GNINA
Deep-learning scoring and flexible ligand docking
GNINA docks ligands into protein binding sites with deep-learning scoring functions trained on binding affinity data, combined with CNN-based rescoring and flexible sidechain support. It runs exhaustive sampling via differential evolution. Widely used for virtual screening and pose prediction with learned rescoring.
GNINA is being onboarded — request access and be first in line.
At a glance
- Input
- Protein and ligand (PDB, SDF)
- Output
- Docked poses with scores (SDF)
- Developed by
- GNINA Foundation
- Published
- McNutt et al., 2021 · 2021
#docking#deep-learning#virtual-screening
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