Improved protein structure refinement guided by deep learning based accuracy estimation

We develop a deep learning framework (DeepAccNet) that estimates per-residue accuracy and residue-residue distance signed error in protein models and uses these predictions to guide Rosetta protein structure refinement. The network uses 3D convolutions to evaluate local atomic environments followed...

Descripción completa

Detalles Bibliográficos
Autores principales: Hiranuma, Naozumi, Park, Hahnbeom, Baek, Minkyung, Anishchenko, Ivan, Dauparas, Justas, Baker, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7910447/
https://www.ncbi.nlm.nih.gov/pubmed/33637700
http://dx.doi.org/10.1038/s41467-021-21511-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7910447/
https://www.ncbi.nlm.nih.gov/pubmed/33637700
http://dx.doi.org/10.1038/s41467-021-21511-x

Ejemplares similares