def parse_GoodVibes_exclude_flexible(
pdb,
path,
):
##
## calculate amplitudes
##
d_mmCIF = parse_mmCIF.main(pdb[:4], )
d_coords, l_coords_alpha = mmCIF2coords.main(pdb[:4],
d_mmCIF,
query_chain=pdb[-1])
print len(l_coords_alpha)
##
## eigenvector
##
cutoff = 10
matrix_hessian = NMA.hessian_calculation(
l_coords_alpha,
cutoff,
)
eigenvectors, eigenvalues = NMA.diagonalize_hessian(matrix_hessian)
l_amplitudes = [
math.sqrt(eigenvectors[6][i]**2 + eigenvectors[6][i + 1]**2 +
eigenvectors[6][i + 2]**2)
for i in range(0, len(eigenvectors[6]), 3)
]
## ## write pdb (color by bfactor)
## l_bfactors = [100*(l_amplitudes[i]-min(l_amplitudes))/(max(l_amplitudes)-min(l_amplitudes)) for i in range(len(l_amplitudes))]
## fd = open('output/%s/%s_%s_probe.pdb' %(path,pdb[:4],pdb[-1],),'r')
## lines = fd.readlines()
## fd.close()
## index = [-1,None,]
## lines_out = []
## for line in lines:
## record = line[:6].strip()
## if record != 'ATOM':
## lines_out += [line]
## else:
## res_no = int(line[22:26])
## if res_no != index[1]:
## index = [index[0]+1,res_no,]
## bfactor = l_bfactors[index[0]]
## line_out = '%s%6.2f%s' %(line[:60],bfactor,line[66:],)
## lines_out += [line_out]
## fd = open('output/%s/%s_%s_probe_color_by_amplitude.pdb' %(path,pdb[:4],pdb[-1],),'w')
## fd.writelines(lines_out)
## fd.close()
## average amplitude
average = sum(l_amplitudes) / len(l_amplitudes)
average, stddev = statistics.do_stddev(l_amplitudes)
##
l_coords_rigid = []
for i in range(len(l_coords_alpha)):
if l_amplitudes[i] < average:
l_coords_rigid += [l_coords_alpha[i]]
l_coords_flexible = []
for i in range(len(l_coords_alpha)):
if l_amplitudes[i] > average + 0.5 * stddev:
l_coords_flexible += [l_coords_alpha[i]]
## parse output
fd = open('output/%s/%s_%s_probe.pdb' % (
path,
pdb[:4],
pdb[-1],
), 'r')
lines = fd.readlines()
fd.close()
max_bfactor = None
coord = None
for line in lines:
record = line[:6].strip()
if record not in [
'ATOM',
'HETATM',
]:
continue
res_name = line[17:20]
if res_name != 'EXT':
continue
bfactor = float(line[60:66])
if bfactor > max_bfactor:
x = float(line[30:38])
y = float(line[38:46])
z = float(line[46:54])
## coord_tmp = numpy.array([x,y,z,])
## bool_vicinal_to_rigid = False
## for coord_rigid in l_coords_rigid:
## dist_from_rigid = math.sqrt(sum((coord_rigid-coord_tmp)**2))
## if dist_from_rigid < 6:
## bool_vicinal_to_rigid = True
## break
## if bool_vicinal_to_rigid == False:
## continue
## bool_vicinal_to_flexible = False
## for coord_flexible in l_coords_flexible:
## dist_from_flexible = math.sqrt(sum((coord_flexible-coord_tmp)**2))
## if dist_from_flexible < 6:
## bool_vicinal_to_flexible = True
## break
## if bool_vicinal_to_flexible == True:
## continue
## min_dist = [1000.,None,]
## for i_coord_alpha in range(len(l_coords_alpha)):
## coord_alpha = l_coords_alpha[i_coord_alpha]
## dist_from_alpha = math.sqrt(sum((coord_alpha-coord_tmp)**2))
## if dist_from_alpha < min_dist[0]:
## min_dist = [dist_from_alpha,i_coord_alpha,]
## if l_amplitudes[min_dist[1]] > average+stddev:
## continue
coord = numpy.array([
x,
y,
z,
])
max_bfactor = bfactor
return coord
def main():
d_MV = {}
path = '/data/mmCIF'
l_dn = os.listdir(path)
l_dn.sort()
for dn in l_dn:
if dn == 'mmCIF.py':
continue
if dn < sys.argv[-2]:
continue
if dn > sys.argv[-1]:
continue
l_fn = os.listdir('%s/%s' % (path, dn))
for fn in l_fn:
pdb = fn[:4]
## if pdb.upper() not in s_pdbs:
## continue
d_mmCIF = parse_mmCIF.main(
pdb,
d_breaks={'_exptl.method': 'SOLUTION NMR'},
l_data_categories=[
'_cell',
'_entity',
'_exptl',
'_exptl_crystal',
'_entity_poly',
'_symmetry',
## virus
'_pdbx_struct_assembly',
## split structure
'_pdbx_database_related',
],
)
## x-ray structure
if d_mmCIF['_exptl.method'] != ['X-RAY DIFFRACTION']:
continue
## polymer present
if not '_entity_poly.type' in d_mmCIF.keys():
continue
## only polymer present is protein
if d_mmCIF['_entity_poly.type'] != len(
d_mmCIF['_entity_poly.type']) * ['polypeptide(L)']:
continue
if not '_pdbx_struct_assembly.oligomeric_count' in d_mmCIF.keys():
continue
if d_mmCIF['_pdbx_struct_assembly.oligomeric_count'] == len(
d_mmCIF['_pdbx_struct_assembly.oligomeric_count']) * ['?']:
continue
## virus
if int(d_mmCIF['_pdbx_struct_assembly.oligomeric_count']
[0]) % 60 == 0:
continue
## not monomer
if d_mmCIF['_pdbx_struct_assembly.oligomeric_count'] != len(
d_mmCIF['_pdbx_struct_assembly.oligomeric_count']) * ['1']:
continue
## split structure
if '_pdbx_database_related' in d_mmCIF.keys():
if 'split' in d_mmCIF['_pdbx_database_related']:
continue
if 'SPLIT' in d_mmCIF['_pdbx_database_related']:
print pdb
stop
if not '_cell.Z_PDB' in d_mmCIF.keys():
continue
if pdb in [
## treshold
'1e54',
'1e9i',
## difference between calculated MV and MV in mmCIF
'3eiq',
## The crystals diffracted to 1.7Angstrom and appeared to be I centered tetragonal with
## unit cell dimension a=198.42Angstrom and c=396.6Angstrom, however the data only merged successfully in P1
## unit cell a=196.61 b=196.48 c=240.63 alpha=65.91 beta=65.91 gamma=90.01.
## Toscana has published with Hellinga...
'2cjf',
'2bt4',
]:
continue
## if not ''.join(d_mmCIF['_symmetry.space_group_name_H-M']) in [
## 'P 1','P 43 21 2','P 21 3','P 42 3 2','C 1 2 1','F 2 3','P 64 2 2','H 3',
## ]:
## continue ## tmp!!!
a = float(d_mmCIF['_cell.length_a'][0])
b = float(d_mmCIF['_cell.length_b'][0])
c = float(d_mmCIF['_cell.length_c'][0])
alpha = float(d_mmCIF['_cell.angle_alpha'][0])
beta = float(d_mmCIF['_cell.angle_beta'][0])
gamma = float(d_mmCIF['_cell.angle_gamma'][0])
Z = int(d_mmCIF['_cell.Z_PDB'][0])
mw = 0
for i in range(len(d_mmCIF['_entity.id'])):
## if d_mmCIF['_entity.type'][i] == 'polymer':
s = d_mmCIF['_entity.formula_weight'][i]
## unknown ligand
if s == '?':
continue
mw += float(s)
MV = matthews_coefficient.main(a, b, c, alpha, beta, gamma, mw, Z)
spacegroup = ''.join(d_mmCIF['_symmetry.space_group_name_H-M'])
if spacegroup not in [
'F 4 3 2',
'F 41 3 2',
'I 41 3 2',
]:
continue ## tmp!!!
if MV > 10:
print pdb
print 'mw', mw
print 'MV', MV, d_mmCIF['_exptl_crystal.density_Matthews']
print 'Z', Z
import math
alpha *= math.pi / 180.
beta *= math.pi / 180.
gamma *= math.pi / 180.
V = a * b * c * math.sqrt(
1 - math.cos(alpha)**2 - math.cos(beta)**2 -
math.cos(gamma)**2 + 2 *
(math.cos(alpha) * math.cos(beta) * math.cos(gamma)))
print 'V', V
continue
stop_treshold
stop
if '_exptl_crystal.density_Matthews' in d_mmCIF.keys():
if d_mmCIF['_exptl_crystal.density_Matthews'] not in [
['?'],
len(d_mmCIF['_exptl_crystal.density_Matthews']) *
['?'],
]:
if abs(MV -
float(d_mmCIF['_exptl_crystal.density_Matthews'][0])
) > 1:
print 'MV', MV
print 'MV', d_mmCIF['_exptl_crystal.density_Matthews']
print 'mw', mw
print 'Z', Z
continue
stop_difference
if not spacegroup in d_MV.keys():
d_MV[spacegroup] = []
d_MV[spacegroup] += [MV]
print pdb, round(MV, 2), spacegroup
## fd = open('MV_v_spacegroup.txt','w')
## fd.write(str(d_MV))
## fd.close()
l = ['# MV_average MV_stddev n spacegroup\n']
for spacegroup in d_MV.keys():
l_MV = d_MV[spacegroup]
if len(l_MV) <= 1:
continue
average, stddev = statistics.do_stddev(l_MV)
average, stderr = statistics.do_stderr(l_MV)
## l += ['%s %s %s %s\n' %(average,stddev,len(l_MV),spacegroup,)]
l += ['%s %s %s %s\n' % (
average,
stderr,
len(l_MV),
spacegroup,
)]
fd = open('MV_v_spacegroup.txt', 'w')
fd.writelines(l)
fd.close()
return
def parse_GoodVibes_exclude_flexible(pdb,path,):
##
## calculate amplitudes
##
d_mmCIF = parse_mmCIF.main(pdb[:4],)
d_coords, l_coords_alpha = mmCIF2coords.main(pdb[:4],d_mmCIF,query_chain=pdb[-1])
print len(l_coords_alpha)
##
## eigenvector
##
cutoff = 10
matrix_hessian = NMA.hessian_calculation(l_coords_alpha,cutoff,)
eigenvectors, eigenvalues = NMA.diagonalize_hessian(matrix_hessian)
l_amplitudes = [
math.sqrt(
eigenvectors[6][i]**2+eigenvectors[6][i+1]**2+eigenvectors[6][i+2]**2
)
for i in range(0,len(eigenvectors[6]),3)
]
## ## write pdb (color by bfactor)
## l_bfactors = [100*(l_amplitudes[i]-min(l_amplitudes))/(max(l_amplitudes)-min(l_amplitudes)) for i in range(len(l_amplitudes))]
## fd = open('output/%s/%s_%s_probe.pdb' %(path,pdb[:4],pdb[-1],),'r')
## lines = fd.readlines()
## fd.close()
## index = [-1,None,]
## lines_out = []
## for line in lines:
## record = line[:6].strip()
## if record != 'ATOM':
## lines_out += [line]
## else:
## res_no = int(line[22:26])
## if res_no != index[1]:
## index = [index[0]+1,res_no,]
## bfactor = l_bfactors[index[0]]
## line_out = '%s%6.2f%s' %(line[:60],bfactor,line[66:],)
## lines_out += [line_out]
## fd = open('output/%s/%s_%s_probe_color_by_amplitude.pdb' %(path,pdb[:4],pdb[-1],),'w')
## fd.writelines(lines_out)
## fd.close()
## average amplitude
average = sum(l_amplitudes)/len(l_amplitudes)
average,stddev = statistics.do_stddev(l_amplitudes)
##
l_coords_rigid = []
for i in range(len(l_coords_alpha)):
if l_amplitudes[i] < average:
l_coords_rigid += [l_coords_alpha[i]]
l_coords_flexible = []
for i in range(len(l_coords_alpha)):
if l_amplitudes[i] > average+0.5*stddev:
l_coords_flexible += [l_coords_alpha[i]]
## parse output
fd = open('output/%s/%s_%s_probe.pdb' %(path,pdb[:4],pdb[-1],),'r')
lines = fd.readlines()
fd.close()
max_bfactor = None
coord = None
for line in lines:
record = line[:6].strip()
if record not in ['ATOM','HETATM',]:
continue
res_name = line[17:20]
if res_name != 'EXT':
continue
bfactor = float(line[60:66])
if bfactor > max_bfactor:
x = float(line[30:38])
y = float(line[38:46])
z = float(line[46:54])
## coord_tmp = numpy.array([x,y,z,])
## bool_vicinal_to_rigid = False
## for coord_rigid in l_coords_rigid:
## dist_from_rigid = math.sqrt(sum((coord_rigid-coord_tmp)**2))
## if dist_from_rigid < 6:
## bool_vicinal_to_rigid = True
## break
## if bool_vicinal_to_rigid == False:
## continue
## bool_vicinal_to_flexible = False
## for coord_flexible in l_coords_flexible:
## dist_from_flexible = math.sqrt(sum((coord_flexible-coord_tmp)**2))
## if dist_from_flexible < 6:
## bool_vicinal_to_flexible = True
## break
## if bool_vicinal_to_flexible == True:
## continue
## min_dist = [1000.,None,]
## for i_coord_alpha in range(len(l_coords_alpha)):
## coord_alpha = l_coords_alpha[i_coord_alpha]
## dist_from_alpha = math.sqrt(sum((coord_alpha-coord_tmp)**2))
## if dist_from_alpha < min_dist[0]:
## min_dist = [dist_from_alpha,i_coord_alpha,]
## if l_amplitudes[min_dist[1]] > average+stddev:
## continue
coord = numpy.array([x,y,z,])
max_bfactor = bfactor
return coord
def main():
d_MV = {}
path = '/data/mmCIF'
l_dn = os.listdir(path)
l_dn.sort()
for dn in l_dn:
if dn == 'mmCIF.py':
continue
if dn < sys.argv[-2]:
continue
if dn > sys.argv[-1]:
continue
l_fn = os.listdir('%s/%s' %(path,dn))
for fn in l_fn:
pdb = fn[:4]
## if pdb.upper() not in s_pdbs:
## continue
d_mmCIF = parse_mmCIF.main(
pdb,
d_breaks = {'_exptl.method':'SOLUTION NMR'},
l_data_categories = [
'_cell','_entity','_exptl','_exptl_crystal',
'_entity_poly',
'_symmetry',
## virus
'_pdbx_struct_assembly',
## split structure
'_pdbx_database_related',
],
)
## x-ray structure
if d_mmCIF['_exptl.method'] != ['X-RAY DIFFRACTION']:
continue
## polymer present
if not '_entity_poly.type' in d_mmCIF.keys():
continue
## only polymer present is protein
if d_mmCIF['_entity_poly.type'] != len(d_mmCIF['_entity_poly.type'])*['polypeptide(L)']:
continue
if not '_pdbx_struct_assembly.oligomeric_count' in d_mmCIF.keys():
continue
if d_mmCIF['_pdbx_struct_assembly.oligomeric_count'] == len(d_mmCIF['_pdbx_struct_assembly.oligomeric_count'])*['?']:
continue
## virus
if int(d_mmCIF['_pdbx_struct_assembly.oligomeric_count'][0]) % 60 == 0:
continue
## not monomer
if d_mmCIF['_pdbx_struct_assembly.oligomeric_count'] != len(d_mmCIF['_pdbx_struct_assembly.oligomeric_count'])*['1']:
continue
## split structure
if '_pdbx_database_related' in d_mmCIF.keys():
if 'split' in d_mmCIF['_pdbx_database_related']:
continue
if 'SPLIT' in d_mmCIF['_pdbx_database_related']:
print pdb
stop
if not '_cell.Z_PDB' in d_mmCIF.keys():
continue
if pdb in [
## treshold
'1e54','1e9i',
## difference between calculated MV and MV in mmCIF
'3eiq',
## The crystals diffracted to 1.7Angstrom and appeared to be I centered tetragonal with
## unit cell dimension a=198.42Angstrom and c=396.6Angstrom, however the data only merged successfully in P1
## unit cell a=196.61 b=196.48 c=240.63 alpha=65.91 beta=65.91 gamma=90.01.
## Toscana has published with Hellinga...
'2cjf','2bt4',
]:
continue
## if not ''.join(d_mmCIF['_symmetry.space_group_name_H-M']) in [
## 'P 1','P 43 21 2','P 21 3','P 42 3 2','C 1 2 1','F 2 3','P 64 2 2','H 3',
## ]:
## continue ## tmp!!!
a = float(d_mmCIF['_cell.length_a'][0])
b = float(d_mmCIF['_cell.length_b'][0])
c = float(d_mmCIF['_cell.length_c'][0])
alpha = float(d_mmCIF['_cell.angle_alpha'][0])
beta = float(d_mmCIF['_cell.angle_beta'][0])
gamma = float(d_mmCIF['_cell.angle_gamma'][0])
Z = int(d_mmCIF['_cell.Z_PDB'][0])
mw = 0
for i in range(len(d_mmCIF['_entity.id'])):
## if d_mmCIF['_entity.type'][i] == 'polymer':
s = d_mmCIF['_entity.formula_weight'][i]
## unknown ligand
if s == '?':
continue
mw += float(s)
MV = matthews_coefficient.main(a,b,c,alpha,beta,gamma,mw,Z)
spacegroup = ''.join(d_mmCIF['_symmetry.space_group_name_H-M'])
if spacegroup not in [
'F 4 3 2',
'F 41 3 2',
'I 41 3 2',
]:
continue ## tmp!!!
if MV > 10:
print pdb
print 'mw', mw
print 'MV', MV, d_mmCIF['_exptl_crystal.density_Matthews']
print 'Z', Z
import math
alpha *= math.pi/180.
beta *= math.pi/180.
gamma *= math.pi/180.
V = a*b*c*math.sqrt(1-math.cos(alpha)**2-math.cos(beta)**2-math.cos(gamma)**2+2*(math.cos(alpha)*math.cos(beta)*math.cos(gamma)))
print 'V', V
continue
stop_treshold
stop
if '_exptl_crystal.density_Matthews' in d_mmCIF.keys():
if d_mmCIF['_exptl_crystal.density_Matthews'] not in [['?'],len(d_mmCIF['_exptl_crystal.density_Matthews'])*['?'],]:
if abs(MV-float(d_mmCIF['_exptl_crystal.density_Matthews'][0])) > 1:
print 'MV', MV
print 'MV', d_mmCIF['_exptl_crystal.density_Matthews']
print 'mw', mw
print 'Z', Z
continue
stop_difference
if not spacegroup in d_MV.keys():
d_MV[spacegroup] = []
d_MV[spacegroup] += [MV]
print pdb, round(MV,2), spacegroup
## fd = open('MV_v_spacegroup.txt','w')
## fd.write(str(d_MV))
## fd.close()
l = ['# MV_average MV_stddev n spacegroup\n']
for spacegroup in d_MV.keys():
l_MV = d_MV[spacegroup]
if len(l_MV) <= 1:
continue
average, stddev = statistics.do_stddev(l_MV)
average, stderr = statistics.do_stderr(l_MV)
## l += ['%s %s %s %s\n' %(average,stddev,len(l_MV),spacegroup,)]
l += ['%s %s %s %s\n' %(average,stderr,len(l_MV),spacegroup,)]
fd = open('MV_v_spacegroup.txt','w')
fd.writelines(l)
fd.close()
return
if d['spacegroup'] == 'different':
d_statistics['diffSG']['alpha'] += [rmsd_alpha]
d_statistics['diffSG']['heavy'] += [rmsd_heavy]
d_statistics['diffSG']['chi1'] += [chi1_diff_average]
else:
d_statistics['sameSG']['alpha'] += [rmsd_alpha]
d_statistics['sameSG']['heavy'] += [rmsd_heavy]
d_statistics['sameSG']['chi1'] += [chi1_diff_average]
prefix = 'CA_v_%s_%s_%s' %(y_property,protein,suffix_exclusion,)
fd = open('%s.gnuplotdata' %(prefix),'w')
fd.writelines(lines)
fd.close()
average_alpha, stddev_alpha = statistics.do_stddev(l_rmsds_alpha)
average_heavy, stddev_heavy = statistics.do_stddev(l_rmsds_heavy)
print 'alpha rmsd', len(l_rmsds_alpha), 'average', average_alpha, 'stddev', stddev_alpha
print 'heavy rmsd', len(l_rmsds_heavy), 'average', average_heavy, 'stddev', stddev_heavy
################################################################################
#### mutants
##for i in range(n_columns):
## l_columns += [[l_columns[i][0]+n_columns,'',l_columns[i][2],]]
#### put mutants in the background behind wts
##l_columns = l_columns[n_columns:]+l_columns[:n_columns]
l_colors = []
l_pointsizes = []
l_pointtypes = []
