Letter Cite This: J. Chem. Theory Comput. XXXX, XXX, XXX−XXX
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Modulation of Amyloid-β42 Conformation by Small Molecules Through Nonspecific Binding Chungwen Liang,*,† Sergey N. Savinov,‡,† Jasna Fejzo,¶ Stephen J. Eyles,§ and Jianhan Chen∥,‡
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†
Computational Modeling Core Facility, Institute for Applied Life Sciences (IALS), University of Massachusetts Amherst, Amherst, Massachusetts 01003, United States ‡ Department of Biochemistry and Molecular Biology, University of Massachusetts Amherst, Amherst, Massachusetts 01003, United States ¶ Biomolecular NMR Core Facility, Institute for Applied Life Sciences (IALS), University of Massachusetts Amherst, Amherst, Massachusetts 01003, United States § Mass Spectrometry Core Facility, Institute for Applied Life Sciences (IALS), University of Massachusetts Amherst, Amherst, Massachusetts 01003, United States ∥ Department of Chemistry, University of Massachusetts Amherst, Amherst, Massachusetts 01003, United States S Supporting Information *
ABSTRACT: Aggregation of amyloid-β (Aβ) peptides is a crucial step in the progression of Alzheimer’s disease (AD). Identifying aggregation inhibitors against AD has been a great challenge. We report an atomistic simulation study of the inhibition mechanism of two small molecules, homotaurine and scyllo-inositol, which are AD drug candidates currently under investigation. We show that both small molecules promote a conformational change of the Aβ42 monomer toward a more collapsed phase through a nonspecific binding mechanism. This finding provides atomistic-level insights into designing potential drug candidates for future AD treatments.
N
molecules for blocking Aβ aggregation.20−25 The latter is deemed to be one of the most promising strategies since blocking aggregation has an advantage of not interfering with Aβ production and would not lead to mechanism-based toxicity. However, due to the disordered and dynamic nature of Aβ peptides, the protein−protein binding interfaces in oligomer states lack defined hotspots for pharmacological intervention. Therefore, designing novel small molecule drugs to prevent Aβ self-aggregation is extremely challenging. To date, several small molecules have been proposed and verified on their inhibitory effects on Aβ aggregation.26 Among these candidates, homotaurine (HT) and scyllo-inositol (SI) are naturally occurring, relatively nontoxic, and able to cross the blood-brain barrier (BBB) rapidly. Both compounds are currently under investigation for AD treatments. Although similar in size, the two polar molecules are chemically distinct and are expected to engage different physical contacts with Aβ peptides. While HT is a zwitterion at the physiological pH with a hydrophobic tether separating two charged terminals, SI is a relatively rigid neutral polyol with stacking-capable hydrophobic surfaces and H-bonding-capable edges.
umerous intrinsically disordered proteins (IDPs) are associated with human diseases. However, it is very challenging to target such proteins for medical purposes due to the fact that they generally lack stable and well-defined secondary and/or tertiary structures under physiological conditions. Among these human diseases, Alzheimer’s disease (AD) is the most common neurodegenerative disorder, which causes progressive dementia in older populations.1 The major hypothesis regarding the pathogenesis of AD is the oligomerization/aggregation process of amyloid-β (Aβ) peptides in human brains.2−5 Aβ oligomers have been found to play a critical role in the pathogenesis of AD and established as a promising target for drug development.6−8 Among different forms of Aβ peptides in terms of length (39−43 residues), Aβ42 is the most amyloidogenic one that constitutes neurotoxic oligomeric species due to its strongly intrinsic tendency for self-assembly.9−11 Therefore, understanding the molecular mechanism of aggregation and designing inhibitors to prevent Aβ42 from self-assembly are of great interest for both experimentalists and theorists.12 To design inhibitors preventing the ultimate amyloid formation from Aβ peptides,13 several strategies have been proposed, including compounds targeting Aβ secretases,14,15 immunotherapeutic vaccines,16,17 antibodies,18,19 and small © XXXX American Chemical Society
Received: June 17, 2019 Published: September 2, 2019 A
DOI: 10.1021/acs.jctc.9b00599 J. Chem. Theory Comput. XXXX, XXX, XXX−XXX
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converged within the first 4 and 6 μs, respectively. The calculated NMR chemical shifts and J-coupling constants were compared with the latest experimental NMR data, and their root-mean-square deviations (RMSD) were consistent with a recent simulation study.46 This guarantees the Aβ42 monomer representative structures sampled by the REST method are in good agreement with NMR experiments.47 Then, the propensity to form specific secondary structures (β-strand, turn, coil, and helix, based on the definition of DSSP48) along each Aβ42 residue in three systems is shown in Figure 1. The results reveal that the presence of HT and SI
A Phase III clinical trial of HT was conducted in 2007 and did not achieve its efficacy objectives.27,28 However, a subsequent clinical study on cognitive impairment in a subset of patients showed positive benefits.29 A recent MS and NMR study30 of the antiaggregation mechanism of HT found that the presence of high dosages of HT suppresses Aβ42 oligomerization. Multisite binding of HT onto the Aβ42 αhelical monomer was suggested to be the key mechanism for blocking oligomerization based on short MD simulations. However, a detailed mechanism of how HT disrupts Aβ42 proaggregation conformational states remains unclear. For SI, a Phase II clinical trial demonstrated acceptable safety; however, primary clinical efficacy outcomes were not significant.31 Several studies have shown that incubation of randomly structured Aβ42 with SI induced an immediate secondary structural transition, and SI was found to play a role in stabilizing small Aβ42 oligomers to completely block amyloid fibril formation.32,33 A recent simulation study34 suggested that SI mainly interacts with phenylalanine side chains in the monomeric, disordered aggregate and protofibrillar states of the Aβ (16−22) fragment, which disrupts the lateral stacking of this fragment into amyloid fibrils. However, how SI introduces structural perturbation of the Aβ42 peptide is yet to be investigated. In this Letter, we aim at studying the interaction between Aβ42 and small molecule drugs using atomistic MD simulation. The focus is to understand how they interact with the Aβ42 peptide at the monomer level, and quantify how they modulate the conformational equilibrium of the Aβ42 monomer. Atomistic MD simulation has been applied to study the interaction between small molecule drugs and Aβ peptides extensively.35−37 We leverage an enhanced sampling scheme to adequately and efficiently sample all the significantly populated conformational states of the Aβ42 monomer.38 Specifically, the replica exchange with solute tempering (REST) method39 was employed to perform atomistic MD simulation in explicit solvent using the PLUMED 2.4.3 package40 and GROMACS 2018.41 The CHARMM36m,42 Charmm CGenFF,43 and TIP3P44 models were used to describe the peptide, small molecules, and water, respectively. We note that CHARMM36m has been shown to be one of the most balanced force fields for modeling Aβ systems.45 Three simulations were performed: an additive-free Aβ42 system (as a control group), Aβ42 with HT, and Aβ42 with SI. The concentration of small molecules is chosen to be compatible with a very recent MS/NMR study.30 In each system, 16 replicas were constructed using the starting conformations obtained from previous equilibration NVT simulations at 300 K. The effective temperature of 16 replicas ranges from 300 to 640 K, with the acceptance ratio of 20−29% between neighboring replicas. The production sampling time was 10 μs for each replica (160 μs in total for each system). To our knowledge, these are the most extensive replica exchange simulations of Aβ42 monomer systems reported so far. All other simulation details are described in the Supporting Information. Ensembles of structures sampled at 300 K (total 980,000 snapshots after removing first 200 ns) were then used for all following analyses unless otherwise specified. First, we performed a rigorous sampling convergence check and validation of MD structures by comparing with NMR experimental data (described in the Supporting Information). The results show that the overall secondary structural propensities and the populations of the first top five clusters
Figure 1. Aβ42 monomer secondary structure propensities of forming (a) β-stand, (b) turn, (c) coil, and (d) helix, in Aβ42, Aβ42+HT, and Aβ42+SI systems.
mainly reduces the β-strand propensity of the C-terminus region (I31-A42), while the general structural features in the central hydrophobic cluster (CHC) (L17-A21) and loop (D23-N26) regions remain relatively unperturbed. It is worth noting that the overall β-strand propensity was found to be ∼28% in the additive-free system (Figure S1), which is slightly higher than the β-sheet population (24%) of the pure monomer reported by a CD experiment.49 However, the coil (42%) and helix (1.5%) contents are both underestimated in the present study when compared to the experimental reported values of 67% and 8.7%, respectively.49 To further investigate how small molecules modulate the Cterminus region, a clustering analysis was performed using the Cα atoms of I31-A42 as the structural input. The five highest populated clusters and their corresponding populations in each system are shown in Figure 2. The Gromos clustering method50 was employed using a root-mean-square-deviation (RMSD) cutoff of 2.5 Å to classify total 980,000 frames in the production runs. The results show that the C-terminus region predominantly adopts a slightly kinked strand conformation (the first cluster with a population of 48%) in the absence of small molecule additives. A more collapsed C-shape conformation was found in the fourth cluster (6%). In contrast, in the presence of small molecules, the C-terminus region favors more the C-shape conformation (23% in the first cluster of Aβ42+HT and 20% in the second cluster of Aβ42+SI), while the kinked strand population is largely reduced (20% in the second cluster of Aβ42+HT and 22% in the first cluster of Aβ42+SI). Large population shifts of the kinked strand conformation (from 48% to 20−22%) and the C-shape conformation (from 6% to 20−23%) were found when small B
DOI: 10.1021/acs.jctc.9b00599 J. Chem. Theory Comput. XXXX, XXX, XXX−XXX
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Figure 3. Two-dimensional PMFs that reveal the change of the Aβ42 conformational space in (a) Aβ42, (b) Aβ42+HT, and (c) Aβ42+SI systems.
Figure 2. (a) Five highest populated conformational clusters extracted from Aβ42 (top), Aβ42+HT (middle), and Aβ42+SI (bottom) systems. The C-terminus region is shown as a red (Aβ42), blue (Aβ42+HT), or green (Aβ42+SI) ribbon. The remaining part of the peptide is shown as a gray ribbon. To reveal the quality of clustering, 50 randomly selected structures in each cluster are overlapped. (b) A representative comparison between the kinked strand and C-shape conformations of the C-terminus region.
and shown in Figure 4. A contact is considered whenever the minimal distance between heavy atoms on each Aβ42 residue
molecules interact with Aβ42. This indicates that a significant structural perturbation on the C-terminus region toward a more collapsed state is induced by these small molecules. Several previous studies10,51−54 have highlighted the significance of the C-terminus region in Aβ42 amyloid formation; thus, perturbing its equilibrium conformational distribution may reduce the tendency of Aβ42 for amyloid formation. To further illustrate and quantify the structural modulation of the Aβ42 C-terminus region induced by small molecules, two-dimensional potential of mean force (PMF) plots that reveal the distribution of the C-terminus conformational space were calculated as a function of the end-to-end distance of the C-terminus region and the backbone hydrogen bond number between the C-terminus region and the remainder of the peptide (Figure 3). These plots demonstrate that HT and SI induce significant shifts in Aβ42 conformational populations from an extended state to a more collapsed state, where the end-to-end distance of the C-terminus region decreases approximately from 8 to 3 nm, and the backbone hydrogen bond count is reduced as well from 3 to approximately 1. That is, both small molecules promote the Aβ42 monomer toward more collapsed conformations with smaller end-to-end distance of the C-terminus region and reduced ability for forming backbone hydrogen bonds. It is generally believed that the formation of backbone hydrogen bonding is one of the key factors for promoting/maintaining β-sheet structure of Aβ oligomers.55−58 Therefore, these conformational changes induced by small molecules could hinder Aβ42 oligomerization. To further characterize how small molecules initiate structural modulation on Aβ42, the probability of small molecules contacting with each Aβ42 residue was calculated
Figure 4. Contact probability of HT (a, b) and SI (c, d) as a function of residue number. To determine whether a residue has a contact with small molecules, either only the Aβ42 backbone heavy atoms (a, c) or backbone and side chain heavy atoms (b, d) were used. Contact probabilities for interaction with the sulfate and amino groups of HT and the hydroxyl group of SI are indicated as red, blue, and green bars, respectively. The molecular structures of HT and SI are shown as the insets.
and those on any of the small molecules is within a cutoff range. For detecting contact with the sulfonate and amino groups of HT, the cutoff distances of 4.0 and 3.2 Å were chosen, respectively. For SI, a cutoff distance of 3.5 Å was used. Summarized in Figure 4, the results show that the negatively charged sulfonate group of HT preferentially contacts with the Aβ42 backbone on residues D1-G9, V24-K28, and G37-G38 (contact probability above 20%). The positively charged amino group of HT, however, mainly interacts with the side chains of aspartic and glutamic acids and the C-terminal carboxylate. C
DOI: 10.1021/acs.jctc.9b00599 J. Chem. Theory Comput. XXXX, XXX, XXX−XXX
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ACKNOWLEDGMENTS The authors thank Dr. Petr Kocis, Alzheon Inc. for useful discussions. The computing was performed on the Pikes cluster housed in the Massachusetts Green High-Performance Computing Center (MGHPCC).
Due to the fact that there are three hydrogen bond acceptors on the sulfonate group, a strong tendency for interacting the Aβ42 backbone N−H group can be expected. For SI, the polyol ring was also found to have a noticeable contact with both the Aβ42 backbone and charged/polar residue side chains. The six hydroxyl groups of SI are then expected to form hydrogen bonds with backbone carbonyl groups. Critically, all interactions were found to be transient and not long-lived. Therefore, both small molecules modulate Aβ42 conformation through a nonspecific binding mechanism. Particularly, the sulfonate group of HT and the hydroxy-rich ring of SI mainly interact with the Aβ42 backbone, which likely play a crucial role in blocking the interstrand backbone hydrogen bond formation. In conclusion, by leveraging an enhanced sampling scheme with extensive atomistic MD simulations, we found that small molecule additives induce a large structural perturbation of the Aβ42 monomer, which leads to a more collapsed state of the Aβ42 C-terminus region. In addition, a nonspecific binding mechanism between small molecules and the Aβ42 backbone was identified. This mechanism reduces the propensity for intramolecular backbone hydrogen bond formation between extended strands of the C-terminus and CHC regions, which is expected to destabilize the β-sheet structure of Aβ aggregates. Considering the majority of Aβ population in plagues is Aβ40, we expect HT and SI play a similar role in disturbing the Aβ40 conformation as well, due to the fact that an NMR study showed that the structural ensembles of Aβ40 and Aβ42 are highly consistent in the solution phase.47 The findings disclosed in the present work will shed light on developing future AD inhibitors by providing critical insights into understanding of the antiaggregation mechanism displayed by the two small-molecule drug candidates at the atomic level. We anticipate that these findings will be exploited further via medicinal chemistry approaches to enhance the interaction between inhibitors derived from these leads and the Aβ42 backbone, which is one of the most promising strategies for targeting such an intrinsically disordered peptide.
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ASSOCIATED CONTENT
S Supporting Information *
The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jctc.9b00599. Detailed description of simulations, convergence check of simulation trajectories, and validation of the simulation results (comparison with NMR data) (PDF)
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AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected]. ORCID
Chungwen Liang: 0000-0001-9721-6411 Jianhan Chen: 0000-0002-5281-1150 Funding
This work is partially supported by the National Institutes of Health (GM114300 to J.C.). Notes
The authors declare no competing financial interest. D
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