amino acid zwitterion and side chain partition coefficients. Proteins Struct. Funct. Bioinforma. 2, 130–152. (18) Demuro, A., Mina, E., Kayed, R., Milton, S. C., Parker, I., and Glabe, C. G. (2005) Calcium dysregulation and membrane disruption as a ubiquitous neurotoxic mechanism of soluble amyloid oligomers. J. Biol. Chem. 280, 17294–17300. (19) Valincius, G., Heinrich, F., Budvytyte, R., Vanderah, D. J., McGillivray, D. J., Sokolov, Y., Hall, J. E., and Lösche, M. (2008) Soluble amyloid β-oligomers affect dielectric membrane properties by bilayer insertion and domain formation: Implications for cell toxicity. Biophys. J. 95, 4845–4861. (20) Demuro, A., Parker, I., and Stutzmann, G. E. (2010) Calcium signaling and amyloid toxicity in Alzheimer disease. J. Biol. Chem. 285, 12463-12468. (21) Sciacca, M. F. M., Kotler, S. A., Brender, J. R., Chen, J., Lee, D. K., and Ramamoorthy, A. (2012) Two-step mechanism of membrane disruption by Aβ through membrane fragmentation and pore formation. Biophys. J. 103, 702–710. (22) Zhu, M., Souillac, P. O., Ionescu-Zanetti, C., Carter, S. A., and Fink, A. L. (2002) Surface-catalyzed amyloid fibril formation. J. Biol. Chem. 277, 50914–50922. (23) Knight, J. D., and Miranker, A. D. (2004) Phospholipid catalysis of diabetic amyloid assembly. J. Mol. Biol. 341, 1175–1187. (24) Abelein, A., Jarvet, J., Barth, A., Gräslund, A., and Danielsson, J. (2016) Ionic Strength Modulation of the Free Energy Landscape of

Page 12 of 15

Aβ40 Peptide Fibril Formation. J. Am. Chem. Soc. 138, 6893–6902. (25) Meisl, G., Yang, X., Dobson, C. M., Linse, S., and Knowles, T. P. J. (2017) Modulation of electrostatic interactions to reveal a reaction network unifying the aggregation behaviour of the Aβ42 peptide and its variants. Chem. Sci. 8, 4352–4362. (26) Ryan, T. M., Friedhuber, A., Lind, M., Howlett, G. J., Masters, C., and Roberts, B. R. (2012) Small amphipathic molecules modulate secondary structure and amyloid fibril-forming kinetics of Alzheimer disease peptide Aβ1-42. J. Biol. Chem. 287, 16947–16954. (27) Ilag, L. L., Ubarretxena-Belandia, I., Tate, C. G., and Robinson, C. V. (2004) Drug binding revealed by tandem mass spectrometry of a protein-micelle complex. J. Am. Chem. Soc. 126, 14362–14363. (28) Sharon, M., Ilag, L. L., and Robinson, C. V. (2007) Evidence for micellar structure in the gas phase. J. Am. Chem. Soc. 129, 8740–8746. (29) Barrera, N. P., Di Bartolo, N., Booth, P. J., and Robinson, C. V. (2008) Micelles Protect Membrane Complexes from Solution to Vacuum. Science 321, 243–246. (30) Danielsson, J., Jarvet, J., Damberg, P., and Gräslund, A. (2005) The Alzheimer β-peptide shows temperature-dependent transitions between left-handed 31-helix, β-strand and random coil secondary structures. FEBS J. 272, 3938–3949. (31) Wahlström, A., Hugonin, L., Perálvarez-Marín, A., Jarvet, J., and Gräslund, A. (2008) Secondary structure conversions of Alzheimer’s Aβ(1-40) peptide induced by membrane-mimicking detergents. FEBS J. 275, 5117–5128. (32) Levine, H. (1993) Thioflavine T interaction with synthetic Alzheimer’s disease β‐amyloid peptides: Detection of amyloid aggregation in solution. Protein Sci. 2, 404–410. (33) Cooper, T. M., and Woody, R. W. (1990) The effect of conformation on the CD of interacting helices: A theoretical study of tropomyosin. Biopolymers 30, 657–676. (34) Zhou, N. E., Kay, C. M., and Hodges, R. S. (1994) The role of interhelical ionic interactions in controlling protein folding and stability. De novo designed synthetic two-stranded alpha-helical coiled-coils. J. Mol. Biol. 237, 500–512. (35) Shao, H., Jao, S., Ma, K., and Zagorski, M. G. (1999) Solution structures of micelle-bound amyloid β-(1-40) and β-(1-42) peptides of Alzheimer’s disease. J. Mol. Biol. 285, 755–773. (36) Kalyanasundaram, K., and Thomas, J. K. (1977) Environmental Effects on Vibronic Band Intensities in Pyrene Monomer Fluorescence and Their Application in Studies of Micellar Systems. J. Am. Chem. Soc. 99, 2039–2044. (37) Abelein, A., Kaspersen, J. D., Nielsen, S. B., Jensen, G. V., Christiansen, G., Pedersen, J. S., Danielsson, J., Otzen, D. E., and Gräslund, A. (2013) Formation of dynamic soluble surfactant-induced amyloid β peptide aggregation intermediates. J. Biol. Chem. 288, 23518–23528. (38) Dobo, A., and Kaltashov, I. A. (2001) Detection of multiple protein conformational ensembles in solution via deconvolution of charge-state distributions in ESI MS. Anal. Chem. 73, 4763–4773. (39) Jarvet, J., Danielsson, J., Damberg, P., Oleszczuk, M., and Gräslund, A. (2007) Positioning of the Alzheimer Aβ(1-40) peptide in SDS micelles using NMR and paramagnetic probes. J. Biomol. NMR 39, 63–72. (40) Dongré, A. R., Jones, J. L., Somogyi, Á., and Wysocki, V. H. (1996) Influence of peptide composition, gas-phase basicity, and chemical modification on fragmentation efficiency: Evidence for the mobile proton model. J. Am. Chem. Soc. 118, 8365–8374. (41) Reading, E., Liko, I., Allison, T. M., Benesch, J. L. P., Laganowsky, A., and Robinson, C. V. (2015) The Role of the Detergent Micelle in Preserving the Structure of Membrane Proteins in the Gas Phase. Angew. Chemie - Int. Ed. 54, 4577–4581. (42) Wu, C., Siems, W. F., Klasmeier, J., and Hill, H. H. (2000) Separation of isomeric peptides using electrospray ionization/highresolution ion mobility spectrometry. Anal. Chem. 72, 391–395. (43) Bernstein, S. L., Dupuis, N. F., Lazo, N. D., Wyttenbach, T., Condron, M. M., Bitan, G., Teplow, D. B., Shea, J. E., Ruotolo, B. T., Robinson, C. V., and Bowers, M. T. (2009) Amyloid-β 2 protein oligomerization and the importance of tetramers and dodecamers in the aetiology of Alzheimer’s disease. Nat. Chem. 1, 326–331. (44) Shvartsburg, A. A., and Smith, R. D. (2008) Fundamentals of traveling wave ion mobility spectrometry. Anal. Chem. 80, 9689– 9699. (45) Michaelevski, I., Kirshenbaum, N., and Sharon, M. (2010) T-


Page 13 of 15 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


wave Ion Mobility-mass Spectrometry: Basic Experimental Procedures for Protein Complex Analysis. J. Vis. Exp. (46) Susi, H., and Michael Byler, D. (1983) Protein structure by Fourier transform infrared spectroscopy: Second derivative spectra. Biochem. Biophys. Res. Commun. 115, 391–397. (47) Balestrieri, C., Colonna, G., Giovane, A., Irace, G., and Servillo, L. (1978) Second-derivative spectroscopy of proteins. A method for the quantitative determination of aromatic amino acids in proteins. Eur. J. Biochem. 90, 433–440. (48) Goubran, R. A., and Lawrence, A. H. (1991) Experimental signal analysis in ion mobility spectrometry. Int. J. Mass Spectrom. Ion Process. 104, 163–178. (49) Coles, M., Bicknell, W., Watson, R. A., Fairlie, D. P., and Craik, D. J. (1998) Solution structure of amyloid β-peptide(1-40) in a watermicelle environment. Is the membrane-spanning domain where we think it is? Biochemistry 37, 11064–11077. (50) Onufriev, A., Bashford, D., and Case, D. A. (2004) Exploring Protein Native States and Large-Scale Conformational Changes with a Modified Generalized Born Model. Proteins Struct. Funct. Genet. 55, 383–394. (51) D.A. Case, R.M. Betz, W. Botello-Smith, D.S. Cerutti, T.E. Cheatham, III, T.A. Darden, R.E. Duke, T.J. Giese, H. Gohlke, A.W. Goetz, N. Homeyer, S. Izadi, P. Janowski, J. Kaus, A. Kovalenko, T.S. Lee, S. LeGrand, P. Li, C. Lin, T. Luchko, R. Luo, B. Madej, D. M. Y. and P. A. K. M. Y., and Kollman, P. A. (2016) AMBER 16. Univ. California, San Fr. (52) Marklund, E. G., Degiacomi, M. T., Robinson, C. V., Baldwin, A. J., and Benesch, J. L. P. (2015) Collision cross sections for structural proteomics. Structure 23, 791–799. (53) Huang, Y., Huang, J., and Chen, Y. (2010) Alpha-helical cationic antimicrobial peptides: Relationships of structure and function. Protein Cell. 1, 143-152. (54) Ziehm, T., Brener, O., Van Groen, T., Kadish, I., Frenzel, D., Tusche, M., Kutzsche, J., Reiß, K., Gremer, L., Nagel-Steger, L., and Willbold, D. (2016) Increase of Positive Net Charge and Conformational Rigidity Enhances the Efficacy of d -Enantiomeric Peptides Designed to Eliminate Cytotoxic Aβ Species. ACS Chem. Neurosci. 7, 1088–1096. (55) Olubiyi, O. O., Frenzel, D., Bartnik, D., Gluck, J. M., Brener, O., Nagel-Steger, L., Funke, S. A., Willbold, D., and Strodel, B. (2014) Amyloid Aggregation Inhibitory Mechanism of Arginine-rich Dpeptides. Curr. Med. Chem. 21, 1448–1457. (56) Månsson, C., Arosio, P., Hussein, R., Kampinga, H. H., Hashem, R. M., Boelens, W. C., Dobson, C. M., Knowles, T. P. J., Linse, S., and Emanuelsson, C. (2014) Interaction of the molecular chaperone DNAJB6 with growing amyloid-beta 42 (Aβ42) aggregates leads to sub-stoichiometric inhibition of amyloid formation. J. Biol. Chem. 289, 31066–31076. (57) Luo, J., Wärmländer, S. K. T. S., Gräslund, A., and Abrahams, J. P. (2014) Non-chaperone proteins can inhibit aggregation and cytotoxicity of Alzheimer amyloid β peptide. J. Biol. Chem. 289, 27766–27775. (58) Sciacca, M. F. M., Brender, J. R., Lee, D. K., and Ramamoorthy, A. (2012) Phosphatidylethanolamine enhances amyloid fiberdependent membrane fragmentation. Biochemistry 51, 7676–7684. (59) Kakio, A., Nishimoto, S. I., Yanagisawa, K., Kozutsumi, Y., and Matsuzaki, K. (2001) Cholesterol-dependent Formation of GM1 Ganglioside-bound Amyloid β-Protein, an Endogenous Seed for Alzheimer Amyloid. J. Biol. Chem. 276, 24985–24990. (60) Matsuzaki, K., Kato, K., and Yanagisawa, K. (2010) Aβ polymerization through interaction with membrane gangliosides. Biochim. Biophys. Acta - Mol. Cell Biol. Lipids. 1801, 868-877 (61) Korshavn, K. J., Satriano, C., Lin, Y., Zhang, R., Dulchavsky, M., Bhunia, A., Ivanova, M. I., Lee, Y. H., La Rosa, C., Lim, M. H., and Ramamoorthy, A. (2017) Reduced lipid bilayer thickness regulates the aggregation and cytotoxicity of amyloid-β. J. Biol. Chem. 292, 4638– 4650. (62) Soscia, S. J., Kirby, J. E., Washicosky, K. J., Tucker, S. M., Ingelsson, M., Hyman, B., Burton, M. A., Goldstein, L. E., Duong, S., Tanzi, R. E., and Moir, R. D. (2010) The Alzheimer’s diseaseassociated amyloid β-protein is an antimicrobial peptide. PLoS One 5. (63) Kagan, B. L., Jang, H., Capone, R., Teran Arce, F., Ramachandran, S., Lal, R., and Nussinov, R. (2012) Antimicrobial properties of amyloid peptides. Mol. Pharm. 9, 708-717.

(64) Hansson Petersen, C. A., Alikhani, N., Behbahani, H., Wiehager, B., Pavlov, P. F., Alafuzoff, I., Leinonen, V., Ito, A., Winblad, B., Glaser, E., and Ankarcrona, M. (2008) The amyloid β-peptide is imported into mitochondria via the TOM import machinery and localized to mitochondrial cristae. Proc. Natl. Acad. Sci. 105, 13145– 13150. (65) Van Meer, G., Voelker, D. R., and Feigenson, G. W. (2008) Membrane lipids: Where they are and how they behave. Nat. Rev. Mol. Cell Biol. 9, 112-124. (66) Fezoui, Y., Hartley, D. M., Harper, J. D., Khurana, R., Walsh, D. M., Condron, M. M., Selkoe, D. J., Lansbury, P. T., Fink, a L., and Teplow, D. B. (2000) An improved method of preparing the amyloid beta-protein for fibrillogenesis and neurotoxicity experiments. Amyloid 7, 166–178. (67) Danielsson, J., Andersson, A., Jarvet, J., and Gräslund, A. (2006) 15N relaxation study of the amyloid β-peptide: Structural propensities and persistence length. Magn. Reson. Chem. 44, S114-S121. (68) Micsonai, A., Wien, F., Kernya, L., Lee, Y. H., Goto, Y., Refregiers, M., and Kardos, J. (2015) Accurate secondary structure prediction and fold recognition for circular dichroism spectroscopy. Proc Natl Acad Sci U S A, 112, E3095–E3103. (69) Mavridis, L., and Janes, R. W. (2017) PDB2CD: A web-based application for the generation of circular dichroism spectra from protein atomic coordinates. Bioinformatics 33, 56–63. (70) Vivekanandan, S., Brender, J. R., Lee, S. Y., and Ramamoorthy, A. (2011) A partially folded structure of amyloid-beta(1-40) in an aqueous environment. Biochem. Biophys. Res. Commun. 411, 312– 316. (71) Hoyer, W., Gronwall, C., Jonsson, A., Stahl, S., and Hard, T. (2008) Stabilization of a beta-hairpin in monomeric Alzheimer’s amyloid-beta peptide inhibits amyloid formation. Proc Natl Acad Sci U S A 105, 5099–5104. (72) Paravastu, A. K., Leapman, R. D., Yau, W.-M., and Tycko, R. (2008) Molecular structural basis for polymorphism in Alzheimer’s beta-amyloid fibrils. Proc. Natl. Acad. Sci. U. S. A. 105, 18349–54. (73) Danielsson, J., Pierattelli, R., Banci, L., and Gräslund, A. (2007) High-resolution NMR studies of the zinc-binding site of the Alzheimer’s amyloid β-peptide. FEBS J. 274, 46–59. (74) Kessner, D., Chambers, M., Burke, R., Agus, D., and Mallick, P. (2008) ProteoWizard: Open source software for rapid proteomics tools development. Bioinformatics 24, 2534–2536. (75) Marty, M. T., Baldwin, A. J., Marklund, E. G., Hochberg, G. K. A., Benesch, J. L. P., and Robinson, C. V. (2015) Bayesian deconvolution of mass and ion mobility spectra: From binary interactions to polydisperse ensembles. Anal. Chem. 87, 4370–4376. (76) Pluskal, T., Castillo, S., Villar-Briones, A., and Orešič, M. (2010) MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data. BMC Bioinformatics 11, 395. (77) Berman, H. M. (2000) The Protein Data Bank. Nucleic Acids Res. 28, 235–242. (78) Krüger, D. M., and Kamerlin, S. C. L. (2017) Micelle Maker: An Online Tool for Generating Equilibrated Micelles as Direct Input for Molecular Dynamics Simulations. ACS Omega 2, 4524–4530. (79) Schrodinger LLC. (2015) The PyMOL Molecular Graphics System, Version 1.8. (80) D.A. Case W. Botello-Smith, D.S. Cerutti, T.E. Cheatham, III, T.A. Darden, R.E. Duke, T.J. Giese, H. Gohlke, A.W. Goetz, N. Homeyer, S. Izadi, P. Janowski, J. Kaus, A. Kovalenko, T.S. Lee, S. LeGrand, P. Li, C. Lin, T. Luchko, R. Luo, B. Madej, D.M. York, R. M. B., and Kollman, P. A. (2016) AMBER 16. Univ. California, San Fr. (81) Maier, J. A., Martinez, C., Kasavajhala, K., Wickstrom, L., Hauser, K. E., and Simmerling, C. (2015) ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SB. J. Chem. Theory Comput. 11, 3696–3713. (82) Kirschner, K. N., Yongye, A. B., Tschampel, S. M., GonzálezOuteiriño, J., Daniels, C. R., Foley, B. L., and Woods, R. J. (2008) GLYCAM06: A generalizable biomolecular force field. carbohydrates. J. Comput. Chem. 29, 622–655. (83) Roe, D. R., and Cheatham, T. E. (2013) PTRAJ and CPPTRAJ: Software for Processing and Analysis of Molecular Dynamics Trajectory Data. J. Chem. Theory Comput. 9, 3084–3095. (84) Frishman, D., and Argos, P. (1995) Knowledge-based protein



secondary structure assignment. Proteins Struct. Funct. Genet. 23, 566–579. (85) Miller, B. R., McGee, T. D., Swails, J. M., Homeyer, N., Gohlke, H., and Roitberg, A. E. (2012) MMPBSA.py : An Efficient Program for End-State Free Energy Calculations. J. Chem. Theory Comput. 8, 3314–3321. (86) Abraham, M. J., Murtola, T., Schulz, R., Páll, S., Smith, J. C., Hess, B., and Lindahl, E. (2015) GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 1–2, 19–25.

Page 14 of 15

(87) Pronk, S., Páll, S., Schulz, R., Larsson, P., Bjelkmar, P., Apostolov, R., Shirts, M. R., Smith, J. C., Kasson, P. M., van der Spoel, D., Hess, B., and Lindahl, E. (2013) GROMACS 4.5: a highthroughput and highly parallel open source molecular simulation toolkit. Bioinformatics 29, 845–854. (88) Daura, X., Gademann, K., Jaun, B., Seebach, D., van Gunsteren, W. F., and Mark, A. E. (1999) Peptide Folding: When Simulation Meets Experiment. Angew. Chemie Int. Ed. 38, 236–240.


Page 15 of 15 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


For Table of Contents Use Only Amyloid-β peptide interactions with amphiphilic surfactants: elec-trostatic and hydrophobic effects Nicklas Österlund, Yashraj S. Kulkarni, Agata D. Misiaszek, Cecilia Wallin, Dennis M. Krüger, Qinghua Liao, Farshid Mashayekhy Rad, Jüri Jarvet, Birgit Strodel, Sebastian K.T.S. Wärmländer, Leopold L. Ilag, Shina C.L. Kamerlin, Astrid Gräslund


Amyloid-Î² peptide interactions with amphiphilic ... - ACS Publications

Recommend Documents