BrunaPavlack/kallisto

The Kallisto software enables the efficient calculation of atomic features that can be used within a quantitative structure-activity relationship (QSAR) approach. Furthermore, several modelling helpers are implemented.

Table of Contents

• Full Author List
• Introduction
• Installation
• Reference

Full Author List

Eike Caldeweyher and Philipp Pracht

Introduction

We developed the kallisto program for the efficient and robust calculation of atomic features using molecular geometries either in a xmol or a Turbomole format. Furthermore, several modelling tools are implemented, e.g., to calculate root-mean squared deviations via quaternions (including rotation matrices), sorting of molecular geometries and many more. All features of kallisto are described in detail within our documentation.

Installation

kallisto runs on python3

Python development setup. Install the pyenv python version manager:

curl https://pyenv.run | bash

and add this to the ~/.bashrc and source it:

export PATH="~/.pyenv/bin:$PATH"
eval "$(pyenv init -)"
eval "$(pyenv virtualenv-init -)"

Install the latest python versions:

pyenv install 3.8.2
pyenv install 3.7.7
pyenv local 3.8.2 3.7.7

Now we are ready to set up kallisto. Clone the repository:

git clone git@github.com:AstraZeneca/kallisto.git

Install a python dependency manager. We choose to go with poetry:

curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python
source ~/.poetry/env

or alternatively via pip:

pip install --user poetry

Now, if you haven't already done so, change into the cloned kallisto directory and download the dependencies via poetry:

cd kallisto
poetry install

Finally install the test automation environment nox via pip:

pip install --user --upgrade nox

Run nox to test the setup.

Reference

tba