def split_states_chains_save( sel1 ):
'''
Simple script to split states of NMR ensemble and then save the complex and chain A separately for each state
'''
cmd.remove("resn hoh")
for ind in range(1,cmd.count_states(sel1)+1):
if cmd.count_states(sel1) > 1:
cmd.split_states(sel1)
file_prefix="{0}_{1:04d}".format(sel1, ind)
else:
file_prefix=sel1
cmd.save(file_prefix + "_complex.pdb", file_prefix)
cmd.split_chains(file_prefix)
cmd.save(file_prefix + ".pdb", file_prefix + "_A")
def display_graphkernel(pdb_id, pdb_path):
'''
'''
# Load PDB
cmd.bg_color('white')
cmd.load(pdb_path + pdb_id[:-2] + '.pdb')
cmd.split_chains(pdb_id[:-2])
for name in cmd.get_names('objects', 0, '(all)'):
if not name.endswith(pdb_id[-1].upper()) and name.startswith(
pdb_id[:4]):
cmd.delete(name)
else:
zero_residues(name)
cmd.reset()
pdb_id2 = pdb_id + 'copy'
cmd.create(pdb_id2, pdb_id)
cmd.hide('everything', pdb_id)
cmd.show_as('lines', pdb_id + ' and (name ca or name c or name n)')
cmd.set('line_width', 5)
cmd.set_bond('line_width', 5,
pdb_id + ' and (name ca or name c or name n)')
cmd.show('spheres', pdb_id + ' and name ca')
cmd.set('sphere_transparency', 0.0, pdb_id + ' and name ca')
cmd.set('sphere_scale', 0.5, pdb_id + ' and name ca')
cmd.hide('everything', pdb_id2)
cmd.show('spheres', pdb_id2 + ' and name ca')
cmd.set('sphere_transparency', 0.8, pdb_id2 + ' and name ca')
cmd.set('sphere_scale', code2[elem], elem + '&' + selection)
#cmd.set('sphere_scale', 2, pdb_id2 + ' and name ca')
data = cmd.get_coords(selection=pdb_id + ' and name ca', state=1)
j = 55
cmd.set('dash_width', 1.0)
cmd.set('dash_color', 'marine')
for i in range(len(data)):
cmd.distance('d' + str(i) + str(j),
pdb_id2 + ' and name ca and res ' + str(i),
pdb_id2 + ' and name ca and res ' + str(j))
cmd.hide('labels', 'd' + str(i) + str(j))
resicolor(pdb_id)
resicolor(pdb_id)
resicolor(pdb_id2, True)
def stucture_attribution(pdb_id, attributions_path, pdb_path, flag=False):
'''
'''
data = np.load(attributions_path)
attributions = data['data']
kernels = data['kernels']
labels = data['labels']
offsets = data['offsets']
ind = np.where(labels == pdb_id)
#attribution = attributions[ind][0][:,-1]
if flag:
a_ = data["all_"][0]
a_[a_ <= 0] = 0.0
attribution = data['all_'][0] + data['all_'][1]
attribution[attribution <= 0] = 0.0
attribution = a_ * attribution
else:
a_ = data["all_"][1]
a_[a_ <= 0] = 0.0
attribution = data['all_'][0] + data['all_'][1]
attribution[attribution <= 0] = 0.0
attribution = a_ * attribution
# Load PDB
cmd.load(pdb_path + pdb_id[:-2] + '.pdb')
cmd.split_chains(pdb_id[:-2])
for name in cmd.get_names('objects', 0, '(all)'):
if not name.endswith(pdb_id[-1].upper()) and name.startswith(
pdb_id[:4]):
cmd.delete(name)
else:
zero_residues(name)
cmd.reset()
cmd.color('white', pdb_id)
for i, _ in enumerate(attribution):
#if flag: _ = _ *-1
cmd.select('toBecolored',
pdb_id + ' and res ' + str(i + offsets[ind][0]))
cmd.set_color('saliency' + str(i) + pdb_id, list(cmap(norm(_)))[:3])
#else: cmd.set_color('saliency'+str(i)+pdb_id, list(cmap2(norm(_)))[:3])
cmd.color('saliency' + str(i) + pdb_id, 'toBecolored')
cmd.select('selected', pdb_id)
#cmd.show('mesh', 'selected')
#cmd.show('sticks', 'selected')
cmd.deselect()
def kernels(pdb_id, data_path, pdb_path, flag=False):
'''
'''
data = np.load(data_path)
kernels = data['kernels']
labels = data['labels']
offsets = data['offsets']
ind = np.where(labels == pdb_id)
kernels = kernels[ind][0][0]
# Load PDB
cmd.load(pdb_path + pdb_id[:-2] + '.pdb')
cmd.split_chains(pdb_id[:-2])
for name in cmd.get_names('objects', 0, '(all)'):
if not name.endswith(pdb_id[-1].upper()) and name.startswith(
pdb_id[:4]):
cmd.delete(name)
else:
zero_residues(name)
cmd.reset()
pdb_id2 = pdb_id + 'kernel'
cmd.create(pdb_id2, pdb_id)
cmd.delete(pdb_id)
'''
cmd.hide('everything',pdb_id)
cmd.show_as('lines', pdb_id + ' and (name ca or name c or name n)')
cmd.set('line_width', 5)
cmd.set_bond('line_width', 5, pdb_id + ' and (name ca or name c or name n)')
cmd.show('spheres', pdb_id + ' and name ca')
cmd.set('sphere_transparency', 0.0, pdb_id + ' and name ca')
cmd.set('sphere_scale', 0.5, pdb_id + ' and name ca')
'''
cmd.hide('everything', pdb_id2)
cmd.show('spheres', pdb_id2 + ' and name ca')
cmd.set('sphere_transparency', 0.9, pdb_id2 + ' and name ca')
for i, _ in enumerate(kernels):
print(_)
cmd.set(
'sphere_scale', _ / (1.7 * 2),
pdb_id2 + ' and res ' + str(i + offsets[ind][0]) + ' and name ca')
cmd.deselect()
def structure_attribution(self, pdb_id, flag=False):
# Load Attribution
data = np.load(self.attribution_path, allow_pickle=True)
attributions = data['data']
offsets = data['offsets']
labels = data['labels']
ind = np.where(labels == pdb_id)
attribution = attributions[ind][0][:, -1]
cmd.bg_color('white')
cmd.load(self.data_path + pdb_id[:-2] + '.pdb')
cmd.split_chains()
for name in cmd.get_names('objects', 0, '(all)'):
if not name.endswith(pdb_id[-1].upper()):
cmd.delete(name)
else:
zero_residues(name)
cmd.reset()
cmd.color('white', pdb_id)
for i, _ in enumerate(attribution):
cmd.select('toBecolored', 'res ' + str(i + offsets[ind][0]))
cmd.set_color('saliency' + str(i), list(cmap(norm(_)))[:3])
cmd.color('saliency' + str(i), 'toBecolored')
cmd.select('selected', 'chain ' + pdb_id[-1].upper())
#cmd.show('mesh', 'selected')
cmd.deselect()
cmd.save(self.output_path + pdb_id + '.pse')
return self.output_path + pdb_id + '.pse'
#############################################################
# pdb_id = '4q9z_a'
# attributions_path = 'Output/Kinases/seed1/attributions.npz'
# data_path = 'pdb_extractor/Kinases/PDB/'
# cmd.reinitialize()
# cmd.bg_color('black')
# sA = StructureAttribution(attributions_path,data_path)
# sA.structure_attribution(pdb_id)
def display_graphconv(pdb_id, pdb_path):
'''
'''
cmd.bg_color('white')
cmd.load(pdb_path + pdb_id[:-2] + '.pdb')
cmd.split_chains(pdb_id[:-2])
for name in cmd.get_names('objects', 0, '(all)'):
if not name.endswith(pdb_id[-1].upper()) and name.startswith(
pdb_id[:4]):
cmd.delete(name)
else:
zero_residues(name)
cmd.reset()
pdb_id2 = pdb_id + 'copy'
cmd.create(pdb_id2, pdb_id)
cmd.color('white', pdb_id)
cmd.hide('everything', pdb_id)
cmd.show('spheres', pdb_id + ' and name ca')
cmd.set('sphere_transparency', 0.0, pdb_id + ' and name ca')
cmd.set('sphere_scale', 0.5, pdb_id + ' and name ca')
data = cmd.get_coords(selection=pdb_id + ' and name ca', state=1)
j = 55
cmd.set('dash_width', 1.0)
cmd.set('dash_color', 'marine')
data = np.random.uniform(0, 0.25, len(data))
for i in range(len(data)):
cmd.distance('d' + str(i) + str(j),
pdb_id + ' and name ca and res ' + str(i),
pdb_id + ' and name ca and res ' + str(j))
cmd.hide('labels', 'd' + str(i) + str(j))
cmd.select('toBecolored', pdb_id + ' and name ca and res ' + str(i))
if i == j:
cmd.set_color('saliency' + str(i) + pdb_id,
list(cmap(norm(1)))[:3])
else:
cmd.set_color('saliency' + str(i) + pdb_id,
list(cmap(norm(data[i])))[:3])
cmd.color('saliency' + str(i) + pdb_id, 'toBecolored')
cmd.color('white', pdb_id2)
cmd.hide('everything', pdb_id2)
cmd.show('spheres', pdb_id2 + ' and name ca')
cmd.set('sphere_transparency', 0.0, pdb_id2 + ' and name ca')
cmd.set('sphere_scale', 0.5, pdb_id2 + ' and name ca')
j = 55
cmd.set('dash_width', 1.0)
cmd.set('dash_color', 'marine')
#data = np.random.uniform(0,0.25,len(data))
for i in range(len(data)):
cmd.distance('d' + str(i) + str(j),
pdb_id2 + ' and name ca and res ' + str(i),
pdb_id2 + ' and name ca and res ' + str(j))
cmd.hide('labels', 'd' + str(i) + str(j))
cmd.select('toBecolored', pdb_id2 + ' and name ca and res ' + str(i))
if i == j:
cmd.set_color('saliency' + str(i) + pdb_id2,
list(cmap(norm(0)))[:3])
else:
cmd.set_color('saliency' + str(i) + pdb_id2,
list(cmap(norm(data[i])))[:3])
cmd.color('saliency' + str(i) + pdb_id2, 'toBecolored')
def display_graphpool(pdb_id, pdb_path):
'''
'''
# Load PDB
cmd.bg_color('white')
cmd.load(pdb_path + pdb_id[:-2] + '.pdb')
cmd.split_chains(pdb_id[:-2])
for name in cmd.get_names('objects', 0, '(all)'):
if not name.endswith(pdb_id[-1].upper()) and name.startswith(
pdb_id[:4]):
cmd.delete(name)
else:
zero_residues(name)
cmd.reset()
pdb_id2 = pdb_id + 'copy'
cmd.create(pdb_id2, pdb_id)
cmd.color('grey', pdb_id)
cmd.hide('everything', pdb_id)
cmd.show_as('lines', pdb_id + ' and (name ca)')
cmd.set('line_width', 5)
cmd.set_bond('line_width', 5, pdb_id + ' and (name ca)')
cmd.show('spheres', pdb_id + ' and name ca')
cmd.set('sphere_transparency', 0.0, pdb_id + ' and name ca')
cmd.set('sphere_scale', 0.5, pdb_id + ' and name ca')
data = cmd.get_coords(selection=pdb_id + ' and name ca', state=1)
data_ = []
cmd.set('dash_color', 'marine')
cmd.set('dash_width', 1.0)
j = 55
for i in range(len(data)):
if i % 2 == 0 and i + 1 < len(data):
data[i] = np.mean(data[i:i + 2], axis=0)
data[i + 1] = np.array([10000, 10000, 10000])
#cmd.distance('d'+str(i)+str(j), pdb_id + ' and name ca and res ' + str(i), pdb_id + ' and name ca and res ' + str(j))
#cmd.hide('labels', 'd'+str(i)+str(j))
cmd.color('red', pdb_id2)
cmd.hide('everything', pdb_id2)
cmd.show_as('lines', pdb_id2 + ' and (name ca)')
cmd.set('line_width', 5)
cmd.set_bond('line_width', 5, pdb_id2 + ' and (name ca)')
cmd.show('spheres', pdb_id2 + ' and name ca')
cmd.set('sphere_transparency', 0.0, pdb_id2 + ' and name ca')
cmd.set('sphere_scale', 0.5, pdb_id2 + ' and name ca')
for i in range(len(data)):
if i % 2 == 0 and i + 1 < len(data):
cmd.alter_state(1, pdb_id2 + ' and name ca and res ' + str(i),
'(x,y,z)=' + str(tuple(data[i])))
else:
cmd.hide('spheres', pdb_id2 + ' and name ca and res ' + str(i))
pdb_id3 = pdb_id + 'copy2'
cmd.create(pdb_id3, pdb_id2)
cmd.color('red', pdb_id3)
cmd.hide('everything', pdb_id3)
cmd.show_as('lines', pdb_id3 + ' and (name ca)')
cmd.set('line_width', 5)
cmd.set_bond('line_width', 5, pdb_id3 + ' and (name ca)')
cmd.show('spheres', pdb_id3 + ' and name ca')
cmd.set('sphere_transparency', 0.8, pdb_id3 + ' and name ca')
for i in range(len(data)):
if i % 2 == 0 and i + 1 < len(data):
cmd.set('sphere_scale', np.random.uniform(1.0, 4.5),
pdb_id3 + ' and name ca and res ' + str(i))
else:
cmd.hide('spheres', pdb_id2 + ' and name ca and res ' + str(i))
pdb_id = '4m21_a'
attributions_path = 'out/krashras_graph_new/interpret/attributions.npz'
data_path = 'data/KrasHras/pdb/'
# Load Attribution
data = np.load(attributions_path)
attributions = data['data']
labels = data['labels']
ind = np.where(labels == pdb_id)
attribution = attributions[ind][0][:,-4]
# Load PDB
cmd.reinitialize()
cmd.bg_color('white')
cmd.load(data_path+pdb_id[:-2]+'.pdb')
cmd.split_chains()
for name in cmd.get_names('objects', 0, '(all)'):
if not name.endswith(pdb_id[-1].upper()):
cmd.delete(name)
cmd.reset()
for i, _ in enumerate(attribution):
cmd.select('toBecolored', 'res ' + str(i))
cmd.set_color('saliency'+str(i), list(cmap(norm(_)))[:3])
cmd.color('saliency'+str(i), 'toBecolored')
cmd.select('selected','chain '+pdb_id[-1].upper())
cmd.show('mesh', 'selected')
cmd.deselect()