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AlphaFold2 enables accurate deorphanization of ligands to single-pass receptors
Open accessPreprint — published as 10.1016/j.cels.2024.10.004 · Paper page
Abstract
Secreted proteins play crucial roles in paracrine and endocrine signaling; however, identifying novel ligand-receptor interactions remains challenging. Here, we benchmarked AlphaFold as a screening approach to identify extracellular ligand-binding pairs using a structural library of single-pass transmembrane receptors. Key to the approach is the optimization of AlphaFold input and output for screening ligands against receptors to predict the most probable ligand-receptor interactions. Importantly, the predictions were performed on ligand-receptor pairs not used for AlphaFold training. We demonstrate high discriminatory power and a success rate of close to 90 % for known ligand-receptor pairs and 50 % for a diverse set of experimentally validated interactions. These results demonstrate proof-of-concept of a rapid and accurate screening platform to predict high-confidence cell-surface receptors for a diverse set of ligands by structural binding prediction, with potentially wide applicability for the understanding of cell-cell communication.
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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
A 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
- Danneskiold-Samsøe, N. B., Kavi, D., Jude, K. M., Nissen, S. B., Wat, L. W., Coassolo, L., Zhao, M., Santana-Oikawa, G. A., Broido, B. B., Garcia, K. C., & Svensson, K. J.
- Affiliations
- Stanford Medicine (US)
- Howard Hughes Medical Institute (US)
- University of Copenhagen (DK)
- Corresponding author
- Svensson, Katrin J.
- Venue
- Cell Systems
- Publisher
- openRxiv
- Published
- 2023-03-17
- Volume
- 15
- Issue
- 11
- Pages
- 1046-1060.e3
- ISSN
- 2405-4712 (ISSN-L)
- PMC
- PMC12147870
- OpenAlex
- W4404303937
- Cited by
- 35
- References
- 2
- Citations by year
- 2026: 10 · 2025: 13 · 2024: 10 · 2023: 2
- FWCI
- 4.48
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Cell Systems (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (submittedVersion, cc-by-nc-nd)
- Funders
- Howard Hughes Medical Institute (R01GM150125)
- American Heart Association (905674, 23IPA1042031, COVID-19)
- Cardiovascular Institute of Philadelphia
- Stanford Diabetes Research Center (P30DK116074)
- Carlsbergfondet
- Novo Nordisk (NNF21CC0073729)
- Novo Nordisk Fonden (NNF21CC0073729, NNF20OC0059462)
- National Institutes of Health (COVID-19)
- School of Medicine, Stanford University
- Stanford Bio-X
- National Institute of General Medical Sciences (R01GM150125)
- National Institute of Diabetes and Digestive and Kidney Diseases (R01DK125260, P30DK116074)
- National Institute of Arthritis and Musculoskeletal and Skin Diseases (K99AR081618)
- Stanford Maternal and Child Health Research Institute
- Stanford Cardiovascular Institute, School of Medicine, Stanford University
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Receptor Mechanisms and Signaling
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Keywords
- AlphaFold2, ligand-receptor interactions, deorphanization, secreted proteins, ligand screening, cell surface receptors, intercellular communication, benchmarking
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