Skip to main content

Antibody optimization protocol

Project description

https://img.shields.io/pypi/v/locuaz.svg Documentation Status https://zenodo.org/badge/502907107.svg

Looping Uniquely Catered Amino Acid Sequences

Install

Create a conda environment YAML file named, for example, usr_deps.yaml:

name: locuaz
channels:
  - conda-forge
dependencies:
  - conda-forge::python>=3.10
  - conda-forge::ambertools>=22.0.0
  - conda-forge::tensorflow
  - conda-forge::openbabel
  - conda-forge::pygraphviz

by running:

mamba env create -f usr_deps.yaml

Then, activate the environment and install the protocol through pip:

pip install locuaz

Check the Installation section on the docs for more info.

Post-Install

Using DLPacker based mutators

If you wish to used DLPacker based Mutators (dlp and dlpr), DLPacker weights have to be downloaded. Get them here or here. These weights have to be extracted to a dedicated folder and its path has to be specified in the input config under the paths key, on the mutator option. Check the docs for more info.

Running

After that, running locauz is as simple as:

# Activate your environment
mamba activate locuaz
# Point locuaz to your config file
locuaz config.yaml

Check the tutorials for info on how to write this config file.

Citing

Credits

MIT License

Copyright (c) [2023] [Patricio Barletta]

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

locuaz-0.7.5.4.tar.gz (70.2 MB view hashes)

Uploaded Source

Built Distribution

locuaz-0.7.5.4-py3-none-any.whl (70.3 MB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page