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Pipeline using NMR

Combining deep learning and NMR for protein analysis

Nuclear Magnetic Resonance (NMR) spectroscopy helps scientists understand how proteins are structured and behave. While NMR commonly focuses on the backbone and methyl-bearing side chains of proteins, analysing aromatic side chains, often crucial for protein function, is more difficult. To overcome this, researchers at the Crick and UCL developed a deep learning tool named FID-Net-2. By combining innovative developments in biomolecular NMR with advanced deep learning, FID-Net-2 substantially enhances the quality and resolution of NMR data for aromatic side chains. This allows insights into the mechanism of protein dynamics like folding. This approach works across various protein sizes and promises to improve NMR analysis in structural biology.

A combined NMR and deep neural network approach for enhancing the spectral resolution of aromatic side chains in proteins

Published in Science advances

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Research case studies 

Explore a selection of recent case studies that spotlight particular areas of research at the Crick.