Journal of Cheminformatics (Apr 2019)

TeachOpenCADD: a teaching platform for computer-aided drug design using open source packages and data

  • Dominique Sydow,
  • Andrea Morger,
  • Maximilian Driller,
  • Andrea Volkamer

DOI
https://doi.org/10.1186/s13321-019-0351-x
Journal volume & issue
Vol. 11, no. 1
pp. 1 – 7

Abstract

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Abstract Owing to the increase in freely available software and data for cheminformatics and structural bioinformatics, research for computer-aided drug design (CADD) is more and more built on modular, reproducible, and easy-to-share pipelines. While documentation for such tools is available, there are only a few freely accessible examples that teach the underlying concepts focused on CADD, especially addressing users new to the field. Here, we present TeachOpenCADD, a teaching platform developed by students for students, using open source compound and protein data as well as basic and CADD-related Python packages. We provide interactive Jupyter notebooks for central CADD topics, integrating theoretical background and practical code. TeachOpenCADD is freely available on GitHub: https://github.com/volkamerlab/TeachOpenCADD.

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