Machine-Learning Prediction of Extracellular Vesicle Protein Sorting Expands the Characterization of Secretory Functions in Mucor circinelloides
João Neves-da-Rocha, Marcos E. R. Lopes, Lucas F. Nogueira, Shaghayegh Moghadam, Felipe E. A. De Paiva, Fausto Almeida · 2026
Read Machine-Learning Prediction of Extracellular Vesicle Protein Sorting Expands the Characterization of Secretory Functions in Mucor circinelloides by João Neves-da-Rocha, Marcos E. R. Lopes, Lucas F. Nogueira, Shaghayegh Moghadam, Felipe E. A. De Paiva, Fausto Almeida (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/PMC13301921.txt.
Description
Predicting which proteins a fungus ships out in tiny vesicles can be done from sequence alone, João Neves-da-Rocha and colleagues show in a 2026 computational study of Mucor circinelloides. The fungus matters twice over: it causes dangerous mucormycosis in vulnerable patients and yields useful enzymes for industry. The team first catalogued its full secreted protein set in silico.
A random forest trained on trusted vesicle datasets from other organisms then sorted the fungal proteins for vesicle cargo. The predicted vesicle proteome echoed patterns seen in human vesicles, suggesting the model reads real sorting signals. Carbohydrate-cutting enzymes featured richly in the secretome, feeding both the virulence and the biotechnology sides of the story.
Catalog record
| CREATOR | João Neves-da-Rocha, Marcos E. R. Lopes, Lucas F. Nogueira, Shaghayegh Moghadam, Felipe E. A. De Paiva, Fausto Almeida |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 51027 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |