eQuilibrator is a simple web interface designed to enable easy thermodynamic
analysis of biochemical systems. eQuilibrator enables free-text search for
biochemical compounds and reactions and provides thermodynamic estimates for
both in a variety of conditions. Estimation of thermodynamic parameters
(ΔrG and ΔfG) elucidates how much energy is required to
drive a particular biochemical reaction and in which direction the reaction
will flow in particular cellular conditions .
Because experimental measurement of the free energy of formation
(ΔfG°) of compounds is technically challenging, the vast majority
of known metabolites have not been thermodynamically characterized.
eQuilibrator uses a well-studied approximation of ΔfG called
group contribution ,
enabling thermodynamic analysis of many biochemical reactions and pathways.
Currently, eQuilibrator can provide estimates for many compounds in the KEGG
database (about 4500). Individual compounds and enzymes can
be searched for by their common names (“water”, “glucosamine”, “hexokinase”),
and reactions can be entered in a simple, free-text format
(“ribulose bisphosphate + CO2 + water => 2 3-phosphoglycerate”)
that eQuilibrator parses automatically. eQuilibrator also allows manipulation
of the conditions of a reaction - pH, ionic strength, and reactant and
product concentrations - to help explore the thermodynamic landscape of a
eQuilibrator is a project of the Milo Lab
at the Weizmann Institute in Rehovot, Israel. If you have any thoughts or
questions feel free to write us on the
eQuilibrator Users Google Group
Implementation of eQuilibrator
eQuilibrator makes heavy use of open source libraries and frameworks and is
open-source itself. You can find the eQuilibrator source code on
our GitHub repository called equilibrator.
The eQuilibrator back-end is implemented in pure Python
using the Django web framework and several
other open-source Python libraries, including NumPy
The eQuilibrator user-interface is implemented using HTML, CSS and the
All thermodynamic data presented by eQuilibrator was generated using the
Component Contribution method
which was implemented also in Python and is open-source as well.
You can find the source code on our GitHub repository called