Objective
Protein aggregation is a major concern in biomedical research as this mechanism is responsible for at least 40 increasingly common human disorders, including Parkinson's disease, Alzheimer's disease, Huntington’s disease, Amyotrophic lateral sclerosis and certain types of cancer or type II diabetes. These protein aggregates can be isolated from patients in the form of amyloid depositions. Environmental conditions, such as pH, temperature, the interaction with other proteins, lipids or nucleic acids, the formation of phase-separated compartments or the presence of small molecules, influence the aggregation reaction. Until recently, the only available treatment for amyloidosis was palliative care. Fundamental research has identified small molecules from several hundred thousand different molecular entities and developed antibodies that delay amyloid conversion, leading to disease-modifying therapeutics for some of these pathologies. Yet prioritising the best candidates has led to overlooking the precise chemical and pharmacophoric determinants necessary to inhibit or delay aggregation for each protein variant. By manual curation of decades-long peer-reviewed knowledge, extraction and annotation of the effects of these multiple thousands of molecular entities, we will construct a database with aggregation-inhibiting and non-inhibiting molecules for each pathological protein. This data will be used to train a machine learning model that defines the chemical fingerprints required for preventing aggregation in each proteotype. The model will allow us to identify chemical entities not previously assayed, repurpose existing ones and design novel molecules. The most promising hits will be synthetised and experimentally assayed in vitro. Overall, this project represents a paradigm change to transition from the time and resource-costly trial-and-error screening toward a rational design of disease-modifying therapeutics.
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2025-PF
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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.
01513 Vilnius
Lithuania
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.