Informace o publikaci
EnzymeMiner 2.0: advancing automated enzyme discovery with expansive sequence mining and smart property analysis
| Autoři | |
|---|---|
| Rok publikování | 2026 |
| Druh | Recenzovaný odborný článek |
| Časopis / Zdroj | Nucleic acids research |
| Fakulta / Pracoviště MU | |
| Citace | |
| www | https://academic.oup.com/nar/article/54/W1/W257/8675561 |
| Doi | https://doi.org/10.1093/nar/gkag424 |
| Klíčová slova | HALOALKANE DEHALOGENASES |
| Přiložené soubory | |
| Popis | Enhancing enzymes to improve desired properties remains an expensive and time-consuming process. Scanning databases of known protein sequences to find enzymes with similar catalytic activity and enhanced properties is an efficient and valuable approach. The EnzymeMiner web server has proven integral as an automated, user-friendly tool that identifies enzymes with the desired catalytic activity from provided sequences and essential residues. Here, we introduce EnzymeMiner 2.0 that builds upon its predecessor, retaining its original functionality, while introducing several key improvements: (i) significantly expanded searched protein space; (ii) annotation of discovered sequences with predictions of the melting temperature, optimal pH, catalytic activity and efficiency, and aggregation propensity with state-of-the-art computational tools; and (iii) smart automatic sequence prioritization and filtering based on user-defined goals or a set of predefined scenarios. With all these enhancements, EnzymeMiner 2.0 aims to remain among the leading solutions for efficient discovery of novel enzymes. The server is freely accessible at https://loschmidt.chemi.muni.cz/enzymeminer/. |
| Související projekty: |