Diffdock

---
name: diffdock
description: DiffDock and DiffDock-L molecular docking. Use for protein-small-molecule pose prediction from PDB or sequence plus SMILES/SDF/MOL2, batch docking, virtual screening, and pose-confidence interpretation. Not for binding affinity prediction.
allowed-tools:
  - Read
  - Write
  - Edit
  - Bash
  - Glob
  - Grep
compatibility: Requires the DiffDock repository, Python 3.9 environment from upstream environment.yml or the official Docker image, RDKit, PyTorch/PyG, and optional CUDA GPU acceleration. Current guidance targets DiffDock v1.1.3 / DiffDock-L.
license: MIT license
metadata: {"version": "1.1", "skill-author": "K-Dense Inc."}
---

# DiffDock: Molecular Docking with Diffusion Models

## Overview

DiffDock is a diffusion-based deep learning tool for molecular docking that predicts 3D binding poses of small molecule ligands to protein targets. It represents the state-of-the-art in computational docking, crucial for structure-based drug discovery and chemical biology.

**Core Capabilities:**
- Predict ligand binding poses with high accuracy using deep learning
- Support protein structures (PDB files) or sequences (via ESMFold)
- Process single complexes or batch virtual screening campaigns… load the full skill through Skill Me