IsoDock

IsoDock is LatticeZero's GPU-accelerated molecular docking engine. It performs full pose search using a genetic algorithm optimizer, producing 3D binding poses with physics-based scores — all running in your browser via WebGPU.

Overview

How It Works

IsoDock uses a genetic algorithm to explore ligand conformations within the binding pocket:

1. Initialization — Generate an initial population of random poses within the pocket volume
2. Scoring — Evaluate each pose using the 14-term scoring function on the GPU
3. Selection — Keep the best-scoring poses
4. Crossover & Mutation — Generate new poses by combining and perturbing survivors
5. Convergence — Repeat until the population converges or max generations reached
6. Refinement — Local optimization of the best pose

The scoring function evaluates dispersion, electrostatics, hydrogen bonds, desolvation, strain, and other physics terms. See the Physics Reference for details on all 14 terms.

Using IsoDock

Prerequisites

• A prepared target with compiled scoring grid (see Target Prep)
• Ligand files in SDF or MOL2 format

Running a Docking Job

1. Navigate to Workbench > IsoDock
2. Select target — choose from your project's prepared targets
3. Upload ligands — drag & drop or browse for your SDF/MOL2 file
4. Configure options (optional):
   • Scoring profile — select a target-class-specific profile or use the default
   • Number of poses — how many poses to keep per ligand (default: 1)
   • Exhaustiveness — GA population size and generations (higher = more thorough but slower)
5. Click Run

Understanding Results

Each docked ligand receives:

• Total Score — the weighted sum of all scoring terms (more negative = better)
• Per-term decomposition — individual contributions from each physics term
• 3D Pose — the predicted binding geometry, viewable in the 3D viewer
• RMSD (if reference pose provided) — deviation from a known binding mode

Results Table Columns

Scoring Profiles

IsoDock uses a scoring profile to weight the 14 physics terms. The default profile works well for most targets, but you can improve accuracy by selecting a target-class-specific profile:

• Kinase profiles — emphasize hinge hydrogen bonds and hydrophobic burial
• Protease profiles — weight catalytic residue interactions
• Nuclear receptor profiles — prioritize aromatic burial and shape complementarity

See Scoring Profiles for the full list and customization options.

Performance Tips

• Batch size — IsoDock processes one ligand at a time. For large libraries (>100 ligands), consider using IsoScore for initial screening, then IsoDock for top hits.
• GPU matters — Discrete GPUs (NVIDIA RTX, AMD RX) are significantly faster than integrated graphics.
• File format — SDF files with 3D coordinates dock faster than SMILES-only input (avoids conformer generation).
• Pocket size — Smaller, well-defined pockets produce faster and more accurate results.

Comparison with IsoScore

Troubleshooting

Docking is slow (>10 sec/ligand)

• Check that WebGPU is active (not falling back to CPU)
• Close other GPU-intensive tabs
• Try reducing exhaustiveness

Poor poses (high scores / clashes)

• Verify your pocket definition covers the binding site
• Check that the grid compilation completed without warnings
• Try a target-class-specific scoring profile

"WebGPU not available" error

• Update your browser to Chrome 113+ or Edge 113+
• Check chrome://gpu for WebGPU status
• Ensure hardware acceleration is enabled in browser settings