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specialized-molecular-tasks

specialized-molecular-tasks

Use this Chemprop sub-skill for reaction SMILES, reaction-plus-molecule multicomponent data, atom/bond targets, constrained MolAtomBond prediction, spectral tasks, and specialized descriptor/feature schemas.

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Documentation de la Skill

GitHub

name: specialized-molecular-tasks description: "Use this Chemprop sub-skill for reaction SMILES, reaction-plus-molecule multicomponent data, atom/bond targets, constrained MolAtomBond prediction, spectral tasks, and specialized descriptor/feature schemas." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

Chemprop Specialized Molecular Tasks

Use this sub-skill when a Chemprop request needs specialized molecular schemas or flags rather than ordinary molecule-level training/prediction.

Route Here For

  • Reaction property models using atom-mapped reaction SMILES, --reaction-columns, and --rxn-mode / --reaction-mode.
  • Multicomponent workflows combining reactions and molecule SMILES such as reaction-plus-solvent models.
  • MolAtomBond training where molecule, atom, and/or bond targets use --mol-target-columns, --atom-target-columns, or --bond-target-columns.
  • Constrained atom/bond prediction with --constraints-path and --constraints-to-targets.
  • Spectral task setup with --task-type spectral, sid/earthmovers style metrics, and positivity/normalization caveats.
  • Specialized feature inputs whose component indices, atom ordering, bond ordering, or scaling flags interact with the schema.

Route Elsewhere

  • Use ../training-cli/ for ordinary chemprop train options, split policies, checkpoints, losses, metrics, and generic regression/classification workflows.
  • Use ../prediction-fingerprints/ for general chemprop predict and chemprop fingerprint mechanics after the specialized columns are known.
  • Use ../data-featurization/ for CSV/NPZ validation, molecule featurizer choices, descriptors, and general feature-file shape checks.
  • Use ../python-api-modeling/ for low-level Python API composition of models, dataloaders, Lightning modules, and custom predictors.

Quick Starts

Reaction Training

chemprop train \
  -i reactions.csv \
  --reaction-columns rxn_smiles \
  --rxn-mode REAC_DIFF_BALANCE \
  --target-columns yield \
  --keep-h \
  --epochs 50 \
  --save-dir chemprop_rxn_model

Use the same reaction columns and reaction mode at prediction/fingerprint time as were used for training.

Reaction Plus Solvent

chemprop train \
  -i reaction_solvent.csv \
  --reaction-columns rxn_smiles \
  --smiles-columns solvent_smiles \
  --split-key-molecule 1 \
  --message-hidden-dim 300 200 \
  --depth 3 5 \
  --target-columns rate \
  --save-dir chemprop_rxn_solvent_model

For mixed reaction+molecule inputs, component order is the order implied by reaction columns plus SMILES columns. Match that order when giving per-component feature paths, message dimensions, and prediction inputs.

Atom/Bond Targets

chemprop train \
  -i atom_bond_targets.csv \
  --smiles-columns smiles \
  --mol-target-columns mol_y \
  --atom-target-columns atom_charge atom_shift \
  --bond-target-columns bond_order \
  --reorder-atoms \
  --epochs 50 \
  --save-dir chemprop_mab_model

Atom and bond target cells must be parseable Python/JSON-like lists. Atom target list order follows RDKit atom order unless atom maps are present and --reorder-atoms is used; bond target list order follows the input molecule bond order.

References

  • references/reaction-multicomponent.md covers reaction SMILES, --rxn-mode, reaction-plus-solvent inputs, and per-component model dimensions.
  • references/mol-atom-bond.md covers MolAtomBond target schemas, constraints, bounded targets, extra atom/bond descriptors, and prediction ordering.
  • references/spectral-and-special-tasks.md covers spectral tasks, special task/loss choices, and feature/descriptor interactions.
  • references/troubleshooting.md covers atom-map ordering, constraint mapping, reaction modes, multicomponent dimensions, and constrained output issues.
  • scripts/chemprop_specialized_command_builder.py builds command arrays and shell snippets for reaction, multicomponent, MolAtomBond, constrained, and spectral workflows.

Practical Guardrails

  • Prefer --rxn-mode in generated commands; --reaction-mode is accepted as an alias, but --rxn-mode matches the parser destination.
  • Do not combine --mpn-shared with different --message-hidden-dim or --depth values; mixed reaction+molecule data also rejects shared MPNNs.
  • Do not use --use-cuikmolmaker-featurization when --reorder-atoms is required for mapped atom target order.
  • Treat reaction extra atom/bond features cautiously: the reaction graph featurizer warns that extra atom and bond features are unsupported for reaction components.
  • For MolAtomBond constraints, --constraints-to-targets names must be selected from the atom/bond target column names passed in the same command, in the same order as the constraints CSV columns.
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