eQuilibrator-API

A command-line API with minimal dependencies for calculation of standard thermodynamic potentials of biochemical reactions using the data found on eQuilibrator. Does not require any network connections.

Current Features

• Example scripts for singleton and bulk calculations.
• Calculation of standard Gibbs potentials of reactions (together with confidence intervals).
• Calculation of standard reduction potentials of half-cells.

To access more advanced features, such as adding new compounds that are not available in the KEGG database, try using our full-blown Component Contribution package.

Cite us

If you plan to use results from equilibrator-api in a scientific publication, please cite our paper:

Noor E, Haraldsdóttir HS, Milo R, Fleming RMT. Consistent estimation of Gibbs energy using component contributions. PLoS Comput Biol. 2013;9: e1003098.

Installation

The easiest way to get eQuilibrator-API up and running is using virtualenv, PyPI, and Jupyter notebooks:

virtualenv -p python3 equilibrator
source equilibrator/bin/activate
pip install equilibrator-api jupyter
curl https://gitlab.com/elad.noor/equilibrator-api/raw/develop/scripts/equilibrator_cmd.ipynb > equilibrator_cmd.ipynb
jupyter notebook

Then select the notebook called equilibrator_cmd.ipynb and follow the examples in it.

If you are using a Windows environment, that are a few dependencies that work better under conda. Make sure to first run:

conda install -c conda-forge python-levenshtein

and only then install the pip packages.

Example Usage

Import the API and create an instance. Creating the EquilibratorAPI class instance reads all the data that is used to calculate thermodynamic potentials of reactions.

from equilibrator_api import ComponentContribution, Q_
cc = ComponentContribution()

You can parse a reaction from a KEGG-style reaction string. The example given is ATP hydrolysis to ADP and inorganic phosphate.

rxn = cc.parse_reaction_formula("kegg:C00002 + kegg:C00001 = kegg:C00008 + kegg:C00009")

We highly recommend that you check that the reaction is atomically balanced (conserves atoms) and charge balanced (redox neutral). We've found that it's easy to accidentally write unbalanced reactions in this KEGG-style format and so we always check ourselves.

if not rxn.is_balanced():
    print('%s is not balanced' % rxn)

Now we know that the reaction is "kosher" and we can safely proceed to calculate the standard change in Gibbs potential due to this reaction.

cc.p_h = Q_(6.5)  # set pH
cc.ionic_strength = Q_("200 mM")  # set I

print(f"ΔG0 = {cc.standard_dg(rxn)}")
print(f"ΔG'0 = {cc.standard_dg_prime(rxn)}")
print(f"ΔG'm = {cc.physiological_dg_prime(rxn)}")

You can also calculate the reversibility index (Noor et al. 2012) for this reaction.

print(f"ln(Reversibility Index) = {cc.ln_reversibility_index(rxn)}")

The reversibility index is a measure of the degree of the reversibility of the reaction that is normalized for stoichiometry. If you are interested in assigning reversibility to reactions we recommend this measure because 1:2 reactions are much "easier" to reverse than reactions with 1:1 or 2:2 reactions. You can see the paper linked above for more information.

Pathway analysis tools have been ported to a new project

Running Max-min Driving Force (MDF) or Enzyme Cost Minimization (ECM) anslyses is no longer part of equilibrator-api and has been ported to a separate project names equilibrator-pathway. Note, that the pathway configuration file format used in previous versions of equilibrator-api (prior to 0.2.7) is not longer supported. You can find code and configuration file examples in the new repository.

Further examples for reaction parsing

We support several compound databases, not just KEGG. One can mix between several sources in the same reaction, e.g.:

rxn = cc.parse_reaction_formula("kegg:C00002 + CHEBI:15377 = metanetx.chemical:MNXM7 + bigg.metabolite:pi")

Or, you can use compound names instead of identifiers. However, it is discouraged to use in batch, since we only pick the closest hit in our database, and that can often be the wrong compound. Always verify that the reaction is balanced, and preferably also that the InChIKeys are correct:

rxn = cc.search_reaction("beta-D-glucose = glucose")
print(rxn)

In this case, the matcher arbitrarily chooses alpha-D-glucose as the first hit for the name glucose. Therefore, it is always better to use the most specific synonym to avoid mis-annotations.

Dependencies:

• python >= 3.7
• equilibrator-cache (latest)
• component-contribution (latest)
• numpy
• scipy
• pandas
• matplotlib
• quilt
• path
• pint
• uncertainties
• pyparsing
• python-Levenshtein-wheels
• sqlalchemy
• periodictable