Elucidating the Aβ42 Anti-Aggregation Mechanism of Action of Tramiprosate in Alzheimer’s Disease: Integrating Molecular Analytical Methods, Pharmacokinetic and Clinical Data
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Amyloid beta (Aβ) oligomers play a critical role in the pathogenesis of Alzheimer’s disease (AD) and represent a promising target for drug development. Tramiprosate is a small-molecule Aβ anti-aggregation agent that was evaluated in phase III clinical trials for AD but did not meet the primary efficacy endpoints; however, a pre-specified subgroup analysis revealed robust, sustained, and clinically meaningful cognitive and functional effects in patients with AD homozygous for the ε4 allele of apolipoprotein E4 (APOE4/4 homozygotes), who carry an increased risk for the disease. Therefore, to build on this important efficacy attribute and to further improve its pharmaceutical properties, we have developed a prodrug of tramiprosate ALZ-801 that is in advanced stages of clinical development. To elucidate how tramiprosate works, we investigated its molecular mechanism of action (MOA) and the translation to observed clinical outcomes.
The two main objectives of this research were to (1) elucidate and characterize the MOA of tramiprosate via an integrated application of three independent molecular methodologies and (2) present an integrated translational analysis that links the MOA, conformation of the target, stoichiometry, and pharmacokinetic dose exposure to the observed clinical outcome in APOE4/4 homozygote subjects.
We used three molecular analytical methods—ion mobility spectrometry–mass spectrometry (IMS–MS), nuclear magnetic resonance (NMR), and molecular dynamics—to characterize the concentration-related interactions of tramiprosate versus Aβ42 monomers and the resultant conformational alterations affecting aggregation into oligomers. The molecular stoichiometry of the tramiprosate versus Aβ42 interaction was further analyzed in the context of clinical pharmacokinetic dose exposure and central nervous system Aβ42 levels (i.e., pharmacokinetic–pharmacodynamic translation in humans).
We observed a multi-ligand interaction of tramiprosate with monomeric Aβ42, which differs from the traditional 1:1 binding. This resulted in the stabilization of Aβ42 monomers and inhibition of oligomer formation and elongation, as demonstrated by IMS–MS and molecular dynamics. Using NMR spectroscopy and molecular dynamics, we also showed that tramiprosate bound to Lys16, Lys28, and Asp23, the key amino acid side chains of Aβ42 that are responsible for both conformational seed formation and neuronal toxicity. The projected molar excess of tramiprosate versus Aβ42 in humans using the dose effective in patients with AD aligned with the molecular stoichiometry of the interaction, providing a clear clinical translation of the MOA. A consistent alignment of these preclinical-to-clinical elements describes a unique example of translational medicine and supports the efficacy seen in symptomatic patients with AD. This unique “enveloping mechanism” of tramiprosate also provides a potential basis for tramiprosate dose selection for patients with homozygous AD at earlier stages of disease.
We have identified the molecular mechanism that may account for the observed clinical efficacy of tramiprosate in patients with APOE4/4 homozygous AD. In addition, the integrated application of the molecular methodologies (i.e., IMS-MS, NMR, and thermodynamics analysis) indicates that it is feasible to modulate and control the Aβ42 conformational dynamics landscape by a small molecule, resulting in a favorable Aβ42 conformational change that leads to a clinically relevant amyloid anti-aggregation effect and inhibition of oligomer formation. This novel enveloping MOA of tramiprosate has potential utility in the development of disease-modifying therapies for AD and other neurodegenerative diseases caused by misfolded proteins.
We have elucidated and characterized the molecular mechanism of action of tramiprosate.
Tramiprosate modulates conformational flexibility of amyloid beta Aβ42, leading to the prevention of oligomer seed formation and thus aggregation.
Translational analysis shows an alignment of the three described molecular effects of Aβ42 with pharmacokinetic and published clinical data.
Alzheimer’s disease (AD) is the most prevalent neurodegenerative disorder, affecting a large number of elderly people worldwide. It is widely accepted that amyloid beta (Aβ) is one of the key pathogenic causes for AD [1, 2]. The level of soluble, non-fibrillar Aβ oligomers in the brain correlates strongly with the severity of the disease [1, 3, 4], suggesting that soluble oligomeric species of Aβ, rather than the fibrillary form within amyloid plaques, likely play a pivotal role in AD pathophysiology.
Aβ peptides, particularly Aβ42, have a strong intrinsic tendency to self-assemble and form aggregates that constitute neurotoxic oligomeric species . Monomeric Aβ peptides exhibit very high conformational flexibility [6, 7], which represents one of the major challenges for this therapeutic target. The initial random coil structure shows characteristics of an α-helix and β-sheet mixture that transforms into a final structure predominantly comprising β-sheets . At this stage, a nucleation phase occurs that initiates Aβ aggregation. Soluble Aβ oligomers have been shown to form by a nucleation-dependent process, wherein most neurotoxic Aβ42 becomes a seed in the aggregation process and also enhances the oligomerization of Aβ40, the most prevalent species of Aβ in the central nervous system (CNS) . The conformational state of Aβ42 thus plays a critical role in the formation of oligomers, especially in the formation of initiation seeds for Aβ aggregation.
3.1 Molecular Modeling and Molecular Dynamics Simulations
All molecular modeling was performed using the Schrödinger suite (2015-3; Schrödinger, LLC; New York, NY, USA; 2015). Molecular dynamics simulations were run using Desmond . The simulations were run on GeForce GTX Titan Black graphics processing unit cards. The optimized potential for liquid simulations (OPLS 3.0) force field  was used to model all interactions, and the SPC model was used for waters. The 1IYT Aβ42 NMR structure from the Protein Data Bank (PDB) was used as a starting point for molecular dynamics simulations. This structure is primarily alpha helical and is representative of the peptide in an apolar environment. A 20-Å box of water or a mixed solvent box of 1 % tramiprosate in water was added around the peptide using Schrödinger system set-up tools. Ions were added to neutralize the charge of the entire system. Simulations were equilibrated and run under NPT conditions [constant number (N), pressure (P) and temperature (T)] with periodic boundary conditions. A Nose–Hoover Thermostat and Martina–Tobias–Klein barostat were used to control temperature and pressure, respectively. Simulations were run in replicates of three for 100 ns each, and the results were compiled for analysis. Principal component (PC) analysis was performed using ProDy  and plotted using custom python scripts.
3.2 Ion Mobility Spectrometry–Mass Spectrometry (IMS–MS)
The conditions used for MS, using a Waters Synapt G2-S, were as follows: positive polarity in sensitivity mode; capillary = 2.5 kV; nebulizer = 2 mbar; source temperature = 80 °C; desolvation temperature = 60 °C; sample cone setting = 35 V; source offset setting = 60 V; and mass range = 500–4000 m/z. These conditions were maintained throughout the study to ensure consistency of the data and to avoid influencing the detection of oligomers due to preferential ionization conditions.
Samples were directly infused into the mass spectrometer at a flow rate of 10 µl/min using a Protea PM-1000 Syringe Pump and Hamilton 1-ml syringe. The data acquisition of the amyloid peptide was performed using a Waters Synapt G2-S quadrupole time of flight mass spectrometer (Q-TOF MS) with traveling wave ion mobility (Waters Corp., Milford, MA, USA). The data were acquired using the systems sensitivity mode to allow for the detection of the less abundant oligomers. Samples were infused at room temperature. The IMS–MS studies were conducted at Protea, Inc. (Morgantown, WV, USA).
3.2.1 Sample Preparation
We reconstituted 1 mg of recombinant human Aβ42 peptide from BioLegend (99% purity, cat# 843801) in 200 µl of Fisher Optima LC/MS (liquid chromatography/MS) grade water (cat# W6-1) and vortexed it vigorously for 2 min to solubilize the peptide creating a 5 mg/ml solution. Samples were then diluted to a final concentration of 22 pmol/µl prior to incubation. The sample mixtures were then incubated at room temperature for 0, 4, and 24 h. After the acquisition of incubated samples was completed, the raw data were analyzed using the Waters MassLynx v2.4 suite with DriftScover v2.7 to visualize drift times for the peptide.
3.2.2 Amyloid Beta Aβ42 Species Characterization
Aβ42 species characterization using IMS–MS was performed by direct infusion at 22 pmol/µl in water. The peptide was prepared in water to maintain the native state conformation of the peptide, and ion mobility data acquisition was performed to detect and characterize the conformational changes of the native state monomer and any oligomers that may have formed during the incubation.
3.2.3 Tramiprosate IMS–MS Binding Study
The data acquisition for Aβ42 peptide was performed using a Waters Synapt G2-S Q-TOF MS with traveling wave ion mobility (Waters Corp.). The data were acquired using the systems sensitivity mode to allow for the detection of the less abundant oligomers. Samples were infused at room temperature as in the previous section.
We reconstituted 1 mg of tramiprosate in 1 ml of Fisher Optima LC/MS grade water (cat# W6-1) and vortexed it vigorously for 2 min until completely dissolved. The sample was then diluted to create 220, 2200, and 22,000 pmol/µl solutions to perform a 10-, 100-, and 1000-fold molar excess for the binding experiments with Aβ42.
We reconstituted 1 mg of recombinant human Aβ42 peptide in 200 µl of Fisher Optima LC/MS grade water and vortexed vigorously to solubilize to a 5 mg/ml solution. Samples were then diluted to their final concentrations prior to incubation. The sample mixtures were incubated at room temperature for 0, 4, and 24 h, followed by analysis as described in the previous subsections.
3.3 Nuclear Magnetic Resonance Spectroscopy
3.3.1 Aβ42 Preparation
15N-uniformly labeled Aβ42 peptide was purchased from rPeptide (Bogart, GA, USA) and used without further purification. The buffer system described by Roche et al. , except for NaOH, was used to acquire the NMR data of Aβ42 titrated with tramiprosate (90% H2O/10% D2O sodium phosphate buffer, pH 7.4 at 37 °C). NaOH was omitted from the sample preparation as it may interfere with tramiprosate binding. The total concentration of Aβ42 in the sample was 75 μM to limit any initial aggregation. The D2O was used to lock the NMR spectrometer.
3.3.2 NMR Experiments
NMR experiments were conducted at 800 MHz on a Bruker AVANCE II spectrometer using a 5 mm HCN cryogenic probe. The probe sample temperature was initially set to 10 °C then slowly warmed to 25 °C and to 37 °C upon insertion of the sample. Spectra were recorded at both 25 and 37 °C. A 1D 3919 Watergate  experiment was first conducted to optimize the water suppression and 1H spectral width for the 2D experiments. A relaxation delay of 1.5 s was used with 128 scans. The 1D Watergate experiment was optimized to suppress the largest peak (H2O) in the spectrum. The optimized parameters were then transferred to the 2D experiments. 2D1H-15N SOFAST-HMQC with 3919 Watergate were used [16, 17]. A total of 128 increments was acquired in t1 (15N) with 96 scans per increment. A J(15N-1H) coupling of 95 Hz was used. All spectra were processed using TopSpin 3.5. Assignments were taken from the literature [15, 18, 19].
3.4 Human Plasma and Brain Pharmacokinetic Analyses, Cerebrospinal Fluid (CSF) Aβ42 Levels, and Pharmacokinetic–Pharmacodynamic Translation
Plasma and cerebrospinal fluid (CSF) concentrations of tramiprosate were determined in frozen samples at 78 weeks of the completed North American phase III study using validated LC-MS/MS methods [lower limit of quantitation (LLQ) = 5 and 2.5 ng/ml in plasma and CSF, respectively]. The steady-state drug level in human brain was projected based on the brain/plasma drug exposure relationship derived from a rodent model, assuming comparable brain penetration and intra-cerebral kinetics of tramiprosate between the two species following oral administration [20, 21]. Pharmacokinetic data analyses were conducted using Winnonlin Professional v5.0.1 (Pharsight, Mountain View, CA, USA). The CSF Aβ42 concentrations were measured by enzyme-linked immunosorbent assay (ELISA) in patients with AD in the tramiprosate phase II trial as previously described  and were used in the present pharmacokinetic–pharmacodynamic analyses.
4.1 Multi-Ligand Binding Mode of Tramiprosate and Effects on Aβ42 Monomer Conformation
To address the high conformational flexibility of Aβ42 and characterize its interaction with tramiprosate, we used IMS with a Q-TOF MS with traveling wave ion mobility. IMS is a powerful technique capable of separating molecular ions based on their size and conformation and can also be used to characterize the stoichiometry of ligand–protein complexes .
4.2 Tramiprosate Prevents Formation of Aβ42 Oligomers
Detection of amyloid beta Aβ42 oligomers by ion mobility spectrometry–mass spectrometry in the absence and presence of tramiprosate
m/z (average mass)
Detection of Aβ42 oligomers in the absence of tramiprosatea
Detection of monomers only in the presence of tramiprosateb
Detection of amyloid beta Aβ42 oligomers by ion mobility spectrometry–mass spectrometry in the absence vs. presence of tramiprosate
Aβ42, no tramiprosate
Together, these data show that the tramiprosate-enveloping mechanism, wherein Aβ42 peptide is enveloped by a cloud of tramiprosate reminiscent of a solvation effect (Sect. 4.4), has implications for clinical activity, especially because high molar excess of the tramiprosate was required in the clinical trials .
4.3 NMR Experiments Identify Aβ42 Residues that Interact with Tramiprosate
At a 1000-fold excess of tramiprosate over Aβ42, 22 Aβ42 residues showed significant chemical shift perturbations. The most dramatic changes were observed for R5, H6, S8, G9, Y10, K16, L17, V18, F19, N27, K28, and M35. The 2D 1H-15N HMQC peaks from these residues exhibited at least a 10 Hz chemical shift change in the 1H dimension, with K16 and K28 having chemical shift perturbations of 13.5 and 16.1 Hz, respectively, indicating a substantial interaction with tramiprosate. E3, V12, H13, H14, D23, S26, G25, G33, V36, and V39 showed smaller, yet still significant, chemical shift perturbations, indicating that they also interact with tramiprosate. Taken together, these results show that tramiprosate interacts with residues that span the length of Aβ42 in a concentration-dependent mode, which supports the IMS–MS data. Importantly, the strong tramiprosate binding to K16 and K28 supports tramiprosate-mediated disruption of the Lys28-Asp23 and/or Lys28-Glu22 salt bridges and suppression of neurotoxicity and misfolding [7, 27, 28, 29], given that these two lysine residues have been previously demonstrated to play a key role in mediation of these activities .
4.4 Molecular and Conformational Dynamics
Given the intrinsically disordered nature of Aβ42 and a high conformational dynamics, the interaction with tramiprosate is unlikely to be described by a static structural model with a single tramiprosate molecule bound. Hence, commonly applied structure-based drug-discovery approaches such as molecular docking are unlikely to provide a complete understanding of the MOA of tramiprosate. This represents a challenge to the characterization of the secondary structures of Aβ42 peptides because of their disordered nature and high aggregation propensity.
To describe the large conformational changes observed in these simulations, we performed a PC analysis of the free energy surface. This analysis distills the complex motions of a flexible protein into the largest uncorrelated motions, or PCs. The first major motion (PC1) of Aβ42 can be described as a bending of the two helices towards each other like a hinge, and the second motion (PC2) can be described as a twisting of the two helices. Without tramiprosate, Aβ42 exhibited a typical trait of intrinsically disordered proteins: it lacked a narrow, well-defined energy minimum for any single folded structure (Fig. 7c). When PC1 and PC2 were mapped according to their free energy, a number of energy wells were observed (Fig. 7c), which correspond to the multiple Aβ42 conformations detected experimentally via IMS–MS. The 1% tramiprosate solution, corresponding to an Aβ42 : tramiprosate molar ratio of 1:250, stabilized the peptide in the semi-cyclic conformation; the energy surface as described by PC analysis showed stabilization of the semi-cyclic conformation as a well-defined energy well (Fig. 7d). This correlates well with the conformer stabilization detected by IMS–MS arrival time distribution (Fig. 3). The stabilization of a single conformation prevents Aβ42 from changing form and aggregating into pathogenic oligomers. Both in the stabilization of a single conformation and in the characterization of multiple transient tramiprosate binding sites, these results correlate with the IMS–MS experiments, where we detected up to 13 molecules of tramiprosate bound to Aβ42, in agreement with previous MS data [24, 31]. Interestingly, tramiprosate above 3 mM concentrations did not bind to plasma proteins from human, dogs, and rats in a standard plasma protein-binding study using an ultrafiltration technique , suggesting an absence of non-specific binding to plasma proteins such as albumin (data not shown).
Summary of the ion mobility spectrometry–mass spectrometry, nuclear magnetic resonance, and molecular dynamics data
No chemical shift perturbation
Interaction starts to be noticeable
Strong perturbation/interaction in dose-dependent mode reaching plateau at 1:1000 ratio
No significant effect on conformation. No difference for 1:1, 1:10 ratio and absence of TR
Formation of stabilized semi-cyclic conformation
Dose-dependent inhibition of oligomer formation
Dose-dependent chemical shift perturbations
Dose-dependent effect on conformation
4.5 Translational Analyses of Human Brain Drug Exposure vs. the Target
Steady-state plasma, cerebrospinal fluid, and brain drug exposures following oral administration of tramiprosate 150 mg twice daily in the phase III study
Plasma mean tramiprosate AUC0–12h
4429 ng/ml × h (31.8 µM × h)
CSF mean tramiprosate concentration (Css-ave)
Projecteda brain mean tramiprosate concentration (Css_ave)
CSF Aβ42 concentration
Brain soluble Aβ42 concentration
Multiple excess of brain drug vs. soluble Aβ42
1300- to 3700-fold
Concentration of amyloid beta Aβ42 in the cerebrospinal fluid of subjects with mild to moderate Alzheimer’s disease (n = 46) 
Age of subjects with AD in trial
CSF Aβ42 (pg/ml)
75.1 ± 8.3 years
19.4 ± 0.8
179 ± 101
In this study, we identified a novel enveloping MOA for the small-molecule Aβ-anti-aggregation agent tramiprosate. This mechanism is characterized by a multi-ligand stoichiometry, a critical excess of the ligand to target ratio, and a dose-dependent modulation of the Aβ42 conformational space, resulting in a more stabilized semi-cyclic conformation of Aβ42 and, eventually, the prevention of neurotoxic Aβ42 oligomer formation. This MOA may be responsible for the clinical cognitive and functional benefits of tramiprosate as previously observed in patients with mild-to-moderate AD .
Specifically, at the molecular level, we showed that tramiprosate enveloped soluble Aβ42 monomers and prevented their self-assembly into the primary monomeric misfolded Aβ42 conformation, and consequently arrested the initiation phase of Aβ42 aggregation, thus preventing the formation of neurotoxic Aβ42 oligomer species. This enveloping mechanism exerted a surprising and significant degree of control over the Aβ42 conformational landscape.
This finding is important, especially considering that the tramiprosate molecule is very small (139 Da) yet capable of controlling the structural flexibility of a large peptide/small protein such as Aβ42 under the determined conditions. This may also provide insights for a better understanding of the protein–protein and protein–peptide interaction processes in a living organism and in disease states. The challenge to modulate Aβ42 conformational dynamics has been one of the major reasons that this relatively small protein has been such an elusive target in AD drug development. We hypothesize that the enveloping occurs after a critical mass of tramiprosate (i.e. a sufficient concentration relative to Aβ42 monomer) is reached in the CNS. Because of the relatively weak nature of the transient binding of tramiprosate to Aβ42, the monomeric peptide requires a large excess of tramiprosate molecules to overcome the rapid off rates. Thus, the binding and unbinding occur rapidly enough that, only at a ratio of approximately 1:1000 of Aβ42:tramiprosate (at the ratio of 1:500, functional interaction becomes measurable), Aβ42 becomes enveloped by the drug and a full inhibition of oligomer formation is achieved.
Another important consideration is the putative endogenous role of Aβ42 monomers in brain. To date, the physiological role of Aβ42 is not fully understood. For another aggregating protein, α-synuclein, which is implicated in Parkinson’s disease, a simple reduction of its levels is associated with synaptic failure , whereas whether a substantive reduction of monomeric Aβ42 levels might also result in detrimental clinical defects is unclear. Thus, therapeutic agents such as tramiprosate that preferentially prevent the formation of oligomers by an upstream action directly on Aβ42 monomers, without affecting Aβ production, unlike beta-secretase 1 (BACE1) inhibitors or γ-secretase inhibitors, may yield a new class of AD therapeutics with improved safety and efficacy. Consistent with this MOA, long-term treatment with tramiprosate (over 78 weeks) was well tolerated and devoid of vasogenic edema side effects, also referred to as ARIA (amyloid-related imaging abnormalities reported for some of the immunological therapies), in over 2000 patients with AD treated to date .
We also correlated the molecular mechanism results with the clinical pharmacokinetic and efficacy data [10, 11, 22, 33]. The data from our IMS–MS, NMR, and molecular dynamics experiments suggest the requirement of three orders of magnitude excess of tramiprosate relative to soluble Aβ42 to achieve a complete prevention of Aβ42 oligomer formation and aggregation. This excess ratio is in line with the projected tramiprosate concentrations in the CNS in humans based on the present translational pharmacokinetic dose-exposure analyses. The measured steady-state average concentration of tramiprosate in the brain at the dose of 150 mg tramiprosate bid from the phase III North American AD trial was 130 nM, which is 1300- to 3700-fold in excess of human CNS soluble Aβ42 levels based on the data from subjects with AD in the previous tramiprosate clinical trials, as well as the reported range in patients with AD [4, 34, 36]. Importantly, clinical cognitive and functional improvements have been demonstrated in subjects with AD in the tramiprosate phase III AD trial . This suggests that the results from our current mechanism study reflect the therapeutic effect of tramiprosate in patients with AD.
While clinical efficacy of tramiprosate is suggested in a genetically defined subset of patients with AD with high amyloid burden, and its presented mechanistic understanding represents therapeutic promise, it is clear that a single-target approach to AD has not yet yielded an effective therapy. Considering the rather complex pathophysiological features of this disease, which involves multiple molecular, biochemical, and cellular pathways and systems (e.g., cholinergic function, amyloid, tau, and inflammatory components), combination therapies targeting multiple steps of amyloid cascade (e.g., tramiprosate in combination with BACE1 inhibitors, monoclonal antibodies, or insulin-degrading enzymes, etc.) or both amyloid and non-amyloid pathways (e.g., tramiprosate in combination with tau inhibitors or symptomatic agents), it is likely that future therapies will involve an approach similar to that of precision medicine, which will likely comprise the combination of more than one therapeutic modality tailored to a particular stage of the disease and/or disease phenotype. Important to this point, the clinical efficacy of tramiprosate observed in the phase III North American trial  was identified on top of concurrent acetylcholinesterase inhibitors (e.g., donepezil) and memantine and thus represents the first-step combination therapy approach.
Our study shows that (1) tramiprosate modulates the Aβ42 conformational landscape in a concentration-dependent manner, resulting in the stabilization of Aβ42 monomers and inhibits the formation of oligomers and subsequent aggregation and (2) the observed molecular stoichiometry is consistent with the clinical drug dose exposure versus target relationship that has been shown to achieve a robust clinically meaningful efficacy in patients with APOE4/4 homozygous AD in the previous phase III trials, suggesting that the MOA findings of tramiprosate most likely underpin its clinical outcome. The discovery of the unique enveloping MOA of tramiprosate may broaden our understanding of the control of conformationally flexible peptides/proteins, which may find potential utility in the development of disease-modifying therapies for AD and related neurodegenerative disorders caused by misfolded proteins.
IMS–MS was performed by Protea Biosciences; NMR was performed by MaratechNMR. Dr. Aidan Power (Alzheon) kindly reviewed the manuscript and internal editorial comments. We thank Helena Kocis for her kind help with the preparation of graphics files.
PK conceived the enveloping MOA and designed all studies, interpreted the data in collaboration with JH, and wrote the manuscript in collaboration with JH, JY, WS, SR. Molecular dynamics calculations were performed by WS and SR. Pharmacokinetic/pharmacodynamic analyses were performed by JY and JH. All co-authors reviewed and contributed to the manuscript.
Compliance with Ethical Standards
Alzheon Inc. sponsored the research described in this article and paid the open access fee.
Conflict of interest
PK, MT, JH, and JY are employees of Alzheon Inc. WS and SR are employees of Schrödinger, which had a scientific services agreement in place to perform some of the work in this manuscript. KB has served as a consultant or on advisory boards for Alzheon, Eli Lilly, Fujirebio Europe, IBL International, Novartis, and Roche Diagnostics, and is a co-founder of Brain Biomarker Solutions in Gothenburg AB, a GU Venture-based platform company at the University of Gothenburg. HF has no competing interests.
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