Open-Sourced In Silico Drug Screening

Advances in structure-based computer-aided drug design have yielded robust computational techniques now pivotal for chemical biologists. These tools predict small molecule-protein interactions, significantly accelerating the drug discovery process. Unlike other computational techniques, structure-based design requires prior knowledge of a target molecule's three-dimensional structure, often leveraging molecular docking to predict target-ligand interactions. The primary goal is to design or identify small molecules that can bind to the target with high affinity and modulate its activity. Once a target's binding site(s) are determined, high-throughput in silico screens of large chemical libraries can predict binding energies, non-covalent interactions, and intermolecular forces crucial for target-ligand binding. These powerful methods accelerate the bench-to-bedside process, aiding in the repurposing of FDA-approved drugs, identifying novel ligands, and informing rational drug design, optimization, and/or elucidation of mechanism(s) of action. In this chapter, we describe a structure-based computational approach to perform high-throughput ligand screens of chemical libraries using open-source software programs. We illustrate this workflow with the enzymatic molecular target NAD(P)H:quinone oxidoreductase1 (NQO1), which is overexpressed in a number of human solid tumors. Importantly, this adaptable workflow requires minimal coding knowledge.