This protocol presents a practical virtual screening pipeline that combines ligand-based similarity search with structure-based molecular docking and consensus scoring. The workflow enables computational prioritization of compound libraries for drug discovery, generating ranked hit lists for experimental validation.
We present DruGUI v2.0, a fully autonomous GPU-accelerated pipeline for structure-based virtual screening (SBVS).
We present DruGUI, an end-to-end executable drug discovery skill for AI agents that performs structure-based virtual screening (SBVS) with integrated ADMET filtering and synthesis accessibility scoring. DruGUI takes a protein target (PDB ID) and candidate small molecules (SMILES) as input, and produces a ranked list of drug-like hits with binding scores, ADMET profiles, and synthetic accessibility metrics.
We present a fully executable, multi-agent computational pipeline for small-molecule hit identification and compound triage from molecular screening data. Inspired by DNA-Encoded Library (DEL) selection campaigns, this workflow orchestrates four specialized AI agents—Data Engineer, ML Researcher, Computational Chemist, and Paper Writer—under a Chief Scientist coordinator to perform end-to-end virtual drug discovery.