pss

Using predicted protein structure data from DeepMind's AlphaFold to explore structural similarities among all 23K+ proteins in the human proteome.

Conventions

• When referring to proteins in code or in datasets, use the full filename (ex.: AF-Q7Z5P9-F10-model_v1).

Environment Setup

Local

1. Install miniconda: https://docs.conda.io/projects/conda/en/latest/user-guide/install/macos.html
2. conda env create -f environment.yml --force
3. conda activate pss
4. [upon changes to environment.yml] conda env update -f environment.yml

Colab/JupyterLab

1. Pull in environment.yml into directory
2. In top cell add:

%%bash
MINICONDA_INSTALLER_SCRIPT=Miniconda3-4.5.4-Linux-x86_64.sh
MINICONDA_PREFIX=/usr/local
wget https://repo.continuum.io/miniconda/$MINICONDA_INSTALLER_SCRIPT
chmod +x $MINICONDA_INSTALLER_SCRIPT
./$MINICONDA_INSTALLER_SCRIPT -b -f -p $MINICONDA_PREFIX

conda install --channel conda-forge -f environment.yml

Both:

Install BLAST+

1. Download the BLAST+ utilities from the NIH. Make sure you download the right executable based on your architecture (ex.: Linux, Colab or Google Cloud JupyterLab should use the Linux X64 tarball).
2. Unpack the archive into blast/.
3. Run chmod 777 -R blast/ to change permissions on the executables such that you can run them.
4. Add blast/bin/ to your PATH.

Install TMAlign

1. Download the TM-Align C++ source from Yang Zhang's Research Group at the University of Michigan into tmalign/.
2. Run chmod 777 -R tmalign/.
3. Compile the cpp file using (from your notebook directory /): g++ -static -O3 -ffast-math -lm -o tmalign/TMalign tmalign/TMalign.cpp.
4. Add tmalign/ to your PATH.