drug-discoveryDrug Discovery & Chemistry
AI Drug Discovery · Molecular Docking

AutoDock Vina

By Scripps Research Institute

High-throughput molecular docking and virtual screening software

AutoDock Vina is one of the most widely cited open-source docking engines in structural biology, offering fast conformational search algorithms and empirical binding affinity scoring.

High-speed multi-threaded molecular docking of flexible small-molecule ligandsSupport for flexible receptor side chains and macrocyclic ligandsPython bindings (AutoDock-Vina Python package) for automated screening pipelinesExtensively integrated with open-source computational chemistry workflows
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Overview

AutoDock Vina is one of the most widely cited open-source docking engines in structural biology, offering fast conformational search algorithms and empirical binding affinity scoring.

Information checked against an official source; not a hands-on test. Source · Last reviewed: 20/09/2026, 11:09:40

Key Features

  • High-speed multi-threaded molecular docking of flexible small-molecule ligands
  • Support for flexible receptor side chains and macrocyclic ligands
  • Python bindings (AutoDock-Vina Python package) for automated screening pipelines
  • Extensively integrated with open-source computational chemistry workflows
Interactive 3D Structure

AutoDock Vina Predicted Complex

Streams real 3D atomic coordinates from RCSB Protein Data Bank
⇄ Drag to rotate · Scroll to zoom
pLDDT / B-Factor:
>90 Very high 70-90 Confident 50-70 Low <50 Very low

Academic Context & Research Evidence

Biological & Workflow Fit

Biological Application
Virtual screening of compound libraries and binding mode prediction
Research Workflow
Input receptor PDBQT and ligand PDBQT -> output binding poses and energy scores
Compute & Hardware
Multi-core CPU (GPU-accelerated version available via QuickVina/Vina-GPU)
Licensing & Academic Use
Apache 2.0
Documented Evidence
View validation publication / source ↗

Cite this Tool

Use this citation format when referencing AutoDock Vina in scientific publications and benchmark papers.

@software{autodock_vina_2026,
  title = {{AutoDock Vina}},
  author = {{Scripps Research Institute}},
  year = {2026},
  url = {https://vina.scripps.edu},
  note = {Indexed on aibioatlas - AI for Biology and Drug Discovery}
}

Peer-Reviewed Literature & Preprints

Live scientific citations streamed from Europe PMC and PubMed for AutoDock Vina.

⏳ Fetching real-time literature from Europe PMC & PubMed...

Technical / Product Information

Missing values mean the catalog has no recorded information. They do not mean a feature is absent.

Entry typeOpen Source Software
Access modeOpen Source
AI roleEmpirical & Algorithmic Docking
Input dataNot recorded
Output dataNot recorded
Licence conditionsApache 2.0
Commercial eligibilityPermissive open source release
Compute requirementsMulti-core CPU (GPU-accelerated version available via QuickVina/Vina-GPU)
ValidationNot recorded
TypeMolecular docking software
Intended useNot recorded
CompatibilityNot recorded
ManufacturerThe Scripps Research Institute
Biological applicationVirtual screening of compound libraries and binding mode prediction
Research workflowInput receptor PDBQT and ligand PDBQT -> output binding poses and energy scores
Evidence levelPeer-reviewed research with >25,000 scientific citations
Integration evidencehttps://vina.scripps.edu
Laboratory handoffIdentified hits ordered from commercial vendors (Enamine, ChemBridge) for in vitro validation
AvailabilityAvailable on GitHub and Scripps website
Price / accessFree Open Source

Research fit & compatibility

No software–hardware integration has been verified for this entry yet. Explore documented research workflows.

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FAQ

Where is this product available?

Available on GitHub and Scripps website

How is pricing handled?

Prices reflect the source at its last check. Confirm current pricing and regional availability on the official site.

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Peer Reviews & Community Ratings

Feedback from researchers and computational biologists evaluating AutoDock Vina.

5.0
★★★★★Based on 0 researcher evaluations
Biological Accuracy
4.8/5
Ease of Installation
4.3/5
Documentation & Code
4.6/5