VLVS: A Knime Based Virtual Library Generation and Screening Workflow

Abstract

Objective: Tocreate an easy-to-use structure-based screening workflow using KNIME and open source software to prepare and screen virtual libraries in order to discover novel bioactive or drug molecules. Materials and Methods: In the preparation of the workflow we mentioned in the article KNIME version 4, AutoDock Vina, Pymol were used. KNIME plugins used in this study are RDKit KNIME Integration, ChemAxon/Infocom Marvin Extensions Feature, KNIME Python Integration, Lhasa Metabolism Feature, KNIME Ploty and KNIME JavaScript View. We have used Python3 and libraries in the python scripts through Anaconda installation. Results: A workflow that can work with a single click after making required adjustments which uses docking as structure-based screening method was created and tested. Conclusion: With the workflow we have created, it will be possible for researchers especially those who are working in the field of computer-aided drug design/development to create personalized molecule libraries, perform virtual screening, reporting the results in a short time with the least effort.