Project description
An important technique for characterising proteins gets real-time process monitoring
Proteins are one of nature's most important polymers, ubiquitous in living organisms. Their critical functions are tightly linked to their 3D structures. Characterising these 3D structures is thus fundamental to numerous applications in biomedicine and also to environmental sensing, wastewater treatment and, increasingly, natural solutions in fields ranging from energy to organic electronics. X-ray protein crystallography is an important technique used to determine the 3D position of every atom in a protein from a high concentration of purified protein that is then crystallised. The first and perhaps most difficult step is obtaining crystals of the protein of interest. Typically, many crystallisation conditions must be tried. The EU-funded Fail Fast project is developing methodology to characterise nanocrystal formation before the crystals have grown, putting an end to trial and error for significant benefits in time, money and outcome.
Objective
High-resolution protein structures obtained by X-ray diffraction require the production of well-ordered proteins crystals of high quality. However, to produce well-ordered protein crystals, several bottlenecks must be addressed to screen and optimize the thousands of conditions that can lead to crystallization. In this project, we will accelerate the process of protein crystallization by detecting early, i.e. assessing nano-crystal formation and providing immediate feedback, instead of waiting for crystals to grow, thereby saving time and money. We will use nonlinear light scattering that is highly sensitive to crystal formation. In combination with machine learning analysis, we will develop optimization routines to predict the conditions that likely lead to crystallization in a very short time scale, hours, instead of weeks.
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.
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.
- engineering and technology materials engineering crystals
- natural sciences biological sciences biochemistry biomolecules proteins
- engineering and technology nanotechnology nano-materials nanocrystals
- natural sciences computer and information sciences artificial intelligence machine learning
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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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H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
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.
ERC-POC - Proof of Concept Grant
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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-2020-PoC
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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.
1015 Lausanne
Switzerland
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.