Predict 3D ligand-protein binding poses from PDB files using diffusion models.
npx skills add https://github.com/Sologa/codex-pipeline --skill diffdock-sologa
Please help me install this Agent Skill. Skill: diffdock Source: https://github.com/Sologa/codex-pipeline/tree/main/.codex/skills/diffdock Command: npx skills add https://github.com/Sologa/codex-pipeline --skill diffdock-sologa
This Skill automates the prediction of how small molecules (ligands) bind to proteins, a critical step in drug discovery and understanding biological interactions.
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'.
High-intent search queries and answers about installing and using this skill.
You can predict 3D binding poses by submitting a PDB file or protein sequence alongside a small molecule ligand input. The diffusion model generates the ligand-protein complex structure and assigns confidence scores.
Yes, you can use a protein sequence for molecular docking. The Skill processes protein sequences via ESMFold to generate the required structures for predicting ligand binding poses.
The Skill supports various ligand input formats for structure-based drug design, including SMILES strings, to accurately model small molecule interactions with your target protein.
Diffusion models improve protein-ligand interaction predictions by generating accurate 3D binding poses and confidence scores. This approach enhances structure-based drug design and chemical biology research outcomes.
Yes, this molecular docking tool works without external dependencies. It independently handles protein-ligand complex generation and confidence scoring using its built-in diffusion models.
A limitation of using diffusion models for cheminformatics virtual screening is that predicted poses rely on confidence scores. Actual binding affinity and biological activity require further experimental validation.
robinbarvaagPredict 3D ligand binding poses to protein targets using diffusion models.
ovachieverPredict protein-ligand docking poses and confidence scores from PDB structures or sequences.
sanand0Predict 3D binding poses of small molecules to protein targets using diffusion models.
jimmc414Predicts protein-ligand binding poses and confidence scores via molecular docking.
