def addCoulombBasePair(object1, object2, value):
"""
Adding the Coulomb interaction (a base pair):
the lower pKa is lowered
"""
label1 = object1.label
label2 = object2.label
if object1.pKa_mod < object2.pKa_mod:
newDeterminant = Determinant(label2, -value)
object1.determinants[2].append(newDeterminant)
else:
newDeterminant = Determinant(label1, -value)
object2.determinants[2].append(newDeterminant)
def addCoulombAcidPair(object1, object2, value):
"""
Adding the Coulomb interaction (an acid pair):
the higher pKa is raised
"""
label1 = object1.label
label2 = object2.label
if object1.pKa_mod > object2.pKa_mod:
newDeterminant = Determinant(label2, value)
object1.determinants[2].append(newDeterminant)
else:
newDeterminant = Determinant(label1, value)
object2.determinants[2].append(newDeterminant)
def setBackBoneBaseDeterminants(data_clump, version=None):
"""
adding back-bone determinants/perturbations for bases:
Angle: atom1 -- atom2-atom3, i.e. C=O -- H-N(HIS)
data_clump = [bases, CO]
"""
residues, interactions = data_clump
for residue in residues:
if residue.location != "BONDED":
dpKa_max, cutoff = version.BackBoneParameters[residue.resType]
for interaction in interactions:
distance = 999.
atom1 = interaction[1]
atoms = residue.makeDeterminantAtomList("back-bone", version=version)
for atom in atoms:
current_distance = calculate.InterAtomDistance(atom1, atom)
if current_distance < distance:
atom2 = atom
distance = current_distance
if distance < cutoff[1]:
if residue.resType in version.angularDependentSideChainInteractions:
atom3 = residue.getThirdAtomInAngle(atom2)
distance, f_angle, nada = calculate.AngleFactorX(atom1, atom2, atom3)
else:
f_angle = 1.0
if f_angle > 0.001:
# add determinant
label = "%s%4d%2s" % (atom2.resName, atom2.resNumb, atom2.chainID)
value = residue.Q * calculate.HydrogenBondEnergy(distance, dpKa_max, cutoff, f_angle)
newDeterminant = Determinant(label, value)
residue.determinants[1].append(newDeterminant)
def setBackBoneAcidDeterminants(data_clump, version=None):
"""
adding back-bone determinants/perturbations for acids:
Angle: atom1 -- atom2-atom3, i.e. COO -- H-N
data_clump = [acids, NH]
"""
residues, interactions = data_clump
for residue in residues:
if residue.location != "BONDED":
dpKa_max, cutoff = version.BackBoneParameters[residue.resType]
for interaction in interactions:
atom2 = interaction[1]
atom3 = interaction[0]
atoms = residue.makeDeterminantAtomList("back-bone", version=version)
shortest_distance = 999.
for atom in atoms:
distance = calculate.InterAtomDistance(atom, atom2)
if distance < shortest_distance:
shortest_distance = distance
atom1 = atom
distance, f_angle, nada = calculate.AngleFactorX(atom1, atom2, atom3)
if distance < cutoff[1] and f_angle > 0.001:
label = "%s%4d%2s" % (atom2.resName, atom2.resNumb, atom2.chainID)
value = residue.Q * calculate.HydrogenBondEnergy(distance, dpKa_max, cutoff, f_angle)
newDeterminant = Determinant(label, value)
residue.determinants[1].append(newDeterminant)
def addCoulombIonPair(object1, object2, value):
"""
Adding the Coulomb interaction (an acid-base pair):
the pKa of the acid is lowered & the pKa of the base is raised
"""
label1 = object1.label
label2 = object2.label
# residue1
Q1 = object1.Q
newDeterminant = Determinant(label2, Q1*value)
object1.determinants[2].append(newDeterminant)
# residue2
Q2 = object2.Q
newDeterminant = Determinant(label1, Q2*value)
object2.determinants[2].append(newDeterminant)
def simplex_distance(self, support, sample):
'''Calculate cosine distance among all k examples with respect to m sample
Args:
support: [way*shot, D]
sample: [quiry, D]
Returns:
dists: [way, shot, quiry] same for examples in a same category
'''
support = support.view(self.way, self.shot, 1600)
dists = []
for s in range(self.way):
matrix_A = support[s, 1:].sub(support[s,
0].repeat(self.shot - 1,
1)) # shot-1, D
matrix_A_trans = matrix_A.permute(1, 0) # D, shot-1
matrix_A = matrix_A.unsqueeze(0).bmm(matrix_A_trans.unsqueeze(
0)).squeeze() # self.shot-1, self.shot-1
Volume_A = Determinant(matrix_A) # 0
# print (Volume_A, 'Volume_A')
for q in range(self.quiry):
matrix_B = support[s].sub(sample[q].repeat(self.shot, 1))
# print (matrix)
matrix_B_trans = matrix_B.permute(1, 0) # D, way*shot
matrix_B = matrix_B.unsqueeze(0).bmm(
matrix_B_trans.unsqueeze(0)).squeeze()
# print (matrix)
# print (Determinant(matrix))
Volume_B = Determinant(matrix_B)
dists.append(Volume_B / Volume_A)
dists = torch.stack(dists).squeeze().view(
self.way, self.quiry).unsqueeze(1).repeat(1, self.shot, 1)
# way, shot, quiry
# print (dists)
# print (torch.max(dists))
'''numpy'''
# max_values = torch.max(dists).data.cpu().numpy()[0]
# print (max_values)
'''repeat tensor'''
# max_values = torch.max(dists).unsqueeze(0).unsqueeze(0).repeat(self.way, self.shot, self.quiry)
# dists = dists / (max_values.repeat(1, self.way*self.shot))
# dists = max_values / dists
dists = dists.view(-1, self.quiry)
return dists
def addSidechainDeterminants(residue1, residue2, version=None):
"""
adding side-chain determinants/perturbations
Note, resNumb1 > resNumb2
"""
distance = 999.0
closest_atom1 = None
closest_atom2 = None
atoms1 = residue1.makeDeterminantAtomList(residue2.resName,
version=version)
atoms2 = residue2.makeDeterminantAtomList(residue1.resName,
version=version)
for atom1 in atoms1:
for atom2 in atoms2:
# select the smallest inter-atom distance
current_distance = calculate.InterAtomDistance(atom1, atom2)
if current_distance < distance:
closest_atom1 = atom1
closest_atom2 = atom2
distance = current_distance
dpka_max, cutoff = version.SideChainParameters[residue1.resType][
residue2.resType]
if distance < cutoff[1]:
if residue2.resType in version.angularDependentSideChainInteractions:
atom3 = residue2.getThirdAtomInAngle(closest_atom2)
distance, f_angle, nada = calculate.AngleFactorX(
closest_atom1, closest_atom2, atom3)
elif residue1.resType in version.angularDependentSideChainInteractions:
atom3 = residue1.getThirdAtomInAngle(closest_atom1)
distance, f_angle, nada = calculate.AngleFactorX(
closest_atom2, closest_atom1, atom3)
else:
# i.e. no angular dependence
f_angle = 1.0
weight = version.calculatePairWeight(residue1.Nmass, residue2.Nmass)
exception, value = version.checkExceptions(residue1, residue2)
#exception = False # circumventing exception
if exception == True:
""" do nothing, value should have been assigned """
#pka_print(" exception for %s %s %6.2lf" % (residue1.label, residue2.label, value))
else:
value = version.calculateSideChainEnergy(distance, dpka_max,
cutoff, weight, f_angle)
if residue1.Q == residue2.Q:
# acid pair or base pair
if residue1.pKa_mod < residue2.pKa_mod:
newDeterminant1 = Determinant(residue2.label, -value)
newDeterminant2 = Determinant(residue1.label, value)
else:
newDeterminant1 = Determinant(residue2.label, value)
newDeterminant2 = Determinant(residue1.label, -value)
else:
newDeterminant1 = Determinant(residue2.label, value * residue1.Q)
newDeterminant2 = Determinant(residue1.label, value * residue2.Q)
if residue1.resName not in version.exclude_sidechain_interactions:
residue1.determinants[0].append(newDeterminant1)
if residue2.resName not in version.exclude_sidechain_interactions:
residue2.determinants[0].append(newDeterminant2)
def setIonDeterminants(protein, version=None):
"""
adding ion determinants/perturbations
"""
ionizable_residues = lib.residueList("propka1")
for residue in protein.propka_residues:
if residue.resName in ionizable_residues:
for ion in protein.residue_dictionary["ION"]:
distance = calculate.InterResidueDistance(residue, ion)
if distance < version.coulomb_cutoff[1]:
label = "%s%4d%2s" % (ion.resName, ion.resNumb, ion.chainID)
weight = version.calculatePairWeight(residue.Nmass, ion.Nmass)
# the pKa of both acids and bases are shifted up by negative ions (and vice versa)
value = (-ion.Q) * version.calculateCoulombEnergy(distance, weight)
newDeterminant = Determinant(label, value)
residue.determinants[2].append(newDeterminant)
def addDeterminants(iterative_interactions, version, options=None):
"""
The iterative pKa scheme. Later it is all added in 'calculateTotalPKA'
"""
# --- setup ---
iteratives = []
done_residue = []
#debug.printIterativeDeterminants(iterative_interactions)
# creating iterative objects with references to their real residue counterparts
for interaction in iterative_interactions:
pair = interaction[0]
for residue in pair:
if residue in done_residue:
#print "done already"
""" do nothing - already have an iterative object for this residue """
else:
newIterative = Iterative(residue)
iteratives.append(newIterative)
done_residue.append(residue)
# Initialize iterative scheme
if options.print_iterations == True:
pka_print("\n --- pKa iterations (%d residues, %d interactions) ---" % ( len(iteratives), len(iterative_interactions) ))
converged = False
iteration = 0
for itres in iteratives:
itres.pKa_iter.append(itres.pKa_NonIterative)
# --- starting pKa iterations ---
while converged == False:
# initialize pKa_new
iteration += 1
for itres in iteratives:
itres.determinants = [[], [], []]
itres.pKa_new = itres.pKa_NonIterative
# Adding interactions to temporary determinant container
for interaction in iterative_interactions:
pair = interaction[0]
values = interaction[1]
annihilation = interaction[2]
#print "len(interaction) = %d" % (len(interaction))
object1, object2 = findIterative(pair, iteratives)
Q1 = object1.Q
Q2 = object2.Q
if Q1 < 0.0 and Q2 < 0.0:
""" both are acids """
addIterativeAcidPair(object1, object2, interaction)
elif Q1 > 0.0 and Q2 > 0.0:
""" both are bases """
addIterativeBasePair(object1, object2, interaction)
else:
""" one of each """
addIterativeIonPair(object1, object2, interaction, version)
# Calculating pKa_new values
for itres in iteratives:
for type in range(0,3):
for determinant in itres.determinants[type]:
itres.pKa_new += determinant[1]
# Check convergence
converged = True
for itres in iteratives:
if itres.pKa_new == itres.pKa_old:
itres.converged = True
else:
itres.converged = False
converged = False
# reset pKa_old & storing pKa_new in pKa_iter
for itres in iteratives:
itres.pKa_old = itres.pKa_new
itres.pKa_iter.append(itres.pKa_new)
if iteration == 10:
pka_print("did not converge in %d iterations" % (iteration))
break
# --- Iterations finished ---
# printing pKa iterations
if options.print_iterations == True:
str = "%12s" % (" ")
for index in range(0, iteration+1 ):
str += "%8d" % (index)
pka_print(str)
for itres in iteratives:
str = "%s " % (itres.label)
for pKa in itres.pKa_iter:
str += "%8.2lf" % (pKa)
if itres.converged == False:
str += " *"
pka_print(str)
# creating real determinants and adding them to residue object
for itres in iteratives:
for type in range(0,3):
for interaction in itres.determinants[type]:
value = interaction[1]
if value > 0.005 or value < -0.005:
label = interaction[0]
newDeterminant = Determinant(label, value)
itres.residue.determinants[type].append(newDeterminant)