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 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 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
