molclaw-fpocket-toolkit-base

Detect protein-ligand binding pockets from PDB/mmCIF files and return parsed descriptors and run artifacts.

28|2|Updated Mar 31, 2026
One-click install
npx skills add https://github.com/InternScience/MolClaw --skill molclaw-fpocket-toolkit-base
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: molclaw-fpocket-toolkit-base
Source: https://github.com/InternScience/MolClaw/tree/main/skills/L1_tools/molclaw-fpocket-toolkit-base
Command: npx skills add https://github.com/InternScience/MolClaw --skill molclaw-fpocket-toolkit-base

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill automates detection of ligand binding pockets from protein structure files and returns parsed pocket descriptors and preserved run artifacts for downstream analysis and docking preparation.

Core Features & Use Cases

  • Pocket Detection: Runs fpocket_toolkit on PDB/mmCIF inputs and parses pocket descriptors including scores, centers, and sizes.
  • Filtering & Export: Supports top-N selection, druggability threshold filtering, verbose parsing, and returns output files plus an organized run directory.
  • Docking Safety Rule: Enforces a minimum 25.0 Å per dimension when converting pocket dimensions to docking box sizes to ensure reliable docking inputs.
  • Use Case: Prepare standardized pocket descriptors and docking boxes for virtual screening, hit identification, and structure-based optimization workflows.

Quick Start

Use the molclaw-fpocket-toolkit-base skill to analyze the uploaded PDB file and return parsed pocket descriptors, run artifacts, and output file paths.

Frequently Asked Questions about molclaw-fpocket-toolkit-base

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

FAQPage Schema
How do I detect ligand binding pockets from a PDB file for docking preparation?

To detect ligand binding pockets from a PDB file, you need to run pocket detection tools that parse protein structures and return pocket descriptors like scores, centers, and sizes. This Skill automates that process and preserves fpocket run artifacts for downstream docking preparation.

What is the minimum docking box size for virtual screening generated from protein binding pockets?

The minimum docking box size for virtual screening generated from protein binding pockets is 25.0 Å per dimension. This Skill enforces this docking safety rule when converting pocket dimensions to docking boxes to ensure reliable inputs.

Can I filter protein binding pockets by druggability scores in structure-based analysis?

Yes, you can filter protein binding pockets by druggability scores in structure-based analysis. This Skill supports druggability threshold filtering and top-N selection to identify the most relevant pockets from your protein structure.

Does fpocket work with mmCIF files for molecular screening workflows?

Yes, fpocket works with mmCIF files for molecular screening workflows. This Skill accepts both local PDB and mmCIF inputs to detect binding pockets and return parsed descriptors for structure-based analysis.

How do I get fpocket output files and pocket descriptors for downstream analysis?

To get fpocket output files and pocket descriptors for downstream analysis, run pocket detection on your protein structure. This Skill parses the pocket descriptors and preserves all fpocket run artifacts in an organized output directory.