def pdbWaterContact(pdb, water_radii=1.4):
"""
Residues are considered neighbors if *any* atom of theirs approaches closer
than vdw1 + vd2 + water.
"""
# Grab atoms
atoms = [l for l in pdb if l[0:4] == "ATOM"]
# Grab coordinates and calculate distance matrix
coord = [[float(l[30 + 8 * i:38 + 8 * i]) for i in range(3)]
for l in atoms]
dist = geometry.calcDistances(coord)
# Grab list of unique residues
residues = []
for line in atoms:
if line[21:26] not in residues:
residues.append(line[21:26])
neighbors = dict([(r, []) for r in residues])
wat_sep = 2 * water_radii
for i in range(len(atoms)):
for j in range(i + 1, len(atoms)):
max_sep = wat_sep + \
common.VDW_DICT[atoms[i][13:16]] + \
common.VDW_DICT[atoms[j][13:16]]
if dist[i][j] <= max_sep:
if atoms[j][21:26] not in neighbors[atoms[i][21:26]]:
neighbors[atoms[i][21:26]].append(atoms[j][21:26])
neighbors[atoms[j][21:26]].append(atoms[i][21:26])
return neighbors
def pdbWaterContact(pdb,water_radii=1.4):
"""
Residues are considered neighbors if *any* atom of theirs approaches closer
than vdw1 + vd2 + water.
"""
# Grab atoms
atoms = [l for l in pdb if l[0:4] == "ATOM"]
# Grab coordinates and calculate distance matrix
coord = [[float(l[30+8*i:38+8*i]) for i in range(3)] for l in atoms]
dist = geometry.calcDistances(coord)
# Grab list of unique residues
residues = []
for line in atoms:
if line[21:26] not in residues:
residues.append(line[21:26])
neighbors = dict([(r,[]) for r in residues])
wat_sep = 2*water_radii
for i in range(len(atoms)):
for j in range(i+1,len(atoms)):
max_sep = wat_sep + \
common.VDW_DICT[atoms[i][13:16]] + \
common.VDW_DICT[atoms[j][13:16]]
if dist[i][j] <= max_sep:
if atoms[j][21:26] not in neighbors[atoms[i][21:26]]:
neighbors[atoms[i][21:26]].append(atoms[j][21:26])
neighbors[atoms[j][21:26]].append(atoms[i][21:26])
return neighbors
def pdbContact(pdb,all=False):
"""
Generate array of all atom-atom distances in a pdb file. Defaults to only
look at CA atoms
"""
# Remove non-CA atoms
if not all:
pdb = [l for l in pdb if l[0:4] == "ATOM" and l[13:16] == "CA "]
else:
pdb = [l for l in pdb if l[0:4] == "ATOM"]
coord = [[float(l[30+8*i:38+8*i]) for i in range(3)] for l in pdb]
dist = geometry.calcDistances(coord)
return dist
def pdbContact(pdb, all=False):
"""
Generate array of all atom-atom distances in a pdb file. Defaults to only
look at CA atoms
"""
# Remove non-CA atoms
if not all:
pdb = [l for l in pdb if l[0:4] == "ATOM" and l[13:16] == "CA "]
else:
pdb = [l for l in pdb if l[0:4] == "ATOM"]
coord = [[float(l[30 + 8 * i:38 + 8 * i]) for i in range(3)] for l in pdb]
dist = geometry.calcDistances(coord)
return dist
def pdbContact(pdb,all=False):
"""
Generate array of all atom-atom distances in a pdb file. Defaults to only
look at CA atoms
"""
pdb = other.getPolymerAtoms(pdb)
pdb = other.removeRotamers(pdb)
# Remove non-CA atoms
if not all:
pdb = [l for l in pdb if l[13:15] == "CA"]
coord = [[float(l[30+8*i:38+8*i]) for i in range(3)] for l in pdb]
dist = geometry.calcDistances(coord)
return dist
def pdbIonDist(pdb, hist_step, remove_resid="TYR"):
"""
Calculate ij distances between all titratable atoms in pdb (except residues
in skip_resid) then bin according to hist_step. The output histogram is
a 3 x N nested list where N is the length required to cover all distances
in pdb using hist_step and the 3 overarching lists hold acid/acid,
acid/base, and base/base interactions in 0, 1, and 2 respectively.
"""
pdb = [l for l in pdb if l[0:4] == "ATOM"]
titr_atom = [
l for l in pdb if l[17:20] not in remove_resid
and l[17:20] in TITR_ATOM.keys() and l[13:16] == TITR_ATOM[l[17:20]]
]
# Extract coordinates and charges for each titratable atom
coord = [[float(l[30 + 8 * i:38 + 8 * i]) for i in xrange(3)]
for l in titr_atom]
charge = [CHARGE_DICT[l[17:20]] for l in titr_atom]
# Calculate all ij distances
dist = calcDistances(coord)
N = len(coord)
# Initialize histogram by finding maximum distance that will have to be
# counted.
max_dist_bin = max([max([dist[i][j] for j in range(N)]) for i in range(N)])
max_dist_bin = int(round(max_dist_bin / hist_step)) + 1
histogram = [[0 for j in xrange(max_dist_bin)] for i in xrange(3)]
# Populate histogram
# Interaction types:
# acid/acid --> 0 (-1 + -1)/2 + 1
# acid/base, base/acid --> 1 (-1 + 1)/2 + 1
# base/base --> 2 ( 1 + 1)/2 + 2
for i in xrange(N):
for j in xrange(i + 1, N):
interaction_type = int((charge[i] + charge[j]) / 2 + 1)
dist_bin = int(round(dist[i][j] / hist_step))
histogram[interaction_type][dist_bin] += 1
return histogram
def pdbIonDist(pdb,hist_step,remove_resid="TYR"):
"""
Calculate ij distances between all titratable atoms in pdb (except residues
in skip_resid) then bin according to hist_step. The output histogram is
a 3 x N nested list where N is the length required to cover all distances
in pdb using hist_step and the 3 overarching lists hold acid/acid,
acid/base, and base/base interactions in 0, 1, and 2 respectively.
"""
pdb = [l for l in pdb if l[0:4] == "ATOM"]
titr_atom = [l for l in pdb
if l[17:20] not in remove_resid and
l[17:20] in TITR_ATOM.keys() and
l[13:16] == TITR_ATOM[l[17:20]]]
# Extract coordinates and charges for each titratable atom
coord = [[float(l[30+8*i:38+8*i]) for i in xrange(3)] for l in titr_atom]
charge = [CHARGE_DICT[l[17:20]] for l in titr_atom]
# Calculate all ij distances
dist = calcDistances(coord)
N = len(coord)
# Initialize histogram by finding maximum distance that will have to be
# counted.
max_dist_bin = max([max([dist[i][j] for j in range(N)])
for i in range(N)])
max_dist_bin = int(round(max_dist_bin/hist_step)) + 1
histogram = [[0 for j in xrange(max_dist_bin)] for i in xrange(3)]
# Populate histogram
# Interaction types:
# acid/acid --> 0 (-1 + -1)/2 + 1
# acid/base, base/acid --> 1 (-1 + 1)/2 + 1
# base/base --> 2 ( 1 + 1)/2 + 2
for i in xrange(N):
for j in xrange(i+1,N):
interaction_type = int((charge[i] + charge[j])/2 + 1)
dist_bin = int(round(dist[i][j]/hist_step))
histogram[interaction_type][dist_bin] += 1
return histogram
