External Tools¶

OCDocker can call external docking and preparation tools. The exact requirements depend on the workflow you run.

System packages¶

Ubuntu/Debian baseline:

sudo apt-get install openbabel libopenbabel-dev swig cmake g++

DSSP, when needed:

sudo apt-get install dssp

Tool summary¶

Tool	Used for	Notes
OpenBabel	molecular conversion and preparation support	required by many docking workflows
MGLTools	Vina/Smina PDBQT preparation	configure `pythonsh`, `prepare_ligand`, and `prepare_receptor`
AutoDock Vina	docking/scoring	configure `vina` if not on `PATH`
Smina	docking/scoring	configure `smina` if not on `PATH`
Gnina	CNN-assisted docking/scoring	OCDocker expects a compatible Gnina binary
PLANTS/SPORES	PLANTS docking and preparation	configure `plants` and `spores`
ODDT	optional rescoring models	install through the relevant Python dependency stack

Gnina¶

OCDocker is configured for the Gnina CUDA 12.8 build. Ensure the NVIDIA driver and runtime are compatible with that binary.

mkdir -p gnina
wget -O gnina/gnina.1.3.2.cuda12.8 \
  https://github.com/gnina/gnina/releases/download/v1.3.2/gnina.1.3.2.cuda12.8
chmod +x gnina/gnina.1.3.2.cuda12.8
sudo install -m 0755 gnina/gnina.1.3.2.cuda12.8 /usr/bin/gnina
gnina --version

AutoDock Vina¶

mkdir -p vina
wget -O vina/vina \
  https://github.com/ccsb-scripps/AutoDock-Vina/releases/download/v1.2.3/vina_1.2.3_linux_x86_64
chmod +x vina/vina
sudo install -m 0755 vina/vina /usr/bin/vina

MGLTools¶

Download MGLTools from the official Scripps distribution, extract it, and run its installer. Then point pythonsh, prepare_ligand, and prepare_receptor in OCDocker.cfg to the installed paths.

The preparation scripts are usually under:

<installation_dir>/mgltools/MGLToolsPckgs/AutoDockTools

If MGLTools reports NumPy or Python path issues, check that your conda/system Python paths are not shadowing MGLTools’ bundled Python.

GPU checks¶

nvidia-smi
python -c "import torch; print(torch.cuda.is_available()); print(torch.cuda.device_count())"

If PyTorch cannot see the GPU, verify the driver, torch CUDA build, active conda environment, and CUDA runtime compatibility.