Comprehensive Collection and Prediction of ABC Transmembrane Protein Structures in the AI Era of Structural Biology
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Abstract
The number of unique transmembrane (TM) protein structures doubled in the last four years, which 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 the 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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Cites
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 · see citing works
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Self-citationProtein complex prediction with AlphaFold-Multimer
Evans, R., O’Neill, M., Pritzel, A., Antropova, N., Senior, A., Green, T., Žídek, A., Bates, R., Blackwell, S., Yim, J., et al. (2021) · doi:10.1101/2021.10.04.463034 · Cited by 3,808 · see citing works
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High‐accuracy protein structure prediction in <scp>CASP14</scp>
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“Researchers utilized enormous resources in the last decades to predict protein structures from sequence information [20].”
BackgroundABCG2 transports anticancer drugs via a closed-to-open switch
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Ins and outs of AlphaFold2 transmembrane protein structure predictions
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Challenges in bridging the gap between protein structure prediction and functional interpretation
Varadi, M., Tsenkov, M., & Velankar, S. (2025) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.26614 · Cited by 36 · see citing works
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- Authors
- Tordai, H., Suhajda, E., Sillitoe, I., Nair, S., Varadi, M., & Hegedus, T.
- Affiliations
- Semmelweis University (HU)
- Department of Biophysics and Radiation Biology, Semmelweis University, 1085 Budapest, Hungary
- Institute of Structural and Molecular Biology (GB)
- European Bioinformatics Institute (GB)
- European Bioinformatics Institute, European Molecular Biology Laboratory, Hinxton CB10 1SD, UK
- Venue
- International Journal of Molecular Sciences
- Publisher
- MDPI AG
- Published
- 2022-08-09
- Volume
- 23
- Issue
- 16
- Pages
- 8877
- ISSN
- 1422-0067 (ISSN-L)
- PMC
- PMC9408558
- OpenAlex
- W4292074325
- Cited by
- 22
- References
- 7
- 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
- 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
- NRDIO/NKFIH (K127961, K137610, 2020-2.1.1-ED-2021-00179, HEGEDU20I0, BB/S020071/1)
- Cystic Fibrosis Foundation (CFF) (K127961, K137610, 2020-2.1.1-ED-2021-00179, HEGEDU20I0, BB/S020071/1)
- BBSRC (K127961, K137610, 2020-2.1.1-ED-2021-00179, HEGEDU20I0, BB/S020071/1)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Materials Science › Materials Chemistry › 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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