How Fluidic Analytics Helped Researchers Elucidate the Mechanism of Aducanumab

Aducanumab is a drug that has recently received accelerated approval for the treatment of Alzheimer’s disease from the U.S. Food and Drug Administration (FDA). Professor Sara Linse, Professor in biochemistry and structural biology at Lund University, led a research programme that has shed light on the mechanism of four clinical-stage Alzheimer’s drugs including aducanumab, with the findings published in the prestigious journal Nature Structural and Molecular Biology. 

All four of the drugs studied have undergone three phases of clinical trials. All four of them target known forms of the A-beta peptide. Yet the outcomes of their respective clinical trials varied significantly. The objective of the study was to generate new insights into the way that these four antibody therapeutics bind to different forms of the A-beta peptide, to generate new insights about the similarities and differences between their respective mechanisms of action.

Despite having expert knowledge of all standard techniques for characterizing protein interactions, researchers had previously been unable to explain the distinct differences in the clinical efficacy of these drugs. Using Microfluidic Diffusional Sizing (MDS), however, Prof. Linse was able to uncover unique, quantitative insights about how these four drugs bind to their target, revealing key aspects of aducanumab’s mechanism of action that distinguish it from those of the other three drugs. These insights suggest key links between specific aspects of how drugs bind to the A-beta peptide and their ability to help clear up amyloid plaques.

Key Outcomes:

• Elucidating unique, quantitative insights about the mechanisms of action of four clinical-stage anti-amyloid-β antibody therapeutics
• Quantifying the striking differences between the mechanisms of action of these four antibodies 
• Identifying where these antibody-based drugs attach to amyloid plaques 
• Elucidating links between key aspects of a drug’s mechanism of action and its functional ability to induce the clearance of amyloid plaques
• Publishing a paper about the above in a high-impact journal (Nature Structural and Molecular Biology)

The Challenge: Elucidating the mechanism of action for clinical trial drugs against Alzheimer’s disease

Alzheimer’s disease affects nearly 50 million people globally. Despite the exact mechanism of this disease being largely unknown, its hallmark is the self-assembly of amyloid-ß peptides into different forms of cytotoxic aggregates. Many therapeutic efforts for the past 20 years have therefore targeted the amyloid-ß peptides. Several billion dollars have been spent developing drug candidates that have subsequently failed to produce functional improvements in patients’ conditions.

The challenge for the research team was to identify the mechanism of action for four anti-amyloid-ß antibodies currently in clinical trials, namely, aducanumab, gantenerumab, bapineuzumab, and solanezumab. Because the aggregation process of amyloid-ß peptides is highly complex, starting with an intrinsically disordered monomer progressing through fibrillar aggregates before culminating in amyloid plaques, it was difficult to obtain a clear picture of the overall mechanism of the action of these therapeutic antibodies. 

The Solution: Using Microfluidic Diffusional Sizing (MDS) to quantify antibody interactions against amyloid-ß peptides

Microfluidic Diffusional Sizing (MDS), a recently developed solution-phase technology for characterizing protein interactions, was an ideal technique to quantify and characterize crucial aspects of drug-target interactions for all four clinical-stage antibodies. 

Using MDS, the investigators gained the ability to investigate, quantify, and analyze protein interactions in solution. Thus, MDS enabled the researchers to generate data in a physiologically relevant environment. Based on the data, Prof. Linse and colleagues could characterize and quantify the binding of the different antibodies to the amyloid-ß peptides. 

More specifically, MDS provided information on binding affinity (quantifying the strength of binding between drug and target), changes in sizes (confirming the form of the amyloid-ß peptide being targeted), and stoichiometry (indicating how many drug molecules bind per target molecule). This information helped the researchers identify the mechanism of action for all four of the drugs studied. 

Prof. Linse spoke highly of Fluidic Analytics’ instrument. She says, “This technology allowed us to obtain unique information about the interaction between these antibodies and their targets that could not have been obtained with other technologies.” 

The Result: Elucidating the mechanism of action of anti-amyloid-ß drugs 

Prior to the publication of this study, knowledge of the mechanism of action of these four drugs was limited to largely qualitative information. Specifically, it was not clear which form of the A-beta peptide the drug candidates targeted, for example, small oligomers early on in the plaque-formation process or larger oligomers later on in the process of forming fibrillar aggregates. Using Fluidic Analytics’ system, the researchers were able to not only confirm whether or not each antibody therapeutic interacted with various forms of their A-beta peptide targets but also to quantify how strongly and at what stoichiometry (ratio of drug to target) these interactions were occurring. 

Using the size of the proteins as a measure, the results in the image below show that all the drugs being studied bind to peptide monomers – thereby increasing the size of the monomers from roughly 2 nm to approximately 5 to 7 nm. In a disease state, these peptide monomers come together to make the aggregates (or fibrils). Similar to binding to the monomers, all drugs with the exception of solanezumab bind to the fibrils as can be seen by the change in the size of the complexes formed by antibody drugs and fibrils to roughly 12 to 20+ nm. The results immediately suggest a possible reason why solanezumab may not be particularly effective at treating Alzheimer’s disease: because it binds at extremely high affinity to the monomer – the non-pathological variant of the A-beta peptide – and does not appreciably bind higher-order aggregate.

By contrast, the other three drugs, aducanumab, gantenerumab, and bapineuzumab, bind at much lower affinity to the monomer, and do bind at varying (but relatively high) affinities to A-beta fibrils.

Using Fluidic Analytics’ instrument, which provides information about the change in the size of the drug-protein interactions and the stoichiometry of the interactions, Prof. Linse and colleagues were able to elucidate that solanezumab was unable to bind to protein fibrils, while 2 drug molecules of gantenerumab and bapineuzumab bound to, what is presumed to be, the ends of the fibrils. 

The binding with aducanumab told a completely different story. The size of the amyloid-ß protein-drug interaction, as well as the concentration of these complexes and the stoichiometry of these reactions, informs that over 7 drug molecules were able to bind to the fibrils. The information helped the researchers ascertain that aducanumab was binding across the entire surface of the fibrils, slowing the critical secondary nucleation process that dominates the growth of fibril populations. 

This is further illustrated by the image below. Comprehensive characterization of the binding parameters reveals the correlation between the binding behavior and biological function. Specifically, the fraction of antibody bound shows a striking correlation with the reduction in amyloid-ß plaque in patients as measured using PET SUVr, with aducanumab being clearly distinguished as most effective. Thus, the research team were able to conclude that aducanumab is the drug candidate that most effectively reduces amyloid fibrils associated with disease in Alzheimer’s patients. 

A testimonial from Sara Linse:

“[MDS] technology allowed us to obtain unique information about the interaction between these antibodies and their targets that could not have been obtained with other technologies.”