Installation¶

Quick Installation¶

Using Conda Environment (Recommended)¶

The easiest way to install EasyDock with all dependencies:

conda env create -f env.yml

This installs EasyDock with Vina (docking), MolGpKa (protonation), ProLIF and PoseBusters.

Manual Installation¶

Install EasyDock Package¶

From PyPI:

pip install easydock

From GitHub (latest development version):

pip install git+https://github.com/ci-lab-cz/easydock.git

Required Dependencies¶

From Conda¶

conda env create -n easydock
conda install -c conda-forge python=3.11 rdkit numpy==1.26
conda install -c conda-forge scipy dask distributed scikit-learn

Additional for macOS:

conda install -c conda-forge boost swig

From PyPI¶

pip install paramiko vina prolif gemmi

Meeko (recommended development version):

pip install git+https://github.com/forlilab/Meeko.git@develop

The development version includes fixes that make double bonds non-rotatable, improving accuracy.

Or current release version:

pip install git+https://github.com/forlilab/Meeko.git

Optional Docking Programs¶

Gnina/Smina¶

Installation instructions at https://github.com/gnina/gnina

QVina2 and QVina-W¶

Installation instructions at https://github.com/QVina/qvina

Vina-GPU Family¶

Vina-GPU, QVina2-GPU, and QVinaW-GPU installation at https://github.com/DeltaGroupNJUPT/Vina-GPU-2.1

Pre-built Docking Containers¶

CarsiDock:

The build downloads model checkpoints (~1 GB) from Google Drive and GitHub. An internet connection is required.

cd containers/carsidock

# Apptainer
apptainer build carsidock.sif carsidock_server.def

# Docker
docker build -t carsidock .

Other server-based containers (SurfDock and Vina-GPU) are created in the same way from the corresponding receipt files. Vina-GPU server will include both CPU and GPU Vina family programs (Vina, QVina2 and QVina-W).

Optional Protonation Tools¶

MolGpKa (Recommended)¶

pip install git+https://github.com/ci-lab-cz/MolGpKa.git
pip install torch_geometric
pip install torch==2.2 torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu

For Linux:

pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv \
    -f https://data.pyg.org/whl/torch-2.2.0+cpu.html

For macOS:

pip install torch-scatter torch-sparse torch-cluster torch-spline-conv \
    -f https://data.pyg.org/whl/torch-2.2.0+cpu.html

pkasolver¶

pip install torch==1.13.1+cpu --extra-index-url https://download.pytorch.org/whl/cpu
pip install torch-geometric==2.0.1
pip install torch_scatter==2.1.1 -f https://data.pyg.org/whl/torch-1.13.1%2Bcpu.html
pip install torch_sparse==0.6.17 -f https://data.pyg.org/whl/torch-1.13.1%2Bcpu.html
pip install torch_spline_conv==1.2.2 -f https://data.pyg.org/whl/torch-1.13.1%2Bcpu.html
pip install cairosvg svgutils
pip install git+https://github.com/Feriolet/dimorphite_dl.git
pip install git+https://github.com/DrrDom/pkasolver.git

Containerized Protonation Tools¶

Protonation tools can also be packaged as Apptainer/Singularity or Docker containers and launched via --protonation /path/to/container.sif (or a Docker image name). Make sure your OS has the container runtime installed first — see Container Support for OS-specific setup.

Pre-built Protonation Containers¶

Build from source (Uni-pKa):

cd containers/unipka

# Apptainer
apptainer build unipka.sif unipka.def

# Docker
docker build -t unipka .

Usage example:

easydock -i input.smi -o output.db -c 4 --protonation /path/to/unipka.sif

Container Support¶

EasyDock supports running external tools through Apptainer/Singularity or Docker containers. This section covers the OS-level runtime setup. For concrete container recipes and pre-built images, see Containerized Docking Programs and Containerized Protonation Tools.

Linux¶

Install Singularity or Apptainer following their official documentation. Docker is also supported if preferred.

macOS¶

EasyDock supports Docker natively on macOS. Install Docker and ensure CLI access without sudo — no additional setup is required.

Running SIF Containers via Apptainer Proxy (Advanced)¶

If you need to run Apptainer SIF containers on macOS, you can set up a Docker-based Apptainer proxy. Create a file named Dockerfile:

FROM ubuntu:22.04

RUN apt-get update && apt-get install -y \
    wget build-essential squashfs-tools uidmap fuse3 git \
    && rm -rf /var/lib/apt/lists/*

RUN wget https://github.com/apptainer/apptainer/releases/download/v1.3.4/apptainer_1.3.4_amd64.deb \
    && dpkg -i apptainer_1.3.4_amd64.deb

ENTRYPOINT ["apptainer"]

Switch to the directory with Dockerfile and build the container:

docker build -t apptainer:latest --platform=linux/amd64 .

EasyDock will automatically use the apptainer:latest image as a proxy to run SIF containers.

Windows¶

Install EasyDock in Windows Subsystem for Linux (WSL) to use container features.

Optional Analysis Tools¶

PoseBusters¶

PoseBusters provides physics-based validation of docked poses. Required for the easydock_bust tool and the --bust flag of get_sdf_from_easydock.

pip install posebusters

Verification¶

Verify installation:

easydock --help

You should see the help message with available options.