Project description
Non-invasive disease diagnosis using artificial enzyme pockets to detect biomarkers
Metabolites are molecules produced by the body through normal processes that subserve healthy functioning. They include biomarkers of early disease processes, often changing before symptoms become apparent. Current synthetic sensing systems are challenged by selectivity and sensitivity limitations. The ERC-funded SupraSense project aims to overcome these with biomimetic artificial receptors that mimic enzyme pockets. Integrating molecular recognition, materials science and chemistry-informed deep learning, SupraSense will leverage highly tuneable hybrid zeolitic materials with binding cavities modulated by peptide-based cofactors. The ‘SupraSensors’ will support non-invasive multi-molecular diagnostics of urine, blood and saliva in point-of-care facilities and at home, revolutionising early detection of conditions from cardiovascular to ageing-associated diseases.
Objective
SupraSense combines completely new strategies to design and realize biomimetic artificial receptors for bioactive small molecules, i.e. metabolites, with the aim of overcoming long-standing selectivity and sensitivity limitations that hindered other synthetic sensory systems from reaching diagnostic applications. Sophisticated yet easy to fabricate “SupraSensors” will be developed based on unprecedented hybrid zeolitic materials whose binding cavities are modulated by peptide-based cofactors, thereby mimicking enzyme pockets. SupraSensors will be functional and directly applicable for molecular diagnostics in urine, saliva, and blood and will be of utility in point-of-care units and personal homes. Emphasis is given to the detection of metabolites that are important disease indicators.
I am an expert on “conventional” synthetic chemosensors and have studied both their merits and fundamental shortcomings. Out of this deep routed analysis, I developed the proposed ambitious strategy that marries principles of molecular recognition with materials science and chemistry-informed deep learning. These SupraSensors will advance the field through the following elements: i) high-energy water release from microporous materials ensures high binding affinity; ii) strategically placed peptide-based recognition elements provide selectivity while offering synthetic tunability; iii) information-rich signal output from SupraSensor libraries enables metabolite distinction in biofluids; iv) novel signal amplification concepts increase sensitivity. SupraSensor discovery will be fast and generalizable to many metabolite classes.
SupraSense has the potential to unleash supreme opportunities for multiparameter diagnostics, which will be essential for patient subgrouping based on metabolic phenotypes. The new concepts developed herein have the prospect to revolutionize early detection of emerging cardiovascular events, inflammations, sepsis, and other metabolic or aging-associated diseases.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
This project's classification has been human-validated.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
This project's classification has been human-validated.
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering sensors biosensors
- natural sciences biological sciences biochemistry biomolecules
- natural sciences computer and information sciences artificial intelligence machine learning deep learning
- engineering and technology medical engineering medical laboratory technology diagnostic technologies
- engineering and technology industrial biotechnology biomaterials
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.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
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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
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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-ERC - HORIZON ERC Grants
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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) ERC-2022-COG
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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.
76131 Karlsruhe
Germany
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