/
cosa_single_swap_effect_analysis.py
208 lines (178 loc) · 8.8 KB
/
cosa_single_swap_effect_analysis.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
"""Contains the script for performing the single cofactor swap analysis."""
# IMPORTS #
# External
import cobra
import copy
import os
import numpy
import shutil
from typing import List
# Internal
from cosa_get_all_tcosa_reaction_ids import get_all_tcosa_reaction_ids
from cosa_get_suffix import cosa_get_suffix
from fba import get_fba_base_problem, perform_fba_flux_maximization
from helper import ensure_folder_existence, json_load, json_write, json_zip_load, json_zip_write
from optmdfpathway import STANDARD_R, STANDARD_T, get_optmdfpathway_base_problem
from optimization import perform_variable_maximization
from cosa_load_model_data import (
MIN_OPTMDF, load_model_data
)
from cosa_get_model_with_nadx_scenario import cosa_get_model_with_nadx_scenario
from cosa_add_promiscuity_constraints import cosa_add_promiscuity_constraints
# PUBLIC FUNCTIONS #
def cosa_single_swap_analysis(anaerobic: bool, c_source: str = "glucose"):
"""Performs the single redox cofactor swap analysis.
Args:
anaerobic (bool): Is it anaerobic (True)?
c_source (str, optional): Either 'glucose' or 'acetate'. Defaults to "glucose".
"""
all_base_ids, cobra_model, concentration_values_free, concentration_values_paper,\
standardconc_dG0_values, paperconc_dG0_values,\
num_nad_and_nadp_reactions, num_nad_base_ids, num_nadp_base_ids,\
ratio_constraint_data, nad_base_ids, nadp_base_ids, used_growth, zeroed_reaction_ids = load_model_data(anaerobic=anaerobic, expanded=False, c_source=c_source)
suffix = cosa_get_suffix(anaerobic, expanded=False, c_source=c_source)
nadx_scenario = "WILDTYPE"
old_cobra_model = copy.deepcopy(cobra_model)
biomass_reaction_id = "BIOMASS_Ec_iML1515_core_75p37M"
if (c_source != "glucose") or (anaerobic):
concentration_scenarios = ("STANDARDCONC",)
else:
concentration_scenarios = ("STANDARDCONC", "VIVOCONC",)
for concentration_scenario in concentration_scenarios:
swap_json_path = f"./cosa/results{suffix}/swap_results_{concentration_scenario}.json"
if concentration_scenario == "STANDARDCONC":
dG0_values = copy.deepcopy(standardconc_dG0_values)
used_concentration_values = concentration_values_free
elif concentration_scenario == "VIVOCONC":
dG0_values = copy.deepcopy(paperconc_dG0_values)
used_concentration_values = concentration_values_paper
print("~~~")
print(nadx_scenario)
optmdf_json_path = f"./cosa/results{suffix}/runs/OPTMDF_{concentration_scenario}_{nadx_scenario}.json"
optsubmdf_json_path = f"./cosa/results{suffix}/runs/OPTSUBMDF_{concentration_scenario}_{nadx_scenario}.json"
optmdf_json = json_zip_load(optmdf_json_path)
optsubmdf_json = json_zip_load(optsubmdf_json_path)
growth_rates = optmdf_json.keys()
cobra_model = copy.deepcopy(old_cobra_model)
cobra_model = cosa_get_model_with_nadx_scenario(
nadx_scenario=nadx_scenario,
cobra_model=cobra_model,
)
print(">Get base OptMDFpathway MILP...")
optmdfpathway_base_problem = get_optmdfpathway_base_problem(
cobra_model=cobra_model,
dG0_values=dG0_values,
metabolite_concentration_values=used_concentration_values,
ratio_constraint_data=ratio_constraint_data,
R=STANDARD_R,
T=STANDARD_T,
extra_constraints=[],
sub_network_ids=get_all_tcosa_reaction_ids(cobra_model),
)
print(">Get model variables dictionary")
optmdfpathway_base_variables = optmdfpathway_base_problem.variablesDict()
print(">Set no promiscuity constraint")
optmdfpathway_base_problem = cosa_add_promiscuity_constraints(
optmdfpathway_base_problem=optmdfpathway_base_problem,
optmdfpathway_base_variables=optmdfpathway_base_variables,
cobra_model=cobra_model,
dG0_values=dG0_values,
)
try:
swap_results = json_load(swap_json_path)
except FileNotFoundError:
swap_results = {}
counter = 0
for reaction in cobra_model.reactions:
if (reaction.id not in dG0_values.keys()):
continue
if ((reaction.id != "ICDHyr_FWD_ORIGINAL_NADP_TCOSA") and (reaction.id != "PDH_ORIGINAL_NAD_TCOSA")) or (c_source != "acetate"):
if (reaction.id in swap_results.keys()):
continue
multiplier = 1.0
else:
if (reaction.id == "ICDHyr_FWD_ORIGINAL_NADP_TCOSA"):
multiplier = .9875 # Numeric error at highest growth rate D:
else:
multiplier = .999
if reaction.id.endswith("_ORIGINAL_NAD_TCOSA"):
other_id = reaction.id.replace("_ORIGINAL_NAD_TCOSA", "_VARIANT_NADP_TCOSA")
elif reaction.id.endswith("_VARIANT_NAD_TCOSA"):
continue
elif reaction.id.endswith("_ORIGINAL_NADP_TCOSA"):
other_id = reaction.id.replace("_ORIGINAL_NADP_TCOSA", "_VARIANT_NAD_TCOSA")
elif reaction.id.endswith("_VARIANT_NADP_TCOSA"):
continue
else:
continue
original_real_ub = reaction.upper_bound
original_other_ub = cobra_model.reactions.get_by_id(other_id).upper_bound
if original_other_ub > 0.0:
input(f"ERROR WITH UB in reaction {reaction.id}")
swap_results[reaction.id] = {}
for growth_rate_str in growth_rates:
growth_rate = float(growth_rate_str.replace(",", "."))
swap_results[reaction.id][growth_rate_str] = {}
print("Set growth to", growth_rate)
optmdfpathway_base_variables[biomass_reaction_id].bounds(
growth_rate*multiplier,
1e12
)
# Do swap
optmdfpathway_base_variables[reaction.id].bounds(
0.0,
0.0,
)
optmdfpathway_base_variables[other_id].bounds(
0.0,
reaction.upper_bound,
)
# end of Do swap
print(">OPTMDF calculations")
optmdfpathway_result = perform_variable_maximization(
optmdfpathway_base_problem,
"var_B"
)
print(optmdfpathway_result["status"])
if optmdfpathway_result["status"] != "Optimal":
swap_results[reaction.id][growth_rate_str]["OptMDF"] = float("NaN")
swap_results[reaction.id][growth_rate_str]["OptSubMDF"] = float("NaN")
continue
print("Growth", optmdfpathway_result["values"][biomass_reaction_id])
swapped_optmdf = optmdfpathway_result["values"]["var_B"]
original_optmdf = optmdf_json[growth_rate_str]["values"]["var_B"]
print("Swapped var_B:", swapped_optmdf, "kJ/mol")
print("Original var_B: ", original_optmdf, "kJ/mol")
optmdf_difference = swapped_optmdf - original_optmdf
print(">SubMDF calculations")
optmdfpathway_base_variables["var_B"].bounds(MIN_OPTMDF, 1e6)
optsubmdfpathway_result = perform_variable_maximization(
optmdfpathway_base_problem,
"var_B2"
)
print(optsubmdfpathway_result["status"])
if optsubmdfpathway_result["status"] != "Optimal":
swap_results[reaction.id][growth_rate_str]["OptSubMDF"] = float("NaN")
continue
swapped_optsubmdf = optsubmdfpathway_result["values"]["var_B2"]
original_optsubmdf = optsubmdf_json[growth_rate_str]["values"]["var_B2"]
print("Swapped var_B2:", swapped_optsubmdf, "kJ/mol")
print("Original var_B2: ", original_optsubmdf, "kJ/mol")
optsubmdf_difference = swapped_optsubmdf - original_optsubmdf
swap_results[reaction.id][growth_rate_str]["OptMDF"] = round(optmdf_difference, 6)
swap_results[reaction.id][growth_rate_str]["OptSubMDF"] = round(optsubmdf_difference, 6)
if counter >= 10:
json_write(swap_json_path, swap_results)
counter = 0
counter += 1
# Undo swap
optmdfpathway_base_variables[reaction.id].bounds(
0.0,
original_real_ub,
)
optmdfpathway_base_variables[other_id].bounds(
0.0,
0.0,
)
# end of Undo swap
json_write(swap_json_path, swap_results)