/usr/share/pdb2pqr/pdb2pka/graph_cut/protein_complex.py is in pdb2pqr 2.1.1+dfsg-2.
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from collections import OrderedDict
import sys
import math
titratable_residue_data = {
"ARG": {"model_pka" : 13.0, "ionizable" : 1, "tautomers":{"deprotonated":("1+2+3+4",), "protonated":("1+2+3+4+5",)}},
"ASP": {"model_pka": 3.9, "ionizable":-1, "tautomers":{"protonated":("1", "2", "3", "4"), "deprotonated":("0",)}},
"GLU": {"model_pka": 4.1, "ionizable":-1, "tautomers":{"protonated":("1", "2", "3", "4"), "deprotonated":("0",)}},
"LYS": {"model_pka":10.4, "ionizable": 1, "tautomers":{"protonated":("1",), "deprotonated":("0",)}},
"TYR": {"model_pka": 9.6, "ionizable": 1, "tautomers":{"protonated":("1",), "deprotonated":("0",)}},
"CTR": {"model_pka": 3.2, "ionizable":-1, "tautomers":{"protonated":("1", "2", "3", "4"), "deprotonated":("0",)}},
"NTR": {"model_pka": 8.3, "ionizable": 1, "tautomers":{"deprotonated":("1", "2"), "protonated":("1+2",)}},
"HIS": {"model_pka": 6.6, "ionizable": 1, "tautomers":{"protonated":("1", "2"), "deprotonated":("1+2",)}},
}
all_tautomers = set()
for residue_data in titratable_residue_data.values():
all_tautomers.update(residue_data["tautomers"]["deprotonated"])
all_tautomers.update(residue_data["tautomers"]["protonated"])
state_to_tautomer = {}
for state in ("ASH1c", "GLH1c", "LYS", "TYR", "HSD", "H3", "CTR01c"):
state_to_tautomer[state] = "1"
for state in ("ASH1t", "GLH1t", "HSE", "H2", "CTR01t"):
state_to_tautomer[state] = "2"
for state in ("ASH2c", "GLH2c", "CTR02c"):
state_to_tautomer[state] = "3"
for state in ("ASH2t", "GLH2t", "CTR02t"):
state_to_tautomer[state] = "4"
for state in ("ASP", "GLU", "LYS0", "TYR-", "CTR-"):
state_to_tautomer[state] = "0"
state_to_tautomer["ARG0"] = "1+2+3+4"
state_to_tautomer["ARG"] = "1+2+3+4+5"
for state in ("HSP", "H3+H2"):
state_to_tautomer[state] = "1+2"
class ResidueInstance(object):
"""Storage class for information about a particular residue state."""
def __init__(self, protonated, name, energy = 0.0):
self.name = name
self.protonated = protonated
self.energy = energy
self.energyNF = None
self.energy_with_ph = None
def __hash__(self):
return hash(self.name)
def __repr__(self):
return self.name
#return "{}: {}, {}, {}".format(self.name, self.protonated, self.energy, self.energyNF)
#For sorting state output if we use pretty print.
def __eq__(self, other):
return self._get_self_comp_tuple() == other._get_self_comp_tuple()
def __ne__(self, other):
return self._get_self_comp_tuple() != other._get_self_comp_tuple()
def __gt__(self, other):
return self._get_self_comp_tuple() > other._get_self_comp_tuple()
def __lt__(self, other):
return self._get_self_comp_tuple() < other._get_self_comp_tuple()
def __ge__(self, other):
return self._get_self_comp_tuple() >= other._get_self_comp_tuple()
def __le__(self, other):
return self._get_self_comp_tuple() <= other._get_self_comp_tuple()
def _get_self_comp_tuple(self):
return (self.name, self.energy)
class ResidueVariable(object):
"""Storage class all information about a particular residue
including all possible states."""
def __init__(self, name):
self.name = name
self.instances = OrderedDict()
def get_instance(self, state):
"""Returns a specific ResidueInstance from the state name.
After the protein complex is simplified this will always return None
as the non-consolidated Instances are removed."""
if state not in all_tautomers:
state = state_to_tautomer.get(state)
return self.instances.get(state)
def get_prot_and_deprot_instances(self):
#We don't want the placeholder instances
prot = [value for key, value in self.instances.items() if "PROTONATED" not in key and value.protonated]
deprot = [value for key, value in self.instances.items() if "PROTONATED" not in key and not value.protonated]
return prot, deprot
def __hash__(self):
return hash(self.name)
def __repr__(self):
return self.name
#For sorting state output if we use pretty print.
def __eq__(self, other):
return self.name == other.name
def __ne__(self, other):
return self.name != other.name
def __gt__(self, other):
return self.name > other.name
def __lt__(self, other):
return self.name < other.name
def __ge__(self, other):
return self.name >= other.name
def __le__(self, other):
return self.name <= other.name
class ProteinComplex(object):
def __init__(self, T=300):
self.T = T
self.normalized_constant_energy = 0.0
self.residue_variables = OrderedDict()
self.interaction_energies = OrderedDict()
self.normalized_interaction_energies = None
def add_residue(self, residue_type, chain, location):
"""Adds a residue to the protein if needed.
Automatically creates all instances needed before simplification."""
residue_tuple = (residue_type, chain, location)
if residue_tuple not in self.residue_variables:
residue_data = titratable_residue_data.get(residue_type)
base_name = '_'.join(residue_tuple)+'_'
res_var = ResidueVariable('_'.join(residue_tuple))
tautomers = residue_data["tautomers"]
model_pka = residue_data["model_pka"]
for tautomer in tautomers["deprotonated"]:
instance = ResidueInstance(False, base_name+tautomer)
instance.energy = 0
res_var.instances[tautomer] = instance
for tautomer in tautomers["protonated"]:
instance = ResidueInstance(True, base_name+tautomer)
instance.energy = -1.0*math.log(10)*model_pka
res_var.instances[tautomer] = instance
if residue_type != "HIS":
#Placeholder instances for later consolidation
#HIS is split later so we don't add these as they are not needed.
instance = ResidueInstance(True, base_name+"PROTONATED")
res_var.instances["PROTONATED"] = instance
instance = ResidueInstance(False, base_name+"DEPROTONATED")
res_var.instances["DEPROTONATED"] = instance
self.residue_variables[residue_tuple] = res_var
def get_residue(self, name, chain, location):
"Returns the residue for this specific name, chain, and location."
return self.residue_variables.get((name, chain, location))
def get_instance(self, residue_type, chain, location, state):
"Returns the instance for this specific name, chain, and location and state name."
res_var = self.residue_variables.get((residue_type, chain, location))
if res_var is None:
return None
return res_var.get_instance(state)
def drop_interaction_pairs(self, pair_list):
"Drop each pair of interaction energies in the pair_list"
for instance1_name, instance2_name in pair_list:
del self.interaction_energies[instance1_name, instance2_name]
del self.interaction_energies[instance2_name, instance1_name]
def get_interaction_combinations(self, pair1, pair2):
"Get a list of all pairwise combinations from lists pair1 and pair2."
product_list = [(x,y) for x,y in product(pair1, pair2)]
return product_list
def add_interaction_energy_pair(self, instance1, instance2, energy, normalized=False):
"Insert interaction energy pair."
ie = self.normalized_interaction_energies if normalized else self.interaction_energies
ie[instance1, instance2] = energy
ie[instance2, instance1] = energy
def simplify(self):
"""Simplify the instances into protonated and deprotonated.
Also divides HIS into HID and HIE."""
self.update_special_instance_energies()
self.consolidate()
self.divide_his()
def update_special_instance_energies(self):
"""After we have loaded the backgroind and desolvation files we need to
update the consolidated instances to use the minimum energy of the
instances they are meant to replace."""
for key, residue in self.residue_variables.items():
name = key[0]
if name == 'HIS':
continue
prot_consolidated = residue.instances["PROTONATED"]
deprot_consolidated = residue.instances["DEPROTONATED"]
protonated, deprotonated = residue.get_prot_and_deprot_instances()
#Update consolidated instance energy
prot_consolidated.energy = min(x.energy for x in protonated)
deprot_consolidated.energy = min(x.energy for x in deprotonated)
def consolidate(self):
"""Each residue has multiple protonated and deprotonated states. Here
we consolidate those into two states for each residue, PROT and DEPROT.
We take minimums of energies between states in each class. For example,
assume we have two amino acids, A and B, where A has protonated states 1, 2, 3
and deprotonated state 4, and B has protonated states 1, 2, and deprotonated
state 3. Then
E(A_PROT, B_PROT) = min{E(A1,B1), E(A1,B2), E(A2,B1), E(A2,B2), E(A3,B1), E(A3,B2)},
E(A_PROT, B_DEPROT) = min{E(A1,B3), E(A2,B3), E(A3,B3)},
E(A_DEPROT, B_PROT) = min{E(A4,B1), E(A4,B2)}, and
E(A_DEPROT, B_DEPROT) = E(A4,B3).
We do not deal with HIS here, it is kept in its 3 states for now.
After this is finished all unused interaction energies will be removed from
self.interaction_energies."""
handled_interaction_pairs = set()
#See https://docs.python.org/2/library/itertools.html#itertools.combinations
for v, w in combinations(iter(self.residue_variables.items()),2):
v_key, v_residue = v
w_key, w_residue = w
v_name = v_key[0]
w_name = w_key[0]
#Skip HIS for now
if v_name == 'HIS' or w_name == 'HIS':
continue
v_protinated, v_unprotonated = v_residue.get_prot_and_deprot_instances()
v_prot_consolidated = v_residue.instances["PROTONATED"]
v_deprot_consolidated = v_residue.instances["DEPROTONATED"]
w_protinated, w_unprotonated = w_residue.get_prot_and_deprot_instances()
w_prot_consolidated = w_residue.instances["PROTONATED"]
w_deprot_consolidated = w_residue.instances["DEPROTONATED"]
#For every pairing of v and w (protonated and unprotonated) find the
# minimum interaction energy and update the interaction map accordingly.
v_stuff = ((v_protinated, v_prot_consolidated), (v_unprotonated, v_deprot_consolidated))
w_stuff = ((w_protinated, w_prot_consolidated), (w_unprotonated, w_deprot_consolidated))
for v_product, w_product in product(v_stuff, w_stuff):
v_instances, v_consolidated = v_product
w_instances, w_consolidated = w_product
energies = []
#Find all of the pairs
for v_instance, w_instance in product(v_instances, w_instances):
energy = self.interaction_energies[v_instance, w_instance]
energies.append(energy)
#Mark for deletion.
handled_interaction_pairs.add((v_instance, w_instance))
min_energy = min(energies)
self.add_interaction_energy_pair(v_consolidated, w_consolidated, min_energy)
#Now handle HIS.
#See https://docs.python.org/2/library/itertools.html#itertools.permutations
for v, w in permutations(iter(self.residue_variables.items()),2):
his_key, his_residue = v
other_key, other_residue = w
his_name = his_key[0]
other_name = other_key[0]
#We only care about his this pass
if his_name != 'HIS':
continue
#HIS - HIS is already correct for what this pass does.
if other_name == 'HIS':
continue
other_protinated, other_unprotonated = other_residue.get_prot_and_deprot_instances()
other_prot_consolidated = other_residue.instances["PROTONATED"]
other_deprot_consolidated = other_residue.instances["DEPROTONATED"]
his_protinated, his_unprotonated = his_residue.get_prot_and_deprot_instances()
his_stuff = his_protinated + his_unprotonated
other_stuff = ((other_protinated, other_prot_consolidated), (other_unprotonated, other_deprot_consolidated))
#For every pairing of a HIS instance and another non HIS residue find the
# minimum interaction energy and update the interaction map accordingly.
#See https://docs.python.org/2/library/itertools.html#itertools.product
for his_instance, other_product in product(his_stuff, other_stuff):
other_instances, other_consolidated = other_product
energies = []
for other_instance in other_instances:
energy = self.interaction_energies[his_instance, other_instance]
energies.append(energy)
handled_interaction_pairs.add((his_instance, other_instance))
min_energy = min(energies)
self.add_interaction_energy_pair(his_instance, other_consolidated, min_energy)
#Clean out unused interaction energies
self.drop_interaction_pairs(handled_interaction_pairs)
for key, residue in self.residue_variables.items():
name = key[0]
if name == 'HIS':
continue
residue.instances = OrderedDict((k,v) for k,v in residue.instances.items() if "PROTONATED" in k)
def divide_his(self):
"""Here we divide HIS into two residues - HID, HIE - each with half the pKa value. We
have to set interaction energies between HIS and other residues and for HIS-HIS
interactions. Do this based on the values given in the paper"""
to_drop_his = set()
new_to_old_his = {}
handled_interaction_pairs = set()
items = list(self.residue_variables.items())
#Find all HIS and split them.
for key, residue in items:
name = key[0]
if name != 'HIS':
continue
old_instance_1 = residue.get_instance('1')
old_instance_2 = residue.get_instance('2')
old_instance_12 = residue.get_instance('1+2')
base_name = '_'+'_'.join(key[-2:])+'_'
to_drop_his.add(key)
hid = ResidueVariable("HId"+base_name)
name = "HId"+base_name+"PROTONATED"
hid_prot = ResidueInstance(True, name, energy=old_instance_1.energy)
name = "HId"+base_name+"DEPROTONATED"
hid_deprot = ResidueInstance(False, name)
hid.instances["PROTONATED"] = hid_prot
hid.instances["DEPROTONATED"] = hid_deprot
res_tuple = ("HId",)+key[-2:]
self.residue_variables[res_tuple] = hid
new_to_old_his[hid] = residue
hie = ResidueVariable("HIe"+base_name)
name = "HIe"+base_name+"PROTONATED"
hie_prot = ResidueInstance( True, name, energy=old_instance_2.energy)
name = "HIe"+base_name+"DEPROTONATED"
hie_deprot = ResidueInstance(False, name)
hie.instances["PROTONATED"] = hie_prot
hie.instances["DEPROTONATED"] = hie_deprot
res_tuple = ("HIe",)+key[-2:]
self.residue_variables[res_tuple] = hie
#Keep a mapping to the original residue object so we can look up
# interaction energies in the HIS/HIS interactions loop below.
new_to_old_his[hie] = residue
#Create interaction energies between newly created residues.
energy = old_instance_12.energy - old_instance_1.energy - old_instance_2.energy
self.add_interaction_energy_pair(hid_prot, hie_prot, energy)
self.add_interaction_energy_pair(hid_prot, hie_deprot, 0.0)
self.add_interaction_energy_pair(hid_deprot, hie_prot, 0.0)
self.add_interaction_energy_pair(hid_deprot, hie_deprot, sys.float_info.max)
#Delete residue variables from main map.
for key in to_drop_his:
del self.residue_variables[key]
#This loop is order dependent for HIS/HIS interactions. That is why some of the code paths that
#appear as though they should be duplicate or symmetrical are not
#and why we compare chain locations.
# (In case you were wondering why HIe <-> HId is not the same as
# HId <-> HIe.)
#See https://docs.python.org/2/library/itertools.html#itertools.product
for v, w in product(iter(self.residue_variables.items()), repeat=2):
his_key, his_residue = v
other_key, other_residue = w
his_name, his_chain, his_location = his_key
other_name, other_chain, other_location = other_key
if his_name not in ('HId', 'HIe'):
continue
his_location = int(his_location)
other_location = int(other_location)
his_prot = his_residue.instances["PROTONATED"]
his_deprot = his_residue.instances["DEPROTONATED"]
old_his = new_to_old_his[his_residue]
old_his_instance_1 = old_his.get_instance('1')
old_his_instance_2 = old_his.get_instance('2')
old_his_instance_12 = old_his.get_instance('1+2')
other_prot = other_residue.instances["PROTONATED"]
other_deprot = other_residue.instances["DEPROTONATED"]
#Handle create interaction with HId
if other_name == 'HId':
# HIS/HIS is order dependent.
if his_chain > other_chain or his_location >= other_location:
continue
old_other = new_to_old_his[other_residue]
old_other_instance_1 = old_other.get_instance('1')
old_other_instance_2 = old_other.get_instance('2')
old_other_instance_12 = old_other.get_instance('1+2')
if his_name == 'HIe':
energy = self.interaction_energies[old_his_instance_12, old_other_instance_12]
self.add_interaction_energy_pair(his_prot, other_prot, energy)
self.add_interaction_energy_pair(his_prot, other_deprot, 0.0)
self.add_interaction_energy_pair(his_deprot, other_prot, 0.0)
energy = (self.interaction_energies[old_his_instance_1, old_other_instance_2] -
self.interaction_energies[old_his_instance_1, old_other_instance_12] -
self.interaction_energies[old_his_instance_12, old_other_instance_2])
self.add_interaction_energy_pair(his_deprot, other_deprot, energy)
elif his_name == 'HId':
self.add_interaction_energy_pair(his_prot, other_prot, 0.0)
energy = self.interaction_energies[old_his_instance_12, old_other_instance_2]
self.add_interaction_energy_pair(his_prot, other_deprot, energy)
energy = (self.interaction_energies[old_his_instance_2, old_other_instance_12] -
self.interaction_energies[old_his_instance_12, old_other_instance_12])
self.add_interaction_energy_pair(his_deprot, other_prot, energy)
energy = self.interaction_energies[old_his_instance_2, old_other_instance_2]
self.add_interaction_energy_pair(his_deprot, other_deprot, energy)
combinations = self.get_interaction_combinations((old_his_instance_1, old_his_instance_2, old_his_instance_12),
(old_other_instance_1, old_other_instance_2, old_other_instance_12))
handled_interaction_pairs.update(combinations)
#Handle create interaction with HIe
elif other_name == 'HIe':
# HIS/HIS is order dependent.
if his_chain > other_chain or his_location >= other_location:
continue
old_other = new_to_old_his[other_residue]
old_other_instance_1 = old_other.get_instance('1')
old_other_instance_2 = old_other.get_instance('2')
old_other_instance_12 = old_other.get_instance('1+2')
if his_name == 'HIe':
self.add_interaction_energy_pair(his_prot, other_prot, 0.0)
energy = (self.interaction_energies[old_his_instance_12, old_other_instance_1] -
self.interaction_energies[old_his_instance_12, old_other_instance_12])
self.add_interaction_energy_pair(his_prot, other_deprot, energy)
energy = self.interaction_energies[old_his_instance_1, old_other_instance_12]
self.add_interaction_energy_pair(his_deprot, other_prot, energy)
energy = self.interaction_energies[old_his_instance_1, old_other_instance_1]
self.add_interaction_energy_pair(his_deprot, other_deprot, energy)
elif his_name == 'HId':
self.add_interaction_energy_pair(his_prot, other_prot, 0.0)
self.add_interaction_energy_pair(his_prot, other_deprot, 0.0)
self.add_interaction_energy_pair(his_deprot, other_prot, 0.0)
energy = (self.interaction_energies[old_his_instance_2, old_other_instance_1] +
self.interaction_energies[old_his_instance_12, old_other_instance_12] -
self.interaction_energies[old_his_instance_2, old_other_instance_12] -
self.interaction_energies[old_his_instance_12, old_other_instance_1])
self.add_interaction_energy_pair(his_deprot, other_deprot, energy)
combinations = self.get_interaction_combinations((old_his_instance_1, old_his_instance_2, old_his_instance_12),
(old_other_instance_1, old_other_instance_2, old_other_instance_12))
handled_interaction_pairs.update(combinations)
#Handle create interaction with non-HIS
else:
if his_name == 'HIe':
energy = (self.interaction_energies[old_his_instance_12, other_prot] -
self.interaction_energies[old_his_instance_1, other_prot])
self.add_interaction_energy_pair(his_prot, other_prot, energy)
energy = self.interaction_energies[old_his_instance_2, other_deprot]
self.add_interaction_energy_pair(his_prot, other_deprot, energy)
self.add_interaction_energy_pair(his_deprot, other_prot, 0.0)
energy = (self.interaction_energies[old_his_instance_1, other_deprot] +
self.interaction_energies[old_his_instance_2, other_deprot] -
self.interaction_energies[old_his_instance_12, other_deprot])
self.add_interaction_energy_pair(his_deprot, other_deprot, energy)
elif his_name == 'HId':
energy = self.interaction_energies[old_his_instance_1, other_prot]
self.add_interaction_energy_pair(his_prot, other_prot, energy)
energy = (self.interaction_energies[old_his_instance_12, other_deprot] -
self.interaction_energies[old_his_instance_2, other_deprot])
self.add_interaction_energy_pair(his_prot, other_deprot, energy)
energy = (self.interaction_energies[old_his_instance_1, other_prot] +
self.interaction_energies[old_his_instance_2, other_prot] -
self.interaction_energies[old_his_instance_12, other_prot])
self.add_interaction_energy_pair(his_deprot, other_prot, energy)
self.add_interaction_energy_pair(his_deprot, other_deprot, 0.0)
residue_combinations = self.get_interaction_combinations((old_his_instance_1, old_his_instance_2, old_his_instance_12),
(other_prot, other_deprot))
name_combinations = [(tup[0], tup[1]) for tup in residue_combinations]
handled_interaction_pairs.update(name_combinations)
#Clean out unused interaction energies
self.drop_interaction_pairs(handled_interaction_pairs)
def evaluate_energy(self, labeling, normal_form = True, pH=0.0):
"""Get the total energy for the residue in the state specified by labeling.
normal_form and pH are used for testing."""
energy = 0.0
if not normal_form:
ph_multiplier = 0.0
for instance in list(labeling.values()):
if instance.protonated:
ph_multiplier += 1.0
#See https://docs.python.org/2/library/itertools.html#itertools.combinations
for v, w in combinations(iter(self.residue_variables.items()), 2):
v_key, v_residue = v
w_key, w_residue = w
is_same_his = (v_key[1:] == w_key[1:] and v_key[0] in ("HId", "HIe") and w_key[0] in ("HId", "HIe"))
if is_same_his:
if labeling[v_residue].protonated and labeling[w_residue].protonated:
ph_multiplier -= 2.0
for v in self.residue_variables.values():
v_instance = labeling[v]
energy += v_instance.energyNF if normal_form else v_instance.energy
ie = self.normalized_interaction_energies if normal_form else self.interaction_energies
for v, w in combinations(iter(self.residue_variables.values()),2):
v_instance = labeling[v]
w_instance = labeling[w]
energy += ie[v_instance, w_instance]
if normal_form:
energy += self.normalized_constant_energy
else:
energy += pH*ph_multiplier
return energy
def instance_interaction_energy(self, instance, labeling, interaction_energy):
return sum(interaction_energy.get((instance, labeling[x]),0) for x in self.residue_variables.values())
def evaluate_energy_diff(self, residue, labeling, normal_form = False):
"""Returns the total energy difference between the deprontated and protonated
states for the supplied residue. (protonated total energy - deprotonated total energy)"""
ie = self.normalized_interaction_energies if normal_form else self.interaction_energies
prot_instance = residue.instances["PROTONATED"]
prot_energy = 0
for x in self.residue_variables.values():
prot_energy += ie.get((prot_instance, labeling[x]),0.0)
prot_energy += prot_instance.energyNF if normal_form else prot_instance.energy
deprot_instance = residue.instances["DEPROTONATED"]
deprot_energy = sum(ie.get((deprot_instance, labeling[x]),0.0) for x in self.residue_variables.values())
deprot_energy += deprot_instance.energyNF if normal_form else deprot_instance.energy
return prot_energy - deprot_energy
def evaluate_energy_diff_his(self, hie_residue, hid_residue, labeling, normal_form = False):
"""Returns the total energy differences between
1. HSE total energy and HSP total energy (HSP total energy - HSE total energy)
2. HSD total energy and HSP total energy (HSP total energy - HSD total energy)
in a tuple."""
# With both HIE and HID in protonated states:
# HSP energy adds:
# unary energy of all not-this-HIS residues in current state
# unary energy of HSE_protonated
# unary energy of HSD_protonated
# binary energy of all not-this-HIS residues in current state
# binary energy of all not-this-HIS (current state) with HSE_protonated
# binary energy of all not-this-HIS (current state) with HSD_protonated
#
# HSE energy adds:
# unary energy of all not-this-HIS residues in current state
# unary energy of HSE_protonated
# unary energy of HSD_deprotonated
# binary energy of all not-this-HIS residues in current state
# binary energy of all not-this-HIS (current state) with HSE_protonated
# binary energy of all not-this-HIS (current state) with HSD_deprotonated
#
# HSD energy adds:
# unary energy of all not-this-HIS residues in current state
# unary energy of HSE_deprotonated
# unary energy of HSD_protonated
# binary energy of all not-this-HIS residues in current state
# binary energy of all not-this-HIS (current state) with HSE_deprotonated
# binary energy of all not-this-HIS (current state) with HSD_protonated
#
# HSP-HSE has
# unary energy of HSD_protonated (EHd1) minus
# unary energy of HSD_deprotonated (EHd0)
# binary energy of all not-this-HIS (current state) with HSD_protonated (sum_ErHd_a1) minus
# binary energy of all not-this-HIS (current state) with HSD_deprotonated (sum_ErHd_a0)
#
# HSP-HSD has
# unary energy of HSE_protonated (EHe1) minus
# unary energy of HSE_deprotonated (EHe0)
# binary energy of all not-this-HIS (current state) with HSE_protonated (sum_ErHe_a1) minus
# binary energy of all not-this-HIS (current state) with HSE_deprotonated (sum_ErHe_a0)
labeling_copy = labeling.copy()
ie = self.normalized_interaction_energies if normal_form else self.interaction_energies
hie_prot_instance = hie_residue.instances["PROTONATED"]
hie_deprot_instance = hie_residue.instances["DEPROTONATED"]
hid_prot_instance = hid_residue.instances["PROTONATED"]
hid_deprot_instance = hid_residue.instances["DEPROTONATED"]
labeling_copy[hid_residue] = hid_prot_instance
labeling_copy[hie_residue] = hie_prot_instance
if normal_form:
EHd1 = hid_prot_instance.energyNF
EHd0 = hid_deprot_instance.energyNF
else:
EHd1 = hid_prot_instance.energy
EHd0 = hid_deprot_instance.energy
sum_ErHd_a1 = sum(ie.get((labeling_copy[x], hid_prot_instance), 0) for x in self.residue_variables.values())
sum_ErHd_a0 = sum(ie.get((labeling_copy[x], hid_deprot_instance), 0) for x in self.residue_variables.values())
if normal_form:
EHe1 = hie_prot_instance.energyNF
EHe0 = hie_deprot_instance.energyNF
else:
EHe1 = hie_prot_instance.energy
EHe0 = hie_deprot_instance.energy
sum_ErHe_a1 = sum(ie.get((labeling_copy[x], hie_prot_instance), 0) for x in self.residue_variables.values())
sum_ErHe_a0 = sum(ie.get((labeling_copy[x], hie_deprot_instance), 0) for x in self.residue_variables.values())
hsp_hse = EHd1 - EHd0 + sum_ErHd_a1 - sum_ErHd_a0
hsp_hsd = EHe1 - EHe0 + sum_ErHe_a1 - sum_ErHe_a0
return hsp_hse, hsp_hsd
def normalize(self, pH):
"""Finds and stores the normal form of all instance and interaction energies at the supplied pH value.
Instance energies are saved in instance.energyNF and interaction energies
are stored in self.interaction_energies"""
self.normalized_interaction_energies = self.interaction_energies.copy()
self.normalized_constant_energy = 0.0
#Add the pH to the instances.
for residue in self.residue_variables.values():
residue.instances["DEPROTONATED"].energyNF = residue.instances["DEPROTONATED"].energy
# TODO - I'm not sure why this is +pH....
residue.instances["PROTONATED"].energyNF = residue.instances["PROTONATED"].energy + math.log(10)*pH
rv = self.residue_variables
keys = list(rv.keys())
#Add the pH values to the HIS self interactions.
for v_key, w_key in combinations(keys, 2):
v_residue = rv[v_key]
w_residue = rv[w_key]
is_same_his = (v_key[1:] == w_key[1:] and v_key[0] in ("HId", "HIe") and w_key[0] in ("HId", "HIe"))
if is_same_his:
v_prot = v_residue.instances["PROTONATED"]
w_prot = w_residue.instances["PROTONATED"]
self.normalized_interaction_energies[v_prot, w_prot] -= (2.0*math.log(10)*pH)
self.normalized_interaction_energies[w_prot, v_prot] -= (2.0*math.log(10)*pH)
#Normalize the interaction energies.
for v_key, w_key in permutations(keys, 2):
v_residue = rv[v_key]
w_residue = rv[w_key]
for v_instance in v_residue.instances.values():
w_instances = list(w_residue.instances.values())
min_energy = min(self.normalized_interaction_energies[v_instance, w_instance]
for w_instance in w_instances)
v_instance.energyNF += min_energy
if min_energy != sys.float_info.max:
for w_instance in w_instances:
self.normalized_interaction_energies[v_instance, w_instance] -= min_energy
self.normalized_interaction_energies[w_instance, v_instance] -= min_energy
#Normalize the instance energies.
for residue in self.residue_variables.values():
min_energy = min(instance.energyNF for instance in residue.instances.values())
self.normalized_constant_energy += min_energy
if min_energy != sys.float_info.max:
for instance in residue.instances.values():
instance.energyNF -= min_energy
def energy_at_pH(self, pH):
"""Create a representation of the protein energy at the specified pH
Used primarily for testing."""
self.interaction_energies_for_ph = self.interaction_energies.copy()
for residue in self.residue_variables.values():
residue.instances["DEPROTONATED"].energy_with_ph = residue.instances["DEPROTONATED"].energy
residue.instances["PROTONATED"].energy_with_ph = residue.instances["PROTONATED"].energy + math.log(10)*pH
for v, w in combinations(iter(self.residue_variables.items()), 2):
v_key, v_residue = v
w_key, w_residue = w
is_same_his = (v_key[1:] == w_key[1:] and v_key[0] in ("HId", "HIe") and w_key[0] in ("HId", "HIe"))
if is_same_his:
v_prot = v_residue.instances["PROTONATED"]
w_prot = w_residue.instances["PROTONATED"]
self.interaction_energies_for_ph[v_prot, w_prot] -= (2.0*math.log(10)*pH)
self.interaction_energies_for_ph[w_prot, v_prot] -= (2.0*math.log(10)*pH)
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