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BFVD - a large repository of predicted viral protein structures
Open accessPreprint — published as 10.1093/nar/gkae1119 · Paper page
Abstract
The AlphaFold Protein Structure Database (AFDB) is the largest repository of accurately predicted structures with taxonomic labels. Despite providing predictions for over 214 million UniProt entries, the AFDB does not cover viral sequences, severely limiting their study. To bridge this gap, we created the Big Fantastic Virus Database (BFVD), a repository of 351,242 protein structures predicted by applying ColabFold to the viral sequence representatives of the UniRef30 clusters. BFVD holds a unique repertoire of protein structures as over 63% of its entries show no or low structural similarity to existing repositories. We demonstrate how BFVD substantially enhances the fraction of annotated bacteriophage proteins compared to sequence-based annotation using Bakta. In that, BFVD is on par with the AFDB, while holding nearly three orders of magnitude fewer structures. BFVD is an important virus-specific expansion to protein structure repositories, offering new opportunities to advance viral research. BFVD is freely available at https://bfvd.steineggerlab.workers.dev/
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Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764
Self-citationVaradi, M., Bertoni, D., Magana, P., Paramval, U., Pidruchna, I., Radhakrishnan, M., Tsenkov, M., Nair, S., Mirdita, M., Yeo, J., et al. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkad1011 · Cited by 2,052
Self-citationA structural biology community assessment of AlphaFold2 applications
Akdel, M., Pires, D. E. V., Pardo, E. P., Jänes, J., Zalevsky, A. O., Mészáros, B., Bryant, P., Good, L. L., Laskowski, R. A., Pozzati, G., et al. (2022) · Nature Structural & Molecular Biology · doi:10.1038/s41594-022-00849-w · Cited by 675
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Metadata
- Authors
- Kim, R. S., Karin, E. L., & Steinegger, M.
- Affiliations
- Seoul National University (KR)
- Corresponding author
- Steinegger, Martin
- Venue
- Nucleic Acids Research
- Publisher
- openRxiv
- Published
- 2024-09-09
- Volume
- 53
- Issue
- D1
- Pages
- D340-D347
- ISSN
- 0305-1048 (ISSN-L)
- PMC
- PMC11701548
- OpenAlex
- W4404642782
- Cited by
- 86
- References
- 3
- Citations by year
- 2026: 40 · 2025: 41 · 2024: 5
- FWCI
- 11.67
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Nucleic Acids Research (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- HAL (submittedVersion, cc-by)
- Seoul National University Open Repository (Seoul National University) (submittedVersion)
- Funders
- National Research Foundation (RS-2024-00396026, 2021-R1C1-C102065)
- Seoul National University
- University of Toronto
- National Research Foundation of Korea (2021-R1C1-C102065, 2021-M3A9-I4021220, 2020M3‐A9G7‐103933, RS-2024-00396026, RS-2023-00250470)
- Samsung
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Keywords
- viral protein structure, protein structure prediction, ColabFold, homology modeling, bacteriophage proteins
- MeSH terms
- Bacteriophages, Models, Molecular, Protein Conformation, Viral Proteins, Databases, Protein
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