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
def setup_design(numcores, conf_spaces, eps, num_seqs, algo_index, data):
"""setup_design
Set up the classes required to run the design
conf_spaces: A dictionary containing protein, ligand, and complex conf
spaces along with force-field parameters
num_seqs: The number of top sequences we want (usually 5)
Returns a BBKStar instance, ready to run
"""
parallelism = osprey.Parallelism(cpuCores=numcores)
data['numCpus'] = numcores
# how should we compute energies of molecules?
minimizingEcalc = osprey.EnergyCalculator(conf_spaces['complex'],
conf_spaces['ffparams'],
parallelism=parallelism,
isMinimizing=True)
# record the seq tree file name
data['seq_tree_name'] = data["design name"] + "seqTree.tree"
# configure basic inputs for SHARKStar
design = osprey.BBKStar(
conf_spaces['protein'],
conf_spaces['ligand'],
conf_spaces['complex'],
numBestSequences=num_seqs,
epsilon=
eps, # you proabably want something more precise in your real designs
showPfuncProgress=True,
maxSimultaneousMutations=9,
numConfsPerBatch=BBK_BATCH_SIZE,
maxNumConfsPerBatch=8,
#printSequenceTree=data["seq_tree_name"]
)
# configure SHARK*/BBK* inputs for each conf space
configure_bbk(design, minimizingEcalc, "shark", data["design name"],
algo_index)
return design
ligand = osprey.Strand(mol, templateLib=templateLib, residues=['A38', 'A58'])
ligand.flexibility['A41'].setLibraryRotamers(
osprey.WILD_TYPE).addWildTypeRotamers().setContinuous()
ligand.flexibility['A42'].setLibraryRotamers(
osprey.WILD_TYPE, 'THR', 'LYS').addWildTypeRotamers().setContinuous()
ligand.flexibility['A45'].setLibraryRotamers(
osprey.WILD_TYPE).addWildTypeRotamers().setContinuous()
ligand.flexibility['A46'].setLibraryRotamers(
osprey.WILD_TYPE).addWildTypeRotamers().setContinuous()
# 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)
# configure PAStE
paste = osprey.Paste(
complexConfSpace,
numPDBs=15,
epsilon=
0.68, # you proabably want something more precise in your real designs
useWindowCriterion=True,
writeSequencesToConsole=True,
writeSequencesToFile='paste.results.tsv',
mutFile='mut.txt')
protein.flexibility[resNumsP[i]].setLibraryRotamers(
*AATypeOptions[posP[i]]).addWildTypeRotamers().setContinuous()
# make the conf space for the protein
confSpaceP = osprey.ConfSpace(protein)
# make the conf space for the ligand
confSpaceL = osprey.ConfSpace(ligand)
# make the conf space for the protein+ligand complex
confSpace = 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)
numCPUs = 40
parallelism = osprey.Parallelism(cpuCores=numCPUs)
ecalc = osprey.EnergyCalculator(confSpace, ffparams, parallelism=parallelism)
rigidEcalc = osprey.EnergyCalculator(confSpace,
ffparams,
parallelism=parallelism,
isMinimizing=False)
# how should we define energies of conformations?
eref = osprey.ReferenceEnergies(confSpace, ecalc)
erefRigid = osprey.ReferenceEnergies(confSpace, rigidEcalc)
confECalc = osprey.ConfEnergyCalculator(confSpace,
ecalc,
referenceEnergies=eref)
confRigidECalc = osprey.ConfEnergyCalculator(confSpace,
rigidEcalc,
referenceEnergies=eref)
import osprey
osprey.start()
# what kind of hardware do we have?
parallelism = osprey.Parallelism(cpuCores=2)
# or use GPUs
gpuPrallelism = osprey.Parallelism(cpuCores=2, gpus=1, streamsPerGpu=1)
# choose a forcefield
ffparams = osprey.ForcefieldParams(osprey.Forcefield.AMBER)
ffparams.solvationForcefield = osprey.SolvationForcefield.EEF1 # this is the default
# or turn off solvation energy
#ffparams.solvationForcefield = None
# choose a template library
# (see templateLibrary.py for more detailed examples of custom template libraries)
templateLib = osprey.TemplateLibrary()
# load a molecule
mol = osprey.readPdb('1CC8.ss.pdb')
# define the protein strand
protein = osprey.Strand(mol, residues=['A2', 'A30'])
protein.flexibility['A2'].setLibraryRotamers('ALA', 'GLY')
protein.flexibility['A3'].setLibraryRotamers(osprey.WILD_TYPE, 'VAL',
'ARG').setContinuous(10)
protein.flexibility['A4'].setLibraryRotamers(
osprey.WILD_TYPE).addWildTypeRotamers()
def maked_emat(config, fo):
"""Save complex energy matrix based on dictionary"""
confspaces = loadd_confspaces(config)
parallelism = osprey.Parallelism(cpuCores=multiprocessing.cpu_count())
makeo_emat(confspaces["complex"], confspaces["ffparams"], parallelism, fo)
def make_emat(fi, fo):
"""Save complex energy matrix based on TOML file"""
confspaces = load_confspaces(fi)
parallelism = osprey.Parallelism(cpuCores=multiprocessing.cpu_count())
makeo_emat(confspaces["complex"], confspaces["ffparams"], parallelism, fo)
