Assessment of the CASP14 assembly predictions.
Proteins
; 89(12): 1787-1799, 2021 12.
Article
en En
| MEDLINE
| ID: mdl-34337786
ABSTRACT
In CASP14, 39 research groups submitted more than 2500 3D models on 22 protein complexes. In general, the community performed well in predicting the fold of the assemblies (for 80% of the targets), although it faced significant challenges in reproducing the native contacts. This is especially the case for the complexes without whole-assembly templates. The leading predictor, BAKER-experimental, used a methodology combining classical techniques (template-based modeling, protein docking) with deep learning-based contact predictions and a fold-and-dock approach. The Venclovas team achieved the runner-up position with template-based modeling and docking. By analyzing the target interfaces, we showed that the complexes with depleted charged contacts or dominating hydrophobic interactions were the most challenging ones to predict. We also demonstrated that if AlphaFold2 predictions were at hand, the interface prediction challenge could be alleviated for most of the targets. All in all, it is evident that new approaches are needed for the accurate prediction of assemblies, which undoubtedly will expand on the significant improvements in the tertiary structure prediction field.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Conformación Proteica
/
Programas Informáticos
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Proteínas
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Modelos Moleculares
Tipo de estudio:
Prognostic_studies
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Risk_factors_studies
Idioma:
En
Revista:
Proteins
Asunto de la revista:
BIOQUIMICA
Año:
2021
Tipo del documento:
Article
País de afiliación:
Turquía