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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 ‘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/.
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Category

Academic article

Language

English

Author(s)

  • 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 Elias 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

Affiliation

  • SINTEF Industry / Biotechnology and Nanomedicine
  • Technical University of Denmark
  • VTT Technical Research Centre of Finland Ltd
  • University of Groningen
  • Leiden University
  • Wageningen University & Research
  • University of Warwick
  • University of Basel
  • University of Zürich
  • Swiss Institute of Bioinformatics
  • ETH Zurich
  • Germany
  • Johann Wolfgang Goethe University of Frankfurt am Main
  • University of Bonn
  • Gottfried Wilhelm Leibniz Universität Hannover
  • Saarland University
  • Leibniz Institute for Natural Product Research and Infection Biology
  • Helmholtz Centre for Infection Research
  • LOEWE Centre for Translational Biodiversity Genomics (LOEWE TBG)
  • University of Johannesburg
  • India
  • Regional Centre for Biotechnology
  • Southern University of Science and Technology
  • Korea Advanced Institute of Science and Technology
  • Mexico
  • University of Arizona
  • University of California, Irvine
  • University of California, San Diego
  • Carnegie Institution for Science
  • National Cancer Institute
  • State University of Campinas

Year

2025

Published in

Nucleic Acids Research (NAR)

ISSN

0305-1048

Volume

54

Issue

D1

Page(s)

D635 - D642

View this publication at Norwegian Research Information Repository