https://github.com/volkamerlab/kissim
Subpocket-based fingerprint for kinase pocket comparison
https://github.com/volkamerlab/kissim
Last synced: 7 months ago
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Subpocket-based fingerprint for kinase pocket comparison
- Host: GitHub
- URL: https://github.com/volkamerlab/kissim
- Owner: volkamerlab
- License: mit
- Created: 2019-07-29T13:23:16.000Z (almost 7 years ago)
- Default Branch: main
- Last Pushed: 2023-09-24T14:41:45.000Z (over 2 years ago)
- Last Synced: 2024-11-28T02:35:09.859Z (over 1 year ago)
- Language: Python
- Homepage: https://kissim.readthedocs.io
- Size: 115 MB
- Stars: 32
- Watchers: 2
- Forks: 4
- Open Issues: 9
-
Metadata Files:
- Readme: README.md
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
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README
Structural kinase similarity (`kissim`)
==============================
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**Subpocket-based structural fingerprint for kinase pocket comparison**
## Description
The `kissim` package offers a novel fingerprinting strategy designed specifically for kinase pockets,
allowing for similarity studies across the structurally covered kinome.
The kinase fingerprint is based on the [KLIFS](klifs.net/) pocket alignment,
which defines 85 pocket residues for all kinase structures.
This enables a residue-by-residue comparison without a computationally expensive alignment step.
The pocket fingerprint consists of 85 concatenated residue fingerprints,
each encoding a residue’s spatial and physicochemical properties.
The spatial properties describe the residue’s position in relation to the kinase pocket center and
important kinase subpockets, i.e. the hinge region, the DFG region, and the front pocket.
The physicochemical properties encompass for each residue its size and pharmacophoric features, solvent exposure and side chain orientation.
Take a look at the [repository `kissim_app`](https://github.com/volkamerlab/kissim_app) for pairwise comparison of all kinases to study kinome-wide similarities.
## Documentation
The `kissim` package documentation is available [here](https://kissim.readthedocs.io/), including [installation instructions](https://kissim.readthedocs.io/en/latest/installing.html).
## Contact
Please [open an issue](https://github.com/volkamerlab/kissim/issues) if you have questions or suggestions.
We are looking forward to hearing from you!
## License
This work is published under the [MIT license](https://github.com/volkamerlab/kissim/blob/master/LICENSE).
Copyright (c) 2019, Volkamer Lab
## Citation
Have you used `kissim` in your research or found the tool useful? We'd be very grateful if you cited it using the following:
```
@article{sydow_2022_jcim,
author = {Sydow, Dominique and Aßmann, Eva and Kooistra, Albert J. and Rippmann, Friedrich and Volkamer, Andrea},
title = {KiSSim: Predicting Off-Targets from Structural Similarities in the Kinome},
journal = {Journal of Chemical Information and Modeling},
volume = {62},
number = {10},
pages = {2600-2616},
year = {2022},
doi = {10.1021/acs.jcim.2c00050}
```
## Acknowledgements
### Funding
Volkamer Lab's projects are supported by several public funding sources
(for more info see our [webpage](https://volkamerlab.org/)).
### 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
- [KLIFS](https://klifs.net/)
#### Python packages
- Cheminformatics and structural bioinformatics:
[`opencadd`](https://opencadd.readthedocs.io/en/latest/),
[`biopython`](https://biopython.org/),
[`biopandas`](http://rasbt.github.io/biopandas/)
- Data science (PyData stack):
[`numpy`](https://numpy.org/),
[`pandas`](https://pandas.pydata.org/),
[`scipy`](https://scipy.org/),
[`jupyter`](https://jupyter.org/),
[`ipywidgets`](https://ipywidgets.readthedocs.io)
- Data visualization:
[`matplotlib`](https://matplotlib.org/),
[`seaborn`](https://seaborn.pydata.org/),
[`nglview`](http://nglviewer.org/nglview/latest/)
- Continuous integration:
[`pytest`](https://docs.pytest.org),
[`nbval`](https://nbval.readthedocs.io)
- Documentation:
[`sphinx`](https://www.sphinx-doc.org),
[`nbsphinx`](https://nbsphinx.readthedocs.io)
- Code style:
[`black-nb`](https://github.com/tomcatling/black-nb)
#### Repository
Project is based on the
[Computational Molecular Science Python Cookiecutter](https://github.com/molssi/cookiecutter-cms) version 1.5.