Dockerfile

# Use the specified PyTorch image
FROM pytorch/pytorch:1.9.0-cuda11.1-cudnn8-devel

# Set the working directory
WORKDIR /app

# GPG workaround for CUDA
RUN rm /etc/apt/sources.list.d/cuda.list
RUN rm /etc/apt/sources.list.d/nvidia-ml.list

# Install wget and other required tools
RUN apt-get update && \
    apt-get install -y wget git

# Clone the RFdiffusion repository
RUN git clone https://github.com/RosettaCommons/RFdiffusion.git .

# Install miniconda
RUN wget https://repo.anaconda.com/miniconda/Miniconda3-py39_4.10.3-Linux-x86_64.sh && \
    chmod +x Miniconda3-py39_4.10.3-Linux-x86_64.sh && \
    ./Miniconda3-py39_4.10.3-Linux-x86_64.sh -b -p /app/miniconda && \
    rm Miniconda3-py39_4.10.3-Linux-x86_64.sh

# Set the path to include miniconda
ENV PATH /app/miniconda/bin:$PATH

# Download the model weights
RUN mkdir models && cd models && \
    wget http://files.ipd.uw.edu/pub/RFdiffusion/6f5902ac237024bdd0c176cb93063dc4/Base_ckpt.pt && \
    wget http://files.ipd.uw.edu/pub/RFdiffusion/e29311f6f1bf1af907f9ef9f44b8328b/Complex_base_ckpt.pt && \
    wget http://files.ipd.uw.edu/pub/RFdiffusion/60f09a193fb5e5ccdc4980417708dbab/Complex_Fold_base_ckpt.pt && \
    wget http://files.ipd.uw.edu/pub/RFdiffusion/74f51cfb8b440f50d70878e05361d8f0/InpaintSeq_ckpt.pt && \
    wget http://files.ipd.uw.edu/pub/RFdiffusion/76d00716416567174cdb7ca96e208296/InpaintSeq_Fold_ckpt.pt && \
    wget http://files.ipd.uw.edu/pub/RFdiffusion/5532d2e1f3a4738decd58b19d633b3c3/ActiveSite_ckpt.pt && \
    wget http://files.ipd.uw.edu/pub/RFdiffusion/12fc204edeae5b57713c5ad7dcb97d39/Base_epoch8_ckpt.pt && \
    wget http://files.ipd.uw.edu/pub/RFdiffusion/f572d396fae9206628714fb2ce00f72e/Complex_beta_ckpt.pt

# Create and activate the SE3nv conda environment
RUN conda env create -f /app/env/SE3nv.yml
SHELL ["conda", "run", "-n", "SE3nv", "/bin/bash", "-c"]

# Install SE3-Transformer and RFdiffusion
RUN cd /app/env/SE3Transformer && \
    pip install --no-cache-dir -r requirements.txt && \
    python setup.py install && \
    cd ../.. && \
    pip install -e .

# Set env parameters
RUN export PATH=“/app/miniconda3/bin:$PATH”
ARG PATH /app/miniconda/bin:$PATH
RUN echo "source activate SE3nv" >> ~/.bashrc
ENV PATH /app/miniconda/envs/SE3nv/bin:$PATH
ENV CONDA_DEFAULT_ENV $SE3nv

# Untar the provided scaffold files
RUN tar -xvf /app/examples/ppi_scaffolds_subset.tar.gz -C /app/examples

CMD ["bash"]