What is AutoDock Vina?
AutoDock Vina is a molecular docking program for predicting how a small molecule fits into a protein binding site and for ranking candidate poses by a learned empirical scoring function. It is widely used in structure-based drug discovery because it combines relatively fast search with practical accuracy for routine protein-ligand docking.
On ProteinIQ, the AutoDock Vina interface exposes the current Vina family workflow rather than only the original 2010 defaults. That includes the standard Vina scoring function, the Vinardo variant, and an AutoDock4 scoring option for cases where metal coordination or legacy AutoDock behavior is relevant.
Applications
- Pose prediction: Reproducing or approximating the bound conformation of a ligand in a known binding pocket
- Virtual screening: Ranking a focused compound set against one receptor under a consistent search setup
- Lead optimization: Comparing analogs after small structural changes to prioritize compounds for synthesis or assay
- Binding-site hypothesis testing: Evaluating whether a proposed pocket can accommodate a ligand with plausible geometry
How to use AutoDock Vina online
ProteinIQ runs AutoDock Vina in the browser with cloud execution, so receptor preparation, ligand submission, and docking outputs are available without local installation or command-line setup. The web form supports single-ligand docking, simultaneous co-docking, and small batch runs against the same receptor.
Inputs
| Input | Description |
|---|
Protein (Receptor) | Upload a receptor structure as .pdb or .ent, or fetch one by 4-character PDB ID such as 1HSG. Protein atoms are required, and the validator warns when the uploaded file appears to contain nucleic acids or YASARA-specific formatting. |
Ligand | Provide ligand input as SMILES text, a supported structure file (.pdbqt, .sdf, .mol, .mol2, .smiles, .smi, .txt, .csv), or fetch by PubChem. One ligand is used in Single ligand mode, up to 5 ligands in Simultaneous co-docking, and up to 10 entries in Batch. |
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Ligand validation blocks metal-containing ligands and disconnected multi-fragment submissions in the standard Vina workflow. Those cases are better suited to GNINA or to a more specialized docking setup.
Core settings
| Setting | Description |
|---|
Scoring function | Vina is the default general-purpose choice. Vinardo uses a modified empirical model often favored for virtual screening benchmarks. AutoDock4 uses the classical AutoDock4 force-field-style scoring and is the required option for hydrated ligand and zinc-specific workflows in this interface. |
Docking mode | Dock performs a full search. Score only evaluates the submitted pose without searching. Local only refines the input pose locally. Randomize only generates randomized ligand placement without full docking output ranking. |
Exhaustiveness | Search thoroughness from 1 to 64, with a default of 8. Larger values increase runtime but improve the chance of recovering lower-energy poses. |
Number of poses |
Search space settings
| Setting | Description |
|---|
Search mode | Auto builds a search region around the receptor, Manual exposes explicit center and size fields, and Autobox generates a receptor-centered box with configurable padding. |
Center X, Center Y, Center Z | Coordinates of the search-box center in Manual mode. |
Size X, Size Y, Size Z | Search-box dimensions in A. Smaller boxes are faster and usually more reliable when the binding site is already known. |
Auto-box padding (A) | Extra padding added around the automatically determined search region. |
Advanced settings
| Setting | Description |
|---|
Flexible residues | Comma-separated residues such as A:315,:42 to model selected side-chain flexibility during docking. |
Hydrated ligand workflow | Treats explicit ligand-associated waters as part of the docking setup. Available only with AutoDock4 scoring. |
Zinc metalloprotein mode | Uses zinc-focused receptor preparation assumptions. Available only with AutoDock4 scoring. |
Disable post-docking refinement | Skips the final local refinement step for faster turnaround at some cost to pose quality. |
Continue batch on ligand error | In Batch mode, keeps processing later ligands if one entry fails validation or preparation. |
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Results
ProteinIQ returns docked poses in an interactive structure viewer together with downloadable files and a tabular result summary. In batch runs, each ligand is processed separately under the same receptor and parameter set, which makes the output suitable for side-by-side ranking.
| Output | Description |
|---|
Viewer | Interactive 3D view of receptor and docked pose geometry |
Data | Table of scored poses and associated output files |
Files | Downloadable structure files for the generated docking poses |
Interpreting results
The affinity score reported by Vina-family methods is most useful as a relative ranking within one consistent experiment. Absolute kcal/mol values should not be treated as direct substitutes for measured binding free energies, especially across different targets, protonation states, or receptor preparations.
| Affinity range | Typical interpretation |
|---|
| < -10 kcal/mol | Very favorable predicted binding |
| -7 to -10 kcal/mol | Strong docking score worth follow-up |
| -5 to -7 kcal/mol | Moderate score that often needs visual inspection |
| > -5 kcal/mol | Weak or uncertain binding hypothesis |
Pose geometry matters as much as score. A slightly worse score with sensible hydrogen bonding, steric fit, and ligand burial is often more credible than the top-ranked pose if that pose shows clashes or unrealistic exposure. For batch docking, comparisons are most meaningful when all ligands were prepared with the same protonation and tautomer assumptions.
How does AutoDock Vina work?
AutoDock Vina combines an empirical scoring function with stochastic global search and local optimization. The ligand is translated, rotated, and flexed inside a predefined search volume; each candidate pose is scored; and promising conformations are refined before final clustering and ranking.
Scoring
The default Vina model uses weighted steric, hydrophobic, hydrogen-bonding, and penalty terms to approximate binding favorability. Vinardo modifies the empirical parameterization for improved enrichment in some screening tasks. AutoDock4 uses the older AutoDock4-style interaction terms and is sometimes preferred when metal-aware behavior or older benchmarking conventions are needed.
Search
Vina's optimizer uses multiple independent runs with random initialization. Within each run it alternates broad perturbation steps with local refinement, then keeps the best solutions discovered across the search. The Exhaustiveness parameter increases the amount of independent search effort, while Number of poses and Energy range control how many alternative solutions survive to the final report.
Flexible residue docking
Most docking calculations on this page keep the receptor rigid apart from ligand torsions. When Flexible residues are specified, selected side chains are allowed to move, which can recover poses that rigid docking would miss. The tradeoff is a larger search space and higher runtime, so flexible docking is usually reserved for a few residues with a clear mechanistic reason to move.
Limitations
- Rigid receptor approximation: Whole-protein backbone motion is not modeled, so induced-fit effects can still be missed even when a few side chains are flexible.
- Approximate scoring: Docking scores support prioritization, not definitive affinity prediction.
- Preparation sensitivity: Protonation state, tautomer choice, bound waters, and search-box placement can change rankings substantially.
- Metal handling: Standard Vina scoring is not a good default for metal-dependent binding chemistry.
- Large or highly flexible ligands: Search quality drops as conformational complexity increases, even when runtime is increased.
- GNINA: Vina-derived docking with convolutional neural network rescoring and better support for metal-containing ligands
- DiffDock: Diffusion-based docking that can be useful when the binding site is uncertain
- AutoDock-GPU: High-throughput AutoDock workflow for larger screening workloads
- HADDOCK3: Integrative docking platform for complexes that benefit from experimental restraints
