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Comprehensive collection and prediction of ABC transmembrane protein structures in the AI era of structural biology
Open accessPreprint — published as 10.3390/ijms23168877 · Paper page
Abstract
The number of unique transmembrane (TM) protein structures doubled in the last four years that can be attributed to the revolution of cryo-electron microscopy. In addition, AlphaFold2 (AF2) also provided a large number of predicted structures with high quality. However, if a specific protein family is the subject of a study, collecting the structures of the family members is highly challenging in spite of existing general and protein domain-specific databases. Here, we demonstrate this and assess the applicability and usability of automatic collection and presentation of protein structures via the ABC protein superfamily. Our pipeline identifies and classifies transmembrane ABC protein structures using PFAM search and also aims to determine their conformational states based on special geometric measures, conftors. Since the AlphaFold database contains structure predictions only for single polypeptide chains, we performed AF2-Multimer predictions for human ABC half transporters functioning as dimers. Our AF2 predictions warn of possibly ambiguous interpretation of some biochemical data regarding interaction partners and call for further experiments and experimental structure determination. We made our predicted ABC protein structures available through a web application, and we joined the 3D-Beacons Network to reach the broader scientific community through platforms such as PDBe-KB.
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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
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Metadata
- Authors
- Tordai, H., Suhajda, E., Sillitoe, I., Nair, S., Váradi, M., & Hegedűs, T.
- Affiliations
- Semmelweis University (HU)
- Institute of Structural and Molecular Biology (GB)
- European Bioinformatics Institute (GB)
- Corresponding author
- Hegedűs, Tamás
- Venue
- International Journal of Molecular Sciences
- Publisher
- openRxiv
- Published
- 2022-07-10
- Volume
- 23
- Issue
- 16
- Pages
- 8877-8877
- ISSN
- 1422-0067 (ISSN-L)
- PMC
- PMC9408558
- OpenAlex
- W4292074325
- Cited by
- 22
- References
- 1
- Citations by year
- 2025: 7 · 2024: 6 · 2023: 3 · 2022: 6
- FWCI
- 1.80
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- International Journal of Molecular Sciences (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- Cystic Fibrosis Foundation (2020-2.1.1-ED-2021-00179, HEGEDU20I0, K127961, BB/S020071/1, K137610)
- Nemzeti Kutatási Fejlesztési és Innovációs Hivatal (2020-2.1.1-ED-2021-00179, 2020-2.1.1-ED, K127961)
- Biotechnology and Biological Sciences Research Council (2020-2.1.1-ED-2021-00179, BB/S020071/1, K127961, HEGEDU20I0, 2.1.1, K137610)
- National Research, Development and Innovation Office (K137610, K127961, and 2020-2.1.1-ED-2021-00179)
- 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
- Health Sciences › Medicine › Oncology › Drug Transport and Resistance Mechanisms
- Keywords
- ABC transporters, transmembrane proteins, protein structure prediction, AlphaFold2, conformational states, web application
- MeSH terms
- Artificial Intelligence, Biology, Furylfuramide, Humans, Models, Molecular, Protein Conformation, ATP-Binding Cassette Transporters, Cryoelectron Microscopy
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