Small Molecule Pipeline¶
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from openpharmmdflow.pipeline.sm.pipeline_settings import *
from openpharmmdflow.pipeline.sm.pipeline import SmallMoleculePipeline
import nglview
First we create the pipeline config settings object
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# Any file supported by openff-toolkit or cif
inputA = {"name": "ibuprofen", "path": "ibuprofen.sdf"}
inputB = {"name": "ibuprofen1", "path": "ibuprofen.sdf"}
sm_inputA = SmallMoleculePipelineInputConfig(**inputA)
sm_inputB = SmallMoleculePipelineInputConfig(**inputB)
settings = {
# Not used right now
"work_dir": "/home/mmh/Projects/OpenPharmMDFlow/experiments/sm/scratch",
"inputs": [sm_inputA, sm_inputB],
"prep_config": SmallMoleculePipelinePrepConfig(
bespokefit_config=BespokefitConfig(
bespoke_workflow_factory_config=BespokeWorkflowFactoryConfig(),
bespoke_executor_config=BespokeExecutorConfig(),
mol_to_bespoke="ibuprofen",
)
),
"pack_config": SmallMoleculePipelinePackConfig(
molecule_names=["ibuprofen", "ibuprofen1"],
number_of_copies=[5, 5],
target_density=0.1,
),
"parameterize_config": SmallMoleculePipelineParameterizeConfig(),
"simulate_config": SmallMoleculePipelineSimulateConfig(),
"analyze_config": SmallMoleculePipelineAnalyzeConfig(),
}
sm_config = SmallMoleculePipelineConfig(**settings)
Now we can create our pipeline object¶
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smp = SmallMoleculePipeline(sm_config)
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smp.load()
Prep will run bespoke fit
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# smp.prep()
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smp.pack()
We can view the topology
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smp.topology.to_file("system.pdb")
nglview.show_structure_file("system.pdb")
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
Cell In[11], line 1
----> 1 smp.topology.to_file("system.pdb")
2 nglview.show_structure_file("system.pdb")
AttributeError: 'SmallMoleculePipeline' object has no attribute 'topology'
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smp.parameterize()
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smp.interchange.visualize("nglview")
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smp.simulate()
Starting simulation
Step, volume (nm^3)
0 34.254
500 33.93
1000 32.046
1500 31.12
2000 31.412
2500 32.509
3000 32.153
3500 31.297
4000 27.585
4500 28.9
Elapsed time: 0.60 seconds
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