confgen_failure.parameter_overrides["buffered"] = {"hidden": True}
# Search torsions & select best conformer for each
torsgenCube = ParallelGenerateTorsionalConfs('torsional_conf_gen')
torsgenCube.promote_parameter(
'num_points',
required=True,
title='Number of torsional conformers to generate.',
description="""The number of evenly spaced torsion angles to sample
when generating torsional conformers.""")
torsgenCube.parameter_overrides["split_confs"] = {"hidden": True}
torsgenCube.parameter_overrides["best_conf"] = {"hidden": True}
# Conformer/torsion cube group
group = ParallelCubeGroup(cubes=[confgenCube, torsgenCube])
job.add_group(group)
# Fast QM optimization with hf3c to get approximate geometry
hf3cCube = HiddenParamParallelPsi4EnergyCalculation('hf3c_precalc')
hf3cCube.set_parameters(spe_method='hf3c',
spe_basis='minix',
opt_method='hf3c',
opt_basis='minix',
geom_maxiter=200)
# Full QM optimization & SP for energy
psi4EnergyCube = ParallelPsi4EnergyCalculation(
'parallel_psi4_energy_calculation')
psi4EnergyCube.set_parameters(geom_maxiter=200)
psi4EnergyCube.promote_parameter('spe_method', required=True)
psi4EnergyCube.promote_parameter('spe_basis', required=True)
# NPT Equilibration stage 4
equil4 = ParallelMDNptCube('equil4', title='Equilibration IV')
equil4.modify_parameter(equil4.time, promoted=False, default=0.1)
equil4.promote_parameter("hmr", promoted_name="HMR", default=True)
equil4.modify_parameter(equil4.restraints,
promoted=False,
default="ca_protein or (noh ligand)")
equil4.modify_parameter(equil4.restraintWt, promoted=False, default=0.1)
equil4.set_parameters(trajectory_interval=0.0)
equil4.set_parameters(reporter_interval=0.002)
equil4.set_parameters(suffix='equil4')
equil4.promote_parameter("md_engine", promoted_name="md_engine")
md_group = ParallelCubeGroup(
cubes=[minComplex, warmup, equil1, equil2, equil3, equil4, prod])
job.add_group(md_group)
ofs = DatasetWriterCube('ofs', title='MD Out')
ofs.promote_parameter("data_out",
promoted_name="out",
title="MD Out",
description="MD Dataset out")
fail = DatasetWriterCube('fail', title='Failures')
fail.promote_parameter("data_out",
promoted_name="fail",
title="Failures",
description="MD Dataset Failures out")
# This Cube is necessary for the correct working of collection and shard
coll_close = CollectionSetting("CloseCollection", title="Close Collection")
promoted_name="in",
title="MD Input Dataset",
description="MD Input Dataset")
# This Cube is necessary for the correct work of collection and shard
coll_open = CollectionSetting("OpenCollection", title="Open Collection")
coll_open.set_parameters(open=True)
trajCube = ParallelTrajToOEMolCube("TrajToOEMolCube",
title="Trajectory To OEMols")
IntECube = ParallelTrajInteractionEnergyCube("TrajInteractionEnergyCube",
title="MM Energies")
PBSACube = ParallelTrajPBSACube("TrajPBSACube", title="PBSA Energies")
trajproc_group = ParallelCubeGroup(cubes=[trajCube, IntECube, PBSACube])
job.add_group(trajproc_group)
confGather = ConformerGatheringData("Gathering Conformer Records",
title="Gathering Conformer Records")
catLigTraj = ParallelConfTrajsToLigTraj("ConfTrajsToLigTraj",
title="Combine Pose Trajectories")
catLigMMPBSA = ParallelConcatenateTrajMMPBSACube(
'ConcatenateTrajMMPBSACube', title="Concatenate MMPBSA Energies")
clusCube = ParallelClusterOETrajCube("ClusterOETrajCube", title="Clustering")
clusPop = ParallelClusterPopAnalysis('ClusterPopAnalysis',
title="Clustering Analysis")
clusOEMols = ParallelMakeClusterTrajOEMols('MakeClusterTrajOEMols',
title="Per-Cluster Analysis")
prepDataset = ParallelTrajAnalysisReportDataset('TrajAnalysisReportDataset',
title="Analysis Report")
report_gen = ParallelMDTrajAnalysisClusterReport(
promoted_name="in",
title="MD Input Dataset",
description="MD Input Dataset")
# This Cube is necessary for the correct work of collection and shard
coll_open = CollectionSetting("OpenCollection", title="Open Collection")
coll_open.set_parameters(open=True)
trajCube = ParallelTrajToOEMolCube("TrajToOEMolCube",
title="Trajectory To OEMols")
IntECube = ParallelTrajInteractionEnergyCube("TrajInteractionEnergyCube",
title="MM Energies")
PBSACube = ParallelTrajPBSACube("TrajPBSACube", title="PBSA Energies")
trajproc_group = ParallelCubeGroup(cubes=[trajCube, IntECube, PBSACube])
job.add_group(trajproc_group)
# This Cube is necessary for the correct working of collection and shard
coll_close = CollectionSetting("CloseCollection", title="Close Collection")
coll_close.set_parameters(open=False)
check_rec = ParallelRecordSizeCheck("Record Check Success",
title="Record Check Success")
ofs = DatasetWriterCube('ofs', title='MD Out')
ofs.promote_parameter("data_out",
promoted_name="out",
title="MD Out",
description="MD Dataset out")
fail = DatasetWriterCube('fail', title='Failures')
