| Quick overview subseq.bio is a minimal web + API service for running protein design/analysis and related workloads. It hosts pre-configured, open-source models and programs such as RFdiffusion3, BoltzGen, AlphaFold, and others, in a simple to use interface. Backstory I’ve been obsessed with molecular nanotechnology for a long time. Just before ChatGPT was announced I was following the RFdiffusion work from Baker Lab at the Institute for Protein Design and it felt like a clear inflection point for practical synthetic protein generation. Since then there’s been a steady stream of new ML models in this space, so I put together a system for composing and running them through a consistent and programmatic interface: subseq.bio. Technical bits - All programs use open-source code and weights. (no licensing restrictions and good for reproducibility)
- API-first: anything you can do in the UI is available via the API.
- Focused on synthetic protein design and related workloads.
- Jobs are charged per use (no subscriptions), but new sign-ins get free credits so you can try things out. I also recently added an MCP server for AI agent integration:
https://subseq.bio/mcp There’s no OAuth yet, but it works with an API key env var; you can grab a key from the site.
Example codex config: export SUBSEQ_API_KEY=<subseq_api_key>
codex mcp add subseq --url <subseq_mcp_url> --bearer-token-env-var SUBSEQ_API_KEY
For a visual overview, here’s a short video demo of a BoltzGen binder run on an AlphaFold2 output in the web UI:
https://x.com/0xCF88/status/1995994854585696515I know this is pretty niche and aimed at people already doing protein design / structure prediction, but I’d love to answer questions and to read any feedback. |