AutoDock Vina is an open-source molecular docking program for predicting ligand poses and supporting virtual screening.
The published feature set includes multiple scoring modes, batch docking, specialized docking protocols, and Python bindings. It is free under Apache 2.0, but installation and workflow preparation require scientific-computing tools. No reliable public product-review ratings were verified, so sentiment and support scores have low confidence.
This profile combines documented product information and independent evidence where available. It is not a hands-on test unless TechZella explicitly identifies one.
AutoDock Vina is a molecular docking engine in the AutoDock software suite. It searches for ligand poses and scores predicted interactions with a receptor structure. The Forli Lab at Scripps Research maintains the project.
Researchers can use the command-line program, Python bindings, or integrate Vina into larger workflows. It is software for computational research, not a hosted drug-discovery service; preparing molecular structures and interpreting predictions may require other tools and domain expertise.
A quick way to understand who this product may suit, where its limits matter, and which facts are most relevant before you compare alternatives.
Research teams and computational chemists who need a free, scriptable engine for small-molecule docking or virtual-screening workflows.
Buyers seeking a hosted turnkey platform, built-in graphical workflow, or a complete ligand and receptor preparation suite may need additional tools, and should evaluate alternatives such as GNINA or smina instead.
Linux, macOS, Windows
7.5/10
These are the product-specific differences that may matter when deciding whether the software fits your workflow. They are based on documented evidence rather than a universal ranking.
These are documented constraints or practical friction points that may matter before you adopt the product.
A scripted setup may require separate installation steps for the Python package and command-line application.
Evidence source ↗A predicted pose or score alone does not establish experimental binding or suitability as a drug candidate.
Evidence source ↗Available under the Apache License, Version 2.0. No paid plans or official free-trial terms were found.
Check current pricing →Pricing may change. Verify current plans on the vendor's website.
Compare similar products directly, then see which alternatives may make more sense when your requirements differ.
| Decision factor | AutoDock Vina | GNINA | smina |
|---|---|---|---|
| Core scoring approach | Provides Vina and AutoDock4 scoring options; the project also documents Vinardo. | Adds convolutional-neural-network scoring and optimization to its molecular docking workflow. Source ↗ | Fork of Vina with a focus on scoring-function development and energy minimization. Source ↗ |
| Python bindings | Provides Python 3 bindings, documented for Linux and macOS. | Its project describes a command-line docking program and does not present Python bindings as a core feature. Source ↗ | The cited smina project documents a command-line program and customizable scoring options. Source ↗ |
| Pricing model | Open-source software distributed under Apache License 2.0. | Open-source repository lists Apache and GNU license files. Source ↗ | The cited smina project is distributed as open-source software. Source ↗ |
Only factors supported by the available research are shown. The comparison is descriptive, not a ranking.
These products address broadly similar requirements. The descriptions focus on documented reasons a buyer might compare them with AutoDock Vina.
| License | Apache License 2.0 |
|---|---|
| Latest release found | 1.2.7 |
| Primary workflow | Molecular docking and virtual screening |
| Python bindings | Python 3; Linux and macOS documented |
| Installation | Local binaries, source build, or Python package |
Verified installation, hosting, administration, or environment details that can affect implementation.
| Installation or hosting | Locally installed software distributed as executable binaries, source code, and Python bindings; no official hosted SaaS deployment was identified. Source ↗ |
|---|---|
| License | Apache License, Version 2.0. Source ↗ |
Documented portability, standards, export, or switching considerations. No switching-cost score is shown unless the evidence supports one.
The software reads and writes structure and docking files, including PDBQT output; workflows may also use other preparation and analysis tools.
Evidence source ↗A proprietary editorial score based on product capabilities, usability, value, performance, support and user sentiment evidence.
The published feature set includes multiple scoring modes, batch docking, specialized docking protocols, and Python bindings. It is free under Apache 2.0, but installation and workflow preparation require scientific-computing tools. No reliable public product-review ratings were verified, so sentiment and support scores have low confidence.
Methodology v1.0. The assessment weighs feature coverage (25%), ease of use (15%), value for money (20%), performance (15%), support (10%) and user sentiment (15%), using researched product evidence and verified review evidence where available. It is a TechZella editorial assessment, not a direct user-review average.
Key claims are linked to the sources used to verify them. This evidence record is separate from third-party user ratings.
TechZella evaluates software using documented product capabilities, pricing information, usability and value considerations, independent user evidence where available, and competitive context. The assessment is an editorial review, not a hands-on test unless one is explicitly identified. Our editorial assessment is based on 4 documented sources.
The project repository describes it as a docking and virtual-screening program and identifies its Apache 2.0 license.
View source ↗Verified 2026-11-10The project README and the peer-reviewed version 1.2.0 paper describe these methods and capabilities.
View source ↗Verified 2026-11-10The installation documentation explicitly distinguishes the binding and binary installation processes.
View source ↗Verified 2026-11-10The official manual advises evaluating predictive accuracy against the user's particular target.
View source ↗Verified 2026-11-10Answers begin with the clearest available response, followed by the context that helps you act on it.
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