# resp_protein_toolkit
A toolkit designed to perform some common tasks in protein
engineering, especially encoding protein sequences (in various
formats), assisting in fitting uncertainty-aware models to
data, and using a trained model to search for improved candidates
using the RESP pipeline from [Parkinson et al. 2023 (Nature
Communications).](https://www.nature.com/articles/s41467-023-36028-8)
For an example of the full RESP pipeline, including uncertainty-aware
model training, please [see this repo.](https://github.com/Wang-lab-UCSD/RESP)
### Installation
```
pip install resp_protein_toolkit
```
Alternatively, to install from github, clone this repo, then
from inside the resulting directory run:
```
pip install . --verbose
```
### Usage
For usage and general guidelines, see [the docs](https://resp-protein-toolkit.readthedocs.io/en/latest/).
### Citations
If using this toolkit in work intended for publication, please cite:
[Parkinson, J., Hard, R. & Wang, W. The RESP AI model accelerates the identification of tight-binding antibodies.
Nat Commun 14, 454 (2023).](https://doi.org/10.1038/s41467-023-36028-8)
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