def sumScore(df, key, outputs, output_file_name):
print('')
print('Step 6')
print('###############################')
print('正在统计化合物打分!!!')
df_tmp = pd.DataFrame(columns=[key, 'score'])
scores = []
drugbank_id_list = []
for output in outputs:
output_result_name = output.split('.')[0] + '_score.txt'
score = getScoreFromSmina(output_result_name)
drugbank_id = output.split('/')[-1].split('_')[0]
scores.append(score)
drugbank_id_list.append(drugbank_id)
df_tmp[key] = drugbank_id_list
df_tmp['score'] = scores
df_final = pd.merge(df,df_tmp, how='left', left_on=key, right_on=key)
df_final.score.fillna(999, inplace=True)
df_final.sort_values('score', ascending=True, inplace=True)
print('正在生成化合物结构!!!')
PandasTools.SaveXlsxFromFrame(df_final, output_file_name, molCol='mol')
print('共得到%s个化合物得分!!!' %(df_final.shape[0]))
print('###############################')
return df_final
def makespreadsheet(thesmiles):
mylist = thesmiles.split('\n')
df = pd.DataFrame({'SMILES': mylist})
df['Mol Image'] = [Chem.MolFromSmiles(s) for s in df['SMILES']]
PandasTools.SaveXlsxFromFrame(df, 'test.xlsx', molCol='Mol Image')
'Oc(cccc1)c1O', 'OC(C(C1)C1(Br)Br)=O', 'Cc(cc1)ccc1O', 'Oc(cc1)ccc1Cl',
'OC(c1cocc1)=O', 'CC(C)c1nnn[nH]1', 'CN(C=C1)C=CC1=N', 'CCc1cccnn1',
'C[C@H]([C@H]1NC)[C@@H]1NC', 'CCCc1ncc[nH]1'
]
# 化合物のラベルを作成
label_list = ['sample_{}'.format(i) for i in range(len(smiles_list))]
# molオブジェクトのリストを作成
mols_list = [Chem.MolFromSmiles(smile) for smile in smiles_list]
# RDkit記述子の作成
descriptor_names = [
descriptor_name[0] for descriptor_name in Descriptors._descList[:5]
]
descriptor_calculation = MoleculeDescriptors.MolecularDescriptorCalculator(
descriptor_names)
RDkit = [
descriptor_calculation.CalcDescriptors(mol_temp) for mol_temp in mols_list
]
df = pd.DataFrame(RDkit, columns=descriptor_names, index=label_list)
df['smiles'] = smiles_list
# DataFrameへのImageの追加とエクセルファイルでの出力
PandasTools.AddMoleculeColumnToFrame(df, molCol='IMAGE', smilesCol='smiles')
PandasTools.SaveXlsxFromFrame(df,
'data_frame.xlsx',
molCol='IMAGE',
size=(150, 150))
