🚀 Interactive Consensus Docking Now Live
The consensus docking pipeline (ESMFold → AutoDock Vina → GNINA) is now available as an interactive tool. Launch Consensus Docking →
Molecular Docking — Protein-Ligand Docking with Consensus Scoring Live
What is this tool?
A protein-ligand molecular docking platform that predicts how small molecules bind to protein targets. It combines ESMFold for protein structure prediction from amino acid sequences, AutoDock Vina for physics-based pose screening, and GNINA for deep-learning re-scoring. Built for structural biologists and computational chemists who need reliable binding affinity predictions.
Predict protein-ligand binding affinities using a 3-stage consensus pipeline. VigyanLLM Molecular Docking runs ESMFold structure prediction, AutoDock Vina screening, and GNINA CNN re-scoring — all with no software installation required.
Launch Interactive Docking →Free tier available. Academic discounts for .ac.in / .edu emails.
Last updated: July 2026 · Reviewed by VigyanLLM Research Team
Molecular Docking Capabilities
Protein-Ligand Docking
Screen small molecules against protein targets with configurable search parameters. Consensus scoring combines physics-based and deep-learning methods.
- AutoDock Vina scoring
- GNINA CNN re-scoring
- Consensus ranking (Vina + GNINA)
- Ligand efficiency metrics
ESMFold Structure Prediction
Predict protein 3D structure from amino acid sequence using Meta's ESM-2 transformer model. No experimental structure required.
- Sequence-to-structure in seconds
- pLDDT confidence scores
- Works with any amino acid sequence
Blind Docking
Identify binding sites automatically when the target pocket is unknown. Full surface scanning identifies potential binding cavities.
- Grid mapping across protein surface
- Auto-binding pocket detection
- Consensus cavity detection
- Druggability assessment
Consensus Scoring
Combine physics-based (Vina) and deep-learning (GNINA) scoring for more reliable predictions than either method alone.
- Weighted consensus ranking
- Reduced false positives
- Cross-validation against PDBbind
- Ranking stability analysis
Binding Affinity Prediction
Calculate predicted binding energies using ensemble scoring functions. Rank compounds by predicted affinity for virtual screening.
- Vina affinity scoring (kcal/mol)
- GNINA CNN confidence scores
- Consensus scoring combination
- Hit-rate improvement over single engines
Research Use Only
All docking results are computational predictions that require independent experimental validation. Not validated for clinical diagnostic use.
- Research-grade output
- Full audit trails
- Transparent methodology
- Scientific references included
Ready to Run Your First Docking?
Enter a protein sequence and ligand SMILES. The pipeline predicts the structure, screens poses, and ranks by consensus score.
Consensus Docking on Hosted Servers
VigyanLLM is a protein-ligand molecular docking tool that combines ESMFold for structure prediction, AutoDock Vina for pose screening, and GNINA for CNN re-scoring. The pipeline runs on our hosted servers, enabling binding affinity calculation and pose generation with inputs handled under our Privacy policy.
| Input | Output |
|---|---|
| Protein amino acid sequence or PDB file | Ranked docking poses with binding affinity scores (kcal/mol) |
| Ligand SMILES strings | ESMFold-predicted 3D structure with pLDDT confidence scores |
| Docking parameters (exhaustiveness, top N) | Vina + GNINA consensus scores with CNN-scored refinement |
Frequently Asked Questions About Protein Docking Tool
Everything you need to know about using this tool
Is the docking tool free?
Docking runs cost $1.00 each as a pay-as-you-go top-up — no subscription required for occasional use. Molecular docking is computationally intensive, so subscriptions provide the best value for regular use.
What docking algorithms are used?
The tool uses AutoDock Vina for physics-based pose screening and GNINA for CNN re-scoring. The consensus pipeline combines both methods for more reliable predictions.
What file formats are accepted?
The tool accepts amino acid sequences (text) and SMILES strings for ligands. PDB file support is planned for a future release.
Do I need an account?
No, you can run a basic docking without an account. Creating an account helps track your results and access advanced features like batch screening and export.
How do I get unlimited docking access?
Buy docking runs at $1.00 each, or subscribe through VigyanLLM starting at $9.99/month for Pro access. Academic researchers with a verified .edu or .ac.in email get 30% off.