Theoretical and Computational Chemistry

Icolos: A workflow manager for structure based post-processing of de novo generated small molecules

Authors

Abstract

We present Icolos, a workflow manager written in Python as a tool for automating complex structure-based workflows. Icolos can be used as a standalone tool, for example in virtual screening campaigns, or can be used in conjunction with deep learning-based molecular generation facilitated for example by REINVENT, a previously published de novo design package. In this publication, we focus on the internal structure and general capabilities of Icolos, using docking experiments as an illustration. The source code is freely available at https://github.com/MolecularAI/Icolos under the Apache 2.0 licence. Tutorial notebooks containing minimal working examples can be found at https://github.com/MolecularAI/IcolosCommunity.

Content

Thumbnail image of manuscript.pdf

Supplementary material

Thumbnail image of Icolos_SI.pdf
Manual for docking workflow steps
Contains explanations and instructions for workflow steps (docking) referred to in the main manuscript

Supplementary weblinks

Icolos code-base
Open-source repository of the Icolos code-base
Icolos tutorials
Repository containing notebooks for illustration
Repository with test data
Holds necessary data files for the unit tests and notebooks in Icolos