Prediction of protein structure and AI.
J Hum Genet
; 69(10): 477-480, 2024 Oct.
Article
en En
| MEDLINE
| ID: mdl-38177398
ABSTRACT
AlphaFold, an artificial intelligence (AI)-based tool for predicting the 3D structure of proteins, is now widely recognized for its high accuracy and versatility in the folding of human proteins. AlphaFold is useful for understanding structure-function relationships from protein 3D structure models and can serve as a template or a reference for experimental structural analysis including X-ray crystallography, NMR and cryo-EM analysis. Its use is expanding among researchers, not only in structural biology but also in other research fields. Researchers are currently exploring the full potential of AlphaFold-generated protein models. Predicting disease severity caused by missense mutations is one such application. This article provides an overview of the 3D structural modeling of AlphaFold based on deep learning techniques and highlights the challenges in predicting the pathogenicity of missense mutations.
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Conformación Proteica
/
Inteligencia Artificial
/
Proteínas
/
Modelos Moleculares
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
J Hum Genet
Asunto de la revista:
GENETICA MEDICA
Año:
2024
Tipo del documento:
Article
País de afiliación:
Japón