Add Docker Image

Dockerfile

@@ -0,0 +1,37 @@
+FROM pytorch/pytorch:2.2.1-cuda11.8-cudnn8-runtime
+
+LABEL authors="Colby T. Ford <[email protected]>"
+
+## Install system requirements
+RUN apt update && \
+    apt-get install -y --reinstall \
+        ca-certificates && \
+    apt install -y \
+        git \
+        wget \
+        libxml2 \
+        libgl-dev \
+        libgl1 \
+        gcc \
+        g++
+
+## Set working directory
+RUN mkdir -p /software/flowdock
+WORKDIR /software/flowdock
+
+## Clone project
+RUN git clone https://github.com/BioinfoMachineLearning/FlowDock /software/flowdock 
+
+## Create conda environment
+# RUN conda env create -f environments/flowdock_environment.yaml
+COPY environments/flowdock_environment_docker.yaml /software/flowdock/environments/flowdock_environment_docker.yaml
+RUN conda env create -f environments/flowdock_environment_docker.yaml
+
+## Automatically activate conda environment
+RUN echo "source activate flowdock" >> /etc/profile.d/conda.sh && \
+    echo "source /opt/conda/etc/profile.d/conda.sh" >> ~/.bashrc && \
+    echo "conda activate flowdock" >> ~/.bashrc
+
+## Default shell and command
+SHELL ["/bin/bash", "-l", "-c"]
+CMD ["/bin/bash"]

README.md

@@ -42,6 +42,7 @@ This is the official codebase of the paper
 - [How to create comparative plots of evaluation results](#how-to-create-comparative-plots-of-evaluation-results)
 - [How to predict new protein-ligand complex structures and their affinities using FlowDock](#how-to-predict-new-protein-ligand-complex-structures-using-flowdock)
 - [For developers](#for-developers)
+- [Docker](#docker)
 - [Acknowledgements](#acknowledgements)
 - [License](#license)
 - [Citing this work](#citing-this-work)
@@ -384,6 +385,33 @@ rm env.yaml # clean up temporary environment file
 
 </details>
 
+## Docker
+
+<details>
+
+Given that this tool has a number of dependencies, it may be easier to run it in a Docker container.
+
+Pull from [Docker Hub](https://hub.docker.com/repository/docker/cford38/flowdock): `docker pull cford38/flowdock:latest`
+
+
+
+Alternatively, build the Docker image locally:
+
+```bash
+docker build --platform linux/amd64 -t flowdock .
+```
+
+Then, run the Docker container (and mount your local `checkpoints/` directory)
+
+```bash
+docker run --gpus all -v ./checkpoints:/software/flowdock/checkpoints --rm --name flowdock -it flowdock /bin/bash
+
+# docker run --gpus all -v ./checkpoints:/software/flowdock/checkpoints --rm --name flowdock -it cford38/flowdock:latest /bin/bash
+```
+
+</details>
+
+
 ## Acknowledgements
 
 `FlowDock` builds upon the source code and data from the following projects:

environments/flowdock_environment_docker.yaml

@@ -0,0 +1,50 @@
+name: flowdock
+channels:
+  - pyg
+  - iopath
+  - pytorch
+  - nvidia
+  - defaults
+  - conda-forge
+dependencies:
+  - hydra-core=1.3.2=pyhd8ed1ab_0
+  - mendeleev=0.15.0=pyhc1e730c_0
+  - msgpack-python=1.0.3=py39hd09550d_0
+  - networkx=3.1=py39h06a4308_0
+  - omegaconf=2.3.0=pyhd8ed1ab_0
+  - pandas=2.1.4=py39h1128e8f_0
+  - python=3.9.17=h0755675_0_cpython
+  - pytorch=2.2.1=py3.9_cuda11.8_cudnn8.7.0_0
+  - pytorch-cuda=11.8=h7e8668a_5
+  - pytorch-mutex=1.0=cuda
+  - pytorch-scatter=2.1.2=py39_torch_2.2.0_cu118
+  - rdkit=2024.03.1=py39h6cc1c65_0
+  - rich=13.3.5=py39h06a4308_0
+  - scikit-learn=1.4.1.post1=py39ha22ef79_0
+  - scipy=1.12.0=py39h474f0d3_2
+  - torchaudio=2.2.1=py39_cu118
+  - torchtriton=2.2.0=py39
+  - torchvision=0.17.1=py39_cu118
+  - tqdm=4.66.1=pyhd8ed1ab_0
+  - pip:
+      - beartype==0.17.2
+      - biopandas==0.4.1
+      - biopython>=1.79
+      - dm-tree==0.1.8
+      - einops==0.7.0
+      - fair-esm==2.0.0
+      - hydra-colorlog==1.2.0
+      - lightning==2.2.2
+      - lightning-utilities==0.11.1
+      - lovely-numpy==0.2.11
+      - lovely-tensors==0.1.15
+      - ml-collections==0.1.1
+      - msgpack-numpy==0.4.8
+      - numpy==1.23.5
+      - git+https://github.com/amorehead/openfold.git@fe1275099639bf7e617e09ef24d6af778647dd64
+      - prody==2.4.1
+      - pytorch-lightning==2.2.2
+      - git+https://github.com/facebookresearch/pytorch3d.git@3da7703c5ac10039645966deddffe8db52eab8c5
+      - rootutils==1.0.7
+      - torchmetrics==1.3.1
+      - wandb==0.17.0