def test_resSeqMap3(self):
# See if we can sort out the indexing between the native and model
nativePdb = os.path.join(self.testfiles_dir,"2UUI.pdb")
modelPdb = os.path.join(self.testfiles_dir,"2UUI_S_00000001.pdb")
chainA = "2UUI_A.pdb"
pdb_edit.extract_chain( nativePdb, chainA, chainID='A' )
chainAstd = "2UUI_A_std.pdb"
pdb_edit.standardise(chainA, chainAstd)
resSeqMap = residue_map.residueSequenceMap( chainA, modelPdb )
self.assertEqual( 156, resSeqMap._lenMatch() )
nativeMask = [ False ] * 155 + [ True ]
self.assertEqual( resSeqMap.refCAlphaMask, nativeMask)
self.assertEqual( resSeqMap.ref2target(10), 16 )
self.assertEqual( resSeqMap.target2ref(155), 149 )
# Check ends match up
m1 = resSeqMap.targetResSeq[ resSeqMap.targetOffset ]
n1 = resSeqMap.target2ref( m1 )
self.assertEqual( m1, resSeqMap.ref2target(n1) )
re = resSeqMap.refResSeq[ resSeqMap.refOffset + resSeqMap.lenMatch - 1 ]
self.assertEqual( resSeqMap.ref2target( re ), resSeqMap.targetResSeq[ resSeqMap.targetOffset + resSeqMap.lenMatch - 1 ] )
os.unlink( chainA )
os.unlink( chainAstd )
def test_resSeqMap1(self):
# See if we can sort out the indexing between the native and model
resSeqMap = residue_map.residueSequenceMap()
resSeqMap.targetSequence = ['G', 'G', 'A', 'A', 'A', 'A', 'A', 'A', 'A', 'A', 'A', 'A', 'F', 'F', 'F', 'F', 'F', 'F']
resSeqMap.targetResSeq = [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
resSeqMap.targetCAlphaMask = [False, False, False, False, True, False, False, False, False, False, False, False, False, False, False, False, False, False]
resSeqMap.refSequence = [ 'H', 'H', 'H', 'A', 'A', 'A', 'A', 'A', 'A', 'A', 'A', 'A', 'A', 'G', 'G', 'G', 'G', 'G', 'G' ]
resSeqMap.refResSeq = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18 ]
resSeqMap.refCAlphaMask = [False, False, False, False, False, False, True, False, False, False, False, False, False, False, False, False, False, False, False]
resSeqMap._calc_map()
self.assertEqual( resSeqMap.targetOffset, 2)
self.assertEqual( resSeqMap.refOffset, 3)
self.assertEqual( resSeqMap._lenMatch(), 10)
self.assertEqual( resSeqMap.ref2target( 0 ), -6 )
self.assertEqual( resSeqMap.ref2target( 3 ), -3 )
self.assertEqual( resSeqMap.target2ref( 1 ), 7 )
self.assertEqual( resSeqMap.target2ref( 12 ), 18 )
self.assertEqual( resSeqMap.target2ref( 6 ), 12 )
self.assertEqual( resSeqMap.targetIncomparable(), [-5,-4,-1, 0, 7, 8, 9, 10, 11, 12] )
self.assertEqual( resSeqMap.refIncomparable(), [ 0, 1, 2, 5, 6, 12, 13, 14, 15, 16, 17, 18 ] )
# Check ends match up
m1 = resSeqMap.targetResSeq[ resSeqMap.targetOffset ]
n1 = resSeqMap.target2ref( m1 )
self.assertEqual( m1, resSeqMap.ref2target(n1) )
re = resSeqMap.refResSeq[ resSeqMap.refOffset + resSeqMap.lenMatch - 1 ]
self.assertEqual( resSeqMap.ref2target( re ), resSeqMap.targetResSeq[ resSeqMap.targetOffset + resSeqMap.lenMatch - 1 ] )
def analyseModels(amoptd):
# Get hold of a full model so we can do the mapping of residues
refModelPdb = glob.glob(os.path.join(amoptd['models_dir'], "*.pdb"))[0]
nativePdbInfo=amoptd['native_pdb_info']
refModelPdbInfo = pdb_edit.get_info(refModelPdb)
amoptd['ref_model_pdb_info']=refModelPdbInfo
try:
resSeqMap = residue_map.residueSequenceMap()
resSeqMap.fromInfo( refInfo=refModelPdbInfo,
refChainID=refModelPdbInfo.models[0].chains[0], # Only 1 chain in model
targetInfo=nativePdbInfo,
targetChainID=nativePdbInfo.models[0].chains[0]
)
amoptd['res_seq_map'] = resSeqMap
except Exception as e:
logger.exception("Error calculating resSeqMap: %s" % e)
amoptd['res_seq_map'] = None # Won't be able to calculate RIO scores
if amoptd['have_tmscore']:
try:
tm = tm_util.TMscore(amoptd['tmscore_exe'], wdir=fixpath(amoptd['benchmark_dir']))
# Calculation of TMscores for all models
logger.info("Analysing Rosetta models with TMscore")
model_list = sorted(glob.glob(os.path.join(amoptd['models_dir'], "*pdb")))
structure_list = [amoptd['native_pdb_std']]
amoptd['tmComp'] = tm.compare_structures(model_list, structure_list, fastas=[amoptd['fasta']])
except Exception as e:
logger.exception("Unable to run TMscores: %s", e)
else:
raise RuntimeError("No program to calculate TMSCORES")
def test_resSeqMap3(self):
# See if we can sort out the indexing between the native and model
nativePdb = os.path.join(self.testfiles_dir, "2UUI.pdb")
modelPdb = os.path.join(self.testfiles_dir, "2UUI_S_00000001.pdb")
chainA = "2UUI_A.pdb"
pdb_edit.extract_chain(nativePdb, chainA, chainID='A')
chainAstd = "2UUI_A_std.pdb"
pdb_edit.standardise(chainA, chainAstd)
resSeqMap = residue_map.residueSequenceMap(chainA, modelPdb)
self.assertEqual(156, resSeqMap._lenMatch())
nativeMask = [False] * 155 + [True]
self.assertEqual(resSeqMap.refCAlphaMask, nativeMask)
self.assertEqual(resSeqMap.ref2target(10), 16)
self.assertEqual(resSeqMap.target2ref(155), 149)
# Check ends match up
m1 = resSeqMap.targetResSeq[resSeqMap.targetOffset]
n1 = resSeqMap.target2ref(m1)
self.assertEqual(m1, resSeqMap.ref2target(n1))
re = resSeqMap.refResSeq[resSeqMap.refOffset + resSeqMap.lenMatch - 1]
self.assertEqual(
resSeqMap.ref2target(re), resSeqMap.targetResSeq[resSeqMap.targetOffset + resSeqMap.lenMatch - 1]
)
os.unlink(chainA)
os.unlink(chainAstd)
def test_resSeqMap2(self):
# See if we can sort out the indexing between the native and model
nativePdb = os.path.join(self.testfiles_dir,"2XOV.pdb")
modelPdb = os.path.join(self.testfiles_dir,"2XOV_S_00000001.pdb")
resSeqMap = residue_map.residueSequenceMap( nativePdb, modelPdb )
self.assertEqual( 181, resSeqMap._lenMatch() )
# Check ends match up
m1 = resSeqMap.targetResSeq[ resSeqMap.targetOffset ]
n1 = resSeqMap.target2ref( m1 )
self.assertEqual( m1, resSeqMap.ref2target(n1) )
re = resSeqMap.refResSeq[ resSeqMap.refOffset + resSeqMap.lenMatch - 1 ]
self.assertEqual( resSeqMap.ref2target( re ), resSeqMap.targetResSeq[ resSeqMap.targetOffset + resSeqMap.lenMatch - 1 ] )
def test_resSeqMap4(self):
# See if we can sort out the indexing between the native and model
nativePdb = os.path.join(self.testfiles_dir, "1K33.pdb")
modelPdb = os.path.join(self.testfiles_dir, "1K33_S_00000001.pdb")
nativePdbStd = "1K33_std.pdb"
pdb_edit.standardise(nativePdb, nativePdbStd)
nativeInfo = pdb_edit.get_info(nativePdbStd)
modelInfo = pdb_edit.get_info(modelPdb)
resSeqMap = residue_map.residueSequenceMap()
resSeqMap.fromInfo(nativeInfo, 'A', modelInfo, 'A')
os.unlink(nativePdbStd)
def test_resSeqMap4(self):
# See if we can sort out the indexing between the native and model
nativePdb = os.path.join(self.testfiles_dir,"1K33.pdb")
modelPdb = os.path.join(self.testfiles_dir,"1K33_S_00000001.pdb")
nativePdbStd = "1K33_std.pdb"
pdb_edit.standardise( nativePdb, nativePdbStd )
nativeInfo = pdb_edit.get_info( nativePdbStd )
modelInfo = pdb_edit.get_info( modelPdb )
resSeqMap = residue_map.residueSequenceMap( )
resSeqMap.fromInfo( nativeInfo, 'A', modelInfo, 'A' )
os.unlink( nativePdbStd )
def test_resSeqMap2(self):
# See if we can sort out the indexing between the native and model
nativePdb = os.path.join(self.testfiles_dir, "2XOV.pdb")
modelPdb = os.path.join(self.testfiles_dir, "2XOV_S_00000001.pdb")
resSeqMap = residue_map.residueSequenceMap(nativePdb, modelPdb)
self.assertEqual(181, resSeqMap._lenMatch())
# Check ends match up
m1 = resSeqMap.targetResSeq[resSeqMap.targetOffset]
n1 = resSeqMap.target2ref(m1)
self.assertEqual(m1, resSeqMap.ref2target(n1))
re = resSeqMap.refResSeq[resSeqMap.refOffset + resSeqMap.lenMatch - 1]
self.assertEqual(
resSeqMap.ref2target(re), resSeqMap.targetResSeq[resSeqMap.targetOffset + resSeqMap.lenMatch - 1]
)
def analyseModels(amoptd):
# Get hold of a full model so we can do the mapping of residues
refModelPdb = glob.glob(os.path.join(amoptd['models_dir'], "*.pdb"))[0]
nativePdbInfo = amoptd['native_pdb_info']
resSeqMap = residue_map.residueSequenceMap()
refModelPdbInfo = pdb_edit.get_info(refModelPdb)
resSeqMap.fromInfo(
refInfo=refModelPdbInfo,
refChainID=refModelPdbInfo.models[0].
chains[0], # Only 1 chain in model
targetInfo=nativePdbInfo,
targetChainID=nativePdbInfo.models[0].chains[0])
amoptd['res_seq_map'] = resSeqMap
amoptd['ref_model_pdb_info'] = refModelPdbInfo
if amoptd['have_tmscore']:
try:
tm = tm_util.TMscore(amoptd['tmscore_exe'],
wdir=fixpath(amoptd['benchmark_dir']))
# Calculation of TMscores for all models
logger.info("Analysing Rosetta models with TMscore")
model_list = sorted(
glob.glob(os.path.join(amoptd['models_dir'], "*pdb")))
structure_list = [amoptd['native_pdb_std']]
amoptd['tmComp'] = tm.compare_structures(model_list,
structure_list,
fastas=[amoptd['fasta']])
except Exception as e:
msg = "Unable to run TMscores: {0}".format(e)
logger.critical(msg)
else:
global _MAXCLUSTERER # setting a module-level variable so need to use global keyword to it doesn't become a local variable
_MAXCLUSTERER = maxcluster.Maxcluster(amoptd['maxcluster_exe'])
logger.info("Analysing Rosetta models with Maxcluster")
_MAXCLUSTERER.compareDirectory(nativePdbInfo=nativePdbInfo,
resSeqMap=resSeqMap,
modelsDirectory=amoptd['models_dir'],
workdir=fixpath(
amoptd['benchmark_dir']))
return
def match_resseq(targetPdb=None, outPdb=None, resMap=None, sourcePdb=None):
assert sourcePdb or resMap
assert not (sourcePdb and resMap)
if not resMap:
resMap = residue_map.residueSequenceMap(targetPdb, sourcePdb)
chain = None # The chain we're reading
with open(targetPdb, 'r') as target, open(outPdb, 'w') as out:
for line in target:
if line.startswith("MODEL"):
raise RuntimeError("Multi-model file!")
if line.startswith("ANISOU"):
raise RuntimeError(
"I cannot cope with ANISOU! {0}".format(line))
# Stop at TER
if line.startswith("TER"):
pass
if line.startswith("ATOM"):
atom = pdb_model.PdbAtom(line)
# First atom/chain
if chain == None:
chain = atom.chainID
if atom.chainID != chain:
pass
# Get the matching resSeq for the model
modelResSeq = resMap.ref2target(atom.resSeq)
if modelResSeq == atom.resSeq:
out.write(line)
else:
atom.resSeq = modelResSeq
out.write(atom.toLine() + "\n")
continue
out.write(line)
def analyseModels(amoptd):
# Get hold of a full model so we can do the mapping of residues
refModelPdb = glob.glob(os.path.join(amoptd['models_dir'], "*.pdb"))[0]
nativePdbInfo = amoptd['native_pdb_info']
refModelPdbInfo = pdb_edit.get_info(refModelPdb)
amoptd['ref_model_pdb_info'] = refModelPdbInfo
try:
resSeqMap = residue_map.residueSequenceMap()
resSeqMap.fromInfo(
refInfo=refModelPdbInfo,
refChainID=refModelPdbInfo.models[0].
chains[0], # Only 1 chain in model
targetInfo=nativePdbInfo,
targetChainID=nativePdbInfo.models[0].chains[0],
)
amoptd['res_seq_map'] = resSeqMap
except Exception as e:
logger.exception("Error calculating resSeqMap: %s" % e)
amoptd['res_seq_map'] = None # Won't be able to calculate RIO scores
if amoptd['have_tmscore']:
try:
tm = tm_util.TMscore(amoptd['tmscore_exe'],
wdir=fixpath(amoptd['benchmark_dir']))
# Calculation of TMscores for all models
logger.info("Analysing Rosetta models with TMscore")
model_list = sorted(
glob.glob(os.path.join(amoptd['models_dir'], "*pdb")))
structure_list = [amoptd['native_pdb_std']]
amoptd['tmComp'] = tm.compare_structures(model_list,
structure_list,
fastas=[amoptd['fasta']])
except Exception as e:
logger.exception("Unable to run TMscores: %s", e)
else:
raise RuntimeError("No program to calculate TMSCORES")
def getRmsd(self,
nativePdbInfo=None,
placedPdbInfo=None,
refModelPdbInfo=None,
workdir=None,
cAlphaOnly=True):
"""For now just save lowest rmsd - can look at collecting more nativeInfo later
Currently we assume we are only given one model and that it has already been standardised.
"""
if workdir:
self.workdir = workdir
if not self.workdir:
self.workdir = os.getcwd()
self.cAlphaOnly = cAlphaOnly # Whether to only compare c-alpha atoms
# Run a pass to find the # chains
native_chains = nativePdbInfo.models[0].chains
placed_chains = placedPdbInfo.models[0].chains
rmsds = {
} # dict of rmsd -> ( chainIDnative, chainIDrefined, reforiginLogfile )
# Match each chain in native against refined and pick the best
for nativeChainID in native_chains:
if len(native_chains) == 1:
# Don't need to do owt as we are just using the native as is
nativeChainPdb = nativePdbInfo.pdb
else:
# Extract the chain from the pdb
astr = "chain{0}".format(nativeChainID)
nativeChainPdb = ample_util.filename_append(
filename=nativePdbInfo.pdb,
astr=astr,
directory=self.workdir)
pdb_edit.extract_chain(nativePdbInfo.pdb,
nativeChainPdb,
chainID=nativeChainID)
# Calculate the RefSeqMap - need to do this before we reduce to c-alphas
# The second chain may be a different composition to the first, so we only generate a traceback if we fail
# on the first chain. The model only has one chain, so the residueMap has to be the same for all the chains
try:
resSeqMap = residue_map.residueSequenceMap()
resSeqMap.fromInfo(
refInfo=nativePdbInfo,
refChainID=nativeChainID,
targetInfo=refModelPdbInfo,
targetChainID='A' # Model only has one chain
)
except RuntimeError:
if nativeChainID == native_chains[0]:
raise Exception
else:
# Only compare the first chain
break
for placedChainID in placed_chains:
# Prepare the placed PDB
placedChainPdb = self.preparePlacedPdb(
placedPdb=placedPdbInfo.pdb,
placedChainID=placedChainID,
nativeChainID=nativeChainID,
resSeqMap=resSeqMap)
# Now create a PDB with the matching atoms from native that are in refined
nativePdbMatch = ample_util.filename_append(
filename=nativeChainPdb,
astr="matched",
directory=self.workdir)
pdb_edit.keep_matching(refpdb=placedChainPdb,
targetpdb=nativeChainPdb,
outpdb=nativePdbMatch,
resSeqMap=resSeqMap)
# Now get the rmsd
astr = "chain{0}_reforigin".format(nativeChainID)
reforiginOut = ample_util.filename_append(
filename=placedChainPdb, astr=astr, directory=self.workdir)
try:
rms = self.calculate(refpdb=nativePdbMatch,
targetpdb=placedChainPdb,
outpdb=reforiginOut)
except RuntimeError as e:
logger.critical(
"GOT REFORIGIN ERROR for {0},{1},{2}\n{3}".format(
placedChainPdb, nativeChainPdb, nativeChainID, e))
rms = 99999
rmsds[rms] = (nativeChainID, placedChainID, reforiginOut)
# Clean up
os.unlink(placedChainPdb)
os.unlink(nativePdbMatch)
# Now pick the best...
rmsd = sorted(rmsds.keys())[0]
self.rmsd = rmsd
self.bestNativeChain = rmsds[rmsd][0]
self.bestPlacedChain = rmsds[rmsd][1]
self.bestReforiginPdb = rmsds[rmsd][2]
for k in rmsds.keys():
if k != rmsd:
try:
os.unlink(rmsds[k][2])
except Exception:
pass
def test_resSeqMap1(self):
# See if we can sort out the indexing between the native and model
resSeqMap = residue_map.residueSequenceMap()
resSeqMap.targetSequence = [
'G',
'G',
'A',
'A',
'A',
'A',
'A',
'A',
'A',
'A',
'A',
'A',
'F',
'F',
'F',
'F',
'F',
'F',
]
resSeqMap.targetResSeq = [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
resSeqMap.targetCAlphaMask = [
False,
False,
False,
False,
True,
False,
False,
False,
False,
False,
False,
False,
False,
False,
False,
False,
False,
False,
]
resSeqMap.refSequence = [
'H',
'H',
'H',
'A',
'A',
'A',
'A',
'A',
'A',
'A',
'A',
'A',
'A',
'G',
'G',
'G',
'G',
'G',
'G',
]
resSeqMap.refResSeq = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18]
resSeqMap.refCAlphaMask = [
False,
False,
False,
False,
False,
False,
True,
False,
False,
False,
False,
False,
False,
False,
False,
False,
False,
False,
False,
]
resSeqMap._calc_map()
self.assertEqual(resSeqMap.targetOffset, 2)
self.assertEqual(resSeqMap.refOffset, 3)
self.assertEqual(resSeqMap._lenMatch(), 10)
self.assertEqual(resSeqMap.ref2target(0), -6)
self.assertEqual(resSeqMap.ref2target(3), -3)
self.assertEqual(resSeqMap.target2ref(1), 7)
self.assertEqual(resSeqMap.target2ref(12), 18)
self.assertEqual(resSeqMap.target2ref(6), 12)
self.assertEqual(resSeqMap.targetIncomparable(), [-5, -4, -1, 0, 7, 8, 9, 10, 11, 12])
self.assertEqual(resSeqMap.refIncomparable(), [0, 1, 2, 5, 6, 12, 13, 14, 15, 16, 17, 18])
# Check ends match up
m1 = resSeqMap.targetResSeq[resSeqMap.targetOffset]
n1 = resSeqMap.target2ref(m1)
self.assertEqual(m1, resSeqMap.ref2target(n1))
re = resSeqMap.refResSeq[resSeqMap.refOffset + resSeqMap.lenMatch - 1]
self.assertEqual(
resSeqMap.ref2target(re), resSeqMap.targetResSeq[resSeqMap.targetOffset + resSeqMap.lenMatch - 1]
)
