Preprint
Using AlphaFold Multimer to discover interkingdom protein-protein interactions
- Abstract:
- Structural prediction by artificial intelligence (AI) can be powerful new instruments to discover novel protein-protein interactions, but the community still grapples with the implementation, opportunities and limitations. Here, we discuss and re-analyse our in-silico screen for novel pathogen-secreted inhibitors of immune hydrolases to illustrate the power and limitations of structural predictions. We discuss strategies of curating sequences, including controls, and reusing sequence alignments and highlight important limitations originating from platforms, sequence depth and computing times. We hope these experiences will support similar interactomic screens by the research community.
- Publication status:
- Published
- Peer review status:
- Not peer reviewed
Actions
Access Document
- Files:
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(Preview, Pre-print, pdf, 398.5KB, Terms of use)
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- Preprint server copy:
- 10.1101/2024.06.14.599045
Authors
+ European Research Council
More from this funder
- Funder identifier:
- https://ror.org/0472cxd90
- Grant:
- 101019324
- Preprint server:
- bioRxiv
- Publication date:
- 2024-06-14
- DOI:
- Language:
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English
- Pubs id:
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2009230
- Local pid:
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pubs:2009230
- Deposit date:
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2025-04-29
Terms of use
- Copyright holder:
- Homma et al.
- Copyright date:
- 2024
- Rights statement:
- The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
- Licence:
- CC Attribution (CC BY)
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