drug-ligand-prep

Official

Prepare docking-ready ligands in minutes.

Authorlearningmatter-mit
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill removes the repetitive, error-prone work of turning raw ligand inputs (SMILES/SDF) into docking-ready 3D conformations and structure files, so researchers can move faster to screening and analysis.

Core Features & Use Cases

  • Optional state enumeration: Enumerates protonation states (and optionally tautomers) to produce chemically relevant ligand variants.
  • Reproducible 3D conformer generation: Generates multiple conformers using RDKit ETKDG via MCP.
  • Docking-ready exports: Produces an optimized SDF and an AutoDock-Vina PDBQT suitable for downstream docking workflows.
  • MMFF94/UFF minimization: Minimizes conformers with MMFF94 (falling back to UFF) to select a lowest-energy structure.

Use case: You have a list of candidate ligands as SMILES and want a batch of docking-ready PDBQT files for a small-molecule screening campaign, including physiologically plausible protonation states.

Quick Start

Prepare docking-ready ligand states and PDBQT from a SMILES file by running the ligand preparation script on your inputs with enumeration enabled and an output directory for the generated SDF and PDBQT files.

Dependency Matrix

Required Modules

rdkitmeekodimorphite_dl

Components

scripts

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: drug-ligand-prep
Download link: https://github.com/learningmatter-mit/AtomisticSkills/archive/main.zip#drug-ligand-prep

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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