def make_dry_pdb(self):
envelope = self.msms0.envelope_msms.get_vert(filt=False)
envelope = [(x['x'], x['y'], x['z']) for x in envelope]
envelope_tree = scipy.spatial.KDTree(envelope)
npdb_non = NumPdb(self.no_water_file, features=self.npdb_features)
non_tree = scipy.spatial.KDTree(npdb_non['xyz'])
pr2 = self.probe_radius * 2
pr3 = self.probe_radius * 3
wet_pdb = [(self.dowser.dowser_file, self.dowser_dry_pdb),
(self.processed_pdb, self.original_dry_pdb)]
for pdb_file, out_file in wet_pdb:
npdb = NumPdb(pdb_file, features=self.npdb_features)
sele_het = npdb.sele(record="HETATM")
sele_not_wat = npdb.sele(resname="HOH", invert=True)
hetero_tree = get_tree(
npdb.get('xyz', sele=(sele_het & sele_not_wat)))
sele = npdb.sele()
i = 0
for numa in npdb.iter_resno(incomplete=True):
flag = True
if numa[0]['resname'] == 'HOH':
# assume the first water atom is the oxygen
dist_env = envelope_tree.query(numa['xyz'][0])[0]
dist_het = hetero_tree.query(numa['xyz'][0])[0]
dist_non = non_tree.query(numa['xyz'][0])[0]
# TODO het cutoff only for dowser_file
if dist_env < pr2 or dist_het < 3.9 or dist_non > pr3:
flag = False
for a in numa._atoms:
sele[i] = flag
i += 1
npdb.copy(sele=sele).write2(out_file)
def func( self ):
self.delete_backbone()
npdb=NumPdb( self.pdb_file )
for i, numa in enumerate( npdb.iter_resno() ):
sele={'resno':i+1}
resname1=numa.get('resname') [0]
resno1=numa.get('resno') [0]
chain1=numa.get('chain') [0]
dirg="%s_%s_%i" %(chain1,resname1,resno1)
print resname1, resno1, chain1
if numa.get('resname') [0] not in ('ALA', 'GLY'):
if resname1 in ('SER','CYS','PRO','ASP','THR','ASN','VAL','GLU','GLN'):
SpiderSidechainCorrelation(self.map_file, self.pdb_file, self.pixelsize,self.resolution, resno1, chain1,output_dir=self.subdir(dirg))
else:
SpiderSidechainCorrelation('deletebb.cpv', self.pdb_file, self.pixelsize,self.resolution, resno1, chain1,output_dir=self.subdir(dirg))
aaname="%s.%s" %(dirg,'pdb')
print aaname
aa=npdb.sele(resname=resname1,resno=resno1)
dire="%s/%s" %(dirg,aaname)
npdb.copy(sele=aa).write(dire)
OriSidechainCorrel('deletebb.cpv',dire,self.pixelsize,self.resolution,resno1,chain1,output_dir=self.subdir(dirg))
else:
aaname="%s.%s" %(dirg,'pdb')
print aaname
aa=npdb.sele(resname=resname1,resno=resno1)
dire="%s/%s" %(dirg,aaname)
if not os.path.exists(self.subdir(dirg)): os.makedirs(self.subdir(dirg))
npdb.copy(sele=aa).write(dire)
def get_npdb_dicts(self):
mplanes = np.array(self.opm.get_planes())
dist = abs(point_plane_dist(mplanes[1][0], mplanes[0]))
npdb_dict = {}
npdb_tm_dict = {}
npdb_sol_dict = {}
for suffix, pdb_file in self.water_variants:
npdb = NumPdb(pdb_file, features=self.npdb_features)
npdb_dict[suffix] = npdb
sele = npdb.sele()
i = 0
# create transmembrane region selection
for numa in npdb.iter_resno(incomplete=True):
flag = True
for c in numa._coords:
d1 = abs(point_plane_dist(c, mplanes[0]))
d2 = abs(point_plane_dist(c, mplanes[1]))
if d1 < dist and d2 < dist:
flag = False
break
for a in numa._atoms:
sele[i] = flag
i += 1
npdb_sol_dict[suffix] = npdb.copy(sele=sele)
npdb.copy(sele=sele).write(self.outpath("sol_region.pdb"))
np.logical_not(sele, sele)
npdb_tm_dict[suffix] = npdb.copy(sele=sele)
npdb.copy(sele=sele).write(self.outpath("tm_region.pdb"))
return npdb_dict, npdb_tm_dict, npdb_sol_dict
def func (self):
self.bestbuild()
npdb=NumPdb( "bestrotamers.pdb" )
a=True
z=2
#while a==True:
clashes,a=find_all_clashes(npdb)
gtree=get_tree(npdb['xyz'])
print clashes
for i in clashes:
localresi=[]
#hole CA atom vom ersten clashpartner
r=npdb.sele(resno=i[0],atomname='CA')
p=npdb.get('xyz',sele=r)
#indices im 6 A umkreis um den clash
l=gtree.query_ball_point(p,6)
print l[0]
#aus den indices eine liste mit residuname und nummer machen
for x in l[0]:
a=npdb.get('resname')[x]
b=npdb.get('resno')[x]
c=npdb.get('chain')[x]
localresi.append([b,a,c])
localresi=sorted(localresi)
localresi=list(localresi for localresi,_ in itertools.groupby(localresi))
#print localresi
for index,i in enumerate (localresi):
if i[1] not in ('ALA','GLY'):
rotadir="%s_%s_%i" % (i[2],i[1],i[0])
ccsortpath=os.path.join(self.result_direc,rotadir)
ccsort="%s/%s" % (ccsortpath,'ccsort.cpv')
print ccsortpath
break
def _pre_exec( self ):
backbone = ( ' N ',' C ', ' CA ',' O ' )
npdb=NumPdb( self.pdb_file )
back=npdb.sele(atomname=backbone)
npdb.copy(sele=back).write('nobb.pdb')
self._make_script_file(
map_name=self.relpath(self.map_file, no_ext=True) ,
pixelsize=self.pixelsize,
pdb_file='nobb.pdb'
)
def make_final_pdb(self):
npdb_dow = NumPdb(self.dowser_dry_pdb, features=self.npdb_features)
npdb_org = NumPdb(self.original_dry_pdb, features=self.npdb_features)
dow_tree = get_tree(npdb_dow.get('xyz', resname="HOH"))
sele = npdb_org.sele()
i = 0
for numa in npdb_org.iter_resno(incomplete=True):
flag = False
if numa[0]['resname'] == 'HOH':
dist = dow_tree.query(numa['xyz'][0])[0]
if dist > 2.7:
flag = True
for a in numa._atoms:
sele[i] = flag
i += 1
coords_dow, atoms_dow = npdb_dow._select()
coords_org, atoms_org = npdb_org._select(sele=sele)
npdb_final = NumAtoms(np.hstack((atoms_dow, atoms_org)),
np.vstack((coords_dow, coords_org)))
npdb_final.write2(self.final_pdb)
def get_npdb_dicts(self):
npdb_dict = {}
npdb_tm_dict = {}
npdb_sol_dict = {}
for suffix, pdb_file in self.water_variants:
npdb = NumPdb(pdb_file, features=self.npdb_features)
npdb_dict[suffix] = npdb
sele = npdb.sele()
i = 0
# create transmembrane region selection
for numa in npdb.iter_resno(incomplete=True):
flag = True
for a in numa._atoms:
sele[i] = flag
i += 1
npdb_sol_dict[suffix] = npdb.copy(sele=sele)
npdb.copy(sele=sele).write(self.outpath("sol_region.pdb"))
np.logical_not(sele, sele)
npdb_tm_dict[suffix] = npdb.copy(sele=sele)
npdb.copy(sele=sele).write(self.outpath("tm_region.pdb"))
return npdb_dict, npdb_tm_dict, npdb_sol_dict
def make_processed_pdb(self):
npdb = NumPdb(self.opm.processed_file, features=self.npdb_features)
sele = npdb.sele()
coords_dict = {}
i = 0
tree = scipy.spatial.KDTree(npdb['xyz'])
for numa in npdb._iter_resno():
for c in numa._coords:
c = tuple(c)
# remove atoms with identical coords
if c in coords_dict:
print npdb._atoms[i]
sele[i] = False
else:
coords_dict[c] = True
sele[i] = True
# remove atoms with almost identical coords
rslt = tree.query(c, k=10, distance_upper_bound=0.2)
rslt[1].sort()
if rslt[1][0] != i and rslt[0][1] != np.inf:
print i, npdb._atoms[i]
sele[i] = False
i += 1
npdb.copy(sele=sele).write2(self.processed_pdb)
