DRDOCK

DRDOCK performs systematic virtual screening of 2016 FDA-approved drugs against protein targets to identify drug repurposing candidates using molecular docking, molecular dynamics (MD) simulations, and log-odds–based ranking.

Key Features:

• Automated Virtual Drug Screening: Performs automated virtual screening of a library of 2016 FDA-approved drugs against submitted protein targets.
• Integration of Molecular Docking and MD Simulations: Combines molecular docking with MD-based conformation sampling and pose re-ranking to distinguish strong binders from non-binders.
• Log-Odds-Based Drug Ranking Scheme: Ranks candidate drugs using log-odds (LOD) scores derived from feature distributions of true binders and decoys.
• Input Requirements: Operates on protein structures provided in PDB format with specified target residue IDs for docking.
• 3D Visualization of Docking and Trajectories: Provides 3D visualization of sampled docking poses and MD trajectories.

Scientific Applications:

• SARS-CoV-2 drug repurposing: Identified fluralaner, tegaserod, and fenoterol as candidate repurposed drugs, with tegaserod and fenoterol experimentally confirmed to suppress SARS-CoV-2.

Methodology:

Performs molecular docking on PDB-format protein structures with specified residue IDs, conducts MD-based conformation sampling and pose re-ranking, ranks drugs using log-odds (LOD) scores, and allows selection of top-ranked poses for further MD-based binding affinity evaluation.