AutoDock Vina
The Scripps Research Institute
Classical rigid receptor, flexible ligand docking using empirical and knowledge-based scoring. The most widely used open-source docking tool.
Best For
Standard first-pass virtual screening; academic SBDD
License
Open Source (Apache 2.0)
Strengths
- +Production-ready
- +Widely validated
- +Fast for large libraries
Limitations
- −Rigid receptor only
- −No induced fit
- −Scoring function accuracy limited on flexible targets
R&D Pipeline Coverage
Related Tools
GNINA
Koes Lab (University of Pittsburgh)
AutoDock Vina-based docking engine augmented with a 3D CNN scoring function. Uses Vina for sampling, CNN for scoring and re-ranking.
Uni-Dock
DP Technology
GPU-accelerated molecular docking achieving >2000x speedup over CPU Vina. Enables ultra-large virtual screening of billions of compounds.
More in Docking & Screening
DiffDock / DiffDock-L
MIT CSAIL (Corso et al.)
Diffusion-based generative model that treats docking as a generative problem over ligand poses. No pre-specified binding pocket needed.
GNINA
Koes Lab (University of Pittsburgh)
AutoDock Vina-based docking engine augmented with a 3D CNN scoring function. Uses Vina for sampling, CNN for scoring and re-ranking.
FlowDock
Morehead, Cheng Lab (University of Missouri)
Geometric flow matching model that maps apo protein structures to bound complexes for multiple ligands simultaneously. Outputs confidence scores and affinity estimates.
Stay updated on AutoDock Vina
Weekly newsletter covering AI tool releases, benchmarks, and what practitioners actually use.