configuration_file_I.py

#
# $Id$
#
# configuration file for benchmarking platform
#
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# hardcoded global variables
list_num_query_mols = [5, 10, 20]
num_reps = 50 # number of repetitions
percent_dcy = 0.2 # percentage of decoys used for training
p_value = 0.05 # confidence level for statistical analysis

# collection of data sets
muv_ids = [466, 548, 600, 644, 652, 689, 692, 712, 713, 733, 737, 810, 832, 846, 852, 858, 859]
dud_ids = ['ace', 'ache', 'ar', 'cdk2', 'cox2', 'dhfr', 'egfr', 'er_agonist', 'fgfr1', 'fxa', 'gpb', 'gr', 'hivrt', 'inha', 'na', 'p38', 'parp', 'pdgfrb', 'sahh', 'src', 'vegfr2']
chembl_ids = [11359, 28, 11536, 8, 10434, 12670, 20014, 234, 12261, 12209, 25, 36, 43, 219, 130, 105, 11336, 20174, 126, 11225, 12252, 11682, 134, 116, 11265, 10475, 12679, 10579, 11575, 18061, 237, 276, 11534, 10198, 10498, 12911, 12968, 100579, 100126, 10378, 10417, 10752, 10773, 11631, 10927, 11085, 11442, 11279, 11488, 12840]

set_data = {}
set_data['MUV'] = dict(fullname='MUV', ids=muv_ids, prefix='aid', suffix='_actives.sdf', dcy_prefix='aid', dcy_suffix='_decoys.sdf', propName='PUBCHEM_COMPOUND_CID', dcy_propName='PUBCHEM_COMPOUND_CID')
set_data['DUD'] = dict(fullname='DUD', ids=dud_ids, prefix='', suffix='_clustered_3D_MM.sdf', dcy_prefix='DUD_', dcy_suffix='_decoys_ID_pass_MWPass_I_MM.sdf', propName='id', dcy_propName='Mol_Title')
set_data['ChEMBL'] = dict(fullname='ChEMBL-sereina/diverse_100', ids=chembl_ids, prefix='Target_no_', suffix='.sdf', dcy_name='decoys_10000_zinc.sdf', propName='Name', dcy_propName='_Name')