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complexa-target

Add, edit, inspect, or validate Proteina-Complexa target definitions for protein binders, ligand binders, and AME motif scaffolding. Use for target registries, chain/residue selectors, hotspots, ligand fields, and incomplete motif inputs.

Install / Use

npx skills add NVIDIA/skills --skill bionemo-complexa-target

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

95/100

Supported Platforms

Universal

Our assessment of complexa-target

complexa-target scores 95/100 on our quality scale, 367th of 4,583 Development & Engineering skills we index (top 9%).

Its SKILL.md is 15 KB long, well organised into 21 sections with 4 code examples: a thorough specification that gives an agent plenty to work with.

With 3,421 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
30/30
Structure
20/20
Description
15/15
Adoption
15/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 29 days ago, so complexa-target is actively maintained.
  • It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

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Frequently asked questions

How do I install complexa-target?
Run npx skills add NVIDIA/skills --skill complexa-target. The install tabs above show the steps for each supported agent.
Which AI agents does complexa-target work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is complexa-target safe to use?
It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is complexa-target still maintained?
The repository was last updated 29 days ago, so complexa-target is actively maintained.

name: complexa-target description: > Add, edit, inspect, or validate Proteina-Complexa target definitions for protein binders, ligand binders, and AME motif scaffolding. Use for target registries, chain/residue selectors, hotspots, ligand fields, and incomplete motif inputs. Covers direct YAML edits and complexa target/validate target commands; running a campaign with an already registered target belongs to complexa-design. allowed-tools: Bash, Read, Write, AskUserQuestion metadata: author: Ohad Mosafi omosafi@nvidia.com

complexa-target

Add or edit a design target in Proteina-Complexa. Targets live in three YAML files, one per complexa design pipeline:

  • configs/targets/targets_dict.yaml — protein binder (default pipeline)
  • configs/targets/ligand_targets_dict.yaml — ligand binder
  • configs/design_tasks/ame_dict_v2.yaml — AME / enzyme scaffolding

The complexa target CLI only manages the first two. AME tasks use an extended schema (the same core fields as ligand targets plus contig_atoms for hand-curated per-residue motif atom selections) and are file-edit-only.

Instructions

complexa target add is a thin wrapper around "load YAML → build dict → append a block" (see src/proteinfoundation/cli/target_manager.py:add_target_cli and append_target_to_dict). For agentic use, just edit the targets dict directly — the schema is short, the existing entries are great copy templates, and you skip 14 CLI flags / SMILES shell-escaping. Use the CLI only if you explicitly want its YAML auto-quoter or its overwrite-prompt safety.

For an offline edit, work on the supplied registry or requested output copy. When a copy is requested, create its parent directory and copy into an absent destination. If the destination already exists, inspect and preserve it: reuse it when it is the intended working copy, otherwise report the path conflict. Do not delete the output tree to restart a configuration edit. An installed Complexa runtime, GPU, or target structure is not required to write the configuration. Use the field schema below, preserve unrelated entries, and read back the saved block. Coordinate validation remains pending when the structure is absent; finish the configuration task without installing a runtime. With Read/Edit tools, read the destination copy before editing it; reading the original input path does not satisfy Edit's requirement for the output path.

Use the schema below and the selected registry; the CLI reference is needed only for CLI use. Finish with the saved entry, its consumer pipeline, the downstream generation.task_name, and the validation status.

| Step | Direct file edit (preferred) | CLI | |---|---|---| | Look at existing targets | Read configs/targets/{,ligand_}targets_dict.yaml (or configs/design_tasks/ame_dict_v2.yaml for AME) | complexa target list (protein/ligand only) | | Look at one target | Read the dict and grep for the key | complexa target show NAME | | Add a new target | Append a YAML block (Step 3a) | complexa target add ... (Step 3b) | | Verify configuration | Parse the saved YAML and compare the changed entry and untouched keys | complexa target show NAME --dict PATH | | Check runtime PDB-path resolution | Requires the full pipeline and environment | complexa validate target CONFIG --target NAME |

Step 1: Decide the target type

Targets live in three different files, one per complexa design pipeline. Pick the file by working out which pipeline the user will run, then add the entry to that file. Each file is consumed by exactly one pipeline.

| User intent | Pipeline | Targets dict file | This skill? | |---|---|---|---| | Bind a protein surface (PD-L1, IFNAR2, TNF-α, …) — default | configs/search_binder_local_pipeline.yaml | configs/targets/targets_dict.yaml | Yes — Step 2 (protein) | | Bind a small-molecule pocket (FAD, SAM, OQO, …) | configs/search_ligand_binder_local_pipeline.yaml | configs/targets/ligand_targets_dict.yaml | Yes — Step 2 (ligand) | | AME / enzyme scaffolding (motif + ligand, M####_<pdb> names) | configs/search_ame_local_pipeline.yaml | configs/design_tasks/ame_dict_v2.yaml | Partial — see "AME tasks" below |

AME tasks (enzyme pipeline)

AME tasks live under motif_target_dict_cfg: with source, target_filename, ligand, contig_atoms, binder_length, and use_bonds_from_file. The contig_atoms string contains curated chain/residue/atom selections. Existing entries illustrate the field structure, not the selections for a new motif. If motif atoms, ligand selection, or structure location are missing, list the missing inputs and write a separate, explicitly incomplete template if useful. Leave the registry unchanged until those scientific inputs are supplied. A task name or PDB ID alone does not determine them. In the missing-input handoff, explain that registration will be a direct edit under motif_target_dict_cfg once the curated selections are supplied; complexa target add cannot register AME tasks. Completed entries are selected with ++generation.task_name=<NAME> and configs/search_ame_local_pipeline.yaml.

Step 2: Gather required info

Use the supplied values and ask only for missing required information. Required fields differ for protein, ligand, and AME definitions.

Protein target

| Field | Question | Example | Required | |---|---|---|---| | name | "Target name (used as the dict key and task_name)?" | 02_PDL1, MyTarget_v1 | yes | | source | "Source directory under $DATA_PATH/target_data/?" | bindcraft_targets, custom_targets | yes (or target_path) | | target_filename | "PDB filename (no .pdb extension)?" | PD-L1, IFNAR2 | yes (or target_path) | | target_input | "Chain + residue range — see reference for grammar." | A1-115, A1-50,B1-50 | yes | | hotspot_residues | "Hotspot residues (interface contact residues)?" | ["A33", "A95", "A102"] | optional, recommended | | binder_length | "Binder length range [min, max] or single [length]?" | [80, 150], [100] | optional (default [60, 120]) | | pdb_id | "Reference PDB ID (optional, metadata only)?" | "2lag" | optional |

Hotspot selectors encode chain + residue number, not amino-acid identity. For example, Tyr42 (Y42) on explicitly specified chain B becomes B42; already supplied chain/residue selectors stay unchanged. Preserve the user's residue numbering. Without coordinates, report that residue identities and membership in the structure are unverified.

Ligand target — protein fields above (minus target_input), plus:

| Field | Question | Example | Required | |---|---|---|---| | ligand | "3-letter PDB ligand residue code?" | FAD, OQO, SAM | yes (presence marks target as ligand) | | SMILES | "SMILES string for the ligand?" | "O=C2C3=Nc1cc(c(...)..." | recommended; uppercase YAML key | | ligand_only | "Generate pocket around ligand only (no protein-protein interface)?" | true / false | optional (default true) | | use_bonds_from_file | "Use bond info from the input PDB/CIF?" | true / false | optional (default true) | | target_input | not required for ligand targets | — | no |

Check whether the proposed key already exists in the selected YAML mapping. Preserve an existing entry unless the user requested that entry's update.

Copy a supplied SMILES exactly. Chain-specific ligand selection belongs to preparation of the input structure; do not invent a chain field or protein target_input to represent it in the ligand entry.

Examples

Step 3a: Append the YAML block directly (preferred)

Open configs/targets/targets_dict.yaml (or ligand_targets_dict.yaml for ligand targets), find a similar existing entry as a style template, and append the new block under target_dict_cfg:. Two-space indent, single blank line between entries.

Protein template

  02_PDL1:
    source: bindcraft_targets
    target_filename: PD-L1
    target_input: "A1-115"
    hotspot_residues: ["A37", "A39", "A49", "A98"]
    binder_length: [64, 155]
    pdb_id: "4z18"

Rules to match the existing file style (mirrors what complexa target add would emit):

  • Quote chain/residue ranges ("A1-115", "A33") and any SMILES — flow-style strings get tripped up by : and brackets otherwise.
  • Use flow-style lists (["A33", "A95"], [64, 155]) — that's what the on-disk dump produces.
  • target_input, source, target_filename are required for protein. target_path (absolute path) can replace source + target_filename if the PDB lives outside $DATA_PATH/target_data/.

Ligand template

  41_7BKC_LIGAND:
    source: ligand_targets
    target_filename: 7BKC_ligand_centered
    hotspot_residues: [null]
    binder_length: [100]
    pdb_id: 7BKC
    ligand: 'FAD'
    ligand_only: True
    SMILES: "O=C2C3=Nc1cc(c(cc1N(C3=NC(=O)N2)CC(O)C(O)C(O)COP(=O)(O)OP(=O)(O)OCC6OC(n5cnc4c(ncnc45)N)C(O)C6O)C)C"
    use_bonds_from_file: True

The presence of the ligand: key flips the target into ligand mode — there is no separate is_ligand flag. target_input is not required for ligands.

After saving, skip to Step 4 to verify.

Step 3b: CLI alternative (complexa target add)

Use the CLI when you want its automatic chain/residue quoting, the overwrite-confirm prompt, or to wire target creation into a non-Python script. Prefer non-interactive mode for agentic use (-i / --editor opens an editor and blocks).

Confirmed flags (from src/proteinfoundation/cli/target_cli.py)

Read target_schema.md for the flag table and worked CLI examples when this path is needed. Select the intended dictionary with --dict; --source and --target-filename should be explicit when they differ from the CLI defaults. AME registration remains a direct edit.

Step 4: Verify

First parse the saved YAML with an available YAML parser and check the selected mapping, field types, requested values, and preservation of other entries. Read back the resulting block. This verifies configuration editing only.

With a prepared Complexa installation, pipeline configs, environment, and target structure, additionally check runtime path resolution from that checkout:

# 1. Select the dictionary that was actually edited.
complexa target show 02_PDL1 --dict configs/targets/targets_dict.yaml

# 2. Resolve the PDB path and validate it exists on disk.
#    This traverses Hydra defaults to find the target dict.
complexa validate target configs/search_binder_local_pipeline.yaml --target 02_PDL1

complexa validate target (from src/proteinfoundation/cli/validate.py::validate_target) checks:

  • DATA_PATH is set and target_data/ exists.
  • The target name resolves in target_dict_cfg.
  • Either target_path exists, or $DATA_PATH/target_data/<source>/<target_filename>.pdb exists.
  • target_input, hotspot_residues, binder_length are reported back so a human can sanity-check them.

For ligand targets, use configs/targets/ligand_targets_dict.yaml for show and configs/search_ligand_binder_local_pipeline.yaml for validation; --target is the target key, not a config path. This validator does not check residue identities, ligand chemistry, or AME contig_atoms; do not describe a path check as coordinate or scientific validation.

Step 5: Emit artifact

Save the edited entry and validation status at the user's requested output location (otherwise ./target_<name>/). For an offline edit, the saved YAML block is sufficient; no CLI-generated artifact is required. On a prepared installation, a target-show record can also be saved:

mkdir -p target_02_PDL1
complexa target show 02_PDL1 > target_02_PDL1/target_show.txt

If a standalone definition is requested, save the actual entry under its registry key in target_definition.yaml. The handoff should include the saved path, target key, consumer pipeline from Step 1, and `++generation.task

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars3.4k
CategoryDevelopment
Updated29d ago
Forks412

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

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complexa-target — Universal Skill: Install & Safety Check | SkillAgent