/usr/share/RDKit/Projects/DbCLI/SearchDb.py is in rdkit-data 201503-3.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 | # $Id$
#
# Copyright (c) 2007-2013, Novartis Institutes for BioMedical Research Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above
# copyright notice, this list of conditions and the following
# disclaimer in the documentation and/or other materials provided
# with the distribution.
# * Neither the name of Novartis Institutes for BioMedical Research Inc.
# nor the names of its contributors may be used to endorse or promote
# products derived from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
# OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#
# Created by Greg Landrum, July 2007
#
from __future__ import print_function
_version = "0.14.0"
_usage="""
SearchDb [optional arguments] <sdfilename>
The sd filename argument can be either an SD file or an MDL mol
file.
NOTES:
- The property names may have been altered on loading the
database. Any non-alphanumeric character in a property name
will be replaced with '_'. e.g."Gold.Goldscore.Constraint.Score" becomes
"Gold_Goldscore_Constraint_Score".
- Property names are not case sensitive in the database.
"""
from rdkit import RDConfig
from rdkit.Dbase.DbConnection import DbConnect
from rdkit.RDLogger import logger
logger=logger()
import zlib
from rdkit import Chem
from rdkit.Chem.MolDb.FingerprintUtils import supportedSimilarityMethods,BuildSigFactory,DepickleFP,LayeredOptions
from rdkit.Chem.MolDb import FingerprintUtils
from rdkit import DataStructs
def _molFromPkl(pkl):
if isinstance(pkl,(bytes,str)):
mol = Chem.Mol(pkl)
else:
mol = Chem.Mol(str(pkl))
return mol
def GetNeighborLists(probes,topN,pool,
simMetric=DataStructs.DiceSimilarity,
simThresh=-1.,
silent=False,
**kwargs):
probeFps = [x[1] for x in probes]
validProbes = [x for x in range(len(probeFps)) if probeFps[x] is not None]
validFps=[probeFps[x] for x in validProbes]
from rdkit.DataStructs.TopNContainer import TopNContainer
if simThresh<=0:
nbrLists = [TopNContainer(topN) for x in range(len(probeFps))]
else:
nbrLists=[TopNContainer(-1) for x in range(len(probeFps))]
nDone=0
for nm,fp in pool:
nDone+=1
if not silent and not nDone%1000: logger.info(' searched %d rows'%nDone)
if(simMetric==DataStructs.DiceSimilarity):
scores = DataStructs.BulkDiceSimilarity(fp,validFps)
for i,score in enumerate(scores):
if score>simThresh:
nbrLists[validProbes[i]].Insert(score,nm)
elif(simMetric==DataStructs.TanimotoSimilarity):
scores = DataStructs.BulkTanimotoSimilarity(fp,validFps)
for i,score in enumerate(scores):
if score>simThresh:
nbrLists[validProbes[i]].Insert(score,nm)
elif(simMetric==DataStructs.TverskySimilarity):
av = float(kwargs.get('tverskyA',0.5))
bv = float(kwargs.get('tverskyB',0.5))
scores = DataStructs.BulkTverskySimilarity(fp,validFps,av,bv)
for i,score in enumerate(scores):
if score>simThresh:
nbrLists[validProbes[i]].Insert(score,nm)
else:
for i in range(len(probeFps)):
pfp = probeFps[i]
if pfp is not None:
score = simMetric(probeFps[i],fp)
if score>simThresh:
nbrLists[validProbes[i]].Insert(score,nm)
return nbrLists
def GetMolsFromSmilesFile(dataFilename,errFile,nameProp):
dataFile=open(dataFilename,'r')
for idx,line in enumerate(dataFile):
try:
smi,nm = line.strip().split(' ')
except:
continue
try:
m = Chem.MolFromSmiles(smi)
except:
m=None
if not m:
if errfile:
print(idx,nm,smi,file=errfile)
continue
yield (nm,smi,m)
def GetMolsFromSDFile(dataFilename,errFile,nameProp):
suppl = Chem.SDMolSupplier(dataFilename)
for idx,m in enumerate(suppl):
if not m:
if errFile:
if hasattr(suppl,'GetItemText'):
d = suppl.GetItemText(idx)
errFile.write(d)
else:
logger.warning('full error file support not complete')
continue
smi = Chem.MolToSmiles(m,True)
if m.HasProp(nameProp):
nm = m.GetProp(nameProp)
if not nm:
logger.warning('molecule found with empty name property')
else:
nm = 'Mol_%d'%(idx+1)
yield nm,smi,m
def RunSearch(options,queryFilename):
global sigFactory
if options.similarityType=='AtomPairs':
fpBuilder=FingerprintUtils.BuildAtomPairFP
simMetric=DataStructs.DiceSimilarity
dbName = os.path.join(options.dbDir,options.pairDbName)
fpTableName = options.pairTableName
fpColName = options.pairColName
elif options.similarityType=='TopologicalTorsions':
fpBuilder=FingerprintUtils.BuildTorsionsFP
simMetric=DataStructs.DiceSimilarity
dbName = os.path.join(options.dbDir,options.torsionsDbName)
fpTableName = options.torsionsTableName
fpColName = options.torsionsColName
elif options.similarityType=='RDK':
fpBuilder=FingerprintUtils.BuildRDKitFP
simMetric=DataStructs.FingerprintSimilarity
dbName = os.path.join(options.dbDir,options.fpDbName)
fpTableName = options.fpTableName
if not options.fpColName:
options.fpColName='rdkfp'
fpColName = options.fpColName
elif options.similarityType=='Pharm2D':
fpBuilder=FingerprintUtils.BuildPharm2DFP
simMetric=DataStructs.DiceSimilarity
dbName = os.path.join(options.dbDir,options.fpDbName)
fpTableName = options.pharm2DTableName
if not options.fpColName:
options.fpColName='pharm2dfp'
fpColName = options.fpColName
FingerprintUtils.sigFactory = BuildSigFactory(options)
elif options.similarityType=='Gobbi2D':
from rdkit.Chem.Pharm2D import Gobbi_Pharm2D
fpBuilder=FingerprintUtils.BuildPharm2DFP
simMetric=DataStructs.TanimotoSimilarity
dbName = os.path.join(options.dbDir,options.fpDbName)
fpTableName = options.gobbi2DTableName
if not options.fpColName:
options.fpColName='gobbi2dfp'
fpColName = options.fpColName
FingerprintUtils.sigFactory = Gobbi_Pharm2D.factory
elif options.similarityType=='Morgan':
fpBuilder=FingerprintUtils.BuildMorganFP
simMetric=DataStructs.DiceSimilarity
dbName = os.path.join(options.dbDir,options.morganFpDbName)
fpTableName = options.morganFpTableName
fpColName = options.morganFpColName
extraArgs={}
if options.similarityMetric=='tanimoto':
simMetric = DataStructs.TanimotoSimilarity
elif options.similarityMetric=='dice':
simMetric = DataStructs.DiceSimilarity
elif options.similarityMetric=='tversky':
simMetric = DataStructs.TverskySimilarity
extraArgs['tverskyA']=options.tverskyA
extraArgs['tverskyB']=options.tverskyB
if options.smilesQuery:
mol=Chem.MolFromSmiles(options.smilesQuery)
if not mol:
logger.error('could not build query molecule from smiles "%s"'%options.smilesQuery)
sys.exit(-1)
options.queryMol = mol
elif options.smartsQuery:
mol=Chem.MolFromSmarts(options.smartsQuery)
if not mol:
logger.error('could not build query molecule from smarts "%s"'%options.smartsQuery)
sys.exit(-1)
options.queryMol = mol
if options.outF=='-':
outF=sys.stdout
elif options.outF=='':
outF=None
else:
outF = open(options.outF,'w+')
molsOut=False
if options.sdfOut:
molsOut=True
if options.sdfOut=='-':
sdfOut=sys.stdout
else:
sdfOut = open(options.sdfOut,'w+')
else:
sdfOut=None
if options.smilesOut:
molsOut=True
if options.smilesOut=='-':
smilesOut=sys.stdout
else:
smilesOut = open(options.smilesOut,'w+')
else:
smilesOut=None
if queryFilename:
try:
tmpF = open(queryFilename,'r')
except IOError:
logger.error('could not open query file %s'%queryFilename)
sys.exit(1)
if options.molFormat=='smiles':
func=GetMolsFromSmilesFile
elif options.molFormat=='sdf':
func=GetMolsFromSDFile
if not options.silent:
msg='Reading query molecules'
if fpBuilder: msg+=' and generating fingerprints'
logger.info(msg)
probes=[]
i=0
nms=[]
for nm,smi,mol in func(queryFilename,None,options.nameProp):
i+=1
nms.append(nm)
if not mol:
logger.error('query molecule %d could not be built'%(i))
probes.append((None,None))
continue
if fpBuilder:
probes.append((mol,fpBuilder(mol)))
else:
probes.append((mol,None))
if not options.silent and not i%1000:
logger.info(" done %d"%i)
else:
probes=None
conn=None
idName = options.molIdName
ids=None
names=None
molDbName = os.path.join(options.dbDir,options.molDbName)
molIdName = options.molIdName
mConn = DbConnect(molDbName)
cns = [(x.lower(),y) for x,y in mConn.GetColumnNamesAndTypes('molecules')]
idCol,idTyp=cns[0]
if options.propQuery or options.queryMol:
conn = DbConnect(molDbName)
curs = conn.GetCursor()
if options.queryMol:
if not options.silent: logger.info('Doing substructure query')
if options.propQuery:
where='where %s'%options.propQuery
else:
where=''
if not options.silent:
curs.execute('select count(*) from molecules %(where)s'%locals())
nToDo = curs.fetchone()[0]
join=''
doSubstructFPs=False
fpDbName = os.path.join(options.dbDir,options.fpDbName)
if os.path.exists(fpDbName) and not options.negateQuery :
curs.execute("attach database '%s' as fpdb"%(fpDbName))
try:
curs.execute('select * from fpdb.%s limit 1'%options.layeredTableName)
except:
pass
else:
doSubstructFPs=True
join = 'join fpdb.%s using (%s)'%(options.layeredTableName,idCol)
query = LayeredOptions.GetQueryText(options.queryMol)
if query:
if not where:
where='where'
else:
where += ' and'
where += ' '+query
cmd = 'select %(idCol)s,molpkl from molecules %(join)s %(where)s'%locals()
curs.execute(cmd)
row=curs.fetchone()
nDone=0
ids=[]
while row:
id,molpkl = row
if not options.zipMols:
m = _molFromPkl(molpkl)
else:
m = Chem.Mol(zlib.decompress(molpkl))
matched=m.HasSubstructMatch(options.queryMol)
if options.negateQuery:
matched = not matched
if matched:
ids.append(id)
nDone+=1
if not options.silent and not nDone%500:
if not doSubstructFPs:
logger.info(' searched %d (of %d) molecules; %d hits so far'%(nDone,nToDo,len(ids)))
else:
logger.info(' searched through %d molecules; %d hits so far'%(nDone,len(ids)))
row=curs.fetchone()
if not options.silent and doSubstructFPs and nToDo:
nFiltered = nToDo-nDone
logger.info(' Fingerprint screenout rate: %d of %d (%%%.2f)'%(nFiltered,nToDo,100.*nFiltered/nToDo))
elif options.propQuery:
if not options.silent: logger.info('Doing property query')
propQuery=options.propQuery.split(';')[0]
curs.execute('select %(idCol)s from molecules where %(propQuery)s'%locals())
ids = [x[0] for x in curs.fetchall()]
if not options.silent:
logger.info('Found %d molecules matching the query'%(len(ids)))
t1=time.time()
if probes:
if not options.silent: logger.info('Finding Neighbors')
conn = DbConnect(dbName)
cns = conn.GetColumnNames(fpTableName)
curs = conn.GetCursor()
if ids:
ids = [(x,) for x in ids]
curs.execute('create temporary table _tmpTbl (%(idCol)s %(idTyp)s)'%locals())
curs.executemany('insert into _tmpTbl values (?)',ids)
join='join _tmpTbl using (%(idCol)s)'%locals()
else:
join=''
if cns[0].lower() != idCol.lower():
# backwards compatibility to the days when mol tables had a guid and
# the fps tables did not:
curs.execute("attach database '%(molDbName)s' as mols"%locals())
curs.execute("""
select %(idCol)s,%(fpColName)s from %(fpTableName)s join
(select %(idCol)s,%(molIdName)s from mols.molecules %(join)s)
using (%(molIdName)s)
"""%(locals()))
else:
curs.execute('select %(idCol)s,%(fpColName)s from %(fpTableName)s %(join)s'%locals())
def poolFromCurs(curs,similarityMethod):
row = curs.fetchone()
while row:
id,pkl = row
fp = DepickleFP(pkl,similarityMethod)
yield (id,fp)
row = curs.fetchone()
topNLists = GetNeighborLists(probes,options.topN,poolFromCurs(curs,options.similarityType),
simMetric=simMetric,simThresh=options.simThresh,**extraArgs)
uniqIds=set()
nbrLists = {}
for i,nm in enumerate(nms):
topNLists[i].reverse()
scores=topNLists[i].GetPts()
nbrNames = topNLists[i].GetExtras()
nbrs = []
for j,nbrGuid in enumerate(nbrNames):
if nbrGuid is None:
break
else:
uniqIds.add(nbrGuid)
nbrs.append((nbrGuid,scores[j]))
nbrLists[(i,nm)] = nbrs
t2=time.time()
if not options.silent: logger.info('The search took %.1f seconds'%(t2-t1))
if not options.silent: logger.info('Creating output')
curs = mConn.GetCursor()
ids = list(uniqIds)
ids = [(x,) for x in ids]
curs.execute('create temporary table _tmpTbl (%(idCol)s %(idTyp)s)'%locals())
curs.executemany('insert into _tmpTbl values (?)',ids)
curs.execute('select %(idCol)s,%(molIdName)s from molecules join _tmpTbl using (%(idCol)s)'%locals())
nmDict={}
for guid,id in curs.fetchall():
nmDict[guid]=str(id)
ks = list(nbrLists.keys())
ks.sort()
if not options.transpose:
for i,nm in ks:
nbrs= nbrLists[(i,nm)]
nbrTxt=options.outputDelim.join([nm]+['%s%s%.3f'%(nmDict[id],options.outputDelim,score) for id,score in nbrs])
if outF: print(nbrTxt,file=outF)
else:
labels = ['%s%sSimilarity'%(x[1],options.outputDelim) for x in ks]
if outF: print(options.outputDelim.join(labels),file=outF)
for i in range(options.topN):
outL = []
for idx,nm in ks:
nbr = nbrLists[(idx,nm)][i]
outL.append(nmDict[nbr[0]])
outL.append('%.3f'%nbr[1])
if outF: print(options.outputDelim.join(outL),file=outF)
else:
if not options.silent: logger.info('Creating output')
curs = mConn.GetCursor()
ids = [(x,) for x in set(ids)]
curs.execute('create temporary table _tmpTbl (%(idCol)s %(idTyp)s)'%locals())
curs.executemany('insert into _tmpTbl values (?)',ids)
molIdName = options.molIdName
curs.execute('select %(idCol)s,%(molIdName)s from molecules join _tmpTbl using (%(idCol)s)'%locals())
nmDict={}
for guid,id in curs.fetchall():
nmDict[guid]=str(id)
if outF: print('\n'.join(nmDict.values()),file=outF)
if molsOut and ids:
molDbName = os.path.join(options.dbDir,options.molDbName)
cns = [x.lower() for x in mConn.GetColumnNames('molecules')]
if cns[-1]!='molpkl':
cns.remove('molpkl')
cns.append('molpkl')
curs = mConn.GetCursor()
#curs.execute('create temporary table _tmpTbl (guid integer)'%locals())
#curs.executemany('insert into _tmpTbl values (?)',ids)
cnText=','.join(cns)
curs.execute('select %(cnText)s from molecules join _tmpTbl using (%(idCol)s)'%locals())
row=curs.fetchone()
molD = {}
while row:
row = list(row)
m = _molFromPkl(row[-1])
guid = row[0]
nm = nmDict[guid]
if sdfOut:
m.SetProp('_Name',nm)
print(Chem.MolToMolBlock(m),file=sdfOut)
for i in range(1,len(cns)-1):
pn = cns[i]
pv = str(row[i])
print >>sdfOut,'> <%s>\n%s\n'%(pn,pv)
print('$$$$',file=sdfOut)
if smilesOut:
smi=Chem.MolToSmiles(m,options.chiralSmiles)
if smilesOut:
print('%s %s'%(smi,str(row[1])),file=smilesOut)
row=curs.fetchone()
if not options.silent: logger.info('Done!')
# ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ----
import os
from optparse import OptionParser
parser=OptionParser(_usage,version='%prog '+_version)
parser.add_option('--dbDir',default='/db/camm/CURRENT/rdk_db',
help='name of the directory containing the database information. The default is %default')
parser.add_option('--molDbName',default='Compounds.sqlt',
help='name of the molecule database')
parser.add_option('--molIdName',default='compound_id',
help='name of the database key column')
parser.add_option('--regName',default='molecules',
help='name of the molecular registry table')
parser.add_option('--pairDbName',default='AtomPairs.sqlt',
help='name of the atom pairs database')
parser.add_option('--pairTableName',default='atompairs',
help='name of the atom pairs table')
parser.add_option('--pairColName',default='atompairfp',
help='name of the atom pair column')
parser.add_option('--torsionsDbName',default='AtomPairs.sqlt',
help='name of the topological torsions database (usually the same as the atom pairs database)')
parser.add_option('--torsionsTableName',default='atompairs',
help='name of the topological torsions table (usually the same as the atom pairs table)')
parser.add_option('--torsionsColName',default='torsionfp',
help='name of the atom pair column')
parser.add_option('--fpDbName',default='Fingerprints.sqlt',
help='name of the 2D fingerprints database')
parser.add_option('--fpTableName',default='rdkitfps',
help='name of the 2D fingerprints table')
parser.add_option('--layeredTableName',default='layeredfps',
help='name of the layered fingerprints table')
parser.add_option('--fpColName',default='',
help='name of the 2D fingerprint column, a sensible default is used')
parser.add_option('--descrDbName',default='Descriptors.sqlt',
help='name of the descriptor database')
parser.add_option('--descrTableName',default='descriptors_v1',
help='name of the descriptor table')
parser.add_option('--descriptorCalcFilename',default=os.path.join(RDConfig.RDBaseDir,'Projects',
'DbCLI','moe_like.dsc'),
help='name of the file containing the descriptor calculator')
parser.add_option('--outputDelim',default=',',
help='the delimiter for the output file. The default is %default')
parser.add_option('--topN',default=20,type='int',
help='the number of neighbors to keep for each query compound. The default is %default')
parser.add_option('--outF','--outFile',default='-',
help='The name of the output file. The default is the console (stdout).')
parser.add_option('--transpose',default=False,action="store_true",
help='print the results out in a transposed form: e.g. neighbors in rows and probe compounds in columns')
parser.add_option('--molFormat',default='sdf',choices=('smiles','sdf'),
help='specify the format of the input file')
parser.add_option('--nameProp',default='_Name',
help='specify the SD property to be used for the molecule names. Default is to use the mol block name')
parser.add_option('--smartsQuery','--smarts','--sma',default='',
help='provide a SMARTS to be used as a substructure query')
parser.add_option('--smilesQuery','--smiles','--smi',default='',
help='provide a SMILES to be used as a substructure query')
parser.add_option('--negateQuery','--negate',default=False,action='store_true',
help='negate the results of the smarts query.')
parser.add_option('--propQuery','--query','-q',default='',
help='provide a property query (see the NOTE about property names)')
parser.add_option('--sdfOut','--sdOut',default='',
help='export an SD file with the matching molecules')
parser.add_option('--smilesOut','--smiOut',default='',
help='export a smiles file with the matching molecules')
parser.add_option('--nonchiralSmiles',dest='chiralSmiles',default=True,action='store_false',
help='do not use chiral SMILES in the output')
parser.add_option('--silent',default=False,action='store_true',
help='Do not generate status messages.')
parser.add_option('--zipMols','--zip',default=False,action='store_true',
help='read compressed mols from the database')
parser.add_option('--pharm2DTableName',default='pharm2dfps',
help='name of the Pharm2D fingerprints table')
parser.add_option('--fdefFile','--fdef',
default=os.path.join(RDConfig.RDDataDir,'Novartis1.fdef'),
help='provide the name of the fdef file to use for 2d pharmacophores')
parser.add_option('--gobbi2DTableName',default='gobbi2dfps',
help='name of the Gobbi2D fingerprints table')
parser.add_option('--similarityType','--simType','--sim',
default='RDK',choices=supportedSimilarityMethods,
help='Choose the type of similarity to use, possible values: RDK, AtomPairs, TopologicalTorsions, Pharm2D, Gobbi2D, Avalon, Morgan. The default is %default')
parser.add_option('--morganFpDbName',default='Fingerprints.sqlt',
help='name of the morgan fingerprints database')
parser.add_option('--morganFpTableName',default='morganfps',
help='name of the morgan fingerprints table')
parser.add_option('--morganFpColName',default='morganfp',
help='name of the morgan fingerprint column')
parser.add_option('--similarityMetric','--simMetric','--metric',
default='',choices=('tanimoto','dice','tversky',''),
help='Choose the type of similarity to use, possible values: tanimoto, dice, tversky. The default is determined by the fingerprint type')
parser.add_option('--tverskyA',default=0.5,type='float',
help='Tversky A value')
parser.add_option('--tverskyB',default=0.5,type='float',
help='Tversky B value')
parser.add_option('--simThresh',default=-1,type='float',
help='threshold to use for similarity searching. If provided, this supersedes the topN argument')
if __name__=='__main__':
import sys,getopt,time
options,args = parser.parse_args()
if len(args)!=1 and not (options.smilesQuery or options.smartsQuery or options.propQuery):
parser.error('please either provide a query filename argument or do a data or smarts query')
if len(args):
queryFilename=args[0]
else:
queryFilename=None
options.queryMol=None
RunSearch(options,queryFilename)
|