Awesome
Chainsaw
Chainsaw is a deep learning method for predicting protein domain boundaries for a given protein structure.
If you find Chainsaw useful in your research, please cite:
Chainsaw: protein domain segmentation with fully convolutional neural networks
Jude Wells, Alex Hawkins-Hooker, Nicola Bordin, Brooks Paige and Christine Orengo
Installation
Ensure that python 3.8, 3.9, 3.10, or 3.11 is installed, then install dependencies with
the command bash setup.sh
Optional:
To visualise the domain assignments, ensure that you have pymol installed and update the
PYMOL_EXE
variable in src/constants.py
to point to the pymol executable.
Chainsaw is tested on Linux and MacOS. It may work on Windows but this is not guaranteed.
Usage
python get_predictions.py --structure_file /path/to/file.pdb
or
python get_predictions.py --structure_directory /path/to/pdb_or_mmcif_directory
Note that the output predicted boundaries are based on residue consecutive indexing starting from 1 (not based on pdb auth numbers).
Installation Troubleshooting
If setup.sh fails follow the instructions below:
-
install stride: source code and instructions are packaged in this repository in the
stride
directory. See stride/README_stride for instructions. -
install the python dependencies:
pip install -r requirements.txt
-
test it's working by running
python get_predictions.py --structure_file example_files/AF-A0A1W2PQ64-F1-model_v4.pdb --output results/test.tsv
by default the output will be saved in theresults
directory.