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mosaic webapp

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# easymosaic

Protein binder design using [Mosaic](https://github.com/escalante-bio/mosaic) with Boltz-2 and Protenix models.

![easymosaic screenshot](https://raw.githubusercontent.com/hgbrian/easymosaic/main/assets/easymosaic_screenshot.jpg)

## Quick Start

```bash
# Serve web UI (prints a temporary Modal URL)
uv run modal serve easymosaic.py

# Deploy permanently
uv run modal deploy easymosaic.py
```

## Design Modes

- **VHH**: Design nanobody CDRs on a fixed framework. Provide sequence with `X` marking designable positions.
- **Minibinder**: Design a small de novo binder. Specify length (default 80 aa).

## Models

- **Boltz-2**: Default. Fast and accurate.
- **Protenix**: Uses multisample loss. May be better for complex targets.

## Interactive Notebooks

The marimo notebooks give full control over the design pipeline with live loss plots, structure visualization, and editable parameters. They run on a Modal GPU.

```bash
# Launch minibinder notebook on GPU
uv run modal run deploy_notebook.py::run_minibinder

# Launch VHH notebook on GPU
uv run modal run deploy_notebook.py::run_vhh
```

This starts a marimo notebook server on a B200 GPU and prints a public URL. The notebook workflow is:

1. Load model (Protenix or Boltz-2)
2. Configure target sequence and hotspots
3. (VHH only) Select scaffold preset or enter custom sequence with X's
4. Fold target to verify it folds correctly
5. Build features & loss (triggers JIT compilation)
6. Run design with live loss trajectory plot
7. Rank designs — results in a sortable table with PAE plots and 3D viewer
8. Download CSV

## CLI Usage

```bash
# Create a test target
echo ">target
MKTVRQERLKSIVRILERSKEPVSGAQLAEELSVSRQVIVQDIAYLRSLGYNIVATPRGYVLAGG" > /tmp/test_target.fasta

# Minibinder design (1 design)
uv run modal run easymosaic.py --target /tmp/test_target.fasta --mode minibinder --binder-length 60 --num-designs 1

# VHH design with preset
uv run modal run easymosaic.py --target /tmp/test_target.fasta --mode vhh --preset caplacizumab --num-designs 1
```

The first design takes 20+ minutes due to JIT compilation. Subsequent designs are faster.

## Project Structure

```
easymosaic.py            # Main app: Flask web server + CLI entrypoint
index.html               # Web UI
design.py                # Shared library: configs, losses, optimization, ranking
backends/
  boltz.py               # Boltz-2 backend (Modal function + image)
  protenix.py            # Protenix backend (Modal function + image + precycling)
minibinder_notebook.py   # Interactive marimo notebook for de novo binder design
vhh_notebook.py          # Interactive marimo notebook for VHH CDR design
deploy_notebook.py       # Deploys notebooks on Modal GPU (B200)
```

## Output

Each design includes:
- Sequence
- ipTM score (interface predicted TM-score, higher is better)
- Ranking score (ipTM + IPSAE combined)
- Structure (CIF and PDB formats)

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