Objective
Cancer and cardiovascular diseases are the leading causes of death in the EU, resulting in 54% of deaths in 2021. There is an urgent need for more effective therapeutics for these diseases, but drug discovery is slow, taking 16 to 20 years from target identification to drug approval.
To accelerate drug discovery, pharmaceutical companies use computational tools. Among the most successful are physical molecular simulations, which are limited by the availability of experimental structural data. A new generation of machine learning (ML) powered structure prediction tools, such as AlphaFold, offer the potential to supply structural data suitable for physics-based modeling without the need to experimentally solve structures. However, these tools produce 3D structures missing key physical details, which are vital for accurate molecular modeling. A critical physical detail is the assignment of relevant protein protonation states, where misprediction results in large errors in drug binding affinity predictions, slowing down drug discovery.
PROTONIX will bridge this gap between physical molecular simulations and ML structure prediction tools to improve the speed and accuracy of computational drug discovery, by adding protonation details to structure predictions. I will focus on the human kinase superfamily, the main therapeutic target class for cancer and cardiovascular diseases. PROTONIX will contain two open-source ML models. First, PROTONFOLD will use a diffusion model to predict relevant protonation states with their corresponding proton positions from ML protein structure predictions, generating simulation-ready files. Second, PROTONCON will use a flow-matching model to integrate protonation state prediction with multiconformer protein structure generation, providing insights into the coupling between protonation states and protein conformations. PROTONIX will point the way for future AlphaFold-like models to produce structures immediately useful for drug discovery.
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.
- natural sciences biological sciences biochemistry biomolecules proteins
- medical and health sciences clinical medicine oncology
You need to log in or register to use this function
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.
-
HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
See all projects funded under this programme
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
See all projects funded under this funding scheme
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-2024-PF-01
See all projects funded under this callCoordinator
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.
14195 BERLIN
Germany
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.