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Current structure predictors are not learning the physics of protein folding

Abstract:

Summary

Motivation. Predicting the native state of a protein has long been considered a gateway problem for understanding protein folding. Recent advances in structural modeling driven by deep learning have achieved unprecedented success at predicting a protein’s crystal structure, but it is not clear if these models are learning the physics of how proteins dynamically fold into their equilibrium structure or are just accurate knowledge-based predic...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1093/bioinformatics/btab881

Authors


More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Oxford college:
Green Templeton College
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Author
ORCID:
0000-0003-1388-2252
Publisher:
Oxford University Press Publisher's website
Journal:
Bioinformatics Journal website
Volume:
38
Issue:
7
Pages:
1881–1887
Publication date:
2022-01-31
Acceptance date:
2021-12-29
DOI:
EISSN:
1460-2059
ISSN:
1367-4803
Language:
English
Keywords:
Pubs id:
1230307
Local pid:
pubs:1230307
Deposit date:
2022-01-07

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