Kinome-wide structural pocket similarity

All-against all comparison of structurally covered kinases using the kissim fingerprint.

Project Organization

├── LICENSE
├── README.md          <- The top-level README for this project.
├── data
│   ├── external       <- Data from third party sources.
│   ├── interim        <- Intermediate data that has been transformed.
│   ├── processed      <- The final, canonical data sets.
│   └── raw            <- The original, immutable data dump.
│
├── devtools           <- Test and user environment; script to generate notebook folder READMEs.
│   ├── test_env.yaml
│   ├── user_env.yaml
│   └── regenerate_readmes.py
│
├── docs               <- A default Sphinx project; see sphinx-doc.org for details (not used by us so far).
│
├── notebooks          <- Jupyter notebooks.
│
├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
│   └── figures        <- Generated graphics and figures to be used in reporting.
│
├── results            <- Encodings (fingerprints) and comparisons. Needs to be downloaded from zenodo as described in the installation section.
│
├── setup.py           <- Makes project pip installable (pip install -e .) so src can be imported.
│
├── scripts            <- KiSSim and other scripts; includes README with details.
│
├── src                <- Source code for use in this project.
│   ├── __init__.py    <- Makes src a Python module.
│   ├── data           <- Download or generate data.
│   ├── evaluation     <- Evaluate data and results.
│   ├── definitions.py <- Module definitions.
│   ├── paths.py       <- Module paths to data and results folders.
│   └── utils.py       <- Module utility functions.
│
├── test               <- Test data, results, and scripts for CI notebook checks.
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└── tox.ini            <- tox file with settings for running tox; see tox.readthedocs.io

Installation

We are assuming you have a working mamba installation in your computer. If this is not the case, please refer to their official documentation. If you installed mamba into an existing conda installation, also make sure that the conda-forge channel is configured by running conda config --add channels conda-forge.

1. Clone this repository.

   git clone [email protected]:volkamerlab/kissim_app.git
   

2. Create the kissim-app conda environment.

   # Change to kissim_app directory
   cd /path/to/kissim_app
   
   # Create and activate environment
   mamba env create -f devtools/user_env.yaml
   conda activate kissim-app
   
   # Install the kissim_app src package (pip)
   cd ..
   pip install -e kissim_app
   

3. Download (a) kissim fingerprints and distances to results/ folder and (b) KLIFS structures to data/external/structures folder as described in our zenodo release (some files were just not suitable upload to GitHub).

4. Open the notebooks, e.g. a quick start on how to load kissim results.

   # Change to kissim_app notebook directory
   cd /path/to/kissim_app/notebooks
   
   # Start JupyterLab to explore the notebooks
   jupyter lab
   

Contact

If you have questions or suggestions regarding the notebooks in this repository, please open an issue here.

If you have questions or suggestions regarding the kissim package, please open an issue here.

We are looking forward to hearing from you!

License

This work is published under the MIT license.

Copyright (c) 2020, Volkamer Lab

Acknowledgements

Funding

Volkamer Lab's projects are supported by several public funding sources (for more info see our webpage).

Collaborators

The kissim project is a collaboration between the Volkamer Lab (Dominique Sydow, Eva Aßmann and Andrea Volkamer), Albert Kooistra (University of Copenhagen), and Friedrich Rippmann (Merck).

External resources

Databases/websites

• KLIFS
• KinMap

Python packages

See Python packages listed in the kissim repository README.

Repository

Project based on the cookiecutter data science project template. #cookiecutterdatascience