Accurate structure prediction of biomolecular interactions with AlphaFold 3.
Nature
; 630(8016): 493-500, 2024 Jun.
Article
em En
| MEDLINE
| ID: mdl-38718835
ABSTRACT
The introduction of AlphaFold 21 has spurred a revolution in modelling the structure of proteins and their interactions, enabling a huge range of applications in protein modelling and design2-6. Here we describe our AlphaFold 3 model with a substantially updated diffusion-based architecture that is capable of predicting the joint structure of complexes including proteins, nucleic acids, small molecules, ions and modified residues. The new AlphaFold model demonstrates substantially improved accuracy over many previous specialized tools far greater accuracy for protein-ligand interactions compared with state-of-the-art docking tools, much higher accuracy for protein-nucleic acid interactions compared with nucleic-acid-specific predictors and substantially higher antibody-antigen prediction accuracy compared with AlphaFold-Multimer v.2.37,8. Together, these results show that high-accuracy modelling across biomolecular space is possible within a single unified deep-learning framework.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Software
/
Proteínas
/
Modelos Moleculares
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Aprendizado Profundo
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Ligantes
Limite:
Humans
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article