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| Format: | Artículo científico |
| Language: | en |
| Published: |
Nucleic acids research
2026
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| Subjects: | |
| Online Access: | https://pubmed.ncbi.nlm.nih.gov/41001881/ |
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| _version_ | 1868266149463982082 |
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| author | Rutz, Adriano Probst, Daniel Aguilar, César Akiyama, Daniel Y Alberti, Fabrizio Augustijn, Hannah E Avalon, Nicole E Beemelmanns, Christine Barbieri, Hellen Bertoletti Biermann, Friederike Bridge, Alan J Girón, Esteban Charria Cox, Russell Crüsemann, Max D'Agostino, Paul M Feuermann, Marc Gerke, Jennifer García, Karina Gutiérrez Holme, Jonathan E Hwang, Ji-Yeon Iacovelli, Riccardo Jeronimo Barbosa, Júlio César Kaur, Navneet Klapper, Martin Köhler, Anna M Korenskaia, Aleksandra Kubach, Noel Lee, Byung T Loureiro, Catarina Mantri, Shrikant Narula, Simran Meijer, David Navarro-Muñoz, Jorge C Nguyen, Giang-Son Paliyal, Sunaina Panghal, Mohit Rao, Latika Sieber, Simon Sokolova, Nika Sowa, Sven T Szenei, Judit Terlouw, Barbara R Weddeling, Heiner G Yu, Jingwei Ziemert, Nadine Weber, Tilmann Blin, Kai van der Hooft, Justin J J Medema, Marnix H Zdouc, Mitja M |
| author_facet | Rutz, Adriano Probst, Daniel Aguilar, César Akiyama, Daniel Y Alberti, Fabrizio Augustijn, Hannah E Avalon, Nicole E Beemelmanns, Christine Barbieri, Hellen Bertoletti Biermann, Friederike Bridge, Alan J Girón, Esteban Charria Cox, Russell Crüsemann, Max D'Agostino, Paul M Feuermann, Marc Gerke, Jennifer García, Karina Gutiérrez Holme, Jonathan E Hwang, Ji-Yeon Iacovelli, Riccardo Jeronimo Barbosa, Júlio César Kaur, Navneet Klapper, Martin Köhler, Anna M Korenskaia, Aleksandra Kubach, Noel Lee, Byung T Loureiro, Catarina Mantri, Shrikant Narula, Simran Meijer, David Navarro-Muñoz, Jorge C Nguyen, Giang-Son Paliyal, Sunaina Panghal, Mohit Rao, Latika Sieber, Simon Sokolova, Nika Sowa, Sven T Szenei, Judit Terlouw, Barbara R Weddeling, Heiner G Yu, Jingwei Ziemert, Nadine Weber, Tilmann Blin, Kai van der Hooft, Justin J J Medema, Marnix H Zdouc, Mitja M Rutz, Adriano Probst, Daniel Aguilar, César Akiyama, Daniel Y Alberti, Fabrizio Augustijn, Hannah E Avalon, Nicole E Beemelmanns, Christine Barbieri, Hellen Bertoletti Biermann, Friederike Bridge, Alan J Girón, Esteban Charria Cox, Russell Crüsemann, Max D'Agostino, Paul M Feuermann, Marc Gerke, Jennifer García, Karina Gutiérrez Holme, Jonathan E Hwang, Ji-Yeon Iacovelli, Riccardo Jeronimo Barbosa, Júlio César Kaur, Navneet Klapper, Martin Köhler, Anna M Korenskaia, Aleksandra Kubach, Noel Lee, Byung T Loureiro, Catarina Mantri, Shrikant Narula, Simran Meijer, David Navarro-Muñoz, Jorge C Nguyen, Giang-Son Paliyal, Sunaina Panghal, Mohit Rao, Latika Sieber, Simon Sokolova, Nika Sowa, Sven T Szenei, Judit Terlouw, Barbara R Weddeling, Heiner G Yu, Jingwei Ziemert, Nadine Weber, Tilmann Blin, Kai van der Hooft, Justin J J Medema, Marnix H Zdouc, Mitja M |
| collection | PubMed - marine biology |
| contents | MITE: the Minimum Information about a Tailoring Enzyme database for capturing specialized metabolite biosynthesis. Rutz, Adriano Probst, Daniel Aguilar, César Akiyama, Daniel Y Alberti, Fabrizio Augustijn, Hannah E Avalon, Nicole E Beemelmanns, Christine Barbieri, Hellen Bertoletti Biermann, Friederike Bridge, Alan J Girón, Esteban Charria Cox, Russell Crüsemann, Max D'Agostino, Paul M Feuermann, Marc Gerke, Jennifer García, Karina Gutiérrez Holme, Jonathan E Hwang, Ji-Yeon Iacovelli, Riccardo Jeronimo Barbosa, Júlio César Kaur, Navneet Klapper, Martin Köhler, Anna M Korenskaia, Aleksandra Kubach, Noel Lee, Byung T Loureiro, Catarina Mantri, Shrikant Narula, Simran Meijer, David Navarro-Muñoz, Jorge C Nguyen, Giang-Son Paliyal, Sunaina Panghal, Mohit Rao, Latika Sieber, Simon Sokolova, Nika Sowa, Sven T Szenei, Judit Terlouw, Barbara R Weddeling, Heiner G Yu, Jingwei Ziemert, Nadine Weber, Tilmann Blin, Kai van der Hooft, Justin J J Medema, Marnix H Zdouc, Mitja M Enzymes Substrate Specificity Software Humans Machine Learning Computational Biology Internet Databases, Protein Secondary or specialized metabolites show extraordinary structural diversity and potent biological activities relevant for clinical and industrial applications. The biosynthesis of these metabolites usually starts with the assembly of a core 'scaffold', which is subsequently modified by tailoring enzymes to define the molecule's final structure and, in turn, its biological activity profile. Knowledge about reaction and substrate specificity of tailoring enzymes is essential for understanding and computationally predicting metabolite biosynthesis, but this information is usually scattered in the literature. Here, we present MITE, the Minimum Information about a Tailoring Enzyme database. MITE employs a comprehensive set of parameters to annotate tailoring enzymes, defining substrate and reaction specificity by the expressive reaction SMARTS (Simplified Molecular Input Line Entry System Arbitrary Target Specification) chemical pattern language. Both human and machine readable, MITE can be used as a knowledge base, for in silico biosynthesis, or to train machine-learning applications, and tightly integrates with existing resources. Designed as a community-driven and open resource, MITE employs a rolling release model of data curation and expert review. MITE is freely accessible at https://mite.bioinformatics.nl/. |
| format | Artículo científico |
| id | pubmed_41001881 |
| institution | PubMed |
| language | en |
| publishDate | 2026 |
| publisher | Nucleic acids research |
| record_format | pubmed |
| spellingShingle | MITE: the Minimum Information about a Tailoring Enzyme database for capturing specialized metabolite biosynthesis. Rutz, Adriano Probst, Daniel Aguilar, César Akiyama, Daniel Y Alberti, Fabrizio Augustijn, Hannah E Avalon, Nicole E Beemelmanns, Christine Barbieri, Hellen Bertoletti Biermann, Friederike Bridge, Alan J Girón, Esteban Charria Cox, Russell Crüsemann, Max D'Agostino, Paul M Feuermann, Marc Gerke, Jennifer García, Karina Gutiérrez Holme, Jonathan E Hwang, Ji-Yeon Iacovelli, Riccardo Jeronimo Barbosa, Júlio César Kaur, Navneet Klapper, Martin Köhler, Anna M Korenskaia, Aleksandra Kubach, Noel Lee, Byung T Loureiro, Catarina Mantri, Shrikant Narula, Simran Meijer, David Navarro-Muñoz, Jorge C Nguyen, Giang-Son Paliyal, Sunaina Panghal, Mohit Rao, Latika Sieber, Simon Sokolova, Nika Sowa, Sven T Szenei, Judit Terlouw, Barbara R Weddeling, Heiner G Yu, Jingwei Ziemert, Nadine Weber, Tilmann Blin, Kai van der Hooft, Justin J J Medema, Marnix H Zdouc, Mitja M Enzymes Substrate Specificity Software Humans Machine Learning Computational Biology Internet Databases, Protein MITE: the Minimum Information about a Tailoring Enzyme database for capturing specialized metabolite biosynthesis. Rutz, Adriano Probst, Daniel Aguilar, César Akiyama, Daniel Y Alberti, Fabrizio Augustijn, Hannah E Avalon, Nicole E Beemelmanns, Christine Barbieri, Hellen Bertoletti Biermann, Friederike Bridge, Alan J Girón, Esteban Charria Cox, Russell Crüsemann, Max D'Agostino, Paul M Feuermann, Marc Gerke, Jennifer García, Karina Gutiérrez Holme, Jonathan E Hwang, Ji-Yeon Iacovelli, Riccardo Jeronimo Barbosa, Júlio César Kaur, Navneet Klapper, Martin Köhler, Anna M Korenskaia, Aleksandra Kubach, Noel Lee, Byung T Loureiro, Catarina Mantri, Shrikant Narula, Simran Meijer, David Navarro-Muñoz, Jorge C Nguyen, Giang-Son Paliyal, Sunaina Panghal, Mohit Rao, Latika Sieber, Simon Sokolova, Nika Sowa, Sven T Szenei, Judit Terlouw, Barbara R Weddeling, Heiner G Yu, Jingwei Ziemert, Nadine Weber, Tilmann Blin, Kai van der Hooft, Justin J J Medema, Marnix H Zdouc, Mitja M Enzymes Substrate Specificity Software Humans Machine Learning Computational Biology Internet Databases, Protein Secondary or specialized metabolites show extraordinary structural diversity and potent biological activities relevant for clinical and industrial applications. The biosynthesis of these metabolites usually starts with the assembly of a core 'scaffold', which is subsequently modified by tailoring enzymes to define the molecule's final structure and, in turn, its biological activity profile. Knowledge about reaction and substrate specificity of tailoring enzymes is essential for understanding and computationally predicting metabolite biosynthesis, but this information is usually scattered in the literature. Here, we present MITE, the Minimum Information about a Tailoring Enzyme database. MITE employs a comprehensive set of parameters to annotate tailoring enzymes, defining substrate and reaction specificity by the expressive reaction SMARTS (Simplified Molecular Input Line Entry System Arbitrary Target Specification) chemical pattern language. Both human and machine readable, MITE can be used as a knowledge base, for in silico biosynthesis, or to train machine-learning applications, and tightly integrates with existing resources. Designed as a community-driven and open resource, MITE employs a rolling release model of data curation and expert review. MITE is freely accessible at https://mite.bioinformatics.nl/. |
| title | MITE: the Minimum Information about a Tailoring Enzyme database for capturing specialized metabolite biosynthesis. |
| topic | Enzymes Substrate Specificity Software Humans Machine Learning Computational Biology Internet Databases, Protein |
| url | https://pubmed.ncbi.nlm.nih.gov/41001881/ |