# Germinal

> >

- **Type:** Skill
- **Install:** `agentstack add skill-adaptyvbio-protein-design-skills-germinal`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [adaptyvbio](https://agentstack.voostack.com/s/adaptyvbio)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [adaptyvbio](https://github.com/adaptyvbio)
- **Source:** https://github.com/adaptyvbio/protein-design-skills/tree/main/skills/germinal

## Install

```sh
agentstack add skill-adaptyvbio-protein-design-skills-germinal
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Germinal Antibody and Nanobody Design

[Germinal](https://github.com/SantiagoMille/germinal) is an open pipeline for
epitope-targeted de novo antibody and nanobody design. It hallucinates CDRs on a
fixed framework, designs sequences with AbMPNN, and cofolds with a structure
predictor (it downloads AlphaFold-Multimer params). Runnable through biomodals.

The biomodals author notes Germinal is finicky and suggests BoltzGen for general
binder design; treat Germinal as the antibody-format option, not a default.

## Prerequisites

| Requirement | Value |
|-------------|-------|
| Runner | Modal (biomodals) |
| GPU | H100 (default; `GPU` env var) |
| Setup | See [Getting started](../../docs/getting-started.md) |

## How to run

```bash
git clone https://github.com/hgbrian/biomodals && cd biomodals

uv run --with modal --with PyYAML modal run modal_germinal.py \
  --target-yaml target_example.yaml \
  --max-trajectories 1 \
  --max-passing-designs 1
```

## Key parameters

| Parameter | Default | Description |
|-----------|---------|-------------|
| `--target-yaml` | required | Target config (target_name, target_pdb_path, target_chain, binder_chain, target_hotspots, length) |
| `--run-type` | `vhh` | `vhh` (nanobody) or `scfv` |
| `--max-trajectories` | 100 | Trajectories to run |
| `--max-passing-designs` | 10 | Stop after this many passing designs |
| `--out-dir` | `./out/germinal` | Output directory |

## Target YAML

```yaml
target_name: PDL1
target_pdb_path: target.pdb
target_chain: A
binder_chain: B
target_hotspots: "45,67,89"
length: 120
```

## Decision tree

```
Antibody-format binder?
│
├─ Nanobody / VHH → germinal (run-type vhh) or mber
├─ scFv → germinal (run-type scfv)
└─ Miniprotein (not antibody) → binder-design (boltzgen, bindcraft, mosaic)
```

For VHH nanobodies, biomodals also has `modal_mber.py` (mBER) and `modal_iggm.py`
(IgGM) as alternatives.

## Cost

Adaptyv's own tests of these models showed Germinal costing about $1.60 per accepted
design, averaged across 7 targets.

## Troubleshooting

| Issue | Cause | Fix |
|-------|-------|-----|
| Pipeline fails early | Missing PyYAML | Add `--with PyYAML` to the invocation |
| No passing designs | Hard epitope or low budget | Raise `--max-trajectories` |
| OOM | Large target | Use the default H100 or trim the target |

---

**Next**: Validate with `boltz` or `chai`, rank with `ipsae`, filter with `protein-qc`.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [adaptyvbio](https://github.com/adaptyvbio)
- **Source:** [adaptyvbio/protein-design-skills](https://github.com/adaptyvbio/protein-design-skills)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-adaptyvbio-protein-design-skills-germinal
- Seller: https://agentstack.voostack.com/s/adaptyvbio
- Browse the marketplace: https://agentstack.voostack.com/browse

---
Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.