Design and Implementation of an Accessible and Open-Sourced In Silico Drug Screening Activity for Cancer Drug Discovery

Abstract

The application of chemistry concepts in biological settings plays an important role in the interdisciplinary field of drug discovery and development. This is true for molecular docking, where an understanding of intermolecular forces and noncovalent interactions is useful for rational drug design and development. Here we report the design and use of a molecular docking activity for cancer drug discovery for users that requires minimal coding knowledge. Although used in a drug discovery context, this activity can be incorporated into a range of undergraduate/graduate chemistry and biochemistry courses either as a stand-alone activity or integrated into existing curricula. The activity uses AutoDock Vina, AutoDockTools, Strawberry Perl, and PyMOL, all of which are free, open-source software. The activity is used to carry out molecular docking of multiple ligands at once and predict the binding energy of hits identified from a high-throughput drug repurposing screen against a target enzyme overexpressed in human tumors. Students analyze their docking results to determine drugs that should go on to further in vitro testing based on the predicted noncovalent ligand–protein interactions. This activity serves as an introduction to molecular docking and as a review of intermolecular forces, highlighting their importance in biological fields.