eliminate_circulars.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "edb2dfe1-0317-41c6-9954-d967e3b1e38e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import cobra\n",
    "import pandas as pd\n",
    "\n",
    "model = cobra.io.read_sbml_model(\"2.2/finegoldia_magna_ATCC_29328_2.2.fo.ch.mp.mcb.lt.re.ar.gpr.pw.gf1.gfmm.gf2.gfco3.xml\")\n",
    "\n",
    "unwanted_metabolites = [\"EX_o2_e\"]\n",
    "\n",
    "# import medium\n",
    "snm3 = pd.read_csv(\"SNM3.csv\", sep=\"\\t\")\n",
    "snm3_dict = {f\"EX_{met['BiGG']}_e\" : 10.0 for i,met in snm3.iterrows()}\n",
    "snm3_dict = {k: v for k,v in snm3_dict.items() if k not in unwanted_metabolites}\n",
    "            \n",
    "# For all exchanges open\n",
    "for reac in model.exchanges:\n",
    "    if reac.id in unwanted_metabolites:    # elimintes unwanted metabolites (O2)\n",
    "        reac.lower_bound = 0.0\n",
    "    else:\n",
    "        reac.lower_bound = -1000.0\n",
    "\n",
    "# Define SNM3 medium\n",
    "#for reac in model.exchanges:\n",
    "#    if reac.id in snm3_dict and reac.id not in unwanted_metabolites: \n",
    "#        reac.lower_bound = -10.0\n",
    "#    else:\n",
    "#        reac.lower_bound = 0.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "bcc6addc-28a5-4e38-aaf3-21bff0d5cab5",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>type</th>\n",
       "      <th>equation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ATP</td>\n",
       "      <td>atp_c + h2o_c --&gt; adp_c + h_c + pi_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CTP</td>\n",
       "      <td>ctp_c + h2o_c --&gt; cdp_c + h_c + pi_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>GTP</td>\n",
       "      <td>gtp_c + h2o_c --&gt; gdp_c + h_c + pi_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>UTP</td>\n",
       "      <td>utp_c + h2o_c --&gt; udp_c + h_c + pi_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ITP</td>\n",
       "      <td>itp_c + h2o_c --&gt; idp_c + h_c + pi_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NADH</td>\n",
       "      <td>nadh_c --&gt; h_c + nad_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>NADPH</td>\n",
       "      <td>nadph_c --&gt; h_c + nadp_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>FADH2</td>\n",
       "      <td>fadh2_c --&gt; 2 h_c + fad_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>FMNH2</td>\n",
       "      <td>fmnh2_c --&gt; 2 h_c + fmn_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Q8H2</td>\n",
       "      <td>q8h2_c --&gt; 2 h_c + q8_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>MQL8</td>\n",
       "      <td>mql8_c --&gt; 2 h_c + mqn8_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>DMMQL8</td>\n",
       "      <td>2dmmql8_c --&gt; 2 h_c + 2dmmq8_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>ACCOA</td>\n",
       "      <td>h2o_c + accoa_c --&gt; h_c + ac_c + coa_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>GLU</td>\n",
       "      <td>glu__L_c + h2o_c --&gt; akg_c + nh4_c + 2 h_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>PROTON</td>\n",
       "      <td>h_p --&gt; h_c</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      type                                    equation\n",
       "0      ATP        atp_c + h2o_c --> adp_c + h_c + pi_c\n",
       "1      CTP        ctp_c + h2o_c --> cdp_c + h_c + pi_c\n",
       "2      GTP        gtp_c + h2o_c --> gdp_c + h_c + pi_c\n",
       "3      UTP        utp_c + h2o_c --> udp_c + h_c + pi_c\n",
       "4      ITP        itp_c + h2o_c --> idp_c + h_c + pi_c\n",
       "5     NADH                      nadh_c --> h_c + nad_c\n",
       "6    NADPH                    nadph_c --> h_c + nadp_c\n",
       "7    FADH2                   fadh2_c --> 2 h_c + fad_c\n",
       "8    FMNH2                   fmnh2_c --> 2 h_c + fmn_c\n",
       "9     Q8H2                     q8h2_c --> 2 h_c + q8_c\n",
       "10    MQL8                   mql8_c --> 2 h_c + mqn8_c\n",
       "11  DMMQL8              2dmmql8_c --> 2 h_c + 2dmmq8_c\n",
       "12   ACCOA      h2o_c + accoa_c --> h_c + ac_c + coa_c\n",
       "13     GLU  glu__L_c + h2o_c --> akg_c + nh4_c + 2 h_c\n",
       "14  PROTON                                 h_p --> h_c"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dissipation_rxns = pd.read_csv(\"energy_dissipation_rxns.csv\") # see dissipation_reactions_from_Fritzemeier.xlsx\n",
    "dissipation_rxns   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "217c4bb2-c9bb-4495-a9e2-d5c78b68d64a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2dmmq8_c\n"
     ]
    }
   ],
   "source": [
    "import re\n",
    "metabolites = []\n",
    "for row in dissipation_rxns.iterrows():\n",
    "    compounds = re.split(\" &#8652; | ⇌ | <-> | --> | <-- \", row[1]['equation'])\n",
    "    metabolites += re.split(\" [+] \", compounds[0])\n",
    "    metabolites += re.split(\" [+] \", compounds[1])\n",
    "\n",
    "met_id_list = [m.id for m in model.metabolites]\n",
    "for m in metabolites:\n",
    "    if \" \" in m:\n",
    "        m = m.split(\" \")[1]\n",
    "    if m not in met_id_list:\n",
    "        print(m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6058f245-3111-402f-a9ac-1442fe74c6f3",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>type</th>\n",
       "      <th>equation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ATP</td>\n",
       "      <td>atp_c + h2o_c --&gt; adp_c + h_c + pi_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CTP</td>\n",
       "      <td>ctp_c + h2o_c --&gt; cdp_c + h_c + pi_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>GTP</td>\n",
       "      <td>gtp_c + h2o_c --&gt; gdp_c + h_c + pi_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>UTP</td>\n",
       "      <td>utp_c + h2o_c --&gt; udp_c + h_c + pi_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ITP</td>\n",
       "      <td>itp_c + h2o_c --&gt; idp_c + h_c + pi_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NADH</td>\n",
       "      <td>nadh_c --&gt; h_c + nad_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>NADPH</td>\n",
       "      <td>nadph_c --&gt; h_c + nadp_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>FADH2</td>\n",
       "      <td>fadh2_c --&gt; 2 h_c + fad_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>FMNH2</td>\n",
       "      <td>fmnh2_c --&gt; 2 h_c + fmn_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Q8H2</td>\n",
       "      <td>q8h2_c --&gt; 2 h_c + q8_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>MQL8</td>\n",
       "      <td>mql8_c --&gt; 2 h_c + mqn8_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>ACCOA</td>\n",
       "      <td>h2o_c + accoa_c --&gt; h_c + ac_c + coa_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>GLU</td>\n",
       "      <td>glu__L_c + h2o_c --&gt; akg_c + nh4_c + 2 h_c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>PROTON</td>\n",
       "      <td>h_p --&gt; h_c</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      type                                    equation\n",
       "0      ATP        atp_c + h2o_c --> adp_c + h_c + pi_c\n",
       "1      CTP        ctp_c + h2o_c --> cdp_c + h_c + pi_c\n",
       "2      GTP        gtp_c + h2o_c --> gdp_c + h_c + pi_c\n",
       "3      UTP        utp_c + h2o_c --> udp_c + h_c + pi_c\n",
       "4      ITP        itp_c + h2o_c --> idp_c + h_c + pi_c\n",
       "5     NADH                      nadh_c --> h_c + nad_c\n",
       "6    NADPH                    nadph_c --> h_c + nadp_c\n",
       "7    FADH2                   fadh2_c --> 2 h_c + fad_c\n",
       "8    FMNH2                   fmnh2_c --> 2 h_c + fmn_c\n",
       "9     Q8H2                     q8h2_c --> 2 h_c + q8_c\n",
       "10    MQL8                   mql8_c --> 2 h_c + mqn8_c\n",
       "12   ACCOA      h2o_c + accoa_c --> h_c + ac_c + coa_c\n",
       "13     GLU  glu__L_c + h2o_c --> akg_c + nh4_c + 2 h_c\n",
       "14  PROTON                                 h_p --> h_c"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The Metabolite 2dmmq8_c does not exist in model\n",
    "dissipation_rxns.drop(11, inplace = True)\n",
    "dissipation_rxns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "010b4e4e-bd1c-462d-a1eb-95bfac374768",
   "metadata": {},
   "outputs": [],
   "source": [
    "# from A. Grekova\n",
    "# input : reaction string\n",
    "# output : {<Metabolite object> : stoichiometry (integer)}\n",
    "# this method is only useful, if coefficients are either 1 or 2 \n",
    "def parse_reaction(eq):\n",
    "    eq = eq.split(' ')\n",
    "    eq_matrix={}\n",
    "    \n",
    "    are_products = False\n",
    "    coeff = 1\n",
    "    for i,part in enumerate(eq):\n",
    "        if part == '-->':\n",
    "            are_products = True\n",
    "            continue          \n",
    "        if part == '+':\n",
    "            continue\n",
    "        if part == '2':\n",
    "            coeff = 2\n",
    "            continue\n",
    "        if are_products:\n",
    "            eq_matrix[model.metabolites.get_by_id(part)] = 1*coeff\n",
    "            coeff = 1\n",
    "        else:\n",
    "            eq_matrix[model.metabolites.get_by_id(part)] = -1*coeff\n",
    "            coeff = 1\n",
    "    return eq_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ea3f3579-f68c-4713-a08b-040a1871a147",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Set objective to ATP : 1.0\n",
      "ADK1: amp_c + atp_c <=> 2.0 adp_c\n",
      "DDCAt2pp: ddca_p + h_p --> ddca_c + h_c\n",
      "PPK: atp_c + pi_c --> adp_c + ppi_c\n",
      "FACOAE120: ddcacoa_c + h2o_c <=> coa_c + ddca_c + h_c\n",
      "FACOAL120t2pp: atp_c + coa_c + ddca_p + h_p <=> amp_c + ddcacoa_c + h_c + ppi_c\n",
      "ATP: atp_c + h2o_c --> adp_c + h_c + pi_c\n",
      "----------------------------\n",
      "Set objective to CTP : 1.0\n",
      "DDCAt2pp: ddca_p + h_p --> ddca_c + h_c\n",
      "PPDK: atp_c + pi_c + pyr_c --> amp_c + h_c + pep_c + ppi_c\n",
      "PYK4: cdp_c + h_c + pep_c --> ctp_c + pyr_c\n",
      "FACOAE120: ddcacoa_c + h2o_c <=> coa_c + ddca_c + h_c\n",
      "FACOAL120t2pp: atp_c + coa_c + ddca_p + h_p <=> amp_c + ddcacoa_c + h_c + ppi_c\n",
      "CTP: ctp_c + h2o_c --> cdp_c + h_c + pi_c\n",
      "----------------------------\n",
      "Set objective to GTP : 1.0\n",
      "ADK1: amp_c + atp_c <=> 2.0 adp_c\n",
      "DDCAt2pp: ddca_p + h_p --> ddca_c + h_c\n",
      "PPK: atp_c + pi_c --> adp_c + ppi_c\n",
      "PPK50_B: 47.0 gdp_c + ppi50_c --> 47.0 gtp_c + pppi_c\n",
      "PPK50r: 47.0 atp_c + pppi_c <=> 47.0 adp_c + ppi50_c\n",
      "FACOAE120: ddcacoa_c + h2o_c <=> coa_c + ddca_c + h_c\n",
      "FACOAL120t2pp: atp_c + coa_c + ddca_p + h_p <=> amp_c + ddcacoa_c + h_c + ppi_c\n",
      "GTP: gtp_c + h2o_c --> gdp_c + h_c + pi_c\n",
      "----------------------------\n",
      "Set objective to UTP : 1.0\n",
      "DDCAt2pp: ddca_p + h_p --> ddca_c + h_c\n",
      "PPDK: atp_c + pi_c + pyr_c --> amp_c + h_c + pep_c + ppi_c\n",
      "PYK2: h_c + pep_c + udp_c --> pyr_c + utp_c\n",
      "FACOAE120: ddcacoa_c + h2o_c <=> coa_c + ddca_c + h_c\n",
      "FACOAL120t2pp: atp_c + coa_c + ddca_p + h_p <=> amp_c + ddcacoa_c + h_c + ppi_c\n",
      "UTP: h2o_c + utp_c --> h_c + pi_c + udp_c\n",
      "----------------------------\n",
      "Set objective to ITP : 1.0\n",
      "DDCAt2pp: ddca_p + h_p --> ddca_c + h_c\n",
      "PPDK: atp_c + pi_c + pyr_c --> amp_c + h_c + pep_c + ppi_c\n",
      "PYK5: h_c + idp_c + pep_c --> itp_c + pyr_c\n",
      "FACOAE120: ddcacoa_c + h2o_c <=> coa_c + ddca_c + h_c\n",
      "FACOAL120t2pp: atp_c + coa_c + ddca_p + h_p <=> amp_c + ddcacoa_c + h_c + ppi_c\n",
      "ITP: h2o_c + itp_c --> h_c + idp_c + pi_c\n",
      "----------------------------\n",
      "Set objective to NADH : 0.0\n",
      "----------------------------\n",
      "Set objective to NADPH : 0.0\n",
      "----------------------------\n",
      "Set objective to FADH2 : 0.0\n",
      "----------------------------\n",
      "Set objective to FMNH2 : 0.0\n",
      "----------------------------\n",
      "Set objective to Q8H2 : 0.0\n",
      "----------------------------\n",
      "Set objective to MQL8 : 0.0\n",
      "----------------------------\n",
      "Set objective to ACCOA : 1.0\n",
      "ACKr: ac_c + atp_c <=> actp_c + adp_c\n",
      "ADK1: amp_c + atp_c <=> 2.0 adp_c\n",
      "DDCAt2pp: ddca_p + h_p --> ddca_c + h_c\n",
      "PPK: atp_c + pi_c --> adp_c + ppi_c\n",
      "PTAr: accoa_c + pi_c <=> actp_c + coa_c\n",
      "FACOAE120: ddcacoa_c + h2o_c <=> coa_c + ddca_c + h_c\n",
      "FACOAL120t2pp: atp_c + coa_c + ddca_p + h_p <=> amp_c + ddcacoa_c + h_c + ppi_c\n",
      "ACCOA: accoa_c + h2o_c --> ac_c + coa_c + h_c\n",
      "----------------------------\n",
      "Set objective to GLU : 0.0\n",
      "----------------------------\n",
      "Set objective to PROTON : 1.0\n",
      "ACKr: ac_c + atp_c <=> actp_c + adp_c\n",
      "ADK1: amp_c + atp_c <=> 2.0 adp_c\n",
      "ATPS4rpp: adp_c + 4.0 h_p + pi_c <=> atp_c + h2o_c + 3.0 h_c\n",
      "DDCAt2pp: ddca_p + h_p --> ddca_c + h_c\n",
      "PPK: atp_c + pi_c --> adp_c + ppi_c\n",
      "PTAr: accoa_c + pi_c <=> actp_c + coa_c\n",
      "FACOAE120: ddcacoa_c + h2o_c <=> coa_c + ddca_c + h_c\n",
      "FACOAL120t2pp: atp_c + coa_c + ddca_p + h_p <=> amp_c + ddcacoa_c + h_c + ppi_c\n",
      "ACCOA: accoa_c + h2o_c --> ac_c + coa_c + h_c\n",
      "PROTON: h_p --> h_c\n",
      "----------------------------\n"
     ]
    }
   ],
   "source": [
    "from cobra import Reaction\n",
    "\n",
    "#simulate changed conditions without changing the entire model\n",
    "with model: \n",
    "    \n",
    "    # add dissipation reactions\n",
    "    for i, row in dissipation_rxns.iterrows():\n",
    "        met_atp = parse_reaction(row['equation'])\n",
    "        rxn = Reaction(row['type'])\n",
    "        rxn.name = 'Test ' + row['type'] + ' dissipation reaction'\n",
    "        rxn.add_metabolites(met_atp)\n",
    "        model.add_reaction(rxn)\n",
    "        \n",
    "    for rxn in model.reactions:\n",
    "        \n",
    "        if 'EX_' in rxn.id:\n",
    "            rxn.upper_bound = 0.0\n",
    "            rxn.lower_bound = 0.0\n",
    "            #print('Set exchange rxn to 0', rxn.name)\n",
    "            \n",
    "        # set reversible reactions fluxes to [-1,1]    \n",
    "        elif rxn.reversibility:\n",
    "            rxn.upper_bound = 1.0\n",
    "            rxn.lower_bound = -1.0\n",
    "            #print('Reversible rxn', rxn.name)\n",
    "            \n",
    "        # irreversible reactions have fluxes [1,0]    \n",
    "        else:\n",
    "            rxn.upper_bound = 1.0\n",
    "            rxn.lower_bound = 0.0\n",
    "            #print('Irreversible rxn', rxn.name)\n",
    "     \n",
    "    reactions_to_check = []\n",
    "    # optimize by choosing one of dissipation reactions as an objective\n",
    "    for i, row in dissipation_rxns.iterrows():\n",
    "        model.objective = row['type']\n",
    "        print('Set objective to', row['type'], ':', model.optimize().objective_value)\n",
    "        \n",
    "        if model.optimize().objective_value != 0.0:\n",
    "            \n",
    "            # check which reactions are active related to each metabolite that is produced after adding dissipation reactions\n",
    "            fba_fluxes = pd.DataFrame(model.optimize().fluxes)\n",
    "            fba_fluxes.reset_index(level=0,inplace=True)\n",
    "\n",
    "            for react in list(fba_fluxes.loc[fba_fluxes['fluxes'] != 0]['index']):\n",
    "                \n",
    "                reactions_to_check.append(model.reactions.get_by_id(react).id)\n",
    "                # print only active reactions\n",
    "                print(model.reactions.get_by_id(react))\n",
    "        \n",
    "        print(\"----------------------------\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e2ea9fb7-8906-405c-b99d-f8ee929ac194",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <table>\n",
       "            <tr>\n",
       "                <td><strong>Reaction identifier</strong></td><td>FACOAL120t2pp</td>\n",
       "            </tr><tr>\n",
       "                <td><strong>Name</strong></td><td>Fatty-acid-CoA ligase (dodecanoate transport via vectoral Co-A coupling)</td>\n",
       "            </tr><tr>\n",
       "                <td><strong>Memory address</strong></td>\n",
       "                <td>0x07fe139f2af40</td>\n",
       "            </tr><tr>\n",
       "                <td><strong>Stoichiometry</strong></td>\n",
       "                <td>\n",
       "                    <p style='text-align:right'>atp_c + coa_c + ddca_p + h_p --> amp_c + ddcacoa_c + h_c + ppi_c</p>\n",
       "                    <p style='text-align:right'>ATP C10H12N5O13P3 + Coenzyme A + Dodecanoate (n-C12:0) + H+ --> AMP C10H12N5O7P + Dodecanoyl-CoA (n-C12:0CoA) + H+ + Diphosphate</p>\n",
       "                </td>\n",
       "            </tr><tr>\n",
       "                <td><strong>GPR</strong></td><td>FMG_1293</td>\n",
       "            </tr><tr>\n",
       "                <td><strong>Lower bound</strong></td><td>0</td>\n",
       "            </tr><tr>\n",
       "                <td><strong>Upper bound</strong></td><td>1000.0</td>\n",
       "            </tr>\n",
       "        </table>\n",
       "        "
      ],
      "text/plain": [
       "<Reaction FACOAL120t2pp at 0x7fe139f2af40>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# ADK1: is reversible\n",
    "# DDCAt2pp: not in MetaCyc\n",
    "# FACOAE120: ddcacoa_c + h2o_c <=> coa_c + ddca_c + h_c  =====> ddcacoa_c + h2o_c --> coa_c + ddca_c + h_c\n",
    "model.reactions.get_by_id(\"FACOAE120\").build_reaction_from_string(\"ddcacoa_c + h2o_c --> coa_c + ddca_c + h_c\")\n",
    "model.reactions.get_by_id(\"FACOAE120\")\n",
    "# FACOAL120t2pp: atp_c + coa_c + ddca_p + h_p <=> amp_c + ddcacoa_c + h_c + ppi_c ====> atp_c + coa_c + ddca_p + h_p --> amp_c + ddcacoa_c + h_c + ppi_c\n",
    "model.reactions.get_by_id(\"FACOAL120t2pp\").build_reaction_from_string(\"atp_c + coa_c + ddca_p + h_p --> amp_c + ddcacoa_c + h_c + ppi_c\")\n",
    "model.reactions.get_by_id(\"FACOAL120t2pp\")\n",
    "# ACKr: is reversible (Acetate kinase)\n",
    "# PPK50r: is reversible\n",
    "# PTAr: is reversible"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b8bf1793-5bc1-48b5-bbdb-61c0deb8b0f9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "94.24459770349941"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.slim_optimize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "669b3d13-6e1f-4e35-a4f7-a5ec0674b914",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Set objective to ATP : 0.0\n",
      "----------------------------\n",
      "Set objective to CTP : 0.0\n",
      "----------------------------\n",
      "Set objective to GTP : 0.0\n",
      "----------------------------\n",
      "Set objective to UTP : 0.0\n",
      "----------------------------\n",
      "Set objective to ITP : 0.0\n",
      "----------------------------\n",
      "Set objective to NADH : 0.0\n",
      "----------------------------\n",
      "Set objective to NADPH : 0.0\n",
      "----------------------------\n",
      "Set objective to FADH2 : 0.0\n",
      "----------------------------\n",
      "Set objective to FMNH2 : 0.0\n",
      "----------------------------\n",
      "Set objective to Q8H2 : 0.0\n",
      "----------------------------\n",
      "Set objective to MQL8 : 0.0\n",
      "----------------------------\n",
      "Set objective to ACCOA : 0.0\n",
      "----------------------------\n",
      "Set objective to GLU : 0.0\n",
      "----------------------------\n",
      "Set objective to PROTON : 0.0\n",
      "----------------------------\n"
     ]
    }
   ],
   "source": [
    "from cobra import Reaction\n",
    "\n",
    "#simulate changed conditions without changing the entire model\n",
    "with model: \n",
    "    \n",
    "    # add dissipation reactions\n",
    "    for i, row in dissipation_rxns.iterrows():\n",
    "        met_atp = parse_reaction(row['equation'])\n",
    "        rxn = Reaction(row['type'])\n",
    "        rxn.name = 'Test ' + row['type'] + ' dissipation reaction'\n",
    "        rxn.add_metabolites(met_atp)\n",
    "        model.add_reaction(rxn)\n",
    "        \n",
    "    for rxn in model.reactions:\n",
    "        \n",
    "        if 'EX_' in rxn.id:\n",
    "            rxn.upper_bound = 0.0\n",
    "            rxn.lower_bound = 0.0\n",
    "            #print('Set exchange rxn to 0', rxn.name)\n",
    "            \n",
    "        # set reversible reactions fluxes to [-1,1]    \n",
    "        elif rxn.reversibility:\n",
    "            rxn.upper_bound = 1.0\n",
    "            rxn.lower_bound = -1.0\n",
    "            #print('Reversible rxn', rxn.name)\n",
    "            \n",
    "        # irreversible reactions have fluxes [1,0]    \n",
    "        else:\n",
    "            rxn.upper_bound = 1.0\n",
    "            rxn.lower_bound = 0.0\n",
    "            #print('Irreversible rxn', rxn.name)\n",
    "     \n",
    "    reactions_to_check = []\n",
    "    # optimize by choosing one of dissipation reactions as an objective\n",
    "    for i, row in dissipation_rxns.iterrows():\n",
    "        model.objective = row['type']\n",
    "        print('Set objective to', row['type'], ':', model.optimize().objective_value)\n",
    "        \n",
    "        if model.optimize().objective_value != 0.0:\n",
    "            \n",
    "            # check which reactions are active related to each metabolite that is produced after adding dissipation reactions\n",
    "            fba_fluxes = pd.DataFrame(model.optimize().fluxes)\n",
    "            fba_fluxes.reset_index(level=0,inplace=True)\n",
    "\n",
    "            for react in list(fba_fluxes.loc[fba_fluxes['fluxes'] != 0]['index']):\n",
    "                \n",
    "                reactions_to_check.append(model.reactions.get_by_id(react).id)\n",
    "                # print only active reactions\n",
    "                print(model.reactions.get_by_id(react))\n",
    "        \n",
    "        print(\"----------------------------\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd7a15e3-b8c6-4956-936d-a1449abc8997",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### => No more circles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "932e202d-8579-412d-9fe5-c4e5c46a6530",
   "metadata": {},
   "outputs": [],
   "source": [
    "cobra.io.write_sbml_model(model, \"2.2/finegoldia_magna_ATCC_29328_2.2.fo.ch.mp.mcb.lt.re.ar.gpr.pw.gf1.gfmm.gf2.gfco3.circ.xml\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "14d523db-e951-4029-bd64-e71c50ec4e4c",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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