Critical Assessment of Methods for Predicting ...
Type de document :
Article dans une revue scientifique: Article de synthèse/Review paper
PMID :
URL permanente :
Titre :
Critical Assessment of Methods for Predicting the 3D Structure of Proteins and Protein Complexes
Auteur(s) :
Wodak, Shoshana J [Auteur]
VIB-VUB Center for Structural Biology [Bruxelles]
Vajda, Sandor [Auteur]
Department of Biomedical Engineering [Boston]
Boston University [Boston] [BU]
Lensink, Marc [Auteur]
Unité de Glycobiologie Structurale et Fonctionnelle (UGSF) - UMR 8576
Kozakov, Dima [Auteur]
Stony Brook University [SUNY] [SBU]
Bates, Paul A [Auteur]
Biomolecular Modelling laboratory [London]
VIB-VUB Center for Structural Biology [Bruxelles]
Vajda, Sandor [Auteur]
Department of Biomedical Engineering [Boston]
Boston University [Boston] [BU]
Lensink, Marc [Auteur]
Unité de Glycobiologie Structurale et Fonctionnelle (UGSF) - UMR 8576
Kozakov, Dima [Auteur]
Stony Brook University [SUNY] [SBU]
Bates, Paul A [Auteur]
Biomolecular Modelling laboratory [London]
Titre de la revue :
Annual Reviews of Biophysics
Nom court de la revue :
Annu Rev Biophys
Numéro :
52
Pagination :
183-206
Éditeur :
Annual Reviews
Date de publication :
2023-05-09
ISSN :
1936-1238
Mot(s)-clé(s) en anglais :
Artificial Intelligence
Protein Conformation
CAPRI
CASP
artificial intelligence
critical assessment of predicted interactions
critical assessment of structure predictions
protein interactions
protein structure prediction
Protein Conformation
CAPRI
CASP
artificial intelligence
critical assessment of predicted interactions
critical assessment of structure predictions
protein interactions
protein structure prediction
Discipline(s) HAL :
Chimie/Chimie théorique et/ou physique
Résumé en anglais : [en]
Advances in a scientific discipline are often measured by small, incremental steps. In this review, we report on two intertwined disciplines in the protein structure prediction field, modeling of single chains and modeling ...
Lire la suite >Advances in a scientific discipline are often measured by small, incremental steps. In this review, we report on two intertwined disciplines in the protein structure prediction field, modeling of single chains and modeling of complexes, that have over decades emulated this pattern, as monitored by the community-wide blind prediction experiments CASP and CAPRI. However, over the past few years, dramatic advances were observed for the accurate prediction of single protein chains, driven by a surge of deep learning methodologies entering the prediction field. We review the mainscientific developments that enabled these recent breakthroughs and feature the important role of blind prediction experiments in building up and nurturing the structure prediction field. We discuss how the new wave of artificial intelligence-based methods is impacting the fields of computational and experimental structural biology and highlight areas in which deep learning methods are likely to lead to future developments, provided that major challenges are overcome.Lire moins >
Lire la suite >Advances in a scientific discipline are often measured by small, incremental steps. In this review, we report on two intertwined disciplines in the protein structure prediction field, modeling of single chains and modeling of complexes, that have over decades emulated this pattern, as monitored by the community-wide blind prediction experiments CASP and CAPRI. However, over the past few years, dramatic advances were observed for the accurate prediction of single protein chains, driven by a surge of deep learning methodologies entering the prediction field. We review the mainscientific developments that enabled these recent breakthroughs and feature the important role of blind prediction experiments in building up and nurturing the structure prediction field. We discuss how the new wave of artificial intelligence-based methods is impacting the fields of computational and experimental structural biology and highlight areas in which deep learning methods are likely to lead to future developments, provided that major challenges are overcome.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Établissement(s) :
Université de Lille
CNRS
CNRS
Équipe(s) de recherche :
Computational Molecular Systems Biology
Date de dépôt :
2023-10-20T13:22:36Z
2023-10-25T07:40:17Z
2023-11-09T18:32:33Z
2023-10-25T07:40:17Z
2023-11-09T18:32:33Z
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- wodak-et-al-2023-critical-assessment-of-methods-for-predicting-the-3d-structure-of-proteins-and-protein-complexes.pdf
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