The four-year project, which began in 2014, aims to design tools to catch Alzheimer’s earlier, as well as lay the groundwork for future findings on tackling this important and poorly understood disease.
Alzheimer’s disease, the most common form of dementia, affects an estimated 850,000 people in the UK alone. According to the NHS, roughly 1 in 14 people over the age of 65 suffer the disease, and that increases to 1 in 6 above the age of 80. The debilitating condition, typified by memory loss, confusion, personality changes, anxiety, speech difficulties and other symptoms, currently has no cure. The treatments available today can limit or slow neurological damage, but none can reverse the damage already done by the disease and, as there is no reliable indicator by which to diagnose the disease early or predict its occurrence, treatments are usually administered too late to save sufferer’s cognitive function.
“We’re all living longer and getting older and it’s going to be even more of an issue in the future, so it’s an important area of medical research”, says Professor Val Gillet of the Information School, part of the Sheffield team working on Diagnostic and Drug Discovery Initiative for Alzheimer’s Disease (D3i4AD), a European Marie Curie Industry-Academia Partnerships and Pathways (IAPP) funded project. The four-year project, which began in 2014, aims to design tools to catch Alzheimer’s earlier, as well as lay the groundwork for future findings on tackling this important and poorly understood disease.
Led by the Department of Chemistry at the University of Sheffield, D3i4AD brings research-active academic institutions (the Information School and the University of Lisbon complete the trio) together with the expertise of industry specialists (UK pharmaceutical company Eli Lilly and small Italian biotech Biofordrug) with the aim of identifying small, drug-like chemical compounds which can be used as diagnostics for Alzheimer’s. In order to find out which compounds these could be, they must be tested to see how they would bind to certain proteins in the body, but this cannot be done in actual humans. Instead, the Chemistry department are designing what are known as biological assays – processes of seeing whether compounds demonstrate a particular effect. Biofordrug are also involved in the assay process, specifically looking at the detection of copper (a copper-binding protein is one that is thought likely to be involved in Alzheimer’s). Eli Lilly’s and the Information School’s roles in the project are closely aligned and involve identifying small molecules to be tested in these assays. The University of Lisbon use their expertise in synthetic organic chemistry to synthesise small molecules which are ‘shortlisted’ as possibly useful for this purpose.
One of the main aims of the project
is building networks and sharing expertise
across the different partners.
“Chemoinformatics in general is about building computer models that help you select compounds that may be of interest in a particular biological setting”, says Professor Gillet of her specialist field. In the Information School, research on this project is focussed on developing computer models that help predict and select the most useful compounds from the vast available set, using ‘in silico screening’, an alternative to the live testing techniques of ‘biological screening’. “Our models are a surrogate for biological screening”, says Professor Gillet.
Usually, drug and diagnostic tool discovery like this is done by designing assays based on very specific protein targets. However, since the specific proteins involved in Alzheimer’s are not yet known, this cannot be done. The closest information we have is some knowledge of the pathways involved, which are built up of multiple proteins, so the experimental processes have to be generalised, using what are known as ‘cell-based’ assays.
Professor Gillet describes it as “a bit like putting your compound into a stew and testing that: you might see the effect, but you don’t know which bit of the stew caused the interaction.” The idea is to work out which ingredients to put into the ‘stew’, but also gradually work out which specific part causes the desired interaction. These computational processes are substantially cheaper, quicker and easier to run than biological screening tests and will hopefully massively focus the search for the potential diagnostic compounds by outputting a much reduced set to work with. “The hope is that once our models and the assays are complete, we would work closely with our partners on an iterative process to further hone the results”, adds Dr Antonio de la Vega de León, the research associate working on the project in Sheffield alongside Professor Gillet. Their work is also bolstered by some PhD student work.
“One of the main aims of the project is building networks and sharing expertise across the different partners”, says Professor Gillet of the other intended project outcome. There are many researchers involved in the project across the various partners, including five full-time post-doctoral researchers (of which Dr de la Vega de León is one) and several related PhD projects. Fostering the sharing of knowledge and best practice, the Marie Curie funding stipulates the movement of researchers and students between countries to enhance the expertise available on the project and build connections. “As a full-time researcher on the project, you cannot be a citizen of the country you are working in”, says Dr de la Vega de León, who is Spanish but came to Sheffield from Germany. “The whole point is promoting mobility of researchers.”
It goes without saying that Alzheimer’s disease is a huge area of concern which, right now, has no solution.
It goes without saying that Alzheimer’s disease is a huge area of concern which, right now, has no solution. “If you see some of the predictions of the social and human costs of Alzheimer’s in the future, it is kind of scary”, says Dr de la Vega de León. The motivation for the D3i4AD project is obvious, when the only currently available methods of detection of the disease are far too late in its progression (either by late-stage MRI scans or even by looking at a deceased brain).
“The project is more about diagnosis than cure”, says Professor Gillet, “although one could reasonably lead to the other.” Building on many years of collaboration with the Department of Chemistry, the Information School submitted the project proposal together with them, and following a long history and strong reputation in building predictive models, the research done here stands to be an important piece in one of the most threatening puzzles of modern healthcare.