data/software/README.md

Software setup

This directory contains installation instructions for the third-party docking software used by the OpenBind docking workflow.

GNINA, Smina, and DiffDock are not included in this repository and must be installed separately. The paths to the installed software, optional Singularity/Apptainer images, and Slurm profiles are configured in ../configs/docking/software_settings.yaml.

Expected directory structure

A local installation can follow this structure:

software/
├── gnina/
│   ├── gnina
│   └── gnina_singularity.sif          # optional
├── smina/
│   └── smina
└── DiffDock/
    ├── inference.py
    ├── default_inference_args.yaml
    └── diffdock_singularity.sif        # optional

The exact locations are configurable, so this structure is recommended rather than required.

Software and Slurm configuration

Update ../configs/docking/software_settings.yaml after installation. For example:

methods:
  diffdock:
    executable: software/DiffDock/
    singularity: software/DiffDock/diffdock_singularity.sif
    profile: gpu

  gnina:
    executable: software/gnina/gnina
    singularity: software/gnina/gnina_singularity.sif
    profile: gpu

  smina:
    executable: software/smina/smina
    profile: cpu

Relative paths are resolved from the OpenBind docking repository root.

The profiles section accepts Slurm options as key-value pairs and passes them through as #SBATCH directives. Add the settings required by your cluster, for example partition, account, cluster, or qos. Boolean true values are emitted as flag-only options, while false, empty, and null values are omitted.

profiles:
  gpu:
    cpus-per-task: 8
    mem: 16G
    time: "24:00:00"
    gres: gpu:1
    account: my-project
    partition: gpu
    exclusive: true

No site-specific partition, account, or cluster is set in the repository defaults.

Optional Singularity / Apptainer environments

Optional Singularity/Apptainer images can be used for GNINA and DiffDock. These images provide reproducible runtime dependency environments for the locally installed software; the executable or DiffDock source tree is still provided separately through software_settings.yaml.

They are primarily useful for:

• HPC environments;
• CUDA compatibility;
• avoiding dependency conflicts; and
• improving reproducibility across systems.

If a Singularity image is configured for a GPU Slurm profile, the OpenBind launcher adds GPU support when the profile requests a GPU resource.

GNINA

Recommended version: v1.3.2

Create the software directory:

mkdir -p software/gnina

Download the precompiled GNINA binary:

wget https://github.com/gnina/gnina/releases/download/v1.3.2/gnina.1.3.2
mv gnina.1.3.2 software/gnina/gnina
chmod +x software/gnina/gnina

Optional Singularity image

singularity pull software/gnina/gnina_singularity.sif \
    oras://ghcr.io/jnelen/gnina_singularity:v1

Smina

Download Smina from its project page and place the executable at:

software/smina/smina

Then make it executable:

chmod +x software/smina/smina

DiffDock

Clone DiffDock into software/:

cd software
git clone https://github.com/gcorso/DiffDock.git
cd ..

Follow the official DiffDock installation instructions to install its Python dependencies and model files. For reproducible benchmark runs, record and reuse the exact DiffDock version or commit used for the calculation.

Important: configure the number of generated poses

DiffDock reads inference settings from:

software/DiffDock/default_inference_args.yaml

The value of samples_per_complex in this file must match methods.diffdock.num_modes in the OpenBind docking experiment YAML.

For the supplied A71EV2A benchmark configuration:

methods:
  diffdock:
    num_modes: 40

set the DiffDock configuration to:

samples_per_complex: 40

This manual change is required because the current DiffDock inference implementation loads default_inference_args.yaml after parsing command-line arguments. As a result, the YAML value for samples_per_complex overrides a value supplied on the command line.

The OpenBind runner checks this setting before starting DiffDock and raises a clear error if the two values do not match. This prevents a run configured for, for example, 40 poses from silently producing the DiffDock YAML default instead.

If you change methods.diffdock.num_modes for another experiment, update samples_per_complex in default_inference_args.yaml to the same value before submitting the jobs.

Optional Singularity image

singularity pull software/DiffDock/diffdock_singularity.sif \
    oras://ghcr.io/jnelen/diffdock_singularity:v1

Final checks

Before submitting a benchmark, confirm that:

• the configured executable and installation paths exist;
• any configured Singularity/Apptainer images exist;
• the required Slurm profile contains the settings needed by your cluster;
• GNINA and Smina binaries are executable; and
• DiffDock samples_per_complex matches methods.diffdock.num_modes in the experiment configuration.

For method-specific installation or advanced configuration, refer to the corresponding upstream documentation.