eQuilibrator 3.0: a database solution for thermodynamic constant estimation
Abstract
eQuilibrator (equilibrator.weizmann.ac.il) is a database of biochemical equilibrium constants and Gibbs free energies, originally designed as a web-based interface. While the website now counts around 1,000 distinct monthly users, its design could not accommodate larger compound databases and it lacked a scalable Application Programming Interface (API) for integration into other tools developed by the systems biology community. Here, we report on the recent updates to the database as well as the addition of a new Python-based interface to eQuilibrator that adds many new features such as a 100-fold larger compound database, the ability to add novel compounds, improvements in speed and memory use, and correction for Mg²⁺ ion concentrations. Moreover, the new interface can compute the covariance matrix of the uncertainty between estimates, for which we show the advantages and describe the application in metabolic modelling. We foresee that these improvements will make thermodynamic modelling more accessible and facilitate the integration of eQuilibrator into other software platforms.
Additional Information
© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. Received: 13 September 2021. Revision received: 16 October 2021. Accepted: 21 October 2021. Published: 29 November 2021. Dedicated to the memory of Arren Bar-Even (1980–2020). We thank Jörg Stelling for a helpful discussion on the effect of magnesium ions. M.E.B. was partly supported by Horizon 2020—Research and Innovation Framework Programme [686070 (DD-DeCaF)]; M.G.G. was supported by the Swiss National Science Foundation Sinergia project [177164]; K.M.S. was supported by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research [DE-SC0018249]. Funding for open access charge: Research budget. The authors wish it to be known that, in their opinion, the first and last authors should be regarded as Joint First Authors. DATA AVAILABILITY. The source code for all the Python packages mentioned in this manuscript can be found at https://gitlab.com/equilibrator. All relevant data and models are stored on Zenodo, and are linked to from the repository (Training data - https://doi.org/10.5281/zenodo.3978439; Compound database - https://doi.org/10.5281/zenodo.4128542; Model parameters - https://doi.org/10.5281/zenodo.4013788; Group definitions - https://doi.org/10.5281/zenodo.4010929). The documentation can be found at https://equilibrator.readthedocs.io. The eQuilibrator suite depends on several open-source packages, such as: OpenBabel (54), RDKit, NumPy, SciPy, Pandas, Pint, and SQLAlchemy. In addition, estimating acid-base dissociation constants was done using Marvin Calculator, Calculator version 21.13.0, ChemAxon (www.chemaxon.com), under an academic license. Marvin Calculator is also required for adding new compounds to a local database. Conflict of interest statement. None declared.Attached Files
Published - gkab1106.pdf
Supplemental Material - gkab1106_supplemental_file.pdf
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Additional details
- PMCID
- PMC8728285
- Eprint ID
- 112306
- Resolver ID
- CaltechAUTHORS:20211208-951115000
- 686070
- European Research Council (ERC)
- 177164
- Swiss National Science Foundation (SNSF)
- DE-SC0018249
- Department of Energy (DOE)
- Created
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2021-12-10Created from EPrint's datestamp field
- Updated
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2022-01-10Created from EPrint's last_modified field