Agent skill · research science · k-dense-ai

diffdock

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.

Why this skill is useful

Adds executable scripts for molecular docking workflows and integrates deep learning models for pose prediction that the AI wouldn't generate on its own.

What it needs

Requires docker, python installed locally. About 9k tokens when loaded. Last updated 2026-08-03. 32,849 stars on the source repository.

What this skill does

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

How to use it

Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:

@skills k-dense-ai/diffdock

View the source on GitHub

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