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AlphaFold heralds a data-driven revolution in biology and medicine
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“the AF2 model of insulin deviates significantly from its experimental NMR structure (Fig. 2b), potentially due to the inability of AF2 to orient cysteine pairs for disulfide bond formation31”
From The power and pitfalls of AlphaFold2 for structure prediction beyond rigid globular proteins (2024) · cites this paper as [31]
Citations
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Metadata
- Authors
- Thornton, J. M., Laskowski, R. A., & Borkakoti, N.
- Affiliations
- European Bioinformatics Institute (GB)
- Corresponding author
- Thornton, Janet M.
- Venue
- Nature Medicine
- Published
- 2021-10
- Volume
- 27
- Issue
- 10
- Pages
- 1666-1669
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- OpenAlex
- W3207457994
- Cited by
- 185
- References
- 17
- Citations by year
- 2026: 14 · 2025: 22 · 2024: 41 · 2023: 57 · 2022: 46 · 2021: 5
- FWCI
- 11.69
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Nature Medicine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Keywords
- AlphaFold, protein structure prediction, artificial intelligence in biology, clinical data, human disease, data-driven medicine
- MeSH terms
- Artificial Intelligence, Humans, Protein Conformation, Proteins, Software, Biomedical Research
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