# Protein Binder Design

Orchestrate an end-to-end de novo protein binder design campaign against a protein...

- Repository: https://github.com/NVIDIA-BioNeMo/bionemo-agent-toolkit (503 stars)
- Category: Design
- License: Apache-2.0
- Last updated: 2026-10-28
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add NVIDIA-BioNeMo/bionemo-agent-toolkit --skill protein-binder-design -g -a claude-code -y`
Codex: `npx skills add NVIDIA-BioNeMo/bionemo-agent-toolkit --skill protein-binder-design -g -a codex -y`
Cursor: `npx skills add NVIDIA-BioNeMo/bionemo-agent-toolkit --skill protein-binder-design -g -a cursor -y`
Gemini CLI: `npx skills add NVIDIA-BioNeMo/bionemo-agent-toolkit --skill protein-binder-design -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add NVIDIA-BioNeMo/bionemo-agent-toolkit`

## Description

Orchestrate an end-to-end de novo protein binder design campaign against a protein target by composing BioNeMo NIM skills. Use for binder design, minibinder design, de novo binders, RFdiffusion + ProteinMPNN + Boltz2/OpenFold3 pipelines, epitope/hotspot-targeted design, in-silico binder validation, and ranking designs by interface confidence.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Protein Binder Design (workflow)

Run a de novo binder design campaign by composing atomic NIM skills. This skill
owns orchestration, handoff contracts, filtering, validation, and the run
manifest. It does NOT duplicate per-NIM API details, defer those to each
atomic skill's `SKILL.md`.

## Composed skills

| Step | Skill | Owns |
|---|---|---|
| Backbones | `rfdiffusion-nim` | binder backbone PDBs (contigs + hotspots) |
| Sequences | `proteinmpnn-nim` | sequences for each backbone |
| Co-fold / score | `boltz2-nim` or `openfold3-nim` | binder, target complex + confidence / ipTM |
| MSA (optional) | `msa-search-nim` | target A3M for higher-quality folding |

The atomic NIM skills are recommended companions (one per NIM, from the BioNeMo
NIM skill set). They are **not required**: `references/pipeline.md` carries the
concrete request shape for every NIM call, so an agent with NIM access can follow
this skill standalone. For endpoints/auth see **Configuration** below.

## Pipeline

1. **Target prep**, get the target PDB + epitope; map epitope/hotspot author
   residue numbers to RFdiffusion `hotspot_res` strings; optionally build a
   target MSA with `msa-search-nim`.
2. **Backbones** (`rfdiffusion-nim`), binder contig + `hotspot_res`; N backbones.
3. **Sequences** (`proteinmpnn-nim`), k sequences per backbone; drop the
   native/WT row from `mfasta`.
4. **Co-fold + score** (`boltz2-nim` / `openfold3-nim`), co-fold binder+target;
   collect interface confidence (ipTM) and binder pLDDT.
5. **Self-consistency**, CA-RMSD between the RFdiffusion backbone and the
   predicted binder (`scripts/metrics.py`).
6. **Filter + rank**, apply thresholds; rank survivors; write manifest + CSV.

Full handoff contracts, branching, and the cost funnel: `references/pipeline.md`.

## Handoff contracts (the fragile glue)

The rest: https://github.com/NVIDIA-BioNeMo/bionemo-agent-toolkit/blob/HEAD/skills/bionemo-agent-toolkit/skills/protein-binder-design/SKILL.md