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Protein Design Skills

24 Claude Code skills for computational protein design, from binder design to structure QC.

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About

Adaptyv Bio's protein-design-skills is a focused package of 24 Claude Code skills covering the standard computational protein design pipeline: structure prediction and binder design with tools like BoltzGen, Chai, RFdiffusion, and ProteinMPNN, plus quality-control steps. The README's quick start is telling: ask Claude to design a binder for a PDB target and it picks the right skill chain for the job. Installation is a two-command Claude Code plugin setup, and the repo documents a full pipeline flow from design through validation.

Honest limits: this is a methods package, not wet-lab validation. Designed proteins still need experimental testing, and running the underlying structure-prediction models needs serious compute. The skills encode workflows; they don't replace a protein engineer's judgment on whether a design is worth synthesizing.

What it can do

  • Binder design workflows (BoltzGen, RFdiffusion)
  • Sequence design with ProteinMPNN
  • Structure prediction and validation with Chai
  • Standard design-to-QC pipeline orchestration
  • 24 composable skills across design stages

Setup

In Claude Code, run /plugin marketplace add adaptyvbio/protein-design-skills followed by /plugin install adaptyv@protein-design-skills. Then describe a design goal (e.g. 'Design a binder for PDB 1ALU') and Claude selects the appropriate skill chain. See the repo's getting-started docs for compute setup.

Prerequisites

Claude Code; GPU compute for structure prediction models; familiarity with protein design concepts.

Use cases

protein-designdrug-discoverystructural-biology

Works with

Claude Code

Trust score — 8/10

/10 trustVerified

Scored 8/10 (verified tier, metrics-v1). Evidence: 165 GitHub stars, 21 forks, MIT license, from Adaptyv Bio; 24 protein design skills with concrete two-command Claude Code plugin install; Covers BoltzGen, Chai, RFdiffusion, ProteinMPNN pipeline; Caveat: methods package only; wet-lab validation and heavy compute still required.

★ 165 GitHub stars

Sources

Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.