def change_enzyme():
selected_node = request.form['selected_node']
selected_enzyme = request.form['selected_enzyme']
task_id = request.form['task_id']
data = json.loads(current_app.redis.get(task_id))
graph_dict = json.loads(data['graph_dict'])
attr_dict = json.loads(data['attr_dict'])
target_smiles = data['target_smiles']
network_options = json.loads(data['network_options'])
graph = nx.from_dict_of_lists(graph_dict, create_using=nx.DiGraph)
network = Network(graph=graph, target_smiles=target_smiles)
network.settings = network_options
network.add_attributes(attr_dict)
network.calculate_scores()
network.graph.nodes[selected_node]['attributes']['selected_enzyme'] = selected_enzyme
data['attr_dict'] = json.dumps(network.attributes_dict())
current_app.redis.mset({task_id: json.dumps(data)})
time_to_expire = 15 * 60 # 15 mins * 60 seconds
current_app.redis.expire(task_id, time_to_expire)
successors = list(network.graph.successors(selected_node))
predecessors = list(network.graph.predecessors(selected_node))
subgraph = network.graph.subgraph([selected_node]+successors+predecessors)
nodes, edges = network.get_visjs_nodes_and_edges(graph=subgraph)
result = {'nodes': nodes,
'edges': edges}
return jsonify(result=result)
def test_product_against_rules():
target_smiles = request.form['target_smiles']
smarts = request.form['smarts']
try:
smarts_list = yaml.load(smarts, Loader=yaml.FullLoader)
except:
return jsonify(result={'status': 'fail'})
try:
rxn_list = []
for sma in smarts_list:
rxn_list.append(rdchiralReaction(sma))
except:
return jsonify(result={'status': 'fail'})
try:
network = Network()
if request.form['combine_enantiomers'] == 'true':
network.settings['combine_enantiomers'] = True
else:
network.settings['combine_enantiomers'] = False
network.rxn_obj.rxns = {'test_smarts': rxn_list}
network.rxns = {'test_smarts': rxn_list}
network.generate(target_smiles, 1)
nodes, edges = network.get_visjs_nodes_and_edges()
print(nodes)
result = {'status': 'success', 'nodes': nodes, 'edges': edges}
except:
result = {'status': 'fail'}
return jsonify(result=result)
def change_network_options():
reaction_colours = request.form['reaction_colours']
edge_colours = request.form['edge_colours']
task_id = request.form['task_id']
data = json.loads(current_app.redis.get(task_id))
graph_dict = json.loads(data['graph_dict'])
attr_dict = json.loads(data['attr_dict'])
target_smiles = data['target_smiles']
network_options = json.loads(data['network_options'])
graph = nx.from_dict_of_lists(graph_dict, create_using=nx.DiGraph)
network = Network(graph=graph, target_smiles=target_smiles)
network.update_settings(network_options)
network.add_attributes(attr_dict)
network.settings['colour_reactions'] = reaction_colours
network.settings["colour_arrows"] = edge_colours
nodes, edges = network.get_visjs_nodes_and_edges()
data['nodes'] = add_new(data['nodes'], nodes)
data['edges'] = add_new(data['edges'], edges)
data['network_options'] = json.dumps(network.settings)
current_app.redis.mset({task_id: json.dumps(data)})
time_to_expire = 15 * 60 #15 mins * 60 seconds
current_app.redis.expire(task_id, time_to_expire)
result = {
'nodes': nodes,
'edges': edges,
}
return jsonify(result=result)
def aizynth_step():
clicked_node = request.form['smiles']
x = request.form['x']
y = request.form['y']
task_id = request.form['task_id']
max_reactions = request.form['max_reactions']
aizynth_reaction_mode = request.form['aizynth_reaction_mode']
data = json.loads(current_app.redis.get(task_id))
graph_dict = json.loads(data['graph_dict'])
attr_dict = json.loads(data['attr_dict'])
target_smiles = data['target_smiles']
network_options = json.loads(data['network_options'])
graph = nx.from_dict_of_lists(graph_dict, create_using=nx.DiGraph)
network = Network(graph=graph,
target_smiles=target_smiles,
print_log=not current_app.config['PRODUCTION'])
network.update_settings(network_options)
network.add_attributes(attr_dict)
network.update_settings({
'max_reactions': int(max_reactions),
'aizynth_reaction_mode': aizynth_reaction_mode
})
new_substrate_nodes, new_reaction_nodes = network.add_chemical_step(
clicked_node)
all_new_nodes = [clicked_node] + new_substrate_nodes + new_reaction_nodes
subgraph = network.graph.subgraph(all_new_nodes)
nodes, edges = network.get_visjs_nodes_and_edges(graph=subgraph)
for i, node in enumerate(nodes):
nodes[i].update({'x': x, 'y': y})
result = {'nodes': nodes, 'edges': edges}
data['graph_dict'] = json.dumps(nx.to_dict_of_lists(network.graph))
data['attr_dict'] = json.dumps(network.attributes_dict())
nodes = add_new(data['nodes'], nodes)
edges = add_new(data['edges'], edges)
nodes, edges = delete_nodes_and_edges([], nodes, edges)
data['nodes'] = nodes
data['edges'] = edges
current_app.redis.mset({task_id: json.dumps(data)})
time_to_expire = 15 * 60 #15 mins * 60 seconds
current_app.redis.expire(task_id, time_to_expire)
return jsonify(result=result)
def task_add_retrorule_step(form_data, network_id):
job = get_current_job()
job.meta['progress'] = 'started'
job.save_meta()
clicked_node = form_data['smiles']
x = form_data['x']
y = form_data['y']
data = json.loads(current_app.redis.get(network_id))
graph_dict = json.loads(data['graph_dict'])
attr_dict = json.loads(data['attr_dict'])
target_smiles = data['target_smiles']
network_options = json.loads(data['network_options'])
graph = nx.from_dict_of_lists(graph_dict, create_using=nx.DiGraph)
network = Network(graph=graph, target_smiles=target_smiles)
network.update_settings(network_options)
network.add_attributes(attr_dict)
network.retrorules.retrorules_rxns = current_app.retrorules_rxns
network.retrorules.retrorule_db = current_app.retrorules_db
new_substrate_nodes, new_reaction_nodes = network.retrorules.add_step(
clicked_node)
all_new_nodes = [clicked_node] + new_substrate_nodes + new_reaction_nodes
subgraph = network.graph.subgraph(all_new_nodes)
nodes, edges = network.get_visjs_nodes_and_edges(graph=subgraph)
for i, node in enumerate(nodes):
nodes[i].update({'x': x, 'y': y})
result = {
'nodes': nodes,
'edges': edges,
'to_delete': [],
}
data['graph_dict'] = json.dumps(nx.to_dict_of_lists(network.graph))
data['attr_dict'] = json.dumps(network.attributes_dict())
data['nodes'] = add_new(data['nodes'], nodes)
data['edges'] = add_new(data['edges'], edges)
current_app.redis.mset({network_id: json.dumps(data)})
current_app.redis.expire(network_id, 5 * 60)
return result
def custom_reaction():
product_smiles = str(request.form['product'])
substrate_smiles = str(request.form['substrate'])
reaction_name = str(request.form['name'])
task_id = request.form['task_id']
data = json.loads(current_app.redis.get(task_id))
graph_dict = json.loads(data['graph_dict'])
attr_dict = json.loads(data['attr_dict'])
target_smiles = data['target_smiles']
network_options = json.loads(data['network_options'])
graph = nx.from_dict_of_lists(graph_dict, create_using=nx.DiGraph)
network = Network(graph=graph, target_smiles=target_smiles)
network.update_settings(network_options)
network.add_attributes(attr_dict)
new_substrate_nodes, new_reaction_nodes = network.custom_reaction(
product_smiles, substrate_smiles, reaction_name)
all_new_nodes = new_substrate_nodes + new_reaction_nodes
subgraph = network.graph.subgraph(all_new_nodes)
nodes, edges = network.get_visjs_nodes_and_edges(graph=subgraph)
result = {
'nodes': nodes,
'edges': edges,
}
data['graph_dict'] = json.dumps(nx.to_dict_of_lists(network.graph))
data['attr_dict'] = json.dumps(network.attributes_dict())
nodes = add_new(data['nodes'], nodes)
edges = add_new(data['edges'], edges)
data['nodes'] = nodes
data['edges'] = edges
current_app.redis.mset({task_id: json.dumps(data)})
current_app.redis.expire(task_id, 5 * 60)
return jsonify(result=result)
def task_make_network(form_data):
job = get_current_job()
job.meta['progress'] = 'started'
job.save_meta()
network = Network(include_experimental=bool(form_data['include_experimental']),
include_two_step=bool(form_data['include_two_step']),
include_requires_absence_of_water=bool(form_data['include_requires_absence_of_water']),
print_log=not current_app.config['PRODUCTION'])
network.update_settings({"allow_backwards_steps": bool(form_data['allow_backwards']),
"remove_simple": bool(form_data['remove_small']),
"similarity_score_threshold": float(form_data['sub_thres']),
"combine_enantiomers" : bool(form_data['combine_enantiomers']),
"num_enzymes": 1,
"calculate_complexities": bool(form_data['calc_complexity']),
"calculate_substrate_specificity": bool(form_data['sub_sim']),
"max_nodes": int(form_data['max_initial_nodes'],),
"colour_reactions" : form_data['colour_reactions'],
"colour_arrows": form_data['colour_edges'],
"show_negative_enzymes" : form_data['show_neg_enz'],
"only_postitive_enzyme_data" : not form_data['show_neg_enz'],
"max_reactions": form_data["max_reactions"],
'only_reviewed_activity_data': bool(form_data["only_reviewed"])})
if form_data["specificity_scoring_mode"] == 'Product + substrates (slower)':
network.update_settings({'specificity_score_substrates' : True})
#print(f"include_experimental = {network.settings['include_experimental']}")
#print(f"include_two_step = {network.settings['include_two_step']}")
network.generate(form_data['target_smiles'], form_data['number_steps'], calculate_scores=False)
job.meta['progress'] = 'network_generated'
job.save_meta()
network.calculate_scores()
job.meta['progress'] = 'scores_calculated'
job.save_meta()
nodes, edges = network.get_visjs_nodes_and_edges()
#options = {'interaction': {'multiselect': 'true',}}
options = {}
default_network_name = 'Network for ' + str(network.target_smiles)
result = {'save_id':str(uuid.uuid4()),
'save_links' : [],
'save_name' : default_network_name,
'nodes':nodes,
'edges':edges,
'options':json.dumps(options),
'graph_dict':json.dumps(nx.to_dict_of_lists(network.graph)),
'target_smiles':str(network.target_smiles),
'network_options':json.dumps(network.settings),
'attr_dict':json.dumps(network.attributes_dict()),
'max_reactions' : int(network.settings['max_reactions'])}
current_app.redis.mset({job.id: json.dumps(result)})
time_to_expire = 15*60 #15 mins * 60 seconds
current_app.redis.expire(job.id, time_to_expire)
return result
