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Found 5 Skills
Molecular docking pipeline using AutoDock Vina for structure-based drug discovery. Triggers on docking, AutoDock Vina, receptor preparation, ligand preparation, PDBQT, grid box, virtual screening, binding affinity, pose prediction, structure-based virtual screening, "redocking RMSD", "Vina score", "docking pose", "prepare receptor", "ligand library screening".
Reasoning skill for structure-based drug design strategy. Use when the user asks to assess target druggability, choose a docking strategy, select a scoring function, define a binding site, interpret docking results, plan molecular dynamics or free energy perturbation (FEP), design a virtual screening cascade, or decide between fragment-based and HTS screening. Triggers include "drug design", "druggability", "docking strategy", "scoring function", "binding pocket", "molecular dynamics", "FEP", "SAR", "virtual screening", "induced fit", "allosteric site", "fragment-based drug discovery", "lead optimization", "MM-GBSA", "pharmacophore".
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.
Discover novel small molecule binders for protein targets using structure-based and ligand-based approaches. Creates actionable reports with candidate compounds, ADMET profiles, and synthesis feasibility. Use when users ask to find small molecules for a target, identify novel binders, perform virtual screening, or need hit-to-lead compound identification.
Run DiffDock molecular docking via NVIDIA NIM to predict small-molecule binding poses against protein targets. Use for DiffDock, molecular docking, ligand docking, blind docking, SMILES or SDF ligands, ranked poses, confidence scores, hosted NVIDIA API, or local Docker deployment.