# Diffdock

Diffusion-based molecular docking.

- Repository: https://github.com/LeonChaoX/qinyan-academic-skills (996 stars)
- Category: Design
- License: MIT license
- Last updated: 2026-07-20
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add LeonChaoX/qinyan-academic-skills --skill diffdock -g -a claude-code -y`
Codex: `npx skills add LeonChaoX/qinyan-academic-skills --skill diffdock -g -a codex -y`
Cursor: `npx skills add LeonChaoX/qinyan-academic-skills --skill diffdock -g -a cursor -y`
Gemini CLI: `npx skills add LeonChaoX/qinyan-academic-skills --skill diffdock -g -a gemini-cli -y`

## Description

Diffusion-based molecular docking. Predict protein-ligand binding poses from PDB/SMILES, confidence scores, virtual screening, for structure-based drug design. Not for affinity prediction.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# 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
- Generate confidence scores to assess prediction reliability
- Handle diverse ligand inputs (SMILES, SDF, MOL2)

**Key Distinction:** DiffDock predicts **binding poses** (3D structure) and **confidence** (prediction certainty), NOT binding affinity (ΔG, Kd). Always combine with scoring functions (GNINA, MM/GBSA) for affinity assessment.

## When to Use This Skill

This skill should be used when:

- "Dock this ligand to a protein" or "predict binding pose"
- "Run molecular docking" or "perform protein-ligand docking"
- "Virtual screening" or "screen compound library"
- "Where does this molecule bind?" or "predict binding site"
- Structure-based drug design or lead optimization tasks
- Tasks involving PDB files + SMILES strings or ligand structures
- Batch docking of multiple protein-ligand pairs

## Installation and Environment Setup

### Check Environment Status

Before proceeding with DiffDock tasks, verify the environment setup:

```bash
# Use the provided setup checker
python scripts/setup_check.py
```

This script validates Python version, PyTorch with CUDA, PyTorch Geometric, RDKit, ESM, and other dependencies.

### Installation Options

**Option 1: Conda (Recommended)**
```bash
git clone https://github.com/gcorso/DiffDock.git
cd DiffDock
conda env create --file environment.yml
conda activate diffdock
```

The rest: https://github.com/LeonChaoX/qinyan-academic-skills/blob/HEAD/skills/06-化学信息与药物发现/diffdock/SKILL.md