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name: motif-scaffolding description: "Design scaffolds around fixed motifs or active sites with RFdiffusion contigs, target-chain chain breaks, sequence/structure masking, and checkpoint overrides." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

Motif Scaffolding

Use this sub-skill when a user needs RFdiffusion to scaffold motif residues from an input PDB, preserve or redesign parts of a motif, include a fixed target chain, or choose a motif-specific checkpoint.

Route Here

• Scaffold one or more residue spans from an input PDB into a new monomeric scaffold.
• Build around catalytic/active-site residues, especially tiny motifs that drift with the base checkpoint.
• Add a fixed target/receptor chain to a motif-scaffolding contig using /0 chain-break syntax.
• Mask motif sequence with contigmap.inpaint_seq or motif structure with contigmap.inpaint_str.
• Constrain generated-chain length with contigmap.length.
• Choose ActiveSite_ckpt.pt, Complex_base_ckpt.pt, or automatic inpaint checkpoints.

Route Elsewhere

• For PPI binder hotspot selection with ppi.hotspot_res, route to the binder-design sub-skill.
• For cyclic, dihedral, tetrahedral, or symmetric motif scaffolding, route to the symmetric-oligomers sub-skill.
• For scaffold-guided secondary-structure fold conditioning, route to ../scaffold-guided-design/SKILL.md.
• For generic unconditional monomer generation, route to ../unconditional-generation/SKILL.md.

Inputs To Confirm

• inference.input_pdb: a PDB containing every referenced motif, target, and ligand/substrate residue.
• Motif residue identity: chain letters and inclusive residue numbers exactly as they appear in the PDB.
• Generated residue ranges: numeric ranges such as 10-40; RFdiffusion samples a value each design.
• Chain layout: whether a target chain should remain separate using /0 with a required space after 0.
• Output prefix: a writable prefix such as $OUT_DIR/motif_run.
• Model weights: default model directory, or explicit checkpoint path for active-site/complex use.
• Number of designs and optional deterministic/restart behavior.

Core Command Shape

Run from an RFdiffusion installation where rfdiffusion imports and the installed run_inference.py launcher is available:

run_inference.py \
  inference.output_prefix="$OUT_DIR/motif_scaffold" \
  inference.input_pdb="$INPUT_PDB" \
  inference.model_directory_path="$MODEL_DIR" \
  inference.num_designs=10 \
  'contigmap.contigs=[10-40/A163-181/10-40]'

Keep Hydra list-like overrides in single quotes. Do not let the shell interpret brackets, commas, spaces, or embedded quotes.

Contig Decisions

• Use A10-25 for residues 10 through 25 on chain A from inference.input_pdb.
• Use 5-15 for a generated segment whose length is sampled independently each design.
• Use 5-15/A10-25/30-40 to build N-terminal and C-terminal scaffold segments around one motif.
• Use A25-109/0 0-70/B17-29/0-70 to keep target chain A25-109 separate from a generated chain that contains motif B17-29.
• Use contigmap.length=70-120 when variable segment ranges must produce a generated chain in a total length window.
• Use multiple motif fragments in one generated chain as 10-100/A1083-1083/10-100/A1051-1051/10-100.

See references/contig-patterns.md for validated patterns and interpretation rules.

Standard Workflows

• Simple motif scaffolding: input PDB plus contig such as 10-40/A163-181/10-40.
• Motif sequence redesign: add contigmap.inpaint_seq for nonessential motif residues that should have masked amino-acid identity.
• Target-aware motif scaffolding: include the fixed target/receptor as a receptor block before /0 and use a complex checkpoint when needed.
• Active-site/enzyme scaffolding: use several single-residue motif fragments and usually inference.ckpt_override_path=$MODEL_DIR/ActiveSite_ckpt.pt.
• Structure masking: use contigmap.inpaint_str when coordinates for selected input residues should be hidden while preserving sequence context.

Detailed commands are in references/workflows.md.

Checkpoint Selection

• Default motif scaffolding normally uses $MODEL_DIR/Base_ckpt.pt via RFdiffusion's automatic checkpoint choice.
• contigmap.inpaint_seq, contigmap.inpaint_str, or contigmap.provide_seq triggers an inpaint-capable checkpoint automatically unless inference.ckpt_override_path is set.
• Fixed target/complex motif tasks can use inference.ckpt_override_path=$MODEL_DIR/Complex_base_ckpt.pt when the complex-finetuned model is desired.
• Tiny active-site motifs should use inference.ckpt_override_path=$MODEL_DIR/ActiveSite_ckpt.pt to reduce motif drift.
• If overriding, verify checkpoint compatibility with the provided contig and masks; incompatible model/config features can crash at inference.

Sequence And Structure Masking

• contigmap.inpaint_seq masks amino-acid identities for selected input residues, letting RFdiffusion reason over better identities while keeping the motif coordinates in context.
• Use inclusive chain-residue spans: 'contigmap.inpaint_seq=[A163-168/A170-171/A179]'.
• contigmap.inpaint_str masks structure for selected input residues and uses an inpaint-capable checkpoint.
• Do not mask residues that are absent from the contig/input PDB mapping.
• For residues that must remain functionally fixed, leave sequence and structure unmasked.

Target Chains And Chain Breaks

• The /0 token creates a 200-residue index jump so RFdiffusion treats following residues as a separate chain.
• The space after /0 is semantically important because contig parsing splits receptor and inpaint blocks by whitespace.
• A target block made only of chain-prefixed residues plus final /0 is treated as a receptor/fixed chain.
• contigmap.length applies to the generated/inpaint chain length, not necessarily fixed receptor length.
• For hotspot-guided binder design with ppi.hotspot_res, switch to binder-design guidance rather than this sub-skill alone.

Validation Checklist

• PDB exists and contains every chain/residue span in contigmap.contigs, contigmap.inpaint_seq, and contigmap.inpaint_str.
• Contig override is single quoted and passed as one Hydra argument.
• Any target chain break is written as /0 , not /0/ or /0 without the separating space when a new block follows.
• contigmap.length is compatible with the generated segment ranges; incompatible ranges can loop and exit with a length error.
• Model weights include the checkpoint named by inference.ckpt_override_path or the automatically selected file under inference.model_directory_path.
• Outputs include *.pdb and *.trb; the .trb records the sampled contig and residue mappings.
• Motif residues in output should be inspected/aligned against the input motif; tiny active sites may need ActiveSite_ckpt.pt.

Common Fixes

• Hydra parse error: wrap list overrides in single quotes and avoid unquoted brackets.
• Missing checkpoint: set inference.model_directory_path=$MODEL_DIR or pass the correct inference.ckpt_override_path.
• Missing residues: check PDB numbering and chain IDs; residue insertion codes or renumbered files often cause mismatches.
• Motif drift: use the active-site checkpoint for very small motifs, reduce design difficulty, or tighten motif definition.
• Target merges with scaffold: correct /0 chain-break syntax and confirm the fixed target block is chain-prefixed.

See references/troubleshooting.md for diagnosis details.

Outputs To Explain

• Final *.pdb contains backbone design output; designed residues are written as glycine while motif residues can retain identity context.
• *.trb stores config, sampled contig, mappings such as motif input/output indices, and inpaint masks.
• traj/ contains reverse-ordered trajectory PDBs when inference.write_trajectory=True.
• Use .trb mappings for downstream motif alignment, sequence design, and filtering.

Minimal Examples

Use these as templates after replacing paths:

run_inference.py \
  inference.output_prefix="$OUT_DIR/design_motifscaffolding" \
  inference.input_pdb="$INPUT_PDB" \
  inference.model_directory_path="$MODEL_DIR" \
  'contigmap.contigs=[10-40/A163-181/10-40]' \
  inference.num_designs=10

run_inference.py \
  inference.output_prefix="$OUT_DIR/design_motif_with_target" \
  inference.input_pdb="$INPUT_PDB" \
  inference.model_directory_path="$MODEL_DIR" \
  'contigmap.contigs=[A25-109/0 0-70/B17-29/0-70]' \
  contigmap.length=70-120 \
  inference.ckpt_override_path="$MODEL_DIR/Complex_base_ckpt.pt" \
  inference.num_designs=10