def find_proasis_repeats(protein):
project_strucids = paf.get_strucids_from_project(protein)
project_titles = [paf.get_strucid_json(strucid)['allStrucs'][0]['TITLE'].split()[-1] for strucid in
project_strucids]
counts = dict(Counter(project_titles))
repeats = {'crystal': [], 'strucids': [], 'bound_confs':[]}
for key in counts.keys():
if counts[key] > 1:
repeats['crystal'].append(key)
repeats['strucids'].append([project_strucids[i] for i, x in enumerate(project_titles) if x == key])
conn, c = dbf.connectDB()
for strucid_list in repeats['strucids']:
bound_list = []
for struc in strucid_list:
c.execute('select bound_conf from proasis_hits where strucid=%s', (struc,))
rows = c.fetchall()
for row in rows:
bound_list.append(str(row[0]))
repeats['bound_confs'].append(bound_list)
return repeats
for row in rows:
crystal_list.append(str(row[0]))
crystal_list = list(set(crystal_list))
protein_list = []
c.execute('select protein from proasis_hits')
rows = c.fetchall()
for row in rows:
protein_list.append(str(row[0]))
protein_list = list(set(protein_list))
count = 0
for protein in protein_list:
project_strucids = paf.get_strucids_from_project(protein)
db_strucids = []
# print(protein)
# print('----------')
current_list = []
status_list = []
good_list = []
file_checks = {'crystal': [], 'bound_state': [], 'mod_date': [], 'pdb': [], 'mtz': [], '2fofc': [], 'fofc': [],
'ligs': []}
good_structures = {'crystal': [], 'bound_state': [], 'mod_date': [], 'strucid': []}
# results_summary = {'crystal': []}
for crys in crystal_list:
if str(protein + '-') in crys:
current_list.append(crys)
for crystal in list(set(current_list)):
def run(self):
project_strucids = paf.get_strucids_from_project(self.protein)
# get crystal names for protein according to db
conn, c = dbf.connectDB()
c.execute('select crystal_name from proasis_hits where protein=%s', (self.protein,))
rows = c.fetchall()
crystal_list = []
for row in rows:
crystal_list.append(str(row[0]))
crystal_list = list(set(crystal_list))
db_strucids = []
# status_list = []
# good_list = []
file_checks = {'crystal': [], 'bound_state': [], 'mod_date': [], 'pdb': [], 'mtz': [], '2fofc': [], 'fofc': [],
'ligs': []}
# get info for crystals identified
for crystal in list(set(crystal_list)):
c.execute(
"select strucid, bound_conf, modification_date from proasis_hits "
"where crystal_name like %s and strucid NOT LIKE ''",
(crystal,))
bound_list = []
strucid_list = []
mod_date_list = []
rows = c.fetchall()
for row in rows:
strucid = str(row[0])
strucid_list.append(strucid)
bound_conf = str(row[1])
bound_list.append(bound_conf)
modification_date = str(row[2])
mod_date_list.append(modification_date)
unique_bound = list(set(bound_list))
unique_modification_date = list(set(mod_date_list))
unique_strucids = list(set(strucid_list))
for ids in unique_strucids:
db_strucids.append(ids)
c.execute("select strucid from proasis_leads where protein=%s and strucid!=''", (self.protein,))
rows = c.fetchall()
for row in rows:
db_strucids.append(str(row[0]))
# # get info about crystals in proasis_hits (ones identified as in refinement) that haven't made it to
# # proasis
#
# if sum([len(unique_modification_date), len(unique_bound), len(unique_strucids)]) == 0:
#
# c.execute(
# "select bound_conf, modification_date, exists_pdb, exists_mtz, exists_2fofc, exists_fofc, "
# "ligand_list from proasis_hits where crystal_name like %s",
# (crystal,))
# rows = c.fetchall()
#
# for row in rows:
# file_checks['crystal'].append(crystal)
# file_checks['bound_state'].append(str(row[0]))
# file_checks['mod_date'].append(str(row[1]))
# file_checks['pdb'].append(str(row[2]))
# file_checks['mtz'].append(str(row[3]))
# file_checks['2fofc'].append(str(row[4]))
# file_checks['fofc'].append(str(row[5]))
# file_checks['ligs'].append(str(row[6]))
# clear up mismatching entries
in_common = list(set(db_strucids) & set(project_strucids))
for strucid in db_strucids:
if strucid not in in_common:
print(self.protein + ': ' + strucid + ' found in database but not in proasis')
print('removing entry from db...')
c.execute("UPDATE proasis_hits set strucid='' where strucid=%s", (strucid,))
conn.commit()
c.execute("UPDATE proasis_leads set strucid='' where strucid=%s", (strucid,))
conn.commit()
print('\n')
for strucid in project_strucids:
if strucid not in in_common:
print(self.protein + ': ' + strucid + ' found in proasis but not in db')
print('removing entry from proasis...')
paf.delete_structure(strucid)
print('\n')
# good_structures = {'crystal': [], 'bound_state': [], 'mod_date': [], 'strucid': []}
# if len(set([len(unique_modification_date), len(unique_bound), len(unique_strucids)])) == 1:
# status_list.append(0)
# good_list.append(crystal)
# for i in range(0, len(unique_bound)):
# good_structures['crystal'].append(crystal)
# good_structures['bound_state'].append(unique_bound[i])
# good_structures['mod_date'].append(unique_modification_date[i])
# good_structures['strucid'].append(unique_strucids[i])
# for i in range(0, len(good_structures['strucid'])):
# if good_structures['strucid'][i] not in project_strucids:
# print('missing or incorrect strucid in db for '
# + str(good_structures['crystal'][i] + ' (' + str(good_structures['strucid'][i]) + ')'))
# for key in file_checks.keys():
# if '0' in file_checks[key]:
# error_list.append(str('missing ' + str(key) + ' file!'))
#
# if 'None' in file_checks[key]:
# error_list.append(str('None value found for ' + str(key)))
#
# elif len(set([len(unique_modification_date), len(unique_bound), len(unique_strucids)])) > 1:
# status_list.append(1)
#
# error_frame = pd.DataFrame.from_dict(file_checks)
# cols = ['crystal', 'bound_state', 'mod_date', 'ligs', 'mtz', 'pdb', '2fofc', 'fofc']
# error_frame = error_frame[cols]
# error_frame.sort_values(by=['crystal'], inplace=True)
#
# good_frame = pd.DataFrame.from_dict(good_structures)
# cols = ['crystal', 'bound_state', 'mod_date', 'strucid']
# good_frame = good_frame[cols]
# good_frame.sort_values(by=['crystal'], inplace=True)
#
#
# clean up repeats
repeats = find_proasis_repeats(self.protein)
for i, x in enumerate(repeats['crystal']):
bound_list = repeats['bound_confs'][i]
strucids = repeats['strucids'][i]
if len(bound_list)==len(strucids):
if len(list(set(bound_list)))==1:
print(str('identical uploaded structures: ' + str(strucids)) + ' (' + x + ')')
print('removing repeat structures from proasis, and updating database...')
to_delete_strucs=strucids[1:]
to_delete_confs=bound_list[1:]
for j in range(0, len(to_delete_strucs)):
c.execute('DELETE FROM proasis_hits WHERE strucid=%s and bound_conf=%s', (to_delete_strucs[j],
to_delete_confs[j]))
conn.commit()
paf.delete_structure(to_delete_strucs[j])
pd.DataFrame.from_dict(repeats).to_csv('test.csv')