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Calculate protein structural representations (dihedral angles, CA pairwise distances, and strain analysis) for downstream analysis (e.g., PCA, t-SNE, or UMAP).

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# colav

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`colav` (Conformational Landscape Visualization) provides tools for representing protein structures and mapping conformational landscapes.

`colav` supports calculations for dihedral angles, pairwise distances, and strain. It is built on `biopandas`, `NumPy`, and `SciPy`. The methods analyze `.pdb` files, either one-by-one or all together. The three methods currently implemented are:

## Installation

You can install `colav` using `pip`:

```
pip install colav
```

## Documentation

Documentation can be found [here](https://hekstra-lab.github.io/colav/).

## Examples

Examples of how to use the software can be found in `scripts/`.

## Support

If you are having issues, please email Ammaar at aasaeed@college.harvard.edu or file an [issue](https://github.com/Hekstra-Lab/colav/issues).

## License

This code is provided under the [MIT license](LICENSE).

## Reference

If you use `colav` in your work, please use the following citation: <br>
Saeed, A.A., Klureza, M.A., and Hekstra, D.R. (Forthcoming!). Mapping protein conformational ensembles using crystallographic drug fragment screens. [doi]()

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