Critical Assessment of Methods for Predicting the 3D Structure of Proteins and Protein Complexes

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 t...

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Veröffentlicht in:Annual review of biophysics Jg. 52; S. 183
Hauptverfasser: Wodak, Shoshana J, Vajda, Sandor, Lensink, Marc F, Kozakov, Dima, Bates, Paul A
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States 09.05.2023
Schlagworte:
Artificial Intelligence
Protein Conformation
protein interactions
CASP
CAPRI
critical assessment of structure predictions
critical assessment of predicted interactions
protein structure prediction
artificial intelligence
ISSN:1936-1238, 1936-1238
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Zusammenfassung: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.
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ISSN:1936-1238
1936-1238
DOI:10.1146/annurev-biophys-102622-084607