def WriteSDFDataSelect(Top_List, Top_sdf, arg_pat, all_top, top_name, dock):
Others, Matched = [], []
#w = Chem.SDWriter(top_name+'.smt-filt.sdf')
#OUT = open(top_name+'.smt-filt.txt', 'w')
m = Chem.SDWriter(top_name + '.smt-selec.sdf')
SMA = open(top_name + '.smt-selec.txt', 'w')
## Use the Ranked list to rebuild a consolidated SDF
## if molecule matches SMARTS filter, separate it
for idx, Item in enumerate(Top_List):
score, name = Item[0], Item[1]
## If mol_name has conformer number appended on it, remove _NUM
if re.search(r'_', name):
name = name.split('_')[0]
if Top_sdf.get(name):
mol = Top_sdf[name]
switch = False
## Rename mol name property to include data (ZINC, Rank, Score, Software)
mol.SetProp(
'_Name',
'{0}::{1}::{2:.1f}::{3}'.format(name, idx + 1, float(score),
dock))
for smarts in [p for p in arg_pat.split('|')]:
if mol.HasSubstructMatch(Chem.MolFromSmarts(smarts)):
Matched.append(mol)
SMA.write('{0}\t{1}\n'.format(name, score))
switch = True
break
if not switch:
# print(' ** {0} not match SMARTS {1} - Skip '.format(name, arg_pat))
Others.append(mol)
# OUT.write('{0}\t{1}\n'.format(name, score))
else:
print(' --> Molecule not found: {0} <--'.format(name))
continue
## Close all files when reached the Max. output number
if len(Matched) == all_top or idx == len(Top_List) - 1:
# for mol in Others:
# w.write(mol)
for mol in Matched:
m.write(mol)
print("\n ## Total Molecule Looked Thru: " + str(idx + 1))
print(' ## Molecule Not Matched: ' + str(len(Others)))
print(' ## Molecule Matched {0}: {1}'.format(
arg_sel, len(Matched)))
# OUT.close()
SMA.close()
# w.flush()
# w.close()
m.close()
gc.collect()
break
if grid is True: grid_print(top_name, Matched, 'sdf')
def main(list_name, Chemicals, option):
## Read in the list of selected ligand ID
# List = remove_remark(file_handle(list_name))
List = [line.split()[0] for line in remove_remark(file_handle(list_name))]
print len(List)
## Extract the selected ligands from the supplied SDF
temp = rdkit_open(Chemicals)
sdf = dict()
for m in temp:
if re.search(r'::', m.GetProp('_Name')):
name, rank, score, x = m.GetProp('_Name').split('::')
sdf[name] = [m, name, rank, score]
else:
name = m.GetProp('_Name')
sdf[name] = [m, name, 0, 0.0]
Molecules = [sdf[chem] for chem in List if chem is not None]
## Sort data, if needed
if option is not None:
if option == 'name': Molecules.sort(key=lambda tup: tup[1])
elif option == 'rank': Molecules.sort(key=lambda tup: int(tup[2]))
elif option == 'score': Molecules.sort(key=lambda tup: float(tup[3]))
Mols = [mol[0] for mol in Molecules]
out = Chem.SDWriter(list_name.split('.txt')[0] + '.sdf')
for molecule in Mols:
out.write(molecule)
out.flush()
out.close()
grid_print(list_name.split('.txt')[0], Mols, 'sdf')
def WriteSDFDataExclude( Top_List, Top_sdf, arg_pat, all_top, top_name, dock ):
Select, Exclude = [], []
w = Chem.SDWriter(top_name+'.smt-clean.sdf')
OUT = open(top_name+'.smt-clean.txt', 'w')
# m = Chem.SDWriter(top_name+'.smt-excl.sdf')
# SMA = open(top_name+'.smt-excl.txt', 'w')
## Use the Ranked list to rebuild a consolidated SDF
## if molecule matches SMARTS filter, separate it
for idx, Item in enumerate(Top_List):
score, name = Item[0], Item[1]
## If mol_name has conformer number appended on it, remove _NUM
if re.search(r'_', name):
name = name.split('_')[0]
if Top_sdf.get(name):
mol = Top_sdf[name]
switch = False
## Rename mol name property to include data (ZINC, Rank, Score, Software)
mol.SetProp('_Name',
'{0}::{1}::{2:.1f}::{3}'.format(name, idx+1, float(score), dock) )
for smarts in [ p for p in arg_pat.split('|') ]:
if mol.HasSubstructMatch(Chem.MolFromSmarts(smarts)):
# print(' ** {0} matches SMARTS {1} - Skip '.format(name, smarts))
Exclude.append(mol)
# SMA.write(name+'\t'+str(score)+'\n')
switch = True
continue
if switch:
continue
else:
print(' --> Molecule not found: {0} <--'.format(name))
continue
OUT.write(name+"\t"+str(score)+"\n")
Select.append(mol)
## Close all files when reached the Max. output number
if len(Select) == all_top:
for mol in Select:
w.write(mol)
# for mol in Exclude:
# m.write(mol)
print("\n ## Total Molecule Looked Thru: "+str(idx+1))
print(' ## Molecule Selected: '+str(len(Select)))
print(' ## Molecule Matched {0}: {1}'.format(arg_exc,len(Exclude)))
OUT.close()
# SMA.close()
w.flush()
w.close()
# m.close()
gc.collect()
break
if grid is True: grid_print(top_name, Select, 'sdf')
def WriteSDFData(Top_List, Top_sdf, all_top, top_name, dock):
Select = []
w = Chem.SDWriter(top_name + '.sdf')
OUT = open(top_name + '.txt', 'w')
## Use the Ranked list to rebuild a consolidated SDF
for idx, Item in enumerate(Top_List):
score, name = Item[0], Item[1]
## If mol_name has conformer number appended on it, remove _NUM
# if re.search(r'_', name):
# name = name.split('_')[0]
if Top_sdf.get(name):
mol = Top_sdf[name]
else:
print(' --> Molecule not found: {0} <--'.format(name))
continue
## Rename mol name property to include data (ZINC, Rank, Score, Software)
mol.SetProp(
'_Name', '{0}::{1}::{2:.1f}::{3}'.format(name, idx + 1,
float(score), dock))
OUT.write('{0}\t{1}\n'.format(name, score))
Select.append(mol)
## Close all files when reached the Max. output number
if len(Select) == all_top:
for mol in Select:
w.write(mol)
print("\n ## Total Molecule Looked Thru: " + str(idx + 1))
print(' ## Total Molecule Output: ' + str(len(Select)))
OUT.close()
w.flush()
w.close()
gc.collect()
break
if grid is True: grid_print(top_name, Select, 'sdf')
def main(list_name, Chemicals, option):
## Read in the list of selected ligand ID
df = pd.read_csv(list_name, delimiter='\s+', header=None,
comment='#').dropna()
List = df.loc[:, 0].to_numpy()
print('\n > Number of items in <{}>: {}\n'.format(list_name, len(List)))
## Extract the selected ligands from the supplied SDF
print(' > List of structure file(s) read: \n', Chemicals)
temp = rdkit_open(Chemicals)
sdf = dict()
for m in temp:
if re.search(r'::', m.GetProp('_Name')):
name, rank, score, x = m.GetProp('_Name').split('::')
sdf[name] = [m, name, rank, score]
else:
name = m.GetProp('_Name')
sdf[name] = [m, name, 0, 0.0]
Molecules = [sdf[chem] for chem in List if chem is not None]
## Sort data, if needed
if option is not None:
if option == 'name': Molecules.sort(key=lambda tup: tup[1])
elif option == 'rank': Molecules.sort(key=lambda tup: int(tup[2]))
elif option == 'score': Molecules.sort(key=lambda tup: float(tup[3]))
else:
print(
' ## Using SDF tag to sort ligand order: \033[31m{0}\033[0m\n'.
format(option))
Molecules.sort(key=lambda tup: float(tup[0].GetProp(option)))
Mols = [mol[0] for mol in Molecules]
out = Chem.SDWriter(list_name.split('.txt')[0] + '.sdf')
for molecule in Mols:
out.write(molecule)
out.flush()
out.close()
grid_print(list_name.split('.txt')[0], Mols, 'sdf')
def main(filename):
mol_file = glob.glob(filename)[0]
print('\n > File read: {}\n'.format(mol_file))
if re.search(r'.sdf', mol_file):
handle = file_handle(mol_file)
Mol = [
x for x in Chem.ForwardSDMolSupplier(handle, removeHs=True)
if x is not None
]
grid_print(mol_file.split('.sdf')[0], Mol, 'sdf')
if re.search(r'.smi', mol_file):
if re.search(r'.bz2$|.gz$', mol_file):
print(
'\n ## INFO: RDKit cannot take SMILES in zipped format, only ASCII\n'
)
else:
with open(mol_file, 'r') as fi:
first_line = fi.readline()
if re.search(r'smiles', first_line, re.IGNORECASE):
Mol = [
x for x in Chem.SmilesMolSupplier(
mol_file, titleLine=True, delimiter=' |\t|,')
if x is not None
]
else:
Mol = [
x for x in Chem.SmilesMolSupplier(
mol_file, titleLine=False, delimiter=' |\t|,')
if x is not None
]
grid_print(mol_file.split('.smi')[0], Mol, 'smi')
def GenClustTable( Mol_List, output_name, column=5 ):
Img_Data = []
for idx, Mols in enumerate(Mol_List):
Img = []
for mol in Mols:
# Get molecule info
m1 = mol.GetProp('Name')
m2 = mol.GetProp('Rank')
m3 = mol.GetProp('Score')
m4 = mol.GetProp('Type')
# Create tag and write out to sdf file
mol.SetProp('Cluster', str(idx+1))
mol.SetProp('SMILES' , Chem.MolToSmiles(mol, isomericSmiles=True))
AssignStereochemistryFrom3D(mol)
# Create figure using SMILES instead of 3D structure
svg_name = '_TEMP.'+m1+'.svg'
mol = rdMolDraw2D.PrepareMolForDrawing(mol)
mol = Chem.RemoveHs(mol)
AllChem.Compute2DCoords(mol)
DrawingOptions.atomLabelFontSize=18
Draw.MolToFile(mol, svg_name, size=(225,225) )
#cairosvg.svg2png( url=svg_name, write_to=png_name, dpi=240 )
img_link = '<img src="'+svg_name+'">'
# Img = (image_link, Name, Rank, Score, Type)
Img.append([img_link, m1, m2, m3, m4])
Img_Data.append(Img)
## Print out a HTML page, in which every row has a maximum of 5 compound png.
## Every major cluster of compounds is grouped together.
## List the Name of the compound, then the Rank and Score.
grid_print(output_name, Img_Data, 'formatted', column=5)
def main():
Cmpd_File = sys.argv[1].split(',')
Lib_File = sys.argv[2].split(',')
out_pref = sys.argv[3]
cutoff = float(sys.argv[4])
fp_choice = sys.argv[5]
Cmpd = rdkit_open(Cmpd_File)
Lib = rdkit_open(Lib_File)
Cmpd_FP = calculate_FP(Cmpd, fp_choice)
Lib_FP = calculate_FP(Lib, fp_choice)
Selection, Save = pick_similar_cmpd(Cmpd_FP, Lib_FP, cutoff, fp_choice)
grid_print(out_pref, Selection, 'formatted')
#########
df = pd.DataFrame(Save, columns=['name',
'mol']).drop_duplicates(subset='name',
keep='last')
fs = Chem.SmilesWriter(out_pref + '.smi')
for mol in df.to_numpy():
fs.write(mol[1])
fs.close()
m = Cluster[0]
i = m.GetProp("_Name").split()[0]
a = 'TEMP.' + i + '.svg'
l = '<img src="' + a + '">'
h = Chem.RemoveHs(m)
mol = h
rdMolDraw2D.PrepareMolForDrawing(mol)
AllChem.Compute2DCoords(mol)
Draw.MolToFile(m, a, size=(200, 200))
Single_list.append([l, i, "-", "-", '-']) #(Mol, Name, Rank, Score)
else:
clust_list = []
for m in Cluster:
i = m.GetProp("_Name").split()[0]
a = 'TEMP.' + i + '.svg'
l = '<img src="' + a + '">'
h = Chem.RemoveHs(m)
mol = h
rdMolDraw2D.PrepareMolForDrawing(mol)
AllChem.Compute2DCoords(mol)
Draw.MolToFile(m, a, size=(200, 200))
## [mol_data, Name, Rank, Score, Type]
clust_list.append([l, i, "-", '-', '-'])
Multi_list.append(clust_list)
Multi_list.append(Single_list)
grid_print(sys.argv[1], Multi_list, 'formatted')
def make_sdf(SDF_Names, All_Data, all_top, dock, prefix):
from rdkit import Chem
## Build a Top-Selection list, with a 1.5x head-room for failed molecules
print(" ## User-defined output total: " + str(all_top))
Top_Hash = {}
Top_List = [] # [(Score, Name), ...]
for rank, List in enumerate(All_Data):
Top_Hash[List[1]] = List[0]
Top_List.append(List)
if rank == (all_top * 2) - 1: break
## Build a library of molecules found in the Top-Selction List
Top_sdf = {}
for sdf_file in SDF_Names:
print(" # Reading SDF file: " + sdf_file)
sdf_handle = file_handle(sdf_file)
Temp_sdf = [
x for x in Chem.ForwardSDMolSupplier(sdf_handle, removeHs=False)
if x is not None
]
print(" # SDF mol read in from > " + sdf_file + " <: " +
str(len(Temp_sdf)))
## Rename ligand name if previously processed with '::' tag
if re.search(r'::', Temp_sdf[0].GetProp('_Name')):
print(' # Remove "::" tag from ligand name #')
Temp_sdf = RenameSDF(Temp_sdf)
prev_name = ''
for idx, mol in enumerate(Temp_sdf):
if idx % 10000 == 0: print " Mol compared {0}".format(idx)
## RDKit may not handle the molecules and make a 'NoneType' item
## 'Could not sanitize molecule ending'. Ignore this molecule
try:
name = mol.GetProp('_Name')
except AttributeError:
print("A molecule failed after this molecule ID: " + prev_name)
continue
prev_name = name
if Top_Hash.get(name.strip()):
Top_sdf[name.strip()] = mol
del Temp_sdf # Free memory
## Use the Ranked list to rebuild a consolidated SDF
SDF = []
if all_top >= 1000:
top_name = prefix + '.' + dock + '_top' + str(all_top / 1000) + 'k'
w = Chem.SDWriter(top_name + '.sdf')
OUT = open(top_name + '.txt', 'w')
else:
top_name = prefix + '.' + dock + '_top' + str(all_top)
w = Chem.SDWriter(top_name + '.sdf')
OUT = open(top_name + '.txt', 'w')
for idx, Item in enumerate(Top_List):
score = Item[0]
name = Item[1]
if Top_sdf.get(name):
mol = Top_sdf[name]
else:
print(" --> Molecule {0} is not found <--".format(name))
continue
## If the FRED mol_name has conformer number appended on it, remove _NUM
if re.search(r'_', name):
name = name.split('_')[0]
## (ZINC, Rank, Score, Software)
mol.SetProp(
'_Name', name + '::' + str(idx + 1) + '::' +
str("%.1f" % float(score)) + '::' + dock)
w.write(mol)
OUT.write(name + "\t" + str(score) + "\n")
SDF.append(mol)
## Close all files when reached the Max. output number
if idx == all_top - 1:
print("\n ## Total Molecule Ouptut: " + str(idx + 1))
OUT.close()
w.flush()
w.close()
gc.collect()
break
if grid is True: grid_print(fred_top_name, SDF, 'sdf')
