TeachOpenCADD 2021: Open Source and FAIR Python Pipelines to Assist in Structural Bioinformatics and Cheminformatics Research

13 December 2021, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

Computational pipelines have become a crucial part of modern drug discovery campaigns. Setting up and maintaining such pipelines, however, can be challenging and time-consuming --- especially for novice scientists in this domain. TeachOpenCADD is a platform that aims to teach domain-specific skills and to provide pipeline templates as starting points for research projects. We offer Python-based solutions for common tasks in cheminformatics and structural bioinformatics in the form of Jupyter notebooks and based on open source resources only. Including the 12 newly released additions, TeachOpenCADD now contains 22 notebooks that each cover both theoretical background as well as hands-on programming. To promote reproducible and reusable research, we apply software best practices to our notebooks such as testing with an automated continuous integration and adhering to a more idiomatic Python style. The new TeachOpenCADD website is available at https://projects.volkamerlab.org/teachopencadd and all code is deposited on GitHub.

Keywords

Python
Cheminformatics
Structural bioinformatics
FAIR
open source
Jupyter notebooks
TeachOpenCADD
Molecular dynamics
One-hot encoding
Docking
Binding site detection
KLIFS
PubChem

Supplementary weblinks

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