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convenience.py
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convenience.py
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# -*- coding: utf-8 -*-
"""
.. module:: skimpy
:platform: Unix, Windows
:synopsis: Simple Kinetic Models in Python
.. moduleauthor:: SKiMPy team
[---------]
Copyright 2017 Laboratory of Computational Systems Biotechnology (LCSB),
Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
from sympy import sympify
from .mechanism import KineticMechanism,ElementrayReactionStep
from ..core.reactions import Reaction
from ..utils.tabdict import TabDict
from collections import namedtuple
from ..core.itemsets import make_parameter_set, make_reactant_set
from skimpy.utils.general import make_subclasses_dict
from ..utils.namespace import *
from .utils import stringify_stoichiometry
def make_convenience(stoichiometry):
"""
:param stoichiometry is a list of the reaction stoichioemtry
"""
ALL_MECHANISM_SUBCLASSES = make_subclasses_dict(KineticMechanism)
new_class_name = "Convenience"\
+ "_{0}".format(stringify_stoichiometry(stoichiometry))
if new_class_name in ALL_MECHANISM_SUBCLASSES.keys():
return ALL_MECHANISM_SUBCLASSES[new_class_name]
class Convenience(KineticMechanism):
"""A reversible N-M enyme class """
suffix = "_{0}".format(stringify_stoichiometry(stoichiometry))
reactant_list = []
parameter_list = {'vmax_forward': [ODE, MCA, QSSA],
'kcat_forward': [ODE,MCA,QSSA],
'k_equilibrium': [ODE, MCA, QSSA], }
parameter_reactant_links = {}
reactant_stoichiometry = {}
num_substrates = 1
num_products = 1
for s in stoichiometry:
if s < 0:
substrate = 'substrate{}'.format(num_substrates)
km_substrate ='km_substrate{}'.format(num_substrates)
reactant_list.append(substrate)
parameter_list[km_substrate] = [ODE, MCA, QSSA]
parameter_reactant_links[km_substrate] = substrate
reactant_stoichiometry[substrate] = float(s)
num_substrates += 1
if s > 0:
product = 'product{}'.format(num_products)
km_product ='km_product{}'.format(num_products)
reactant_list.append(product)
parameter_list[km_product] = [ODE, MCA, QSSA]
parameter_reactant_links[km_product] = product
reactant_stoichiometry[product] = float(s)
num_products += 1
Reactants = make_reactant_set(__name__ + suffix, reactant_list)
Parameters = make_parameter_set(__name__ + suffix, parameter_list)
ElementaryReactions = namedtuple('ElementaryReactions',[])
def __init__(self, name, reactants, parameters=None, **kwargs):
# FIXME dynamic linking, separaret parametrizations from model init
# FIXME Reaction has a mechanism, and this is a mechanism
KineticMechanism.__init__(self, name, reactants, parameters, **kwargs)
def get_qssa_rate_expression(self):
reactant_km_relation = {self.reactants[v].symbol: k
for k, v in self.parameter_reactant_links.items()}
substrates = {k:r for k,r in self.reactants.items()
if k.startswith('substrate')}
products= {k:r for k,r in self.reactants.items()
if k.startswith('product')}
keq = self.parameters.k_equilibrium.symbol
#TODO EXTEND TO ALL OTHER MECHANISMS
if self.enzyme is None:
vmaxf = self.parameters.vmax_forward.symbol
else:
vmaxf = self.parameters.kcat_forward.symbol * \
self.reactants.enzyme.symbol
common_denominator_substrates = 1
fwd_nominator = vmaxf
bwd_nominator = vmaxf/keq
for type, this_substrate in substrates.items():
common_denominator_this_substrate = 1
s = this_substrate.symbol
kms = self.parameters[reactant_km_relation[s]].symbol
stoich = self.reactant_stoichiometry[type]
for alpha in range(int(abs(stoich))):
common_denominator_this_substrate += (s/kms)**(alpha+1)
# Multiply for every substrate
common_denominator_substrates *= common_denominator_this_substrate
fwd_nominator *= (s/kms)**abs(stoich)
bwd_nominator *= kms**(-1*abs(stoich))
common_denominator_products = 1
for type, this_product in products.items():
common_denominator_this_product = 1
p = this_product.symbol
kmp = self.parameters[reactant_km_relation[p]].symbol
stoich = self.reactant_stoichiometry[type]
for beta in range(int(abs(stoich))):
common_denominator_this_product += (p/kmp)**(beta+1)
# Multiply for every product
common_denominator_products *= common_denominator_this_product
bwd_nominator *= p**abs(stoich)
common_denominator = common_denominator_substrates +\
common_denominator_products - 1
forward_rate_expression = fwd_nominator/common_denominator
backward_rate_expression = bwd_nominator/common_denominator
rate_expression = forward_rate_expression-backward_rate_expression
self.reaction_rates = TabDict([('v_net', rate_expression),
('v_fwd', forward_rate_expression),
('v_bwd', backward_rate_expression),
])
expressions = {}
# TODO Find a better solution to handle duplicate substrates
# The dict currently does not allow for this
for type, this_substrate in substrates.items():
s = this_substrate.symbol
stoich = self.reactant_stoichiometry[type]
if s in expressions.keys():
expressions[s] += stoich * rate_expression
else:
expressions[s] = stoich*rate_expression
for type, this_product in products.items():
p = this_product.symbol
stoich = self.reactant_stoichiometry[type]
if p in expressions.keys():
expressions[p] += stoich * rate_expression
else:
expressions[p] = stoich*rate_expression
self.expressions = expressions
self.expression_parameters = self.get_parameters_from_expression(rate_expression)
def update_qssa_rate_expression(self):
substrates = {k:r for k,r in self.reactants.items()
if k.startswith('substrate')}
products= {k:r for k,r in self.reactants.items()
if k.startswith('product')}
expressions = {}
for type, this_substrate in substrates.items():
s = this_substrate.symbol
stoich = self.reactant_stoichiometry[type]
if s in expressions.keys():
expressions[s] += stoich * self.reaction_rates['v_net']
else:
expressions[s] = stoich*self.reaction_rates['v_net']
for type, this_product in products.items():
p = this_product.symbol
stoich = self.reactant_stoichiometry[type]
if p in expressions.keys():
expressions[p] += stoich * self.reaction_rates['v_net']
else:
expressions[p] = stoich * self.reaction_rates['v_net']
self.expressions = expressions
""""
Convenience kinetics has no detailed mechanism
"""
def get_full_rate_expression(self):
raise NotImplementedError
def calculate_rate_constants(self):
raise NotImplementedError
Convenience.__name__ += Convenience.suffix
return Convenience

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