Projet IDPfun2 (Horizon Europe, appel à projets 2023)
Action : Staff Exchanges
Panel : Life Sciences
Statut du projet : SIGNED

Nearly two decades ago, the unveiling of intrinsically disordered proteins/regions (IDPs/IDRs) disrupted the longstanding structure-function paradigm, challenging the notion that well-defined native protein structures are indispensable for function. IDPs possess the unique ability to sample ensembles of different three dimensional conformations, leading to transition pathways that have a crucial role in various unique molecular functions. However, despite their importance, our understanding of IDPs is limited due to the challenges of studying such dynamic and large molecular systems experimentally, relegating their characterization to computational methods. Although the recent breakthrough in artificial intelligence (AI)-based protein structure prediction methods has raised the awareness of the scientific community about the IDR prevalence in proteomes (up to 50% of residues in higher organisms), their ability to predict reliable IDP ensembles and explain their function remains completely unexplored. Building upon the IDPfun Consortium and in collaboration with the ELIXIR IDP Community and the ML4NGP COST Action, the proposed IDPfun2 Consortium brings together 7 European and 5 Argentinian leading institutions with complementary expertise in data management, machine learning and structural biology. IDPfun2 will combine state-of-the-art AI-based computational technology and novel data to advance the characterization of IDPs and their molecular behaviour also taking into account alternative molecular and evolutionary contexts. The Consortium will establish new standards and formats to better grasp the complexity of IDPs and provide training ground for a new generation of scientists. The ultimate goal of IDPfun2 is to translate the acquired knowledge into major international protein databases, benefiting the broader scientific community and accelerating biomedical applications with a direct impact on health and diseases.

Mots clés : intrinsic disorder in proteins, databases, prediction, machine learning, ontology, protein structure

Participants :
- Université autonome de Barcelone (Espagne) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 230000.0 €
- Institut national de la santé et de la recherche médicale (France) — Partner, associated partner, Recherche, subvention : 0.0 €
- Université Loránd Eötvös (Hongrie) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 230000.0 €
- Université nationale de San Martín (Argentine) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- Université de Padoue (Italie) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 404800.0 €
- Centre national de la recherche scientifique (France) — Partner, beneficiary, Recherche, subvention : 280600.0 €
- Vrije Universiteit Brussel (Belgique) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 170200.0 €
- Fundación Instituto Leloir (Argentine) — Partner, associated partner, Recherche, subvention : 0.0 €
- Université de Toulouse (France) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- Université nationale du Littoral (Argentine) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- National University of Quilmes (Argentine) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- Université nationale de La Plata (Argentine) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- Laboratoire européen de biologie moléculaire (Allemagne) — Partner, beneficiary, Recherche, subvention : 170200.0 €
- Université Johannes-Gutenberg de Mayence (Allemagne) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 170200.0 €