By-molecule ForceBalance Experiment
This page contains an overview of the projects/studies aimed at improving the FF optimization process in general. Specific features and decisions made for each FF optimization cycle should be recorded in Force Field Releases.
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Experiment |
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Select single molecule and run FB optimization fitting only TIG0 (general torsion parameter) | The selected target is: -General torsion ID with wildcards in every bond and atom
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Select single molecule and run FB optimization fitting only TIG-fit0 Smirks: [:1]~[#6X3:2]~!@[#6X3:3]~[:4] | Issues with parameter matching |
Iterate through single molecule and run FB optimization fitting only TIG-fit0 Smirks for |
Workflow: Code is here: Workflow:
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Torsion Barrier versus k value:
A comparison of the torsion barrier and the kvalue. The torsion barrier is determined by an algorithm which checks the slope of a torsion drive record and pulls the maximum. The k value is determined by a single molecule force balance run that fits a general torsion which is applied 4x fold around a single torsion.
Substituted Phenyl Dataset:
OpenFF 1.2.0 Training Datasets and Substituted Phenyl Dataset:
Perform steric filtering on molecules:
Determine the torsion ID using the entry_label from the metadata in the targets folder.
import qcportal as ptl
client = ptl.FractalClient()
ds = client.get_collection("TorsionDriveDataset", "OpenFF Substituted Phenyl Set 1")
ds.status(status="COMPLETE")
entry = ds.get_entry(entry_label)
entry.object_map['default']
Additional targets in fitting experiment:
Original fitting experiment used only the gen 2 torsions and the substituted phenyl dataset. These plots include also the primary benchmark dataset, group1 torsions, and the Rowley dataset.
Fitting experiment for non-ring torsions:
Steric filtered:
Non-steric filtered:
Fitting experiment for general C~C torsion:
Steric filtered:
Non-steric filtered: