9 January 2019

Understanding Alzheimer’s: how chemoinformatics is driving the development of new treatments

With nearly 40 million sufferers worldwide and no known cure, Alzheimer’s is rarely far from the headlines, as the world begins to grapple with the effects of an ageing population.

A photograph of different brain scans.

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 a sufferer’s cognitive function.

Taking on the seemingly insurmountable task of finding treatments has taken a truly interdisciplinary turn.

Away from biochemistry laboratories, a team from the University of Sheffield’s Information School is leading the application of computer and data science to develop new understanding of the complexities of the disease.

This discipline, known as chemoinformatics, in general, is about building computer models that help solve problems in the field of chemistry.

Diagnostic and Drug Discovery Initiative for Alzheimer’s Disease (D3i4AD) is 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.

Working alongside the University of Sheffield’s Department of Chemistry, the aim is to identify small, drug-like chemical compounds which can be used as diagnostic tools 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 is designing what are known as biological assays – processes of seeing whether compounds demonstrate a particular effect.

Professor Val Gillet, leading the Information School’s contribution to the project, explains the highly complex process using an interesting analogy: “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. Professor Gillet explains that the research focuses more on diagnosis that cure, but that progress in one could very well lead to the other.

The project reflects a truly collaborative model of research, forging lasting strategic relationships with key partners, The University of Lisbon and corporate stakeholders, Eli Lilly (UK) and Biofordrug (Italy).

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