MITE: the Minimum Information about a Tailoring Enzyme database for capturing specialized metabolite biosynthesis
Adriano Rutz 
ETH Zürich 
Daniel Probst
Wageningen University & Research
Tecnológico de Monterrey
Daniel Y. Akiyama
Universidade Estadual de Campinas (UNICAMP)
Fabrizio Alberti
University of Warwick
Hannah E. Augustijn
Wageningen University & Research
Leiden University
Nicole E. Avalon
University of California, Irvine
Scripps Institution of Oceanography
Christine Beemelmanns
Helmholtz Centre for Infection Research
Hellen Bertoletti Barbieri
Universidade Estadual de Campinas (UNICAMP)
Friederike Biermann
Wageningen University & Research
Goethe University Frankfurt
LOEWE Centre for Translational Biodiversity Genomics
Alan J. Bridge
SIB Swiss Institute of Bioinformatics
Esteban Charria Girón
Wageningen University & Research
Helmholtz Centre for Infection Research
Russell Cox
Leibniz Universität Hannover
Max Crüsemann
University of Bonn
Goethe University Frankfurt
Paul Michael D’Agostino
Helmholtz Centre for Infection Research
Marc Feuermann
SIB Swiss Institute of Bioinformatics
Jennifer Gerke
Leibniz Universität Hannover
Carnegie Institution for Science
University of Arizona
Jonathan Holme
SINTEF Industry
Frederick National Laboratory for Cancer Research
Riccardo Iacovelli
VTT Technical Research Centre of Finland
Júlio César Jeronimo Barbosa
Universidade Estadual de Campinas (UNICAMP)
National Agri-Food Biotechnology Institute
Martin Klapper
Leibniz-Institut für Naturstoff-Forschung und Infektionsbiologie e. V. - Hans-Knöll-Institut (HKI)
Anna M. Köhler
Leibniz Universität Hannover
Aleksandra Korenskaia
University of Tübingen
Noel Kubach
University of Tübingen
Byung Tae Lee
Korea Advanced Institute of Science and Technology
Catarina Loureiro
Wageningen University & Research
Shrikant Mantri
National Agri-Food Biotechnology Institute
Simran Narula
National Agri-Food Biotechnology Institute
David Meijer
Wageningen University & Research
Jorge C. Navarro-Muñoz
Wageningen University & Research
Giang-Son Nguyen
SINTEF Industry
National Agri-Food Biotechnology Institute
Mohit Panghal
National Agri-Food Biotechnology Institute
Latika Rao
National Agri-Food Biotechnology Institute
Simon Sieber
Department of Chemistry
Nika Sokolova
University of Groningen
Sven T. Sowa
University of Basel
Technical University of Denmark
Barbara Terlouw
Leiden University
Heiner G. Weddeling
University of Basel
Jingwei Yu
Southern University of Science and Technology
Nadine Ziemert
University of Tübingen
Tilmann Weber
Technical University of Denmark
Kai Blin
Technical University of Denmark
Justin J. J. van der Hooft
Wageningen University & Research
University of Johannesburg
Wageningen University & Research
Wageningen University & Research
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/.