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.