#!/usr/bin/env python
# coding: utf-8

# ## Ethanol yield from glucose
# 
# https://groups.google.com/forum/#!topic/cobra-pie/-sPHjNsB974
# 
# This is definitely doable. 
# 
# Steps are:
# 1. Get a genome scale metabolic model for yeast such as iMM904. http://bigg.ucsd.edu/ has it.
# 2. [hardest part - should take a beginner about 1 hour depending on molecule] Add reactions needed to make your molecule and a "demand reaction" for it to leave the cell.  Decide if you want to account for transport costs or not.
# 3. Optimize (maximize) flux just to this demand reaction. This flux is the molar yield assuming you provided 1 mmol glucose gDW-1 h-1 and have no other demands (turn off ATP maintenance reaction, etc.)
# 4. Convert to a g/g yield basis as is typical using the molecular weights of glucose and your product.
# 5. Verify overall stoichiometry is plausible (look at all the exchanges of what is going in and out of the cell in the max yield simulation)
# 
# I'm happy to peer review your progress!  Perhaps write back with the Ethanol max yield?  That is easily doable as the molecule is native and you can skip #2.
# https://cobrapy.readthedocs.io/en/latest/simulating.html#  for the basics. 
# 
# Good luck!
# Josh
# 
# 
# ----
# 
# Hi Björn,
# 
# In addition to what Josh said, take a look at the following materials:
# 
# https://cobrapy.readthedocs.io/en/latest/phenotype_phase_plane.html
# 
# Our general materials for the software carpentry course on cell design:
# https://biosustain.github.io/cell-factory-design-course/
# 
# In particular:
# https://biosustain.github.io/cell-factory-design-course/08-Predict-heterologous-pathways/
# 
# https://biosustain.github.io/cell-factory-design-course/07-Theoretical-maximum-yields/
# 
# Also take a look at the documentation for cameo, our strain design library
# https://cameo.readthedocs.io/en/latest/
# 
# Happy to answer any specific question and congrats to your acquiring a very experienced peer reviewer ;)

# In[1]:


import cobra


# In[2]:


cobra.__version__


# In[3]:


iMM904 = cobra.io.load_json_model("iMM904.json")


# In[4]:


model = iMM904.copy()


# In[5]:


print(model.objective)


# I have to change the model objective from biomass to ethanol

# In[6]:


model.objective = model.reactions.EX_etoh_e


# In[7]:


print(model.objective)


# This optimises the model using fba and parsimonius fba (trying to minimize overall fluxes?).

# In[8]:


fba_solution  = model.optimize()
pfba_solution = cobra.flux_analysis.pfba(model)


# In[9]:


model.summary()


# In[10]:


fba_solution.fluxes.EX_glc__D_e, fba_solution.fluxes.EX_etoh_e


# In[11]:


pfba_solution.fluxes.EX_glc__D_e, pfba_solution.fluxes.EX_etoh_e


# The parsimonius fba solution seems similar to the normal fba.
# https://cobrapy.readthedocs.io/en/latest/simulating.html

# Dividing the ethanol flux by the glucose flux gives the molar yield, expected to be two moles of ethanol for each mole glucose.

# In[12]:


molar_yeld = round( (-1. * fba_solution.fluxes.EX_etoh_e) / fba_solution.fluxes.EX_glc__D_e )
molar_yeld


# In[13]:


mw_et, mw_glc = model.metabolites.etoh_e.formula_weight, model.metabolites.glc__D_c.formula_weight
mw_et, mw_glc


# In[14]:


print(f"{molar_yeld  * (mw_et/mw_glc)} g ethanol / g glucose")


# The expected ethanol yield in g etoh per g glucose should be around 0.51 g/g

# As can be seen below the fba and pfba solutions are similar but not identical.

# In[15]:


fba_solution.fluxes[fba_solution.fluxes.abs() >= 10.0]


# In[16]:


pfba_solution.fluxes[pfba_solution.fluxes.abs() >= 10.0]


# In[17]:


import escher


# In[18]:


reaction_data = pfba_solution.fluxes[pfba_solution.fluxes.abs() > 1E-07].to_dict()


# In[19]:


escher.Builder( map_name='iMM904.Central carbon metabolism',
                model_name='iMM904',
                reaction_data=reaction_data ).display_in_notebook()


# In[20]:


model.reactions.HEX1


# In[21]:


model.reactions.GLUK


# see here for how to overlay solution on metabolic map
# 
# https://nbviewer.jupyter.org/github/zakandrewking/escher/blob/master/docs/notebooks/JavaScript%20development%20and%20offline%20maps.ipynb

# In[22]:


pfba_solution.fluxes.HEX1


# In[23]:


pfba_solution.fluxes.GLUK


# In[24]:


fba_solution.fluxes.HEX1


# In[25]:


fba_solution.fluxes.GLUK