def prepareSource(inFile,
outFile,
wat=1,
sort=1,
foldx=1,
surf=1,
dens=1,
cons=1,
dssp=1,
delphi=0):
"""
Strip waters, add profiles and save as doped source model.
"""
source = PDBModel(inFile)
if wat:
source.remove(lambda a: a['residue_name'] in ['HOH', 'WAT', 'TIP3'])
if sort:
source = source.sort()
doper = PDBDope(source)
if surf:
## doper.addASA()
## doper.addSurfaceMask()
doper.addSurfaceRacer(probe=1.4)
if foldx:
doper.addFoldX()
if dens:
doper.addDensity()
if dssp:
doper.addSecondaryStructure()
if delphi:
doper.addDelphi()
try:
if cons:
doper.addConservation()
except:
errWriteln('\n ERROR: Conservation profile could not be added to '\
+ str(sourceOut) + '\n' )
source.saveAs(outFile)
return source
def prepareSource( inFile, outFile, wat=1, sort=1,
surf=1, dens=1, cons=1, dssp=1, delphi=0 ):
"""
Strip waters, add profiles and save as doped source model.
"""
source = PDBModel( inFile )
if wat:
source.remove( lambda a: a['residue_name'] in ['HOH','WAT','TIP3'] )
if sort:
source = source.sort()
doper = PDBDope( source )
if surf:
## doper.addASA()
## doper.addSurfaceMask()
doper.addSurfaceRacer( probe=1.4 )
## if foldx:
## doper.addFoldX()
if dens:
doper.addDensity()
if dssp:
doper.addSecondaryStructure()
if delphi:
doper.addDelphi()
try:
if cons:
doper.addConservation( )
except:
errWriteln('\n ERROR: Conservation profile could not be added to '\
+ str(sourceOut) + '\n' )
source.saveAs( outFile )
return source
class PDBCleaner:
"""
PDBCleaner performs the following tasks:
* remove HETAtoms from PDB
* replace non-standard AA by its closest standard AA
* remove non-standard atoms from standard AA residues
* delete atoms that follow missing atoms (in a chain)
* remove multiple occupancy atoms (except the one with highest occupancy)
* add ACE and NME capping residues to C- and N-terminals or chain breaks
(see capTerminals(), this is NOT done automatically in process())
Usage:
=======
>>> c = PDBCleaner( model )
>>> c.process()
>>> c.capTerminals( auto=True )
This will modify the model in-place and report changes to STDOUT.
Alternatively, you can specify a log file instance for the output.
PDBCleaner.process accepts several options to modify the processing.
Capping
=======
Capping will add N-methyl groups to free C-terminal carboxy ends
or Acetyl groups to free N-terminal Amines and will thus 'simulate' the
continuation of the protein chain -- a common practice in order to
prevent fake terminal charges. The automatic discovery of missing residues
is guess work at best. The more conservative approach is to use,
for example:
>>> c.capTerminals( breaks=1, capC=[0], capN=[2] )
In this case, only the chain break detection is used for automatic capping
-- the last residue before a chain break is capped with NME and the first
residue after the chain break is capped with ACE. Chain break detection
relies on PDBModel.chainBreaks() (via PDBModel.chainIndex( breaks=1 )).
The normal terminals to be capped are now specified explicitely. The first
chain (not counting chain breaks) will receive a NME C-terminal cap and the
third chain of the PDB will receive a N-terminal ACE cap.
Note: Dictionaries with standard residues and atom content are defined
in Biskit.molUtils. This is a duplicate effort with the new strategy
to parse Amber prep files for very similar information
(AmberResidueType, AmberResidueLibrary) and should change once we
implement a real framework for better residue handling.
"""
#: these atoms always occur at the tip of of a chain or within a ring
#: and, if missing, will not trigger the removal of other atoms
TOLERATE_MISSING = [
'O',
'CG2',
'CD1',
'CD2',
'OG1',
'OE1',
'NH1',
'OD1',
'OE1',
'H5T',
"O5'",
]
## PDB with ACE capping residue
F_ace_cap = t.dataRoot() + '/amber/leap/ace_cap.pdb'
## PDB with NME capping residue
F_nme_cap = t.dataRoot() + '/amber/leap/nme_cap.pdb'
def __init__(self, fpdb, log=None, verbose=True):
"""
@param fpdb: pdb file OR PDBModel instance
@type fpdb: str OR Biskit.PDBModel
@param log: Biskit.LogFile object (default: STDOUT)
@type log: Biskit.LogFile
@param verbose: log warnings and infos (default: True)
@type verbose: bool
"""
self.model = PDBModel(fpdb)
self.log = log or StdLog()
self.verbose = verbose
def logWrite(self, msg, force=1):
if self.log:
self.log.add(msg)
else:
if force:
print msg
def remove_multi_occupancies(self):
"""
Keep only atoms with alternate A field (well, or no alternate).
"""
if self.verbose:
self.logWrite(self.model.pdbCode +
': Removing multiple occupancies of atoms ...')
i = 0
to_be_removed = []
for a in self.model:
if a['alternate']:
try:
str_id = "%i %s %s %i" % (a['serial_number'], a['name'],
a['residue_name'],
a['residue_number'])
if a['alternate'].upper() == 'A':
a['alternate'] = ''
else:
if float(a['occupancy']) < 1.0:
to_be_removed += [i]
if self.verbose:
self.logWrite(
'removing %s (%s %s)' %
(str_id, a['alternate'], a['occupancy']))
else:
if self.verbose:
self.logWrite((
'keeping non-A duplicate %s because of 1.0 '
+ 'occupancy') % str_id)
except:
self.logWrite("Error removing duplicate: " + t.lastError())
i += 1
try:
self.model.remove(to_be_removed)
if self.verbose:
self.logWrite('Removed %i atoms' % len(to_be_removed))
except:
if self.verbose:
self.logWrite('No atoms with multiple occupancies to remove')
def replace_non_standard_AA(self, amber=0, keep=[]):
"""
Replace amino acids with none standard names with standard
amino acids according to L{MU.nonStandardAA}
@param amber: don't rename HID, HIE, HIP, CYX, NME, ACE [0]
@type amber: 1||0
@param keep: names of additional residues to keep
@type keep: [ str ]
"""
standard = MU.atomDic.keys() + keep
if amber:
standard.extend(['HID', 'HIE', 'HIP', 'CYX', 'NME', 'ACE'])
replaced = 0
if self.verbose:
self.logWrite(self.model.pdbCode +
': Looking for non-standard residue names...')
resnames = self.model['residue_name']
for i in self.model.atomRange():
resname = resnames[i].upper()
if resname not in standard:
if resname in MU.nonStandardAA:
resnames[i] = MU.nonStandardAA[resname]
if self.verbose:
self.logWrite('renamed %s %i to %s' % \
(resname, i, MU.nonStandardAA[ resname ]))
else:
resnames[i] = 'ALA'
self.logWrite('Warning: unknown residue name %s %i: ' \
% (resname, i ) )
if self.verbose:
self.logWrite('\t->renamed to ALA.')
replaced += 1
if self.verbose:
self.logWrite('Found %i atoms with non-standard residue names.'% \
replaced )
def __standard_res(self, resname, amber=0):
"""
Check if resname is a standard residue (according to L{MU.atomDic})
if not return the closest standard residue (according to
L{MU.nonStandardAA}).
@param resname: 3-letter residue name
@type resname: str
@return: name of closest standard residue or resname itself
@rtype: str
"""
if resname in MU.atomDic:
return resname
if resname in MU.nonStandardAA:
return MU.nonStandardAA[resname]
return resname
def remove_non_standard_atoms(self):
"""
First missing standard atom triggers removal of standard atoms that
follow in the standard order. All non-standard atoms are removed too.
Data about standard atoms are taken from L{MU.atomDic} and symomym
atom name is defined in L{MU.atomSynonyms}.
@return: number of atoms removed
@rtype: int
"""
mask = []
if self.verbose:
self.logWrite("Checking content of standard amino-acids...")
for res in self.model.resList():
resname = self.__standard_res(res[0]['residue_name']).upper()
if resname == 'DC5':
pass
## bugfix: ignore non-standard residues that have no matching
## standard residue
if resname in MU.atomDic:
standard = copy.copy(MU.atomDic[resname])
## replace known synonyms by standard atom name
for a in res:
n = a['name']
if not n in standard and MU.atomSynonyms.get(
n, 0) in standard:
a['name'] = MU.atomSynonyms[n]
if self.verbose:
self.logWrite('%s: renaming %s to %s in %s %i' %\
( self.model.pdbCode, n, a['name'],
a['residue_name'], a['residue_number']))
anames = [a['name'] for a in res]
keep = 1
## kick out all standard atoms that follow a missing one
rm = []
for n in standard:
if (not n in anames) and not (n in self.TOLERATE_MISSING):
keep = 0
if not keep:
rm += [n]
for n in rm:
standard.remove(n)
## keep only atoms that are standard (and not kicked out above)
for a in res:
if a['name'] not in standard:
mask += [1]
if self.verbose:
self.logWrite('%s: removing atom %s in %s %i '%\
( self.model.pdbCode, a['name'],
a['residue_name'], a['residue_number']))
else:
mask += [0]
self.model.remove(mask)
if self.verbose:
self.logWrite('Removed ' + str(N0.sum(mask)) +
' atoms because they were non-standard' +
' or followed a missing atom.')
return N0.sum(mask)
def capACE(self, model, chain, breaks=True):
"""
Cap N-terminal of given chain.
Note: In order to allow the capping of chain breaks,
the chain index is, by default, based on model.chainIndex(breaks=True),
that means with chain break detection activated! This is not the
default behaviour of PDBModel.chainIndex or takeChains or chainLength.
Please use the wrapping method capTerminals() for more convenient
handling of the index.
@param model: model
@type model: PDBMode
@param chain: index of chain to be capped
@type chain: int
@param breaks: consider chain breaks when identifying chain boundaries
@type breaks: bool
@return: model with added NME capping
@rtype : PDBModel
"""
if self.verbose:
self.logWrite('Capping N-terminal of chain %i with ACE' % chain)
c_start = model.chainIndex(breaks=breaks)
c_end = model.chainEndIndex(breaks=breaks)
Nterm_is_break = False
Cterm_is_break = False
if breaks:
Nterm_is_break = c_start[chain] not in model.chainIndex()
Cterm_is_break = c_end[chain] not in model.chainEndIndex()
m_ace = PDBModel(self.F_ace_cap)
chains_before = model.takeChains(range(chain), breaks=breaks)
m_chain = model.takeChains([chain], breaks=breaks)
chains_after = model.takeChains(range(chain + 1, len(c_start)),
breaks=breaks)
m_term = m_chain.resModels()[0]
## we need 3 atoms for superposition, CB might mess things up but
## could help if there is no HN
## if 'HN' in m_term.atomNames():
m_ace.remove(['CB']) ## use backbone 'C' rather than CB for fitting
## rename overhanging residue in cap PDB
for a in m_ace:
if a['residue_name'] != 'ACE':
a['residue_name'] = m_term.atoms['residue_name'][0]
else:
a['residue_number'] = m_term.atoms['residue_number'][0] - 1
a['chain_id'] = m_term.atoms['chain_id'][0]
a['segment_id'] = m_term.atoms['segment_id'][0]
## fit cap onto first residue of chain
m_ace = m_ace.magicFit(m_term)
cap = m_ace.resModels()[0]
serial = m_term['serial_number'][0] - len(cap)
cap['serial_number'] = range(serial, serial + len(cap))
## concat cap on chain
m_chain = cap.concat(m_chain, newChain=False)
## re-assemble whole model
r = chains_before.concat(m_chain, newChain=not Nterm_is_break)
r = r.concat(chains_after, newChain=not Cterm_is_break)
if len(c_start) != r.lenChains(breaks=breaks):
raise CappingError, 'Capping ACE would mask a chain break. '+\
'This typically indicates a tight gap with high risk of '+\
'clashes and other issues.'
return r
def capNME(self, model, chain, breaks=True):
"""
Cap C-terminal of given chain.
Note: In order to allow the capping of chain breaks,
the chain index is, by default, based on model.chainIndex(breaks=True),
that means with chain break detection activated! This is not the
default behaviour of PDBModel.chainIndex or takeChains or chainLength.
Please use the wrapping method capTerminals() for more convenient
handling of the index.
@param model: model
@type model: PDBMode
@param chain: index of chain to be capped
@type chain: int
@param breaks: consider chain breaks when identifying chain boundaries
@type breaks: bool
@return: model with added NME capping residue
@rtype : PDBModel
"""
if self.verbose:
self.logWrite('Capping C-terminal of chain %i with NME.' % chain)
m_nme = PDBModel(self.F_nme_cap)
c_start = model.chainIndex(breaks=breaks)
c_end = model.chainEndIndex(breaks=breaks)
Nterm_is_break = False
Cterm_is_break = False
if breaks:
Nterm_is_break = c_start[chain] not in model.chainIndex()
Cterm_is_break = c_end[chain] not in model.chainEndIndex()
chains_before = model.takeChains(range(chain), breaks=breaks)
m_chain = model.takeChains([chain], breaks=breaks)
chains_after = model.takeChains(range(chain + 1, len(c_start)),
breaks=breaks)
m_term = m_chain.resModels()[-1]
## rename overhanging residue in cap PDB, renumber cap residue
for a in m_nme:
if a['residue_name'] != 'NME':
a['residue_name'] = m_term.atoms['residue_name'][0]
else:
a['residue_number'] = m_term.atoms['residue_number'][0] + 1
a['chain_id'] = m_term.atoms['chain_id'][0]
a['segment_id'] = m_term.atoms['segment_id'][0]
## chain should not have any terminal O after capping
m_chain.remove(['OXT'])
## fit cap onto last residue of chain
m_nme = m_nme.magicFit(m_term)
cap = m_nme.resModels()[-1]
serial = m_term['serial_number'][-1] + 1
cap['serial_number'] = range(serial, serial + len(cap))
## concat cap on chain
m_chain = m_chain.concat(cap, newChain=False)
## should be obsolete now
if getattr(m_chain, '_PDBModel__terAtoms', []) != []:
m_chain._PDBModel__terAtoms = [len(m_chain) - 1]
assert m_chain.lenChains() == 1
## re-assemble whole model
r = chains_before.concat(m_chain, newChain=not Nterm_is_break)
r = r.concat(chains_after, newChain=not Cterm_is_break)
if len(c_start) != r.lenChains(breaks=breaks):
raise CappingError, 'Capping NME would mask a chain break. '+\
'This typically indicates a tight gap with high risk of '+\
'clashes and other issues.'
return r
def convertChainIdsNter(self, model, chains):
"""
Convert normal chain ids to chain ids considering chain breaks.
"""
if len(chains) == 0:
return chains
i = N0.take(model.chainIndex(), chains)
## convert back to chain indices but this time including chain breaks
return model.atom2chainIndices(i, breaks=1)
def convertChainIdsCter(self, model, chains):
"""
Convert normal chain ids to chain ids considering chain breaks.
"""
if len(chains) == 0:
return chains
## fetch last atom of given chains
index = N0.concatenate((model.chainIndex(), [len(model)]))
i = N0.take(index, N0.array(chains) + 1) - 1
## convert back to chain indices but this time including chain breaks
return model.atom2chainIndices(i, breaks=1)
def unresolvedTerminals(self, model):
"""
Autodetect (aka "guess") which N- and C-terminals are most likely not
the real end of each chain. This guess work is based on residue
numbering:
* unresolved N-terminal: a protein residue with a residue number > 1
* unresolved C-terminal: a protein residue that does not contain either
OXT or OT or OT1 or OT2 atoms
@param model: PDBModel
@return: chains with unresolved N-term, with unresolved C-term
@rtype : ([int], [int])
"""
c_first = model.chainIndex()
c_last = model.chainEndIndex()
capN = [ i for (i,pos) in enumerate(c_first)\
if model['residue_number'][pos] > 1 ]
capN = [i for i in capN if model['residue_name'][c_first[i]] != 'ACE']
capN = self.filterProteinChains(model, capN, c_first)
capC = []
for (i, pos) in enumerate(c_last):
atoms = model.takeResidues(model.atom2resIndices([pos
])).atomNames()
if not( 'OXT' in atoms or 'OT' in atoms or 'OT1' in atoms or \
'OT2' in atoms ):
capC += [i]
capC = self.filterProteinChains(model, capC, c_last)
return capN, capC
#@todo filter for protein positions in breaks=1
def filterProteinChains(self, model, chains, chainindex):
maskProtein = model.maskProtein()
chains = [i for i in chains if maskProtein[chainindex[i]]]
return chains
def capTerminals(self, auto=False, breaks=False, capN=[], capC=[]):
"""
Add NME and ACE capping residues to chain breaks or normal N- and
C-terminals. Note: these capping residues contain hydrogen atoms.
Chain indices for capN and capC arguments can be interpreted either
with or without chain break detection enabled. For example, let's
assume we have a two-chain protein with some missing residues (chain
break) in the first chain:
A: MGSKVSK---FLNAGSK
B: FGHLAKSDAK
Then:
capTerminals( breaks=False, capN=[1], capC=[1]) will add N-and
C-terminal caps to chain B.
However:
capTerminals( breaks=True, capN=[1], capC=[1]) will add N- and
C-terminal caps to the second fragment of chain A.
Note: this operation *replaces* the internal model.
@param auto: put ACE and NME capping residue on chain breaks
and on suspected false N- and C-termini (default: False)
@type auto: bool
@param breaks: switch on chain break detection before interpreting
capN and capC
@type breaks: False
@param capN: indices of chains that should get ACE cap (default: [])
@type capN: [int]
@param capC: indices of chains that should get NME cap (default: [])
@type capC: [int]
"""
m = self.model
c_len = m.lenChains()
i_breaks = m.chainBreaks()
if auto:
if not breaks:
capN = self.convertChainIdsNter(m, capN)
capC = self.convertChainIdsCter(m, capC)
breaks = True
capN, capC = self.unresolvedTerminals(m)
end_broken = m.atom2chainIndices(m.chainBreaks(), breaks=1)
capC = M.union(capC, end_broken)
capN = M.union(capN, N0.array(end_broken) + 1)
capN = self.filterProteinChains(m, capN, m.chainIndex(breaks=breaks))
capC = self.filterProteinChains(m, capC,
m.chainEndIndex(breaks=breaks))
for i in capN:
m = self.capACE(m, i, breaks=breaks)
assert m.lenChains() == c_len, '%i != %i' % \
(m.lenChains(), c_len)
assert len(m.chainBreaks(force=True)) == len(i_breaks)
assert m[
'serial_number'].dtype == N0.Int32, 'serial_number not int'
for i in capC:
m = self.capNME(m, i, breaks=breaks)
assert m.lenChains() == c_len
assert len(m.chainBreaks(force=True)) == len(i_breaks)
self.model = m
return self.model
def process(self, keep_hetatoms=0, amber=0, keep_xaa=[]):
"""
Remove Hetatoms, waters. Replace non-standard names.
Remove non-standard atoms.
@param keep_hetatoms: option
@type keep_hetatoms: 0||1
@param amber: don't rename amber residue names (HIE, HID, CYX,..)
@type amber: 0||1
@param keep_xaa: names of non-standard residues to be kept
@type keep_xaa: [ str ]
@return: PDBModel (reference to internal)
@rtype: PDBModel
@raise CleanerError: if something doesn't go as expected ...
"""
try:
if not keep_hetatoms:
self.model.remove(self.model.maskHetatm())
self.model.remove(self.model.maskH2O())
self.model.remove(self.model.maskH())
self.remove_multi_occupancies()
self.replace_non_standard_AA(amber=amber, keep=keep_xaa)
self.remove_non_standard_atoms()
except KeyboardInterrupt, why:
raise KeyboardInterrupt(why)
except Exception, why:
self.logWrite('Error: ' + t.lastErrorTrace())
raise CleanerError('Error cleaning model: %r' % why)
def capACE(self, model, chain, breaks=True):
"""
Cap N-terminal of given chain.
Note: In order to allow the capping of chain breaks,
the chain index is, by default, based on model.chainIndex(breaks=True),
that means with chain break detection activated! This is not the
default behaviour of PDBModel.chainIndex or takeChains or chainLength.
Please use the wrapping method capTerminals() for more convenient
handling of the index.
@param model: model
@type model: PDBMode
@param chain: index of chain to be capped
@type chain: int
@param breaks: consider chain breaks when identifying chain boundaries
@type breaks: bool
@return: model with added NME capping
@rtype : PDBModel
"""
if self.verbose:
self.logWrite('Capping N-terminal of chain %i with ACE' % chain)
c_start = model.chainIndex(breaks=breaks)
c_end = model.chainEndIndex(breaks=breaks)
Nterm_is_break = False
Cterm_is_break = False
if breaks:
Nterm_is_break = c_start[chain] not in model.chainIndex()
Cterm_is_break = c_end[chain] not in model.chainEndIndex()
m_ace = PDBModel(self.F_ace_cap)
chains_before = model.takeChains(range(chain), breaks=breaks)
m_chain = model.takeChains([chain], breaks=breaks)
chains_after = model.takeChains(range(chain + 1, len(c_start)),
breaks=breaks)
m_term = m_chain.resModels()[0]
## we need 3 atoms for superposition, CB might mess things up but
## could help if there is no HN
## if 'HN' in m_term.atomNames():
m_ace.remove(['CB']) ## use backbone 'C' rather than CB for fitting
## rename overhanging residue in cap PDB
for a in m_ace:
if a['residue_name'] != 'ACE':
a['residue_name'] = m_term.atoms['residue_name'][0]
else:
a['residue_number'] = m_term.atoms['residue_number'][0] - 1
a['chain_id'] = m_term.atoms['chain_id'][0]
a['segment_id'] = m_term.atoms['segment_id'][0]
## fit cap onto first residue of chain
m_ace = m_ace.magicFit(m_term)
cap = m_ace.resModels()[0]
serial = m_term['serial_number'][0] - len(cap)
cap['serial_number'] = range(serial, serial + len(cap))
## concat cap on chain
m_chain = cap.concat(m_chain, newChain=False)
## re-assemble whole model
r = chains_before.concat(m_chain, newChain=not Nterm_is_break)
r = r.concat(chains_after, newChain=not Cterm_is_break)
if len(c_start) != r.lenChains(breaks=breaks):
raise CappingError, 'Capping ACE would mask a chain break. '+\
'This typically indicates a tight gap with high risk of '+\
'clashes and other issues.'
return r
class PDBCleaner:
"""
PDBCleaner performs the following tasks:
* remove HETAtoms from PDB
* replace non-standard AA by its closest standard AA
* remove non-standard atoms from standard AA residues
* delete atoms that follow missing atoms (in a chain)
* remove multiple occupancy atoms (except the one with highest occupancy)
* add ACE and NME capping residues to C- and N-terminals or chain breaks
(see capTerminals(), this is NOT done automatically in process())
Usage:
=======
>>> c = PDBCleaner( model )
>>> c.process()
>>> c.capTerminals( auto=True )
This will modify the model in-place and report changes to STDOUT.
Alternatively, you can specify a log file instance for the output.
PDBCleaner.process accepts several options to modify the processing.
Capping
=======
Capping will add N-methyl groups to free C-terminal carboxy ends
or Acetyl groups to free N-terminal Amines and will thus 'simulate' the
continuation of the protein chain -- a common practice in order to
prevent fake terminal charges. The automatic discovery of missing residues
is guess work at best. The more conservative approach is to use,
for example:
>>> c.capTerminals( breaks=1, capC=[0], capN=[2] )
In this case, only the chain break detection is used for automatic capping
-- the last residue before a chain break is capped with NME and the first
residue after the chain break is capped with ACE. Chain break detection
relies on PDBModel.chainBreaks() (via PDBModel.chainIndex( breaks=1 )).
The normal terminals to be capped are now specified explicitely. The first
chain (not counting chain breaks) will receive a NME C-terminal cap and the
third chain of the PDB will receive a N-terminal ACE cap.
Note: Dictionaries with standard residues and atom content are defined
in Biskit.molUtils. This is a duplicate effort with the new strategy
to parse Amber prep files for very similar information
(AmberResidueType, AmberResidueLibrary) and should change once we
implement a real framework for better residue handling.
"""
#: these atoms always occur at the tip of of a chain or within a ring
#: and, if missing, will not trigger the removal of other atoms
TOLERATE_MISSING = ['O', 'CG2', 'CD1', 'CD2', 'OG1', 'OE1', 'NH1',
'OD1', 'OE1',
'H5T',"O5'", ]
## PDB with ACE capping residue
F_ace_cap = t.dataRoot() + '/amber/leap/ace_cap.pdb'
## PDB with NME capping residue
F_nme_cap = t.dataRoot() + '/amber/leap/nme_cap.pdb'
def __init__( self, fpdb, log=None, verbose=True ):
"""
@param fpdb: pdb file OR PDBModel instance
@type fpdb: str OR Biskit.PDBModel
@param log: Biskit.LogFile object (default: STDOUT)
@type log: Biskit.LogFile
@param verbose: log warnings and infos (default: True)
@type verbose: bool
"""
self.model = PDBModel( fpdb )
self.log = log or StdLog()
self.verbose = verbose
def logWrite( self, msg, force=1 ):
if self.log:
self.log.add( msg )
else:
if force:
print msg
def remove_multi_occupancies( self ):
"""
Keep only atoms with alternate A field (well, or no alternate).
"""
if self.verbose:
self.logWrite( self.model.pdbCode +
': Removing multiple occupancies of atoms ...')
i = 0
to_be_removed = []
for a in self.model:
if a['alternate']:
try:
str_id = "%i %s %s %i" % (a['serial_number'], a['name'],
a['residue_name'],
a['residue_number'])
if a['alternate'].upper() == 'A':
a['alternate'] = ''
else:
if float( a['occupancy'] ) < 1.0:
to_be_removed += [ i ]
if self.verbose:
self.logWrite(
'removing %s (%s %s)' %
(str_id,a['alternate'], a['occupancy']))
else:
if self.verbose:
self.logWrite(
('keeping non-A duplicate %s because of 1.0 '+
'occupancy') % str_id )
except:
self.logWrite("Error removing duplicate: "+t.lastError() )
i+=1
try:
self.model.remove( to_be_removed )
if self.verbose:
self.logWrite('Removed %i atoms' % len( to_be_removed ) )
except:
if self.verbose:
self.logWrite('No atoms with multiple occupancies to remove' )
def replace_non_standard_AA( self, amber=0, keep=[] ):
"""
Replace amino acids with none standard names with standard
amino acids according to L{MU.nonStandardAA}
@param amber: don't rename HID, HIE, HIP, CYX, NME, ACE [0]
@type amber: 1||0
@param keep: names of additional residues to keep
@type keep: [ str ]
"""
standard = MU.atomDic.keys() + keep
if amber:
standard.extend( ['HID', 'HIE', 'HIP', 'CYX', 'NME', 'ACE'] )
replaced = 0
if self.verbose:
self.logWrite(self.model.pdbCode +
': Looking for non-standard residue names...')
resnames = self.model['residue_name']
for i in self.model.atomRange():
resname = resnames[i].upper()
if resname not in standard:
if resname in MU.nonStandardAA:
resnames[i] = MU.nonStandardAA[ resname ]
if self.verbose:
self.logWrite('renamed %s %i to %s' % \
(resname, i, MU.nonStandardAA[ resname ]))
else:
resnames[i] = 'ALA'
self.logWrite('Warning: unknown residue name %s %i: ' \
% (resname, i ) )
if self.verbose:
self.logWrite('\t->renamed to ALA.')
replaced += 1
if self.verbose:
self.logWrite('Found %i atoms with non-standard residue names.'% \
replaced )
def __standard_res( self, resname, amber=0 ):
"""
Check if resname is a standard residue (according to L{MU.atomDic})
if not return the closest standard residue (according to
L{MU.nonStandardAA}).
@param resname: 3-letter residue name
@type resname: str
@return: name of closest standard residue or resname itself
@rtype: str
"""
if resname in MU.atomDic:
return resname
if resname in MU.nonStandardAA:
return MU.nonStandardAA[ resname ]
return resname
def remove_non_standard_atoms( self ):
"""
First missing standard atom triggers removal of standard atoms that
follow in the standard order. All non-standard atoms are removed too.
Data about standard atoms are taken from L{MU.atomDic} and symomym
atom name is defined in L{MU.atomSynonyms}.
@return: number of atoms removed
@rtype: int
"""
mask = []
if self.verbose:
self.logWrite("Checking content of standard amino-acids...")
for res in self.model.resList():
resname = self.__standard_res( res[0]['residue_name'] ).upper()
if resname == 'DC5':
pass
## bugfix: ignore non-standard residues that have no matching
## standard residue
if resname in MU.atomDic:
standard = copy.copy( MU.atomDic[ resname ] )
## replace known synonyms by standard atom name
for a in res:
n = a['name']
if not n in standard and MU.atomSynonyms.get(n,0) in standard:
a['name'] = MU.atomSynonyms[n]
if self.verbose:
self.logWrite('%s: renaming %s to %s in %s %i' %\
( self.model.pdbCode, n, a['name'],
a['residue_name'], a['residue_number']))
anames = [ a['name'] for a in res ]
keep = 1
## kick out all standard atoms that follow a missing one
rm = []
for n in standard:
if (not n in anames) and not (n in self.TOLERATE_MISSING):
keep = 0
if not keep:
rm += [ n ]
for n in rm:
standard.remove( n )
## keep only atoms that are standard (and not kicked out above)
for a in res:
if a['name'] not in standard:
mask += [1]
if self.verbose:
self.logWrite('%s: removing atom %s in %s %i '%\
( self.model.pdbCode, a['name'],
a['residue_name'], a['residue_number']))
else:
mask += [0]
self.model.remove( mask )
if self.verbose:
self.logWrite('Removed ' + str(N.sum(mask)) +
' atoms because they were non-standard' +
' or followed a missing atom.' )
return N.sum( mask )
def capACE( self, model, chain, breaks=True ):
"""
Cap N-terminal of given chain.
Note: In order to allow the capping of chain breaks,
the chain index is, by default, based on model.chainIndex(breaks=True),
that means with chain break detection activated! This is not the
default behaviour of PDBModel.chainIndex or takeChains or chainLength.
Please use the wrapping method capTerminals() for more convenient
handling of the index.
@param model: model
@type model: PDBMode
@param chain: index of chain to be capped
@type chain: int
@param breaks: consider chain breaks when identifying chain boundaries
@type breaks: bool
@return: model with added NME capping
@rtype : PDBModel
"""
if self.verbose:
self.logWrite('Capping N-terminal of chain %i with ACE' % chain )
c_start = model.chainIndex( breaks=breaks )
c_end = model.chainEndIndex( breaks=breaks)
Nterm_is_break = False
Cterm_is_break = False
if breaks:
Nterm_is_break = c_start[chain] not in model.chainIndex()
Cterm_is_break = c_end[chain] not in model.chainEndIndex()
m_ace = PDBModel( self.F_ace_cap )
chains_before = model.takeChains( range(chain), breaks=breaks )
m_chain = model.takeChains( [chain], breaks=breaks )
chains_after = model.takeChains( range(chain+1, len(c_start)),
breaks=breaks )
m_term = m_chain.resModels()[0]
## we need 3 atoms for superposition, CB might mess things up but
## could help if there is no HN
## if 'HN' in m_term.atomNames():
m_ace.remove( ['CB'] ) ## use backbone 'C' rather than CB for fitting
## rename overhanging residue in cap PDB
for a in m_ace:
if a['residue_name'] != 'ACE':
a['residue_name'] = m_term.atoms['residue_name'][0]
else:
a['residue_number'] = m_term.atoms['residue_number'][0]-1
a['chain_id'] = m_term.atoms['chain_id'][0]
a['segment_id'] = m_term.atoms['segment_id'][0]
## fit cap onto first residue of chain
m_ace = m_ace.magicFit( m_term )
cap = m_ace.resModels()[0]
serial = m_term['serial_number'][0] - len(cap)
cap['serial_number'] = range( serial, serial + len(cap) )
## concat cap on chain
m_chain = cap.concat( m_chain, newChain=False )
## re-assemble whole model
r = chains_before.concat( m_chain, newChain=not Nterm_is_break)
r = r.concat( chains_after, newChain=not Cterm_is_break)
if len(c_start) != r.lenChains( breaks=breaks ):
raise CappingError, 'Capping ACE would mask a chain break. '+\
'This typically indicates a tight gap with high risk of '+\
'clashes and other issues.'
return r
def capNME( self, model, chain, breaks=True ):
"""
Cap C-terminal of given chain.
Note: In order to allow the capping of chain breaks,
the chain index is, by default, based on model.chainIndex(breaks=True),
that means with chain break detection activated! This is not the
default behaviour of PDBModel.chainIndex or takeChains or chainLength.
Please use the wrapping method capTerminals() for more convenient
handling of the index.
@param model: model
@type model: PDBMode
@param chain: index of chain to be capped
@type chain: int
@param breaks: consider chain breaks when identifying chain boundaries
@type breaks: bool
@return: model with added NME capping residue
@rtype : PDBModel
"""
if self.verbose:
self.logWrite('Capping C-terminal of chain %i with NME.' % chain )
m_nme = PDBModel( self.F_nme_cap )
c_start = model.chainIndex( breaks=breaks )
c_end = model.chainEndIndex( breaks=breaks)
Nterm_is_break = False
Cterm_is_break = False
if breaks:
Nterm_is_break = c_start[chain] not in model.chainIndex()
Cterm_is_break = c_end[chain] not in model.chainEndIndex()
chains_before = model.takeChains( range(chain), breaks=breaks )
m_chain = model.takeChains( [chain], breaks=breaks )
chains_after = model.takeChains( range(chain+1, len(c_start)),
breaks=breaks )
m_term = m_chain.resModels()[-1]
## rename overhanging residue in cap PDB, renumber cap residue
for a in m_nme:
if a['residue_name'] != 'NME':
a['residue_name'] = m_term.atoms['residue_name'][0]
else:
a['residue_number'] = m_term.atoms['residue_number'][0]+1
a['chain_id'] = m_term.atoms['chain_id'][0]
a['segment_id'] = m_term.atoms['segment_id'][0]
## chain should not have any terminal O after capping
m_chain.remove( ['OXT'] )
## fit cap onto last residue of chain
m_nme = m_nme.magicFit( m_term )
cap = m_nme.resModels()[-1]
serial = m_term['serial_number'][-1]+1
cap['serial_number'] = range( serial, serial + len(cap) )
## concat cap on chain
m_chain = m_chain.concat( cap, newChain=False )
## should be obsolete now
if getattr( m_chain, '_PDBModel__terAtoms', []) != []:
m_chain._PDBModel__terAtoms = [ len( m_chain ) - 1 ]
assert m_chain.lenChains() == 1
## re-assemble whole model
r = chains_before.concat( m_chain, newChain=not Nterm_is_break)
r = r.concat( chains_after, newChain=not Cterm_is_break)
if len(c_start) != r.lenChains( breaks=breaks ):
raise CappingError, 'Capping NME would mask a chain break. '+\
'This typically indicates a tight gap with high risk of '+\
'clashes and other issues.'
return r
def convertChainIdsNter( self, model, chains ):
"""
Convert normal chain ids to chain ids considering chain breaks.
"""
if len(chains) == 0:
return chains
i = N.take( model.chainIndex(), chains )
## convert back to chain indices but this time including chain breaks
return model.atom2chainIndices( i, breaks=1 )
def convertChainIdsCter( self, model, chains ):
"""
Convert normal chain ids to chain ids considering chain breaks.
"""
if len(chains) == 0:
return chains
## fetch last atom of given chains
index = N.concatenate( (model.chainIndex(), [len(model)]) )
i = N.take( index, N.array( chains ) + 1 ) - 1
## convert back to chain indices but this time including chain breaks
return model.atom2chainIndices( i, breaks=1 )
def unresolvedTerminals( self, model ):
"""
Autodetect (aka "guess") which N- and C-terminals are most likely not
the real end of each chain. This guess work is based on residue
numbering:
* unresolved N-terminal: a protein residue with a residue number > 1
* unresolved C-terminal: a protein residue that does not contain either
OXT or OT or OT1 or OT2 atoms
@param model: PDBModel
@return: chains with unresolved N-term, with unresolved C-term
@rtype : ([int], [int])
"""
c_first = model.chainIndex()
c_last = model.chainEndIndex()
capN = [ i for (i,pos) in enumerate(c_first)\
if model['residue_number'][pos] > 1 ]
capN = [i for i in capN if model['residue_name'][c_first[i]] != 'ACE']
capN = self.filterProteinChains( model, capN, c_first )
capC = []
for (i,pos) in enumerate(c_last):
atoms = model.takeResidues(model.atom2resIndices([pos])).atomNames()
if not( 'OXT' in atoms or 'OT' in atoms or 'OT1' in atoms or \
'OT2' in atoms ):
capC += [ i ]
capC = self.filterProteinChains( model, capC, c_last )
return capN, capC
#@todo filter for protein positions in breaks=1
def filterProteinChains( self, model, chains, chainindex ):
maskProtein = model.maskProtein()
chains = [ i for i in chains if maskProtein[ chainindex[i] ] ]
return chains
def capTerminals( self, auto=False, breaks=False, capN=[], capC=[] ):
"""
Add NME and ACE capping residues to chain breaks or normal N- and
C-terminals. Note: these capping residues contain hydrogen atoms.
Chain indices for capN and capC arguments can be interpreted either
with or without chain break detection enabled. For example, let's
assume we have a two-chain protein with some missing residues (chain
break) in the first chain:
A: MGSKVSK---FLNAGSK
B: FGHLAKSDAK
Then:
capTerminals( breaks=False, capN=[1], capC=[1]) will add N-and
C-terminal caps to chain B.
However:
capTerminals( breaks=True, capN=[1], capC=[1]) will add N- and
C-terminal caps to the second fragment of chain A.
Note: this operation *replaces* the internal model.
@param auto: put ACE and NME capping residue on chain breaks
and on suspected false N- and C-termini (default: False)
@type auto: bool
@param breaks: switch on chain break detection before interpreting
capN and capC
@type breaks: False
@param capN: indices of chains that should get ACE cap (default: [])
@type capN: [int]
@param capC: indices of chains that should get NME cap (default: [])
@type capC: [int]
"""
m = self.model
c_len = m.lenChains()
i_breaks = m.chainBreaks()
if auto:
if not breaks:
capN = self.convertChainIdsNter( m, capN )
capC = self.convertChainIdsCter( m, capC )
breaks=True
capN, capC = self.unresolvedTerminals( m )
end_broken = m.atom2chainIndices( m.chainBreaks(), breaks=1 )
capC = M.union( capC, end_broken )
capN = M.union( capN, N.array( end_broken ) + 1 )
capN = self.filterProteinChains(m, capN, m.chainIndex(breaks=breaks))
capC = self.filterProteinChains(m, capC, m.chainEndIndex(breaks=breaks))
for i in capN:
m = self.capACE( m, i, breaks=breaks )
assert m.lenChains() == c_len, '%i != %i' % \
(m.lenChains(), c_len)
assert len(m.chainBreaks(force=True)) == len(i_breaks)
for i in capC:
m = self.capNME( m, i, breaks=breaks )
assert m.lenChains() == c_len
assert len(m.chainBreaks(force=True)) == len(i_breaks)
self.model = m
return self.model
def process( self, keep_hetatoms=0, amber=0, keep_xaa=[] ):
"""
Remove Hetatoms, waters. Replace non-standard names.
Remove non-standard atoms.
@param keep_hetatoms: option
@type keep_hetatoms: 0||1
@param amber: don't rename amber residue names (HIE, HID, CYX,..)
@type amber: 0||1
@param keep_xaa: names of non-standard residues to be kept
@type keep_xaa: [ str ]
@return: PDBModel (reference to internal)
@rtype: PDBModel
@raise CleanerError: if something doesn't go as expected ...
"""
try:
if not keep_hetatoms:
self.model.remove( self.model.maskHetatm() )
self.model.remove( self.model.maskH2O() )
self.model.remove( self.model.maskH() )
self.remove_multi_occupancies()
self.replace_non_standard_AA( amber=amber, keep=keep_xaa )
self.remove_non_standard_atoms()
except KeyboardInterrupt, why:
raise KeyboardInterrupt( why )
except Exception, why:
self.logWrite('Error: '+t.lastErrorTrace())
raise CleanerError( 'Error cleaning model: %r' % why )
def capACE( self, model, chain, breaks=True ):
"""
Cap N-terminal of given chain.
Note: In order to allow the capping of chain breaks,
the chain index is, by default, based on model.chainIndex(breaks=True),
that means with chain break detection activated! This is not the
default behaviour of PDBModel.chainIndex or takeChains or chainLength.
Please use the wrapping method capTerminals() for more convenient
handling of the index.
@param model: model
@type model: PDBMode
@param chain: index of chain to be capped
@type chain: int
@param breaks: consider chain breaks when identifying chain boundaries
@type breaks: bool
@return: model with added NME capping
@rtype : PDBModel
"""
if self.verbose:
self.logWrite('Capping N-terminal of chain %i with ACE' % chain )
c_start = model.chainIndex( breaks=breaks )
c_end = model.chainEndIndex( breaks=breaks)
Nterm_is_break = False
Cterm_is_break = False
if breaks:
Nterm_is_break = c_start[chain] not in model.chainIndex()
Cterm_is_break = c_end[chain] not in model.chainEndIndex()
m_ace = PDBModel( self.F_ace_cap )
chains_before = model.takeChains( range(chain), breaks=breaks )
m_chain = model.takeChains( [chain], breaks=breaks )
chains_after = model.takeChains( range(chain+1, len(c_start)),
breaks=breaks )
m_term = m_chain.resModels()[0]
## we need 3 atoms for superposition, CB might mess things up but
## could help if there is no HN
## if 'HN' in m_term.atomNames():
m_ace.remove( ['CB'] ) ## use backbone 'C' rather than CB for fitting
## rename overhanging residue in cap PDB
for a in m_ace:
if a['residue_name'] != 'ACE':
a['residue_name'] = m_term.atoms['residue_name'][0]
else:
a['residue_number'] = m_term.atoms['residue_number'][0]-1
a['chain_id'] = m_term.atoms['chain_id'][0]
a['segment_id'] = m_term.atoms['segment_id'][0]
## fit cap onto first residue of chain
m_ace = m_ace.magicFit( m_term )
cap = m_ace.resModels()[0]
serial = m_term['serial_number'][0] - len(cap)
cap['serial_number'] = range( serial, serial + len(cap) )
## concat cap on chain
m_chain = cap.concat( m_chain, newChain=False )
## re-assemble whole model
r = chains_before.concat( m_chain, newChain=not Nterm_is_break)
r = r.concat( chains_after, newChain=not Cterm_is_break)
if len(c_start) != r.lenChains( breaks=breaks ):
raise CappingError, 'Capping ACE would mask a chain break. '+\
'This typically indicates a tight gap with high risk of '+\
'clashes and other issues.'
return r