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Protein Structure, Molecular Mechanisms and Human Genetic Disease: Beyond the Loss-of-function Paradigm

Project description

Discovering pathogenic mutations that cause diseases by not loss-of-function mechanism

The ability to identify damaging genetic variants is central to the diagnosis, treatment and prevention of human diseases. The EU-funded PROT-STRUCT-DISEASE project aims to identify pathogenic variants using a combination of computational and experimental approaches. The project's approach will be focused on alternative molecular mechanisms by which mutations can cause disease, versus the loss-of-function mechanism. Structural bioinformatics will uncover the mechanisms underlying pathogenic mutations and their relation to protein structure and phenotype. Deep mutational scanning will measure fitness and elucidate mechanisms linked to all possible single amino-acid substitutions. This will facilitate the direct identification of novel pathogenic variants and their association with human genetic disorders.

Objective

The ability to identify damaging genetic variants is central to the diagnosis, treatment and prevention of human disease. Computational phenotype predictors are widely used for prioritising likely pathogenic mutations, but their utility is limited by their accuracy. Conversely, experimental characterisation of variants is powerful but time consuming and difficult to perform on a large scale, limiting applicability in routine variant prioritisation. In this project, we will improve our ability to identify pathogenic variants through a combination of computational and experimental approaches. Fundamental to our strategy will be our consideration of alternate molecular mechanisms by which mutations can cause disease, in contrast to the current overwhelming focus on loss-of-function.

First, we will use structural bioinformatics to investigate the different molecular mechanisms underlying pathogenic mutations, and learn how they are related to protein structure and phenotype. Next, we will perform deep mutational scanning (DMS) on at least 10 human disease genes, enabling us to measure fitness and elucidate molecular mechanisms for all possible single amino-acid substitutions. This will facilitate the direct identification of novel pathogenic variants, and allow us to evaluate the performance existing computational phenotype predictors. Finally, we will implement our own computational variant prioritisation pipeline and meta-predictor, using our new understanding of molecular mechanisms to integrate computational phenotype and stability predictors and DMS data with structural and other protein-level features. Crucially, we will demonstrate the utility of our approach in application to sequencing data from clinical and population cohort studies. Together, the knowledge we learn, the experimental data we measure, and the tools we develop will improve our ability to identify novel pathogenic variants, and thus diagnose human genetic disorders.

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Programme(s)

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Topic(s)

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Funding Scheme

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ERC-COG - Consolidator Grant

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Call for proposal

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(opens in new window) ERC-2020-COG

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Host institution

THE UNIVERSITY OF EDINBURGH
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 2 000 000,00
Address
OLD COLLEGE, SOUTH BRIDGE
EH8 9YL Edinburgh
United Kingdom

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Region
Scotland Eastern Scotland Edinburgh
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 2 000 000,00

Beneficiaries (1)

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