MITE: the Minimum Information about a Tailoring Enzyme database for capturing specialized metabolite biosynthesis

Adriano Rutz; Daniel Probst; César Aguilar; Daniel Y Akiyama; Fabrizio Alberti; Hannah E Augustijn; Nicole E Avalon; Christine Beemelmanns; Hellen Bertoletti Barbieri; Friederike Biermann; Alan J Bridge; Esteban Charria Girón; Russell Cox; Max Crüsemann; Paul M D’Agostino; Marc Feuermann; Jennifer Gerke; Karina Gutiérrez García; Jonathan E Holme; Ji-Yeon Hwang; Riccardo Iacovelli; Júlio César Jeronimo Barbosa; Navneet Kaur; Martin Klapper; Anna M Köhler; Aleksandra Korenskaia; Noel Kubach; Byung T Lee; Catarina Loureiro; Shrikant Mantri; Simran Narula; David Meijer; Jorge C Navarro-Muñoz; Giang-Son Nguyen; Sunaina Paliyal; Mohit Panghal; Latika Rao; Simon Sieber; Nika Sokolova; Sven T Sowa; Judit Szenei; Barbara R Terlouw; Heiner G Weddeling; Jingwei Yu; Nadine Ziemert; Tilmann Weber; Kai Blin; Justin J J Van der Hooft; Marnix H Medema; Mitja M Zdouc

doi:10.1093/nar/gkaf969

MITE: the Minimum Information about a Tailoring Enzyme database for capturing specialized metabolite biosynthesis

Adriano Rutz
, Daniel Probst
, César Aguilar
, Daniel Y Akiyama
, Fabrizio Alberti
, Hannah E Augustijn
, Nicole E Avalon
, Christine Beemelmanns
, Hellen Bertoletti Barbieri
, Friederike Biermann
, Alan J Bridge
, Esteban Charria Girón
, Russell Cox
, Max Crüsemann
, Paul M D’Agostino
, Marc Feuermann
, Jennifer Gerke
, Karina Gutiérrez García
, Jonathan E Holme
, Ji-Yeon Hwang

Riccardo Iacovelli, Júlio César Jeronimo Barbosa, Navneet Kaur, Martin Klapper, Anna M Köhler, Aleksandra Korenskaia, Noel Kubach, Byung T Lee, Catarina Loureiro, Shrikant Mantri, Simran Narula, David Meijer, Jorge C Navarro-Muñoz, Giang-Son Nguyen, Sunaina Paliyal, Mohit Panghal, Latika Rao, Simon Sieber, Nika Sokolova, Sven T Sowa, Judit Szenei, Barbara R Terlouw, Heiner G Weddeling, Jingwei Yu, Nadine Ziemert, Tilmann Weber, Kai Blin, Justin J J Van der Hooft, Marnix H Medema^*, Mitja M Zdouc^*

^*Corresponding author for this work

BA8501 Microbial and plant cell factory

Swiss Federal Institute of Technology in Zurich (ETH Zürich)
Wageningen University & Research (WUR)
Monterrey Institute of Technology and Higher Education
Universidade Estadual de Campinas
University of Warwick (WMG)
Leiden University
University of California, San Diego
Saarland University
Helmholtz Centre for Infection Research (HZI)
Goethe University Frankfurt
LOEWE Centre for Translational Biodiversity Genomics (LOEWE-TBG)
SIB Swiss Institute of Bioinformatics
Leibniz University Hannover
University of Bonn
Carnegie Institution for Science
University of Arizona
SINTEF AS
National Cancer Institute (NCI)
National Agri-Food and Biomanufacturing Institute (NABI)
Leibniz Institute for Natural Product Research and Infection Biology Hans Knöll Institute (Leibniz HKI)
University of Tübingen
Korea Advanced Institute of Science and Technology (KAIST)
Regional Centre for Biotechnology (RCB)
University of Zurich
University of Groningen
University of Basel
Technical University of Denmark (DTU)
Southern University of Science and Technology (SUSTech)
University of Johannesburg

Research output: Contribution to journal › Article › Scientific › peer-review

10 Citations (Scopus)

Abstract

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/.

Original language	English
Article number	gkaf969
Pages (from-to)	D635-D642
Journal	Nucleic Acids Research
Volume	54
Issue number	D1
DOIs	https://doi.org/10.1093/nar/gkaf969
Publication status	Published - 6 Jan 2026
MoE publication type	A1 Journal article-refereed

Funding

R.I. was supported by the Novo Nordisk Foundation, NNF23OC0086472

Keywords

Enzymes/metabolism
Substrate Specificity
Software
Humans
Machine Learning
Computational Biology/methods
Internet
Databases, Protein

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10.1093/nar/gkaf969Licence: CC BY

Cite this

Rutz, A., Probst, D., Aguilar, C., Akiyama, D. Y., Alberti, F., Augustijn, HE., Avalon, N. E., Beemelmanns, C., Barbieri, H. B., Biermann, F., Bridge, A. J., Girón, E. C., Cox, R., Crüsemann, M., D’Agostino, P. M., Feuermann, M., Gerke, J., García, K. G., Holme, J. E., ... Zdouc, M. M. (2026). MITE: the Minimum Information about a Tailoring Enzyme database for capturing specialized metabolite biosynthesis. Nucleic Acids Research, 54(D1), D635-D642. Article gkaf969. https://doi.org/10.1093/nar/gkaf969

@article{d2802279899d43659a15fbe0fe33f9dd,

title = "MITE: the Minimum Information about a Tailoring Enzyme database for capturing specialized metabolite biosynthesis",

abstract = "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 {\textquoteleft}scaffold{\textquoteright}, which is subsequently modified by tailoring enzymes to define the molecule{\textquoteright}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/.",

keywords = "Enzymes/metabolism, Substrate Specificity, Software, Humans, Machine Learning, Computational Biology/methods, Internet, Databases, Protein",

author = "Adriano Rutz and Daniel Probst and C{\'e}sar Aguilar and Akiyama, \{Daniel Y\} and Fabrizio Alberti and Hannah E Augustijn and Avalon, \{Nicole E\} and Christine Beemelmanns and Barbieri, \{Hellen Bertoletti\} and Friederike Biermann and Bridge, \{Alan J\} and Gir{\'o}n, \{Esteban Charria\} and Russell Cox and Max Cr{\"u}semann and D{\textquoteright}Agostino, \{Paul M\} and Marc Feuermann and Jennifer Gerke and Garc{\'i}a, \{Karina Guti{\'e}rrez\} and Holme, \{Jonathan E\} and Ji-Yeon Hwang and Riccardo Iacovelli and Jeronimo Barbosa, \{J{\'u}lio C{\'e}sar\} and Navneet Kaur and Martin Klapper and K{\"o}hler, \{Anna M\} and Aleksandra Korenskaia and Noel Kubach and Lee, \{Byung T\} and Catarina Loureiro and Shrikant Mantri and Simran Narula and David Meijer and Navarro-Mu{\~n}oz, \{Jorge C\} and Giang-Son Nguyen and Sunaina Paliyal and Mohit Panghal and Latika Rao and Simon Sieber and Nika Sokolova and Sven T Sowa and Judit Szenei and Terlouw, \{Barbara R\} and Weddeling, \{Heiner G\} and Jingwei Yu and Nadine Ziemert and Tilmann Weber and Kai Blin and Van der Hooft, \{Justin J J\} and Marnix H Medema and Zdouc, \{Mitja M\}",

note = "{\textcopyright} The Author(s) 2025. Published by Oxford University Press.",

year = "2026",

month = jan,

day = "6",

doi = "10.1093/nar/gkaf969",

language = "English",

volume = "54",

pages = "D635--D642",

journal = "Nucleic Acids Research",

issn = "0305-1048",

publisher = "Oxford University Press",

number = "D1",

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Rutz, A, Probst, D, Aguilar, C, Akiyama, DY, Alberti, F, Augustijn, HE, Avalon, NE, Beemelmanns, C, Barbieri, HB, Biermann, F, Bridge, AJ, Girón, EC, Cox, R, Crüsemann, M, D’Agostino, PM, Feuermann, M, Gerke, J, García, KG, Holme, JE, Hwang, J-Y, Iacovelli, R, Jeronimo Barbosa, JC, Kaur, N, Klapper, M, Köhler, AM, Korenskaia, A, Kubach, N, Lee, BT, Loureiro, C, Mantri, S, Narula, S, Meijer, D, Navarro-Muñoz, JC, Nguyen, G-S, Paliyal, S, Panghal, M, Rao, L, Sieber, S, Sokolova, N, Sowa, ST, Szenei, J, Terlouw, BR, Weddeling, HG, Yu, J, Ziemert, N, Weber, T, Blin, K, Van der Hooft, JJJ, Medema, MH & Zdouc, MM 2026, 'MITE: the Minimum Information about a Tailoring Enzyme database for capturing specialized metabolite biosynthesis', Nucleic Acids Research, vol. 54, no. D1, gkaf969, pp. D635-D642. https://doi.org/10.1093/nar/gkaf969

TY - JOUR

T1 - MITE: the Minimum Information about a Tailoring Enzyme database for capturing specialized metabolite biosynthesis

AU - Rutz, Adriano

AU - Probst, Daniel

AU - Aguilar, César

AU - Akiyama, Daniel Y

AU - Alberti, Fabrizio

AU - Augustijn, Hannah E

AU - Avalon, Nicole E

AU - Beemelmanns, Christine

AU - Barbieri, Hellen Bertoletti

AU - Biermann, Friederike

AU - Bridge, Alan J

AU - Girón, Esteban Charria

AU - Cox, Russell

AU - Crüsemann, Max

AU - D’Agostino, Paul M

AU - Feuermann, Marc

AU - Gerke, Jennifer

AU - García, Karina Gutiérrez

AU - Holme, Jonathan E

AU - Hwang, Ji-Yeon

AU - Iacovelli, Riccardo

AU - Jeronimo Barbosa, Júlio César

AU - Kaur, Navneet

AU - Klapper, Martin

AU - Köhler, Anna M

AU - Korenskaia, Aleksandra

AU - Kubach, Noel

AU - Lee, Byung T

AU - Loureiro, Catarina

AU - Mantri, Shrikant

AU - Narula, Simran

AU - Meijer, David

AU - Navarro-Muñoz, Jorge C

AU - Nguyen, Giang-Son

AU - Paliyal, Sunaina

AU - Panghal, Mohit

AU - Rao, Latika

AU - Sieber, Simon

AU - Sokolova, Nika

AU - Sowa, Sven T

AU - Szenei, Judit

AU - Terlouw, Barbara R

AU - Weddeling, Heiner G

AU - Yu, Jingwei

AU - Ziemert, Nadine

AU - Weber, Tilmann

AU - Blin, Kai

AU - Van der Hooft, Justin J J

AU - Medema, Marnix H

AU - Zdouc, Mitja M

PY - 2026/1/6

Y1 - 2026/1/6

N2 - 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/.

AB - 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/.

KW - Enzymes/metabolism

KW - Substrate Specificity

KW - Software

KW - Humans

KW - Machine Learning

KW - Computational Biology/methods

KW - Internet

KW - Databases, Protein

UR - https://www.scopus.com/pages/publications/105027814997

U2 - 10.1093/nar/gkaf969

DO - 10.1093/nar/gkaf969

M3 - Article

C2 - 41001881

SN - 0305-1048

VL - 54

SP - D635-D642

JO - Nucleic Acids Research

JF - Nucleic Acids Research

IS - D1

M1 - gkaf969

ER -

MITE: the Minimum Information about a Tailoring Enzyme database for capturing specialized metabolite biosynthesis

Abstract

Funding

Keywords

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