Size Matters: Diffusion Technique Sorts Out Pathological Proteins

Proteinopathies are diseases that feature misfolded, aggregated proteins as a cause or symptom. In the brain, proteinopathies are rife. Many major neurological disorders have “hallmark” proteins which are found to accumulate in brain cells over the disease course. These include alpha-synuclein in Parkinson’s disease, and amyloid-beta in Alzheimer’s disease. Assessing the content and arrangement of these proteins is no small task, but innovative research techniques are facing up to the challenge. These include the diffusional sizing technique developed by Fluidic Analytics. This technology was showcased in a recent presentation at the Federation of European Biochemical Societies (FEBS) Congress in Krakow, Poland. We talked to the University of Cambridge’s Tom Scheidt, a co-author of the presented research, to find out more about the technique. 

Ruairi Mackenzie (RM): Why is it important to understand how proteins bind and self-assemble in Alzheimer’s disease?

Tom Scheidt (TS): Firstly, there’s the impact of the condition – a new case of dementia is diagnosed every three seconds, and the number of people affected is set to increase with an ageing global population. Simultaneously, we see that major pharmaceutical manufacturers are abandoning Alzheimer’s drug development as the success rate in this area is about half compared to other conditions. The reasons for this are manifold.

Despite its prevalence, our understanding of the biochemical basis of the disease, and how to tackle it, is poor. The reason is that the entity of proteins involved is not entirely clear and the proteins proposed to be involved are disordered, form aggregated fibrils and have strong adhesion tendencies, making them generally hard to study.

Understanding and using current knowledge of controlled and uncontrolled protein binding in Alzheimer’s disease can be the foundation for a more streamlined development of new therapeutic strategies.

RM: What is diffusional sizing?

TS: Diffusional sizing is one of the techniques we use to assess the interactions of fibrils and their monomeric building blocks with various therapeutics. It works by introducing a sample into a laminar flow, then using the proportion of diffusion that occurs to calculate the average molecular size. The test is in solution and therefore there is no need for sample immobilization, which reduces the risk of interfering adhesion effects. Furthermore, the technique doesn’t require specialist sample preparation – so it’s easy to get started.

This approach worked well with the disordered proteins and even the fibrils, which was crucial for us.

RM: What information does diffusional sizing give us about amyloid fibrils that we wouldn’t know otherwise?

TS: The fact that absolute size is reported lets us assess more about the binding events that occur – in terms of specificity, stoichiometry and target confirmation.

With the final size of the fully bound complex, we can quickly tell if binding is 1:1, 1:2 or any other stoichiometry. In our recent work, publishing later in 2019, this was integral to understanding how the therapeutic antibodies interact with the fibrils or protein monomers, and connecting this information with the inhibitory mechanisms found previously.

RM: How can diffusional sizing help us in treating neurological proteinopathies? 

TS: Many of the proteins involved in neurological conditions are disordered and studying them by protein immobilization techniques such as Surface Plasmon Resonance is challenging. The solution state, low adhesion nature of diffusional sizing is ideally suited to these challenging targets.

Generally, the simplicity of the technique combined with the detailed insights it gives could help us get a much earlier understanding of drug interactions in these conditions. If we can fully understand how a drug and its target interact before trials and later stages, significant time and costs could be saved.

Tom Scheidt was speaking to Ruairi J Mackenzie, Science Writer for Technology Networks