diffdock
CommunityPredict protein-ligand binding poses.
Education & Research#bioinformatics#virtual screening#drug discovery#molecular docking#cheminformatics#protein-ligand binding
AuthorRowtion
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill automates the prediction of how small molecules (ligands) bind to proteins, a crucial step in drug discovery and understanding biological interactions.
Core Features & Use Cases
- Molecular Docking: Predicts the 3D pose of a ligand within a protein's binding site.
- Virtual Screening: Screens large libraries of compounds to identify potential drug candidates.
- Structure-Based Drug Design: Aids in designing new molecules with desired binding properties.
- Use Case: A researcher wants to find out where a new drug molecule might bind to a target protein. They can use this Skill to predict the most likely binding poses and assess their confidence.
Quick Start
Use the diffdock skill to predict the binding pose of the ligand with SMILES 'CC(=O)Oc1ccccc1C(=O)O' to the protein structure 'protein.pdb'.
Dependency Matrix
Required Modules
None requiredComponents
scriptsreferencesassets
💻 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: diffdock Download link: https://github.com/Rowtion/Bioclaw/archive/main.zip#diffdock Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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