wc_model_gen/prokaryote/rna_degradation.py
""" Generator for RNA degradation submodels based on KBs for random in silico organisms
:Author: Jonathan Karr <karr@mssm.edu>
:Author: Ashwin Srinivasan <ashwins@mit.edu>
:Author: Yin Hoon Chew <yinhoon.chew@mssm.edu>
:Date: 2018-06-11
:Copyright: 2018, Karr Lab
:License: MIT
"""
from wc_onto import onto as wc_ontology
from wc_utils.util.units import unit_registry
import wc_model_gen.utils as utils
import scipy.constants
import wc_model_gen
import wc_lang
import wc_kb
import numpy
import math
class RnaDegradationSubmodelGenerator(wc_model_gen.SubmodelGenerator):
""" Generator for RNA degradation submodel
Options:
* beta (:obj:`float`, optional): ratio of Michaelis-Menten constant to substrate
concentration (Km/[S]) for use when estimating Km values, the default value is 1
"""
def clean_and_validate_options(self):
""" Apply default options and validate options """
options = self.options
beta = options.get('beta', 1.)
options['beta'] = beta
def gen_reactions(self):
""" Generate reactions associated with submodel """
model = self.model
kb = self.knowledge_base
cell = kb.cell
submodel = model.submodels.get_one(id='rna_degradation')
cytosol = model.compartments.get_one(id='c')
amp = model.species_types.get_one(id='amp').species.get_one(compartment=cytosol)
cmp = model.species_types.get_one(id='cmp').species.get_one(compartment=cytosol)
gmp = model.species_types.get_one(id='gmp').species.get_one(compartment=cytosol)
ump = model.species_types.get_one(id='ump').species.get_one(compartment=cytosol)
h2o = model.species_types.get_one(id='h2o').species.get_one(compartment=cytosol)
h = model.species_types.get_one(id='h').species.get_one(compartment=cytosol)
rna_kbs = cell.species_types.get(__type=wc_kb.prokaryote.RnaSpeciesType)
for rna_kb in rna_kbs:
rna_model = model.species_types.get_one(id=rna_kb.id).species.get_one(compartment=cytosol)
seq = rna_kb.get_seq()
reaction = model.reactions.get_or_create(submodel=submodel, id='degradation_' + rna_kb.id)
reaction.name = 'degradation ' + rna_kb.name
reaction.participants = []
# Adding participants to LHS
reaction.participants.add(rna_model.species_coefficients.get_or_create(coefficient=-1))
reaction.participants.add(h2o.species_coefficients.get_or_create(coefficient=-(rna_kb.get_len() - 1)))
# Adding participants to RHS
reaction.participants.add(amp.species_coefficients.get_or_create(coefficient=seq.count('A')))
reaction.participants.add(cmp.species_coefficients.get_or_create(coefficient=seq.count('C')))
reaction.participants.add(gmp.species_coefficients.get_or_create(coefficient=seq.count('G')))
reaction.participants.add(ump.species_coefficients.get_or_create(coefficient=seq.count('U')))
reaction.participants.add(h.species_coefficients.get_or_create(coefficient=rna_kb.get_len() - 1))
# Add members of the degradosome
# Counterintuitively .specie is a KB species_coefficient object
for degradosome_kb in cell.observables.get_one(id='degrade_rnase_obs').expression.species:
degradosome_species_type_model = model.species_types.get_one(id=degradosome_kb.species_type.id)
degradosome_species_model = degradosome_species_type_model.species.get_one(compartment=cytosol)
reaction.participants.add(degradosome_species_model.species_coefficients.get_or_create(
coefficient=-1))
reaction.participants.add(degradosome_species_model.species_coefficients.get_or_create(
coefficient=1))
def gen_rate_laws(self):
""" Generate rate laws for the reactions in the submodel """
model = self.model
modifier = model.observables.get_one(id='degrade_rnase_obs')
for reaction in self.submodel.reactions:
rate_law_exp, parameters = utils.gen_michaelis_menten_like_rate_law(
model, reaction, modifiers=[modifier])
rate_law = model.rate_laws.create(direction=wc_lang.RateLawDirection.forward,
type=None,
expression=rate_law_exp,
reaction=reaction,
)
rate_law.id = rate_law.gen_id()
def calibrate_submodel(self):
""" Calibrate the submodel using data in the KB """
model = self.model
beta = self.options.get('beta')
Avogadro = model.parameters.get_or_create(
id='Avogadro',
type=None,
value=scipy.constants.Avogadro,
units=unit_registry.parse_units('molecule mol^-1'))
cytosol = model.compartments.get_one(id='c')
init_species_counts = {}
modifier = model.observables.get_one(id='degrade_rnase_obs')
for species in modifier.expression.species:
init_species_counts[species.gen_id()] = species.distribution_init_concentration.mean
rnas_kb = self.knowledge_base.cell.species_types.get(__type=wc_kb.prokaryote.RnaSpeciesType)
for rna_kb, reaction in zip(rnas_kb, self.submodel.reactions):
rna_reactant = model.species_types.get_one(id=rna_kb.id).species.get_one(compartment=cytosol)
half_life = rna_kb.properties.get_one(property='half_life').get_value()
mean_concentration = rna_reactant.distribution_init_concentration.mean
average_rate = average_rate = utils.calc_avg_deg_rate(mean_concentration, half_life)
for species in reaction.get_reactants():
init_species_counts[species.gen_id()] = species.distribution_init_concentration.mean
if model.parameters.get(id='K_m_{}_{}'.format(reaction.id, species.species_type.id)):
model_Km = model.parameters.get_one(
id='K_m_{}_{}'.format(reaction.id, species.species_type.id))
model_Km.value = beta * species.distribution_init_concentration.mean \
/ Avogadro.value / species.compartment.init_volume.mean
model_kcat = model.parameters.get_one(id='k_cat_{}'.format(reaction.id))
model_kcat.value = 1.
model_kcat.value = average_rate / reaction.rate_laws[0].expression._parsed_expression.eval({
wc_lang.Species: init_species_counts,
wc_lang.Compartment: {cytosol.id: cytosol.init_volume.mean * cytosol.init_density.value},
})