disco

Design protein backbones and sequences conditioned on ligands, DNA, or RNA.

2|Updated May 12, 2026
One-click install
npx skills add https://github.com/LiorZ/protein-design-skills --skill disco-liorz
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: disco
Source: https://github.com/LiorZ/protein-design-skills/tree/main/skills/disco
Command: npx skills add https://github.com/LiorZ/protein-design-skills --skill disco-liorz

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

DISCO enables end-to-end co-design of a protein's sequence and backbone structure, allowing conditioning on non-protein entities such as ligands, DNA, or RNA to streamline design workflows.

Core Features & Use Cases

  • Joint sequence-structure co-design for ligand-conditioned binders, RNA/DNA-binding proteins, and multi-cofactor active sites.
  • Hydra-based CLI with explicit overrides, input schemas, and scalable options for prototyping and large-scale screens.
  • Outputs include PDBs and sequences suitable for downstream refolding, QC, and ranking pipelines.

Quick Start

Run the DISCO runner with a ligand-conditioned input JSON to generate de novo backbone designs and sequences.

Frequently Asked Questions about disco

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How does diffusion-based protein sequence and structure co-design work?

DISCO enables joint sequence-structure co-design by using diffusion-based generation to create protein backbones and sequences conditioned on non-protein partners. It accepts ligand, DNA, or RNA inputs to generate structured PDBs and sequence files.

Can I design DNA-binding and RNA-binding proteins using diffusion models?

Yes, DISCO supports ligand, DNA, and RNA conditioning for designing binding proteins. It uses a Hydra-based CLI to process input JSON and generate protein backbones and sequences specifically conditioned on these non-protein entities.

What's the best way to run large-scale protein design campaigns with ligand conditioning?

To run large-scale protein design campaigns, use the DISCO Hydra-based CLI with scalable options and explicit overrides. Provide valid ligand-conditioned input JSON to execute large-scale screens and output structured PDB and sequence files.

Do I need a valid input JSON to generate protein backbones and sequences?

Yes, valid input JSON is required to run the DISCO CLI for protein backbone and sequence generation. The input schema defines the conditioning parameters, and the CLI outputs structured PDBs and sequence files under a specified dump directory.

What outputs do I get from an end-to-end protein sequence and structure co-design run?

Outputs from DISCO co-design runs include structured PDBs and sequence files saved under a dump directory. These outputs are specifically formatted for downstream refolding, quality control, and ranking pipelines to validate the generated protein designs.

When should I not use diffusion-based protein co-design for my binding targets?

Avoid using DISCO if your workflow lacks the DISCO CLI or valid input JSON, as these are strictly required. Additionally, it only supports conditioning on ligands, DNA, and RNA, so it may not apply if your targets require other types of molecular conditioning.