def determine_leaflets(universe,phosphateSelection):
'''
From a selection of phosphates, determine which belong to the upper and lower leaflets.
Keyword arguments:
universe -- an MDAnalysis Universe object
phosphateSelection -- a string specifying how to select the phosphate atoms (e.g. "name P1")
'''
leaflets = {}
# calculate the z value of the phosphates defining the bilayer (assumes bilayer is in x and y..)
po4=universe.selectAtoms(phosphateSelection)
bilayerCentre = po4.centerOfGeometry()[2]
# apply the MDAnalysis LeafletFinder graph-based method to determine the two largest groups which
# should correspond to the upper and lower leaflets
phosphates = LeafletFinder(universe,phosphateSelection)
# find the two largest groups - required as the first two returned by LeafletFinder, whilst usually are the largest, this is not always so
(a,b) = largest_groups(phosphates.sizes())
# check to see where the first leaflet lies
if phosphates.group(a).centroid()[2] > bilayerCentre:
leaflets[1] = phosphates.group(a)
leaflets[2] = phosphates.group(b)
else:
leaflets[2] = phosphates.group(a)
leaflets[1] = phosphates.group(b)
return leaflets
def determine_leaflets(universe, phosphateSelection="name P*"):
'''
From a selection of phosphates, determine which belong to the upper and lower leaflets.
Keyword arguments:
universe -- an MDAnalysis Universe object
phosphateSelection -- a string specifying how to select the phosphate atoms (e.g. "name P1")
'''
leaflets = {}
#print(universe)
# calculate the z value of the phosphates defining the bilayer (assumes bilayer is in x and y..)
#po4=universe.atoms.select_atoms(phosphateSelection)
#bilayerCentre = po4.center_of_geometry()[2]
#print(bilayerCentre)
# apply the MDAnalysis LeafletFinder graph-based method to determine the two largest groups which
# should correspond to the upper and lower leaflets
phosphates = LeafletFinder(universe, phosphateSelection)
# find the two largest groups - required as the first two returned by LeafletFinder, whilst usually are the largest, this is not always so
(a, b) = largest_groups(phosphates.sizes())
layer1_avz = np.mean(phosphates.group(a).center_of_geometry()[2])
layer2_avz = np.mean(phosphates.group(b).center_of_geometry()[2])
bilayerCentre = (layer1_avz + layer2_avz) / 2.
# check to see where the first leaflet lies
if phosphates.group(a).centroid()[2] > bilayerCentre:
#print(phosphates.group(b).residues.atoms)
leaflets["upper"] = phosphates.group(a).residues.atoms
leaflets["lower"] = phosphates.group(b).residues.atoms
else:
leaflets["lower"] = phosphates.group(a).residues.atoms
leaflets["upper"] = phosphates.group(b).residues.atoms
return leaflets
def dpth(u): L = LeafletFinder(u, 'name P') L0 = L.group(0) L1 = L.group(1) """bi_cntr = (np.mean(L0.positions,axis=0)[-1]+np.mean(L1.positions,axis=0)[-1])/2""" int_cntr=L0.centroid()[-1] return int_cntr
def dpth(u, pro_z):
L = LeafletFinder(u, 'name P')
L0 = L.group(0)
L1 = L.group(1)
"""bi_cntr = (np.mean(L0.positions,axis=0)[-1]+np.mean(L1.positions,axis=0)[-1])/2"""
int_cntr = L1.centroid()[-1]
bi_cntr_dpth = (pro_z - int_cntr)
return bi_cntr_dpth
def dpth(u):
L = LeafletFinder(u, 'name P')
L0 = L.group(0)
L1 = L.group(1)
"""bi_cntr = (np.mean(L0.positions,axis=0)[-1]+np.mean(L1.positions,axis=0)[-1])/2"""
int_cntr=L0.centroid()[-1]
return int_cntr
if __name__ == "__main__":
u = MDAnalysis.Universe("gs_dopc_laur.gro","gs_dopc_laur_small.trr")
#dye=u.select_atoms("resid 28662 and (type N or type O or name C24)", updating = True)
dye=u.select_atoms("resid 28663 and (not type H)", updating = True)
leaflet_P = u.select_atoms("name P", updating = True)
L = LeafletFinder(u, 'name P')
L0 = L.group(0)
L1 = L.group(1)
data=np.empty([len(dye)+1,len(u.trajectory)])
for i, ts in enumerate(tqdm.tqdm(u.trajectory[0::1])):
leaflet_pos_z = L1.centroid()[-1]
for j, atom in enumerate(dye):
data[0,i] = u.trajectory.time
atom_z = atom.position[-1]
distance_atom_bound = - atom_z + leaflet_pos_z
data[j+1,i] = distance_atom_bound
ax = sns.heatmap(data[1:,:], xticklabels = 1000)
#plotting
i=0
fig = plt.figure(figsize=(24,8))
for name in "Prodan1","Prodan2":
int((u.dimensions[1] * 1.1) * pixelWidth),
int((u.dimensions[2] * 1.1) * pixelWidth)
])
speciesList = ['unsaturated', 'saturated', 'cholesterol']
# find out where the centre of the bilayer lies
bilayer = u.select_atoms("name PO4 or name ROH")
bilayerCentre = bilayer.center_of_geometry()[2]
# use the MDAnalysis analysis function LeafletFinder to identify the two bilayers
bilayerLeaflets = LeafletFinder(u, 'name PO4 or name ROH')
bilayerLeaflet = {}
# check to see where the first leaflet lies
if bilayerLeaflets.group(0).centroid()[2] > bilayerCentre:
leafletList = ["upper", "lower"]
else:
leafletList = ["lower", "upper"]
imageLookup = {}
imageLookup['unsaturated'] = {
'colour': 'Blues',
'range': [0, 0.0240],
'sigma': 4.1,
'ticks': [0, 0.012, 0.024]
}
imageLookup['saturated'] = {
'colour': 'Reds',
'range': [0, 0.0240],
'sigma': 4.1,
# create an array with the maximum number of pixels (voxels)
originalNumberPixels = numpy.array([int((u.dimensions[0]*1.1) * pixelWidth),int((u.dimensions[1]*1.1) * pixelWidth),int((u.dimensions[2]*1.1) * pixelWidth)])
speciesList = ['unsaturated','saturated','cholesterol']
# find out where the centre of the bilayer lies
bilayer = u.select_atoms("name PO4 or name ROH")
bilayerCentre = bilayer.center_of_geometry()[2]
# use the MDAnalysis analysis function LeafletFinder to identify the two bilayers
bilayerLeaflets = LeafletFinder(u,'name PO4 or name ROH')
bilayerLeaflet = {}
# check to see where the first leaflet lies
if bilayerLeaflets.group(0).centroid()[2] > bilayerCentre:
leafletList = ["upper","lower"]
else:
leafletList = ["lower","upper"]
imageLookup = {}
imageLookup['unsaturated'] = {'colour': 'Blues', 'range': [0,0.0240], 'sigma': 4.1, 'ticks': [0,0.012,0.024]}
imageLookup['saturated'] = {'colour': 'Reds', 'range': [0,0.0240], 'sigma': 4.1, 'ticks': [0,0.012,0.024]}
imageLookup['cholesterol'] = {'colour': 'Purples', 'range': [0,0.0240], 'sigma': 4.1, 'ticks': [0,0.012,0.024]}
imageLookup['mask'] = {'colour': 'RdBu', 'range': [-0.2,1.2], 'ticks': [0,1]}
imageLookup['edges'] = {'colour': 'Greys', 'range': [0,1], 'ticks': [0,1]}
# calculate how wide the bilayer is in pixels
numberPixels = numpy.array([int((u.dimensions[0]+2) * pixelWidth),int((u.dimensions[1]+2) * pixelWidth),int((u.dimensions[2]+2) * pixelWidth)])
