DeepNOE: Leveraging deep learning for protein structure solving at ultra-high resolution on the basis of NMR measurements with exact nuclear Overhauser enhancement

Project description

Ultra-high resolution protein structure on the basis of NMR measurements

Nuclear magnetic resonance (NMR) spectroscopy is essential for protein structure analysis allowing the measurement of the dynamics and structure of a protein under nearly physiological conditions. Recent studies on exact nuclear Overhauser enhancements (eNOEs) have enabled distance measurements in proteins by NMR with an accuracy of 0.1 Å. The EU-funded DeepNOE project aims to develop the innovative model/algorithm that automatically transforms raw NMR measurements into high-resolution protein structures that reveal multiple simultaneously populated conformational states in atomic detail. The study will include the application of deep learning, a novel field in machine learning that has revolutionised data science and artificial intelligence.

Fields of science

• natural sciences › chemical sciences › analytical chemistry › spectroscopy
• natural sciences › biological sciences › biochemistry › biomolecules › proteins
• natural sciences › biological sciences › molecular biology › structural biology
• natural sciences › computer and information sciences › data science
• natural sciences › computer and information sciences › artificial intelligence › machine learning › deep learning

Programme(s)

• H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility

Topic(s)

• MSCA-IF-2019 - Individual Fellowships

Call for proposal

H2020-MSCA-IF-2019
See other projects for this call

Funding Scheme

MSCA-IF-EF-ST - Standard EF

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Coordinator

EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH

Address

Raemistrasse 101
8092 Zuerich
Switzerland

Activity type

Higher or Secondary Education Establishments

EU contribution

€ 191 149,44