Calculation of standard thermodynamic potentials of biochemical reactions
Project description
eQuilibrator - a thermodynamics calculator for biochemical reactions
What is equilibrator-api
?
equilibrator-api
is a Python package for obtaining estimates of reactions Gibbs energies.
It is mainly meant for biologists/bioengineers with basic programming skills that
work on metabolism and want to easily add thermodynamic data to their models.
The documentation is browseable online at readthedocs.
If your list of reactions is very short, we recommend trying our
website called eQuilibrator before spending
the time necessary for learning how to use equilibrator-api
.
The main advantages of equilibrator-api
are:
- Batch mode: can be used for large reaction datasets (even more than 1000 reactions)
- Does not require a network connection (except during installation and initialization)
- Works with standard compound identifiers (such as ChEBI, KEGG, BiGG and MetaNetX) for more than 500,000 compounds
To access more advanced features, such as adding new compounds that are not among the 500,000 currently in the MetaNetX database, try using our equilibrator-assets package.
Cite us
If you plan to use results from equilibrator-api
in a scientific publication,
please cite our paper:
M. E. Beber, M. G. Gollub, D. Mozaffari, K. M. Shebek, A. I. Flamholz, R. Milo, and E. Noor, eQuilibrator 3.0: a database solution for thermodynamic constant estimation Nucleic Acids Research (2021), DOI:10.1093/nar/gkab1106
A very simple example
Note that creating a ComponentContribution
object for the first time after
installation, starts an initialization step which downloads ~1.5 GBytes of data
to your computer. It can take more than an hour (depending on the connection speed).
Note that the initialization might not work inside a Jupyter notebook environment -
in that case you should try running it in a standard python shell first and then
run the Jupyter notebook.
from equilibrator_api import ComponentContribution
cc = ComponentContribution()
rxn = cc.parse_reaction_formula("kegg:C00002 + kegg:C00001 = kegg:C00008 + kegg:C00009")
print(f"ΔG'0 = {cc.standard_dg_prime(rxn)}")
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