Mercurial > repos > bgruening > chembl_structure_pipeline

annotate chembl.py @ 0:2f59c6239f25 draft default tip

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"planemo upload for repository https://github.com/chembl/chembl_webresource_client commit 78f2261af4e00c830ea311337d0aed9b297aad8e-dirty"
author bgruening
date Sat, 10 Oct 2020 09:43:40 +0000
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1 import argparse
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3 from chembl_webresource_client.new_client import new_client
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4 from chembl_webresource_client.settings import Settings
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6 Settings.Instance().CACHING = False
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9 def open_file(filename):
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10 with open(filename) as f:
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11 return f.readline().split()[0]
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12
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14 def get_smiles(res):
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15 """
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16 Get a list of SMILES from function results
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17 """
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18 smiles = set()
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19 for smi in res:
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20 try:
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21 smiles.add('{}\t{}'.format(smi['molecule_structures']['canonical_smiles'], smi['molecule_chembl_id']))
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22 except TypeError:
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23 continue
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24 return smiles
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27 def sim_search(smiles, tanimoto):
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28 """
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29 Return compounds which are within a Tanimoto range of the SMILES input
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30 """
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31 similarity = new_client.similarity
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32 return similarity.filter(smiles=smiles, similarity=tanimoto).only(['molecule_structures', 'molecule_chembl_id'])
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33
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34
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35 def substr_search(smiles):
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36 """
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37 Return compounds which contain the SMILES substructure input
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38 """
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39 substructure = new_client.substructure
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40 return substructure.filter(smiles=smiles).only(['molecule_structures', 'molecule_chembl_id'])
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41
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42
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43 def filter_drugs(mols):
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44 """
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45 Return only compounds which are approved drugs
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46 """
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47 return mols.filter(max_phase=4)
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48
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49
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50 def filter_biotherapeutic(mols):
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51 """
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52 Return only biotherapeutic molecules
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53 """
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54 return mols.filter(biotherapeutic__isnull=False)
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55
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56
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57 def filter_nat_prod(mols):
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58 """
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59 Return only natural products
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60 """
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61 return mols.filter(natural_product=1)
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62
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63
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64 def filter_ro5(mols):
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65 """
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66 Return only compounds with no RO5 violations
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67 """
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68 return mols.filter(molecule_properties__num_ro5_violations=0)
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69
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70
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71 def main():
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72 parser = argparse.ArgumentParser(description='Search ChEMBL database for compounds')
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73 parser.add_argument('-i', '--input', help='SMILES input')
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74 parser.add_argument('-f', '--file', help='SMILES input as file')
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75 parser.add_argument('-o', '--output', help="SMILES output")
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76 parser.add_argument('-t', '--tanimoto', type=int, help='Tanimoto similarity score')
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77 parser.add_argument('-s', '--substructure', action='store_true', help='Substructure search using the SMILES input.')
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78 parser.add_argument('-d', '--drugs', action='store_true', help='Filter approved drugs')
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79 parser.add_argument('-b', '--biotherapeutic', action='store_true', help='Filter biotherapeutic molecules')
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80 parser.add_argument('-n', '--nat-prod', action='store_true', help='Filter natural products')
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81 parser.add_argument('-r', '--ro5', action='store_true', help='Filter compounds that pass Lipinski RO5')
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82
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83 args = parser.parse_args()
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84
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85 if args.file: # get SMILES from file rather than -i option
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86 args.input = open_file(args.file)
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87
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88 if len(args.input) < 5:
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89 raise IOError('SMILES must be at least 5 characters long.')
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90
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91 if args.substructure: # specify search type: substructure or similarity
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92 mols = substr_search(args.input)
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93 else:
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94 mols = sim_search(args.input, args.tanimoto)
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95
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96 # filter options:
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97 if args.drugs:
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98 mols = filter_drugs(mols)
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99
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100 if args.biotherapeutic:
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101 mols = filter_biotherapeutic(mols)
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102
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103 if args.nat_prod:
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104 mols = filter_nat_prod(mols)
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105
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106 if args.ro5:
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107 mols = filter_ro5(mols)
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108
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109 # get SMILES from search output
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110 mols = get_smiles(mols)
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111
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112 # write to file
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113 with open(args.output, 'w') as f:
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114 f.write('\n'.join(mols))
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115
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116
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117 if __name__ == "__main__":
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118 main()