Biomolecular NMR spectroscopy in the era of artificial intelligence.
Structure
; 31(11): 1360-1374, 2023 11 02.
Article
em En
| MEDLINE
| ID: mdl-37848030
ABSTRACT
Biomolecular nuclear magnetic resonance (NMR) spectroscopy and artificial intelligence (AI) have a burgeoning synergy. Deep learning-based structural predictors have forever changed structural biology, yet these tools currently face limitations in accurately characterizing protein dynamics, allostery, and conformational heterogeneity. We begin by highlighting the unique abilities of biomolecular NMR spectroscopy to complement AI-based structural predictions toward addressing these knowledge gaps. We then highlight the direct integration of deep learning approaches into biomolecular NMR methods. AI-based tools can dramatically improve the acquisition and analysis of NMR spectra, enhancing the accuracy and reliability of NMR measurements, thus streamlining experimental processes. Additionally, deep learning enables the development of novel types of NMR experiments that were previously unattainable, expanding the scope and potential of biomolecular NMR spectroscopy. Ultimately, a combination of AI and NMR promises to further revolutionize structural biology on several levels, advance our understanding of complex biomolecular systems, and accelerate drug discovery efforts.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Inteligência Artificial
/
Descoberta de Drogas
Idioma:
En
Revista:
Structure
Assunto da revista:
BIOLOGIA MOLECULAR
/
BIOQUIMICA
/
BIOTECNOLOGIA
Ano de publicação:
2023
Tipo de documento:
Article
País de afiliação:
Reino Unido