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Peer-reviewedCC BY-NC 4.0Nucleic Acids Research

OrganiZymeDB: a comprehensive database of enzyme stability and function in the presence of organic solvents

  • Romain Debruyne1,2
  • Fabrizio Pucci1,2
  1. 1Computational Biology and Bioinformatics, Université Libre de Bruxelles , Bruxelles 1050 ,
  2. 2Interuniversity Institute of Bioinformatics in Brussels , Bruxelles 1050 ,
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Abstract

Low enzymatic tolerance to organic solvents is a major bottleneck for the development of industrial biocatalysis, since many substrates have limited water solubility, thus requiring the use of organic solvents for substrate solubilization and process economic viability. Yet, despite decades of experimental research in this field, no public resource currently exists that systematically collects and curates these data, limiting their accessibility and reuse for large-scale analyses and for the development and validation of computational methods. To address this gap, we present OrganiZymeDB (https://organizymedb.org/), a comprehensive, manually curated database of 28,121 experimental measurements of enzyme stability and function in the presence of organic solvents, compiled from 646 publications and covering 704 distinct proteins. Each entry is extensively annotated with the experimental conditions, including assay type, solvent identity and volume fraction, assay solution composition, pH, temperature, substrate(s), product(s), and enzyme production method, as well as the protein 3D structure and cross-links to other databases. OrganiZymeDB will assist both experimentalists, by providing straightforward access to solvent-compatibility data for enzymes of interest, and computational scientists, by providing a well-curated dataset to develop and evaluate methods for predicting enzyme solvent tolerance, ultimately enabling the design of robust industrial biocatalysts.

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Cite

BibTeXRIS
BibTeX
@article{debruyne2026organizymedb,
  title = {{OrganiZymeDB: a comprehensive database of enzyme stability and function in the presence of organic solvents}},
  author = {Romain Debruyne and Fabrizio Pucci},
  journal = {Nucleic Acids Research},
  year = {2026},
  month = nov,
  doi = {10.1093/nar/gkag1069},
  url = {https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag1069/9012870},
  note = {CC BY-NC 4.0},
}
RIS
TY  - JOUR
TI  - OrganiZymeDB: a comprehensive database of enzyme stability and function in the presence of organic solvents
AU  - Romain Debruyne
AU  - Fabrizio Pucci
PY  - 2026
DA  - 2026/11/05
JO  - Nucleic Acids Research
DO  - 10.1093/nar/gkag1069
UR  - https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag1069/9012870
AB  - Low enzymatic tolerance to organic solvents is a major bottleneck for the development of industrial biocatalysis, since many substrates have limited water solubility, thus requiring the use of organic solvents for substrate solubilization and process economic viability. Yet, despite decades of experimental research in this field, no public resource currently exists that systematically collects and curates these data, limiting their accessibility and reuse for large-scale analyses and for the development and validation of computational methods. To address this gap, we present OrganiZymeDB (https://organizymedb.org/), a comprehensive, manually curated database of 28,121 experimental measurements of enzyme stability and function in the presence of organic solvents, compiled from 646 publications and covering 704 distinct proteins. Each entry is extensively annotated with the experimental conditions, including assay type, solvent identity and volume fraction, assay solution composition, pH, temperature, substrate(s), product(s), and enzyme production method, as well as the protein 3D structure and cross-links to other databases. OrganiZymeDB will assist both experimentalists, by providing straightforward access to solvent-compatibility data for enzymes of interest, and computational scientists, by providing a well-curated dataset to develop and evaluate methods for predicting enzyme solvent tolerance, ultimately enabling the design of robust industrial biocatalysts.
SN  - 0305-1048
SN  - 1362-4962
ER  -