All unique small molecule drug structures were docked against the helicase protein structure using the AutoDock Vina (version 1.1.3) package . AutoDock Vina employs a gradient-based conformational search approach and an energy-based empirical scoring function. AutoDock Vina is also flexible, easily scripted, extensively validated in many published studies with a variety of proteins and ligands and takes advantage of large multi-CPU or -GPU machines to run many calculations in parallel. The code has also been employed very successfully to dock millions of small molecule drug candidates into a series of protein targets to discover new potent drug leads. The package includes useful scripts for generating modified .pdb files required for grid calculations and for setting up the grid calculations around each protein automatically. AutoDock Tools (ADT) was used to prepare the required files for Autodock Vina. Non-essential heteroatoms, unnecessary protein chains or substructures (if any) and water molecules were removed, non-polar hydrogen atoms were added to the protein structure and structure converting to .pdbqt format. Binding pockets were predicted using castp () AutoDock Vina requires the removal of hydrogens, the addition of polar hydrogens, setting of the correct atom types, and calculation of atom charges compatible with the AutoGrid code. The algorithm generates a grid around each protein and calculates the interaction energy of a probe noble gas atom at each grid position outside and within the internal cavities of the protein. The grid size used was 137.6 x 210.1 x 135.1Å. Grid resolution was set to 1 Å, the maximum number of binding modes to output was fixed at 10, and the exhaustiveness level (controlling the number of independent runs performed) was set at 8. The docking calculations employed a genetic algorithm to optimize the binding conformations of the ligands during docking to the helicase site. Drugs were docked individually to the active site of the helicase with the grid coordinates (grid centre) and grid boxes of appropriate sizes generated by the bash script vina_screen.sh (Supplementary Information). The top-scoring compounds were identified with a python script script1.py (Supplementary Information) and subjected to molecular dynamics simulation. The docked structures were analysed using UCSF Chimera and LigPlot+ software to illustrate hydrogen-bond and hydrophobic interactions . The 87 drugs from Drugbank database with the most favourable helicase binding energies were selected (see Supplementary Information). Molecular dynamics studies were subsequently conducted on this set of 87 compounds.