PROT-STRUCT-DISEASE
Financiado
Protein Structure Molecular Mechanisms and Human Genetic Disease Beyond the Lo...
Protein Structure Molecular Mechanisms and Human Genetic Disease Beyond the Loss of function Paradigm
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 u...
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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Duración del proyecto: 64 meses
Fecha Inicio: 2021-01-20
Fecha Fin: 2026-05-31
Fecha Fin: 2026-05-31
Línea de financiación: concedida
El organismo H2020 notifico la concesión del proyecto el día 2021-01-20
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
ERC-2020-COG:
ERC CONSOLIDATOR GRANTS
Cerrada
hace 4 años
Presupuesto
El presupuesto total del proyecto asciende a
2M€
Líder del proyecto
THE UNIVERSITY OF EDINBURGH
No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico
TRL
4-5
Perfil tecnológico
TRL
4-5
478.63K€ |
Participante