def solve_pathway(self, subs, prod, html_writer, pathway_name, pathway_prefix, max_levels=4, stop_after_first_solution=False):
G_subs = compound2graph(subs)
G_prod = compound2graph(prod)
if (self.ignore_chirality):
G_subs.reset_chiralities()
G_prod.reset_chiralities()
print >> self.outstream, "*** Starting: %s -> %s" % (subs, prod)
html_writer.write(" <li>%s = %s" % (subs, prod))
(original_compound_map, possible_pathways, min_length) = self.find_shortest_pathway([G_subs], [G_prod], max_levels, stop_after_first_solution)
if (possible_pathways != []):
scene_list = self.get_all_possible_scenes(original_compound_map, possible_pathways)
min_cost = min([m[0] for m in scene_list])
min_cost_string = " (minimal cost = %s)" % str(min_cost)
sub_html_writer = html_writer.branch(pathway_name + "/" + pathway_prefix, min_cost_string)
# add to the sub HTML only the pathways that achieve the minimal cost
pathway_counter = 0
for (cost, pathway_scene) in scene_list:
if (cost == min_cost):
sub_html_writer.write_svg(pathway_scene, pathway_prefix + "/pathway_%d" % pathway_counter)
sub_html_writer.write("<br><br>")
pathway_counter += 1
print >> self.outstream, "*** Success: %s -> %s," % (subs, prod),
print >> self.outstream, "found %d pathways with minimal cost of %s" % (pathway_counter, str(min_cost))
else:
html_writer.write(" (minimal path-length > %d)" % max_levels)
print >> self.outstream, "*** Failure: %s -> %s, after %d steps" % (subs, prod, max_levels)
html_writer.write("</li>\n")
print >> self.outstream, "-"*80
def find_shortest_pathways(self,
substrate,
product,
max_levels,
stop_after_first_solution=True):
G_subs = compound2graph(substrate)
G_prod = compound2graph(product)
return self.pathfinder.find_shortest_pathway(
[G_subs], [G_prod],
max_levels=max_levels,
stop_after_first_solution=stop_after_first_solution)
def solve_pathway(self,
subs,
prod,
html_writer,
pathway_name,
pathway_prefix,
max_levels=4,
stop_after_first_solution=False):
G_subs = compound2graph(subs)
G_prod = compound2graph(prod)
if (self.ignore_chirality):
G_subs.reset_chiralities()
G_prod.reset_chiralities()
print >> self.outstream, "*** Starting: %s -> %s" % (subs, prod)
html_writer.write(" <li>%s = %s" % (subs, prod))
(original_compound_map, possible_pathways,
min_length) = self.find_shortest_pathway([G_subs], [G_prod],
max_levels,
stop_after_first_solution)
if (possible_pathways != []):
scene_list = self.get_all_possible_scenes(original_compound_map,
possible_pathways)
min_cost = min([m[0] for m in scene_list])
min_cost_string = " (minimal cost = %s)" % str(min_cost)
sub_html_writer = html_writer.branch(
pathway_name + "/" + pathway_prefix, min_cost_string)
# add to the sub HTML only the pathways that achieve the minimal cost
pathway_counter = 0
for (cost, pathway_scene) in scene_list:
if (cost == min_cost):
sub_html_writer.write_svg(
pathway_scene,
pathway_prefix + "/pathway_%d" % pathway_counter)
sub_html_writer.write("<br><br>")
pathway_counter += 1
print >> self.outstream, "*** Success: %s -> %s," % (subs, prod),
print >> self.outstream, "found %d pathways with minimal cost of %s" % (
pathway_counter, str(min_cost))
else:
html_writer.write(" (minimal path-length > %d)" % max_levels)
print >> self.outstream, "*** Failure: %s -> %s, after %d steps" % (
subs, prod, max_levels)
html_writer.write("</li>\n")
print >> self.outstream, "-" * 80
def balance_reaction(self, substrate, product):
""" Balances the reaction (by counting atoms)
"""
atom_gap = compound2graph(substrate).node_bag() - compounds2graph(product).node_bag()
extra_bag = bag.Bag()
extra_bag['CO2'] = atom_gap['C']
extra_bag['H2O'] = atom_gap['O'] + atom_gap['N'] - 2 * atom_gap['C']
extra_bag['PO3'] = atom_gap['PO3']
for (atom, count) in atom_gap.itercounts():
if (not atom in ['C', 'O', 'N', 'PO3'] and count != 0):
raise Exception("cannot balance the number of '%s' atoms, between %s and %s" % (atom, substrate, product))
for (metabolite, count) in extra_bag.itercounts():
if (count > 0):
product += (" + " + metabolite) * count
if (count < 0):
substrate += (" + " + metabolite) * (-count)
return (substrate, product)
def test(self, comp=None):
util._mkdir('../results')
util._mkdir('../results/svg')
if (comp == None):
html = html_writer.HtmlWriter("../results/reaction_templates.html")
counter = 0
for rid in self.forward_reaction_list:
html.write(self.get_reaction_info(rid))
html.write_svg(self.template2svg(rid), "svg/reaction_template_%d" % counter)
counter += 1
html.display()
else:
G = compound2graph(comp)
html = html_writer.HtmlWriter("../results/reaction_example.html")
html.write("<h1>Reactions for compound: " + comp + "</h1>")
html.write("<p>")
html.write_svg(G.svg(), "svg/compound")
html.write("</p>")
counter = 0
products_set = set()
print "Products for " + comp + " : "
for (G_new, rid, mapping) in self.apply_all_reactions(G, backward=False):
products_set.add(G_new.hash(ignore_chirality=self.ignore_chirality))
print rid + ": " + graph2compound(G_new, ignore_chirality=False)
html.write(self.get_reaction_info(rid, mapping))
html.write_svg(self.template2svg(rid), "svg/reaction_template_%d" % counter)
html.write("</br>")
html.write_svg(self.reaction2svg(G, G_new, rid), "svg/product_%d" % counter)
counter += 1
product_file = open("../results/products.txt", 'w')
product_file.write("\n".join(products_set))
product_file.close()
html.display()
return
def test(self, comp=None):
util._mkdir("../results")
util._mkdir("../results/svg")
if comp == None:
html = html_writer.HtmlWriter("../results/reaction_templates.html")
counter = 0
for rid in self.forward_reaction_list:
html.write(self.get_reaction_info(rid))
html.write_svg(self.template2svg(rid), "svg/reaction_template_%d" % counter)
counter += 1
html.display()
else:
G = compound2graph(comp)
html = html_writer.HtmlWriter("../results/reaction_example.html")
html.write("<h1>Reactions for compound: " + comp + "</h1>")
html.write("<p>")
html.write_svg(G.svg(), "svg/compound")
html.write("</p>")
counter = 0
products_set = set()
print "Products for " + comp + " : "
for (G_new, rid, mapping) in self.apply_all_reactions(G, backward=False):
products_set.add(G_new.hash(ignore_chirality=self.ignore_chirality))
print rid + ": " + graph2compound(G_new, ignore_chirality=False)
html.write(self.get_reaction_info(rid, mapping))
html.write_svg(self.template2svg(rid), "svg/reaction_template_%d" % counter)
html.write("</br>")
html.write_svg(self.reaction2svg(G, G_new, rid), "svg/product_%d" % counter)
counter += 1
product_file = open("../results/products.txt", "w")
product_file.write("\n".join(products_set))
product_file.close()
html.display()
return
def balance_reaction(self, substrate, product):
""" Balances the reaction (by counting atoms)
"""
atom_gap = compound2graph(substrate).node_bag() - compounds2graph(
product).node_bag()
extra_bag = bag.Bag()
extra_bag['CO2'] = atom_gap['C']
extra_bag['H2O'] = atom_gap['O'] + atom_gap['N'] - 2 * atom_gap['C']
extra_bag['PO3'] = atom_gap['PO3']
for (atom, count) in atom_gap.itercounts():
if (not atom in ['C', 'O', 'N', 'PO3'] and count != 0):
raise Exception(
"cannot balance the number of '%s' atoms, between %s and %s"
% (atom, substrate, product))
for (metabolite, count) in extra_bag.itercounts():
if (count > 0):
product += (" + " + metabolite) * count
if (count < 0):
substrate += (" + " + metabolite) * (-count)
return (substrate, product)
max_depth = 2
reaction_database_fname = "../rec/reaction_templates.dat"
# the substrate and product must be listed in '../metacyc/mcard_sdf_extra.txt'
# which uses the MOL format for describing molecules.
# each one of them can also be a sum of more than one compound (i.e. ribitol + CO2)
substrate, product = 'D-ribulose-5P', 'L-ribulose-5P'
pathfinder = PathFinder(carbon_only=True, pruning_method=None,
ignore_chirality=ignore_chirality, use_antimotifs=True,
reaction_database_fname=reaction_database_fname)
# This loop tries to find all the paths with lengths less than 'max_depth'
for depth in xrange(1, max_depth+1):
sys.stderr.write(substrate + " <=> " + product + ", depth = %d ... " % depth)
G_subs = compound2graph(substrate)
G_prod = compound2graph(product)
(original_compound_map, possible_paths, D) = pathfinder.find_shortest_pathway([G_subs], [G_prod], max_levels=depth)
for (substrate_pathways, product_pathways, h_bridge) in possible_paths:
# the results are given as 3-tuples, characterized by the compound where the two ends
# have met (denoted h_bridge). 'substrate_pathways' is a list of pathways leading from 'substrate' to 'h_bridge'.
# 'product_pathways' is a list of pathways leading from 'h_bridge' to 'product'.
for subs_path in substrate_pathways:
G_subs2 = original_compound_map[subs_path[0]]
subs_reaction_list = pathfinder.expand_rid_list(subs_path[1:])
(subs_log, G_last_subs) = pathfinder.pathway2text(G_subs2.clone(), subs_reaction_list)
for prod_path in product_pathways:
G_prod2 = original_compound_map[prod_path[0]]
# the substrate and product must be listed in '../metacyc/mcard_sdf_extra.txt'
# which uses the MOL format for describing molecules.
# each one of them can also be a sum of more than one compound (i.e. ribitol + CO2)
substrate, product = 'D-ribulose-5P', 'L-ribulose-5P'
pathfinder = PathFinder(carbon_only=True,
pruning_method=None,
ignore_chirality=ignore_chirality,
use_antimotifs=True,
reaction_database_fname=reaction_database_fname)
# This loop tries to find all the paths with lengths less than 'max_depth'
for depth in xrange(1, max_depth + 1):
sys.stderr.write(substrate + " <=> " + product +
", depth = %d ... " % depth)
G_subs = compound2graph(substrate)
G_prod = compound2graph(product)
(original_compound_map, possible_paths,
D) = pathfinder.find_shortest_pathway([G_subs], [G_prod],
max_levels=depth)
for (substrate_pathways, product_pathways, h_bridge) in possible_paths:
# the results are given as 3-tuples, characterized by the compound where the two ends
# have met (denoted h_bridge). 'substrate_pathways' is a list of pathways leading from 'substrate' to 'h_bridge'.
# 'product_pathways' is a list of pathways leading from 'h_bridge' to 'product'.
for subs_path in substrate_pathways:
G_subs2 = original_compound_map[subs_path[0]]
subs_reaction_list = pathfinder.expand_rid_list(subs_path[1:])
(subs_log,
G_last_subs) = pathfinder.pathway2text(G_subs2.clone(),
def get_distance(self, substrate, product, max_levels):
G_subs = compound2graph(substrate)
G_prod = compound2graph(product)
return self.pathfinder.find_distance([G_subs], [G_prod], max_levels=max_levels)
def find_shortest_pathways(self, substrate, product, max_levels, stop_after_first_solution=True):
G_subs = compound2graph(substrate)
G_prod = compound2graph(product)
return self.pathfinder.find_shortest_pathway([G_subs], [G_prod], max_levels=max_levels, stop_after_first_solution=stop_after_first_solution)
def get_distance(self, substrate, product, max_levels):
G_subs = compound2graph(substrate)
G_prod = compound2graph(product)
return self.pathfinder.find_distance([G_subs], [G_prod],
max_levels=max_levels)