def make_pfunc_factory(conf_space, ffparams, numcores, eps, algo_index,
emat_cache_pattern, data):
"""make_pfunc_factory
Return a PartitionFunctionFactory object for the input confspace, which we can use to make
partition functions for various sequences.
"""
parallelism = osprey.Parallelism(cpuCores=numcores)
data['numCpus'] = numcores
# how should we compute energies of molecules?
minimizingEcalc = osprey.EnergyCalculator(conf_space,
ffparams,
parallelism=parallelism,
isMinimizing=True)
# Compute reference energies
eref = osprey.ReferenceEnergies(conf_space, minimizingEcalc)
#Create a minimizing energy calculator
confEcalcMinimized = osprey.ConfEnergyCalculator(conf_space,
minimizingEcalc,
referenceEnergies=eref)
# we need rigid energies too for many algorithms
rigidEcalc = osprey.SharedEnergyCalculator(minimizingEcalc,
isMinimizing=False)
rigidConfEcalc = osprey.ConfEnergyCalculatorCopy(confEcalcMinimized,
rigidEcalc)
confEcalcRigid = rigidConfEcalc
# Specify the type of partitionFunction
if ALGO_LIST[algo_index] == 'SHARK': # using SHARK*
impt_ecalc = rigidConfEcalc
choose_markstar = False
elif ALGO_LIST[algo_index] == 'MARK': # using MARK*
impt_ecalc = rigidConfEcalc
choose_markstar = True
else: # using Gradient descent pfunc
impt_ecalc = None
choose_markstar = False
pfuncFactory = osprey.PartitionFunctionFactory(
conf_space,
confEcalcMinimized,
emat_cache_pattern,
confUpperBoundcalc=impt_ecalc,
useMARK=choose_markstar)
# Set cache pattern
pfuncFactory.setCachePattern(
'%s/emat.%s.%s' % (XTMP_DIR, emat_cache_pattern, data["design name"]))
print('Cache pattern: %s/emat.%s.%s' %
(XTMP_DIR, emat_cache_pattern, data["design name"]))
return pfuncFactory
# make the conf space for the ligand
ligandConfSpace = osprey.ConfSpace(ligand)
# make the conf space for the protein+ligand complex
complexConfSpace = osprey.ConfSpace([protein, ligand])
# how should we compute energies of molecules?
# (give the complex conf space to the ecalc since it knows about all the templates and degrees of freedom)
parallelism = osprey.Parallelism(cpuCores=4)
minimizingEcalc = osprey.EnergyCalculator(complexConfSpace,
ffparams,
parallelism=parallelism,
isMinimizing=True)
# BBK* needs a rigid energy calculator too, for multi-sequence bounds on K*
rigidEcalc = osprey.SharedEnergyCalculator(minimizingEcalc, isMinimizing=False)
# how should we define energies of conformations?
def confEcalcFactory(confSpace, ecalc):
eref = osprey.ReferenceEnergies(confSpace, ecalc)
return osprey.ConfEnergyCalculator(confSpace,
ecalc,
referenceEnergies=eref)
# configure BBK*
bbkstar = osprey.BBKStar(
proteinConfSpace,
ligandConfSpace,
complexConfSpace,
def configure_bbk(instance, minimizingEcalc, type_string, id_obj, algo_index):
"""Configure the energy calculators and info for BBK* instance"""
for info in instance.confSpaceInfos():
# Compute reference energies
eref = osprey.ReferenceEnergies(info.confSpace, minimizingEcalc)
#Create a minimizing energy calculator
info.confEcalcMinimized = osprey.ConfEnergyCalculator(
info.confSpace, minimizingEcalc, referenceEnergies=eref)
# BBK* needs rigid energies too
rigidEcalc = osprey.SharedEnergyCalculator(minimizingEcalc,
isMinimizing=False)
rigidConfEcalc = osprey.ConfEnergyCalculatorCopy(
info.confEcalcMinimized, rigidEcalc)
info.confEcalcRigid = rigidConfEcalc
# Specify the input for the partition functions. Providing the confUpperBoundcalc turns on SHARK*
if ALGO_LIST[algo_index] == 'SHARK':
impt_ecalc = rigidConfEcalc
choose_markstar = False
elif ALGO_LIST[algo_index] == 'MARK':
impt_ecalc = rigidConfEcalc
choose_markstar = True
else:
impt_ecalc = None
choose_markstar = False
info.pfuncFactory = osprey.PartitionFunctionFactory(
info.confSpace,
info.confEcalcMinimized,
info.id,
confUpperBoundcalc=impt_ecalc,
useMARK=choose_markstar)
# Set cache pattern
info.pfuncFactory.setCachePattern('%s/emat.%s.%s' %
(XTMP_DIR, info.id, id_obj))
print('Cache pattern: %s/emat.%s.%s' % (XTMP_DIR, info.id, id_obj))
# compute the energy matrices
info.ematMinimized = info.pfuncFactory.getOrMakeEmat(
info.confEcalcMinimized, 'minimized')
info.ematRigid = info.pfuncFactory.getOrMakeEmat(
info.confEcalcRigid, 'rigid')
# Updating energy matrix?
#info.ematCorrected =\
#osprey.c.ematrix.UpdatingEnergyMatrix(
#info.confSpace,
#info.ematMinimized,
#info.confEcalcMinimized
#)
# how should confs be ordered and searched? (don't forget to capture emat by using a defaulted argument)
def makeAStar_min(rcs, emat=info.ematMinimized):
return osprey.AStarTraditional(emat, rcs, showProgress=True)
info.confSearchFactoryMinimized =\
osprey.KStar.ConfSearchFactory(makeAStar_min)
def makeRigidAStar(rcs, emat=info.ematRigid):
return osprey.AStarTraditional(emat, rcs, showProgress=True)
info.confSearchFactoryRigid =\
osprey.KStar.ConfSearchFactory(makeRigidAStar)
# make the conf space for the ligand
ligandConfSpace = osprey.ConfSpace(ligand)
# make the conf space for the protein+ligand complex
complexConfSpace = osprey.ConfSpace([protein, ligand])
# how should we compute energies of molecules?
# (give the complex conf space to the ecalc since it knows about all the templates and degrees of freedom)
parallelism = osprey.Parallelism(cpuCores=4)
ecalc = osprey.EnergyCalculator(complexConfSpace,
ffparams,
parallelism=parallelism)
# MARK* needs a rigid energy calculator too
ecalcRigid = osprey.SharedEnergyCalculator(ecalc, isMinimizing=False)
# configure K*
kstar = osprey.KStar(
proteinConfSpace,
ligandConfSpace,
complexConfSpace,
epsilon=
0.95, # you proabably want something more precise in your real designs
writeSequencesToConsole=True,
writeSequencesToFile='kstar.results.tsv')
# configure K* inputs for each conf space
for info in kstar.confSpaceInfos():
# how should we define energies of conformations?