Highly significant improvement of protein sequence alignments with AlphaFold2.
Bioinformatics
; 38(22): 5007-5011, 2022 11 15.
Article
en En
| MEDLINE
| ID: mdl-36130276
ABSTRACT
MOTIVATION Protein sequence alignments are essential to structural, evolutionary and functional analysis, but their accuracy is often limited by sequence similarity unless molecular structures are available. Protein structures predicted at experimental grade accuracy, as achieved by AlphaFold2, could therefore have a major impact on sequence analysis. RESULTS:
Here, we find that multiple sequence alignments estimated on AlphaFold2 predictions are almost as accurate as alignments estimated on experimental structures and significantly closer to the structural reference than sequence-based alignments. We also show that AlphaFold2 structural models of relatively low quality can be used to obtain highly accurate alignments. These results suggest that, besides structure modeling, AlphaFold2 encodes higher-order dependencies that can be exploited for sequence analysis. AVAILABILITY AND IMPLEMENTATION All data, analyses and results are available on Zenodo (https//doi.org/10.5281/zenodo.7031286). The code and scripts have been deposited in GitHub (https//github.com/cbcrg/msa-af2-nf) and the various containers in (https//cloud.sylabs.io/library/athbaltzis/af2/alphafold, https//hub.docker.com/r/athbaltzis/pred). SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Programas Informáticos
/
Proteínas
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
Bioinformatics
Asunto de la revista:
INFORMATICA MEDICA
Año:
2022
Tipo del documento:
Article
País de afiliación:
España