AlphaPulldown—a python package for protein–protein interaction screens using AlphaFold-Multimer
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Abstract
SUMMARY: The artificial intelligence-based structure prediction program AlphaFold-Multimer enabled structural modelling of protein complexes with unprecedented accuracy. Increasingly, AlphaFold-Multimer is also used to discover new protein-protein interactions (PPIs). Here, we present AlphaPulldown, a Python package that streamlines PPI screens and high-throughput modelling of higher-order oligomers using AlphaFold-Multimer. It provides a convenient command-line interface, a variety of confidence scores and a graphical analysis tool. AVAILABILITY AND IMPLEMENTATION: AlphaPulldown is freely available at https://www.embl-hamburg.de/AlphaPulldown. SUPPLEMENTARY INFORMATION: Supplementary note is available at Bioinformatics online.
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AlphaFold-Multimer is being used to uncover protein-protein interactions on the scale of pathways and organisms.
“AF-M is being used to uncover PPIs on the scale of pathways and organisms15–24.”
From Predictomes, a classifier-curated database of AlphaFold-modeled protein-protein interactions (2025) · cites this paper as [21]
The Introduction says AlphaFold-Multimer can screen large protein datasets for new PPIs, and §2.3.1 reports a screen involving proteins in the human translation pathway. The paper also describes predicting interaction networks (§2.3.2), but our copy does not establish that it has been used to uncover PPIs at organism-wide scale. (LLM, conf=0.85)
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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 · see citing works
ColabFold - Making protein folding accessible to all
Mirdita, M., Schütze, K., Moriwaki, Y., Heo, L., Ovchinnikov, S., & Steinegger, M. (2021) · doi:10.1101/2021.08.15.456425 · Cited by 9,391 · see citing works
MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets
Steinegger, M., & Söding, J. (2017) · Nature Biotechnology · doi:10.1038/nbt.3988 · Cited by 4,840 · see citing works
Protein complex prediction with AlphaFold-Multimer
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Improved prediction of protein-protein interactions using AlphaFold2
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AI-based structure prediction empowers integrative structural analysis of human nuclear pores
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From interaction networks to interfaces, scanning intrinsically disordered regions using AlphaFold2
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- Authors
- Yu, D., Chojnowski, G., Rosenthal, M., & Kosinski, J.
- Affiliations
- European Molecular Biology Laboratory (DE)
- Bernhard Nocht Institute for Tropical Medicine (DE)
- European Molecular Biology Laboratory Hamburg , Hamburg 22607, Germany
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2022-11-22
- Volume
- 39
- Issue
- 1
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- PMC
- PMC9805587
- OpenAlex
- W4309588718
- Cited by
- 162
- References
- 9
- Citations by year
- 2026: 37 · 2025: 57 · 2024: 44 · 2023: 23 · 2022: 1
- Type
- software paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Bioinformatics (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- German Research Foundation
- DFG (KO 5979/2-1)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- protein-protein interaction, AlphaFold-Multimer, protein complex structure prediction, confidence scores, Python library, command-line interface
- MeSH terms
- Artificial Intelligence, Software
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