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Protein codes promote selective subcellular compartmentalization
Open accessPreprint — published as 10.1126/science.adq2634 · Paper page
Abstract
Cells have evolved mechanisms to distribute ∼10 billion protein molecules to subcellular compartments where diverse proteins involved in shared functions must efficiently assemble. Here, we demonstrate that proteins with shared functions share amino acid sequence codes that guide them to compartment destinations. A protein language model, ProtGPS, was developed that predicts with high performance the compartment localization of human proteins excluded from the training set. ProtGPS successfully guided generation of novel protein sequences that selectively assemble in targeted subcellular compartments. ProtGPS also identified pathological mutations that change this code and lead to altered subcellular localization of proteins. Our results indicate that protein sequences contain not only a folding code, but also a previously unrecognized code governing their distribution in specific cellular compartments.
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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
- Kilgore, H. R., Chinn, I., Mikhael, P. G., Mitnikov, I., Van Dongen, C., Zylberberg, G., Afeyan, L., Banani, S., Wilson-Hawken, S., Lee, T. I., Barzilay, R., & Young, R. A.
- Affiliations
- Whitehead Institute for Biomedical Research (US)
- MIT Computer Science and Artificial Intelligence Laboratory (US)
- Brigham and Women's Hospital (US)
- Corresponding author
- Kilgore, Henry R.
- ORCID
- Venue
- Science
- Publisher
- openRxiv
- Published
- 2024-04-17
- Volume
- 387
- Issue
- 6738
- Pages
- 1095-1101
- ISSN
- 0036-8075 (ISSN-L)
- PMC
- PMC12034300
- OpenAlex
- W4407199666
- Cited by
- 99
- References
- 1
- Citations by year
- 2026: 59 · 2025: 39 · 2024: 1
- FWCI
- 29.29
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- cc-by-nc-nd
- Locations
- Science (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (submittedVersion, cc-by-nc-nd)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-sa)
- Funders
- National Science Foundation (2044895)
- Damon Runyon Cancer Research Foundation (2458-22)
- Broad Institute
- National Institutes of Health
- National Cancer Institute (P01CA155258)
- National Institute of General Medical Sciences (R35GM144283)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- Keywords
- protein localization, protein compartmentalization, protein language models, nucleolus, protein sequence design, protein function
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