Solutions · 6 workflows
Virtual screening
Find the compounds in a library most likely to bind your target, then rescore the best hits with a stronger method.
- Screen a compound library against a targetSMILES → 3D embed → dock
- Find top binding poses with diffusion dockingSMILES → DiffDock → top poses
- Screen an ultra-large combinatorial libraryThompson Sampling → 3D embed → dock
- Rescore docking hits with a CNN scoring functionVina triage → GNINA rescore
- Re-predict docking hits with Boltz-2 affinitiesVina triage → Boltz-2 re-predict (batch)
- Re-dock top hits with surface-aware diffusionVina triage → SurfDock (scatter)
- Workflows
- 6
- Stages
- 5
- Tools
- 8
Your library
Imatinib Nilotinib Dasatinib Your target
A pose in the pocket
- Target
- ABL1 kinase domain
- Structure
- PDB 2HYY · 2.4 Å
- Polar contacts
- 6
Workflows
Pick the one that fits.
Open any of them in the builder: signed out you get a read-only preview, signed in you can add your inputs, see the estimate for your plan, and run. The cost cap is the default; you can change it at launch, and a run pauses instead of spending past it.
- simple3 steps
Screen a compound library against a target
SMILES → 3D embed → dock
Convert SMILES to 3D structures, detect pockets, then dock with AutoDock Vina.
- You provide
- Molecules (SMILES), Protein structure (PDB)
- Runs on
- CPU
- Cost cap
- $10.00 default
- simple2 steps
Find top binding poses with diffusion docking
SMILES → DiffDock → top poses
Dock a SMILES library with DiffDock and keep the top-confidence poses.
- You provide
- Molecules (SMILES), Protein structure (PDB)
- Runs on
- T4 GPU
- Cost cap
- $110.00 default
- moderate4 steps
Screen an ultra-large combinatorial library
Thompson Sampling → 3D embed → dock
Screen a combinatorial library with Thompson Sampling, embed hits to 3D, detect pockets, then dock with AutoDock Vina.
- You provide
- Protein structure (PDB)
- Runs on
- CPU
- Cost cap
- $15.00 default
- moderate5 steps
Rescore docking hits with a CNN scoring function
Vina triage → GNINA rescore
Detect pockets, dock with AutoDock Vina, keep the top poses, and rescore with GNINA.
- You provide
- Molecules (SMILES), Protein structure (PDB)
- Runs on
- CPU · T4 GPU
- Cost cap
- $25.00 default
- moderate5 steps
Re-predict docking hits with Boltz-2 affinities
Vina triage → Boltz-2 re-predict (batch)
Detect pockets, dock a ligand set, keep the top poses, and re-predict affinities with Boltz-2 in batch.
- You provide
- Molecules (SMILES), Protein structure (PDB)
- Runs on
- CPU · A10 GPU
- Cost cap
- $25.00 default
- advanced6 steps
Re-dock top hits with surface-aware diffusion
Vina triage → SurfDock (scatter)
Detect pockets, dock with AutoDock Vina, keep the top hits, and re-dock each ligand with SurfDock (one GPU job per ligand).
- You provide
- Molecules (SMILES), Protein structure (PDB)
- Runs on
- CPU · A10 GPU
- Cost cap
- $25.00 default
Related tools
Run any step on its own.
The tools behind these workflows also run individually.
- Molecule Conversion
Convert molecule file/data format
- Binding-Site Detector
Find ligandable pockets and emit Vina-shaped docking boxes for fold-to-dock workflows
- AutoDock Vina
High performance molecular docking and virtual screening for drug discovery
- DiffDock
Protein-ligand docking with diffusion models and confidence-ranked poses
- Thompson Sampling
Active-learning virtual screening of un-enumerated combinatorial libraries via Thompson Sampling
- GNINA
CNN-accelerated protein–ligand docking and rescoring
- Boltz-2
Accurate in silico screening for early-stage drug discovery
- SurfDock
Surface-informed diffusion docking with a reference-ligand pocket and screen-model rescoring