pxdesign

Generate de novo protein binders against target structures via CLI workflows.

104|10|Updated Mar 23, 2026
One-click install
npx skills add https://github.com/001TMF/blatant-why --skill pxdesign-001tmf
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: pxdesign
Source: https://github.com/001TMF/blatant-why/tree/main/templates/.claude/skills/pxdesign
Command: npx skills add https://github.com/001TMF/blatant-why --skill pxdesign-001tmf

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pyyaml, biopython, and includes scripts (resource) and references (resource) components.

What problem does it solve?

PXDesign enables researchers to design de novo protein binders against a specified target structure by generating a validated YAML configuration, invoking a CLI workflow, parsing outputs, and interpreting results for non-antibody binders.

Core Features & Use Cases

  • YAML config construction from a target structure, hotspot constraints, crops, and MSA options.
  • CLI-driven design pipeline with presets (preview for exploration and extended for production) and multi-chain support.
  • Output parsing into a tidy CSV with ranking metrics such as ptx_iptm and the AF2/Protenix filter results to guide downstream screening.
  • End-to-end workflow suitable for multi-chain targets and hotspot-guided design scenarios.

Quick Start

Create a YAML config for your target, run the pxdesign pipeline, and review the parsed summary to identify top designs.

Frequently Asked Questions about pxdesign

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

FAQPage Schema
How do I design de novo protein binders against a multi-chain target structure?▼

Design de novo protein binders by generating a validated YAML configuration from your target structure and hotspot constraints, then executing the CLI-driven pipeline to produce parsed design outputs.

Can I use hotspot constraints to guide de novo binder design for specific target regions?▼

Yes, hotspot constraints can be specified in the YAML configuration to guide de novo binder design, ensuring the generated protein structures target specific desired regions on the multi-chain target structure.

How does the pipeline parse and rank designed protein binders for downstream screening?▼

The pipeline parses design outputs into a tidy CSV file ranked by ptx_iptm and includes AF2 or Protenix filter results, providing clear ranking metrics to guide your downstream screening process.

Do I need a specific YAML configuration format to run the protein design pipeline?▼

Yes, you need a YAML configuration that specifies target chains parsed via label_asym_id, hotspot constraints, crops, and MSA options, which the pipeline validates before invoking the CLI-driven design workflow.

What is the difference between preview and extended presets in the CLI-driven binder design workflow?▼

The CLI-driven binder design workflow offers preview presets for initial exploration and extended presets for production runs, allowing you to balance computational resource usage with design thoroughness.