🚀 Interactive Consensus Docking Now Live
The consensus docking pipeline (ESMFold → AutoDock Vina → GNINA) is now available as an interactive tool. Launch Consensus Docking →
AI Protein Docking & Molecular Simulation Platform Live
What is this tool?
This AI-powered protein docking and molecular simulation platform predicts protein-protein interactions, protein-ligand binding affinities, and supports molecular dynamics simulations. It is built for structural biologists, computational chemists, and drug discovery researchers who need sovereign AI tools.
Predict protein-protein interactions and protein-ligand binding affinities using sovereign AI. VigyanLLM Protein Docking runs fully on-premises — no external API calls, no data leaving your institution, and full audit trails for every simulation.
Launch Interactive Docking →Free for academic researchers. On-premises deployment available.
Last updated: July 2026 · Reviewed by VigyanLLM Research Team
Molecular Docking & Simulation Capabilities
Protein-Protein Docking
Predict 3D structures of protein complexes using rigid-body and flexible docking algorithms. Interface residue analysis and binding free energy scoring included.
- Rigid-body docking (ZDOCK-style)
- Flexible refinement (RDOCK)
- Interface residue prediction
- Binding free energy (MM-GBSA)
Protein-Ligand Docking
Screen small molecules against protein targets with configurable search parameters. Grid-based scoring with genetic algorithm optimisation.
- AutoDock Vina-compatible scoring
- Genetic algorithm conformational search
- Binding pose clustering
- Ligand efficiency metrics
Blind Docking
Identify binding sites automatically when the target pocket is unknown. Full surface scanning identifies all potential binding cavities.
- Grid mapping across entire protein surface
- Binding site prediction (Fpocket)
- Consensus cavity detection
- Druggability scoring
Molecular Dynamics
Run short-timescale molecular dynamics simulations to refine docked poses and assess complex stability. Temperature and pressure control.
- NPT and NVT ensemble support
- AMBER/CHARMM force fields
- Solvent box with periodic boundaries
- RMSD and energy trajectory analysis
Binding Affinity Prediction
Calculate binding free energies using ensemble-based scoring functions. Rank compounds by predicted affinity for virtual screening.
- MM-PBSA/GBSA free energy
- Machine learning affinity prediction
- Consensus scoring (ML + physics-based)
- Enrichment factor calculation
On-Premises Sovereignty
All simulations run on your hardware. No data transmitted externally. Full encryption, audit logging, and compliance with institutional data governance policies.
- Zero external API calls
- Encrypted PDB file storage
- Audit-ready simulation reports
- HIPAA/GDPR compliant logging
Ready to Run Your First Docking Simulation?
Submit a PDB file or UniProt ID. VigyanLLM predicts binding partners, scores interactions, and generates a full simulation report.
Get Started →GPU-Accelerated Docking with Local AI
VigyanLLM is an autonomous molecular docking tool that utilizes virtual screening with AI-driven protein-ligand binding prediction. Unlike standard web docking tools, it runs entirely on your local GPU via Docker, enabling binding affinity calculation and pose generation without transferring proprietary drug targets to external servers.
| Input | Output |
|---|---|
| Protein structure (PDB/PDBQT) + Ligand (SDF/PDBQT) | Top docking poses with binding affinity scores (kcal/mol) |
| UniProt ID for structure retrieval | ESMFold-predicted 3D structure with confidence metrics |
| Docking parameters (exhaustiveness, box center/size) | 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 Protein Docking tool free?
The protein docking tool offers 5 free docking analyses per user. Molecular docking simulations are computationally intensive and use GPU-accelerated backend resources. After 5 free uses, a subscription is required.
What docking algorithms are used?
The tool supports AutoDock Vina and GNINA (CNN-scored docking) for accurate protein-ligand and protein-protein docking pose prediction and scoring.
What file formats are accepted?
PDB and PDBQT formats are accepted for both receptor and ligand files. The tool includes basic structure preparation options.
Do I need an account?
No, you can use protein docking without an account for your first 5 analyses. Account creation helps track usage.
How do I get unlimited docking access?
Subscribe through VPrime 2.0 starting at ₹99/day. Academic researchers at partner institutions may qualify for free access.