TeachOpenCADD-KNIME: A Teaching Platform for Computer-Aided Drug Design Using KNIME Workflows.

Area of Science:

• Computational chemistry
• Drug discovery informatics

Background:

• Open-source workflows are crucial for reproducible computer-aided drug design (CADD).
• Existing methods often require coding expertise or complex workflow managers.
• The TeachOpenCADD platform previously provided educational Jupyter Notebooks for CADD topics.

Purpose of the Study:

• To convert TeachOpenCADD educational materials into a code-free, graphical user interface (GUI) format.
• To enhance accessibility of CADD education for a broader audience.
• To enable users to explore CADD concepts without programming knowledge.

Main Methods:

• Conversion of existing Jupyter Notebooks (talktorials) into KNIME workflows.
• Utilizing the KNIME Analytics Platform for workflow development and deployment.
• Leveraging open-source data and Python packages within the KNIME environment.

Main Results:

• Successfully created interactive KNIME workflows from TeachOpenCADD talktorials.
• Provided a no-code solution for learning central CADD topics.
• Made these KNIME workflows freely available on the KNIME Hub.

Conclusions:

• KNIME workflows significantly lower the barrier to entry for CADD education.
• This approach promotes wider adoption and understanding of CADD principles.
• The TeachOpenCADD KNIME workflows facilitate accessible, reproducible CADD learning.