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name: docking-and-structure description: "Handle DeepChem protein-ligand docking, binding pocket discovery, complex structure featurization, material featurizers, DFT surfaces, and optional dependency triage." disable-model-invocation: true metadata: disco-role: operating license: MIT

DeepChem Docking and Structure

Use this sub-skill when a user asks about protein-ligand complexes, binding pockets, docking poses/scores, PDB/PDBQT/SDF structure inputs, complex featurizers, material/crystal featurizers, DFT/XC models, or missing optional structural dependencies.

Route First

• For molecule fingerprints, graph featurizers, descriptors, or ordinary SMILES-only featurization, use ../featurization/ instead.
• For PDBBind, MolNet dataset loading, splits, transformers, or DiskDataset handling, use ../data-and-molnet/ unless the question is specifically about structure featurizers or docking inputs.
• For model training loops, metrics, hyperparameters, or checkpointing, use ../model-training/ after choosing the structure featurizer or docking output here.
• Do not promise docking in a base DeepChem install. Treat Vina, GNINA, mdtraj, pymatgen, matminer, torch, dqc, OpenMM/PDBFixer, CUDA, and docking binaries as environment gates.

Fast Decisions

• Need candidate pockets only: use deepchem.dock.ConvexHullPocketFinder(scoring_model=None, pad=5.0) and validate a protein structure can be loaded.
• Need actual poses/scores: use deepchem.dock.VinaPoseGenerator or deepchem.dock.GninaPoseGenerator, then wrap with deepchem.dock.Docker only when a generic pose/scoring pipeline is needed.
• Need fixed complex features for ML: choose AtomicConvFeaturizer, RdkitGridFeaturizer, ContactCircularFingerprint, SplifFingerprint, or voxelizers based on the downstream model shape.
• Need pocket residue summaries: use BindingPocketFeaturizer, but require mdtraj and pockets from a pocket finder.
• Need crystal/material features: choose composition featurizers for formulas/compositions and structure featurizers for pymatgen.core.Structure objects.
• Need DFT/XC surfaces: confirm torch and DFT quantum chemistry extras before importing DFT modules or creating XCNNSCF/XCModel workflows.

Required References

• references/structure-workflows.md: choose pocket finding, docking, complex featurization, material featurization, or DFT.
• references/api-reference.md: key DeepChem APIs, expected inputs, outputs, and dependency notes.
• references/optional-dependencies.md: dependency and binary gates before running structural workflows.
• references/troubleshooting.md: common failures for formats, hydrogens, sanitization, optional imports, GPU/CUDA, and DFT extras.

Bundled Helper

Run python scripts/check_structure_dependencies.py from this sub-skill directory, or copy the script into any project, to report available Python packages and external vina/gnina commands without running docking.