vonBertalanffy¶

configureSetupThermoModelInputs(model, T, compartments, ph, is, chi, concMinDefault, concMaxDefault, confidenceLevel)¶

Configures inputs to setupThermoModel (sets defaults etc.). All optional inputs are empty by default.

USAGE:

model = configureSetupThermoModelInputs(model, T, compartments, ph, is, chi, concMinDefault, concMaxDefault, confidenceLevel)

INPUT:: model:
OPTIONAL INPUTS:: T: compartments: ph: is: chi: concMinDefault: concMaxDefault: confidenceLevel:
OUTPUT:: model:

estimateDG_temp(model)¶

Estimates standard transformed Gibbs energies of formation for metabolites

USAGE:

model = estimateDG_temp(model)

INPUT:

model: Model structure with following fields:

.S - m x n stoichiometric matrix.

.mets - m x 1 array of metabolite identifiers.

.metFormulas - m x 1 cell array of metabolite formulas. Formulas for protons should be ‘H’.

.metCharges - m x 1 array of metabolite charges.

.T - Temperature in Kelvin.

.cellCompartments - c x 1 array of cell compartment identifiers.

.ph - c x 1 array of compartment specific pH values.

.is - c x 1 array of compartment specific ionic strength values in mol/L.

.chi - c x 1 array of compartment specific electrical potential values in mV.

.metCompartments - m x 1 cell array of compartment assignments for metabolites in model.mets. Compartment identifiers should be the same as in model.cellCompartments.

.DfG0 - m x 1 array of standard Gibbs energies of formation.

.pKa - m x 1 structure array with metabolite pKa values.

OUTPUT:

model: Model structure with following fields added:

.DfG0_pseudoisomers - Four column matrix with pseudoisomer standard Gibbs energies of formation in kJ/mol.

Column 1. Row index of pseudoisomer group in model.S.

Column 2. Standard Gibbs energy of formation.

Column 3. Number of hydrogen atoms.

Column 4. Charge.

.DfGt0 - Standard transformed Gibbs energies of formation in kJ/mol.

.DrGt0 - Standard transformed reaction Gibbs energy in kJ/mol.

estimateDfGt0(model, confidenceLevel)¶

Estimates standard transformed Gibbs energies of formation for metabolites

USAGE:

model = estimateDfGt0(model, confidenceLevel)

INPUT:

model: Model structure with following fields:

.S - m x n stoichiometric matrix.

.mets - m x 1 array of metabolite identifiers.

.metFormulas - m x 1 cell array of metabolite formulas. Formulas for protons should be H.

.metCharges - m x 1 array of metabolite charges.

.T - Temperature in Kelvin.

.cellCompartments - c x 1 array of cell compartment identifiers.

.ph - c x 1 array of compartment specific pH values.

.is - c x 1 array of compartment specific ionic strength values in mol/L.

.chi - c x 1 array of compartment specific electrical potential values in mV.

.metCompartments - m x 1 cell array of compartment assignments for metabolites in model.mets. Compartment identifiers should be the same as in model.compartments.

.DfG0 - m x 1 array of standard Gibbs energies of formation.

.pKa - m x 1 structure array with metabolite pKa values.

.DfG0_Uncertainty - m x 1 array of uncertainty in estimated standard Gibbs energies of formation. uf will be large for metabolites that are not covered by component contributions.

OPTIONAL INPUT:

confidenceLevel: {0.50, 0.70, (0.95), 0.99}. Confidence level for DGft0

and DrGt0 interval estimates. Default is 0.95, corresponding to 95% confidence intervals.

.DfH0 - m x 1 array of standard Enthalpies of formation.

OUTPUT:

model: Model structure with following fields added:

.DfG0_pseudoisomers - Four column matrix with pseudoisomer standard Gibbs energies of formation in kJ/mol.

Column 1. Row index of pseudoisomer group in model.S.

Column 2. Standard Gibbs energy of formation.

Column 3. Number of hydrogen atoms.

Column 4. Charge.

.DfGt0 - Standard transformed Gibbs energies of formation in kJ/mol.

.DfGtMin - Lower bounds on transformed Gibbs energies of formation in kJ/mol.

.DfGtMax - Upper bounds on transformed Gibbs energies of formation in kJ/mol.

estimateDrGt0(model, confidenceLevel)¶

Estimates bounds on transformed Gibbs energies for metabolites and reactions in model.

USAGE:

model = estimateDrGt0(model, confidenceLevel)

INPUT:

model: Model structure with following fields:

.S - m x n stoichiometric matrix.

.mets - m x 1 array of metabolite identifiers.

.metFormulas - m x 1 cell array of metabolite formulas. Formulas for protons should be H.

.T - Temperature in Kelvin.

.DfGt0 - Standard transformed Gibbs energies of formation in kJ/mol.

.DrGt0_Uncertainty Uncertainty in standard transformed reaction Gibbs energies kJ/mol.

.ph - c x 1 array of compartment specific pH values.

.chi c x 1 array of compartment specific electricalpotential values in mV.

.concMin - m x 1 array of lower bounds on metabolite concentrations in mol/L.

.concMax - m x 1 array of upper bounds on metabolite concentrations in mol/L.

OPTIONAL INPUT:

confidenceLevel: {0.50, 0.70, (0.95), 0.99}. Confidence level for DGft0: and DrGt0 interval estimates. Default is 0.95, corresponding to 95% confidence intervals.

OUTPUT:

model: Model structure with following fields added:

.DrGt0 - n x 1 array of standard transformed reaction Gibbs energies in kJ/mol.

.ur - n x 1 array of uncertainties in DrGt0.

.DrGtMin - Lower bounds on transformed reaction Gibbs energies in kJ/mol.

.DrGtMax - Upper bounds on transformed reaction Gibbs energies in kJ/mol.

getCompartment(mets)¶

Gets the compartment for each metabolite, and the unique compartments, from metabolite abbreviation(s), each of which must have compartment symbol concatentated on the right hand side (i.e. metAbbr[*]).

USAGE:

[compartments, uniqueCompartments] = getCompartment(mets)

INPUT:

mets: char array with a single metabolite abbreviation: or m x 1 cell array of metabolite abbreviations

OUTPUTS:

compartments: char array with a single compartment identifier: or m x 1 cell array of compartment identifiers
uniqueCompartments: char array with a single compartment identifier: or cell array of unique compartment identifiers
abbr: char array with a single metabolite: abbreviation, without compartment or m x 1 cell array of metabolite abbreviations, without compartments

initVonBertalanffy¶: All the installation instructions are in a separate .md file named vonBertalanffy.md in docs/source/installation Setup the paths to the data, scripts and functions Check if this COBRA toolbox extension is in the Matlab path

setupThermoModel(model, confidenceLevel)¶

Estimates standard transformed reaction Gibbs energy and directionality at in vivo conditions in multicompartmental metabolic reconstructions. Has external dependencies on the COBRA toolbox, the component contribution method, Python (with numpy and Open Babel bindings), ChemAxon’s Calculator Plugins, and Open Babel. See details on availability at the end of help text.

USAGE:

model = setupThermoModel(model, confidenceLevel)

INPUTS:

model: Model structure with following fields:

.S - m x n stoichiometric matrix.

.mets - m x 1 array of metabolite identifiers.

.rxns - n x 1 array of reaction identifiers.

.metFormulas - m x 1 cell array of metabolite formulas. Formulas for protons should be H, and formulas for water should be H2O.

.metCharges - m x 1 numerical array of metabolite charges.

.T - Temperature in Kelvin.

.compartments - c x 1 array of compartment identifiers. Should match the compartment identifiers in model.metCompartments.

.ph - c x 1 array of compartment specific pH values in the range 4.7 to 9.3.

.is - c x 1 array of compartment specific ionic strength values in the range 0 to 0.35 mol/L.

.chi - c x 1 array of compartment specific electrical potential values in mV. Electrical potential in cytosol is assumed to be 0 mV. Electrical potential in all other compartments are relative to that in cytosol.

.concMin - m x 1 array of lower bounds on metabolite concentrations in mol/L.

.concMax - m x 1 array of upper bounds on metabolite concentrations in mol/L.

confidenceLevel: {0.50, 0.70, (0.95), 0.99}. Confidence level for: standard transformed reaction Gibbs energies used to quantitatively assign reaction directionality. Default is 0.95, corresponding to a confidence interval of +/- 1.96 * ur.

OUTPUT:

model: Model structure with following additional fields:

.inchi - Structure containing four m x 1 cell array’s of IUPAC InChI strings for metabolites, with varying levels of structural detail.

.pKa - m x 1 structure containing metabolite pKa values estimated with ChemAxon’s Calculator Plugins.

.DfG0 - m x 1 array of component contribution estimated standard Gibbs energies of formation.

.covf - m x m estimated covariance matrix for standard Gibbs energies of formation.

.DfG0_Uncertainty - m x 1 array of uncertainty in estimated standard Gibbs energies of formation. Will be large for metabolites that are not covered by component contributions.

.DrG0 - n x 1 array of component contribution estimated standard reaction Gibbs energies.

.DrG0_Uncertainty - n x 1 array of uncertainty in standard reaction Gibbs energy estimates. Will be large for reactions that are not covered by component contributions.

.DfG0_pseudoisomers p x 4 matrix with the following columns:

Metabolite index.

Estimated pseudoisomer standard Gibbs energy.

Number of hydrogen atoms in pseudoisomer chemical formula.

Charge on pseudoisomer.

.DfGt0 - m x 1 array of estimated standard transformed Gibbs energies of formation.

.DrGt0 - n x 1 array of estimated standard transformed reaction Gibbs energies.

.DfGtMin - m x 1 array of estimated lower bounds on transformed Gibbs energies of formation.

.DfGtMax - m x 1 array of estimated upper bounds on transformed Gibbs energies of formation.

.DrGtMin - n x 1 array of estimated lower bounds on transformed reaction Gibbs energies.

.DrGtMax - n x 1 array of estimated upper bounds on transformed reaction Gibbs energies.

Written output - MetStructures.sdf - An SDF containing all structures input to the component contribution method for estimation of standard Gibbs energies.