Running molecular docking involves various computational strategies depending on the resources available and the scale of the docking project. For small-scale docking tasks, molecular docking can be performed on a single CPU. This involves installing docking software, preparing the input files, and running the docking process using command-line or graphical interface. This method is straightforward but can be time-consuming if the ligand library is large. Almost all docking software can utilize multiple CPU cores to parallelize the docking process, significantly reducing the computation time. This is achieved by setting the number of CPUs in the docking command, which allows the software to run multiple docking calculations simultaneously. For larger datasets, high-performance computing (HPC) clusters can be used. These systems involve multiple CPUs working in parallel, managed by job scheduling systems like PBS or SLURM. Docking tasks are distributed among the CPUs, greatly enhancing the throughput of virtual screening campaigns. Some docking tools have been optimized to run on Graphics Processing Units (GPUs), which can perform calculations faster than CPUs for certain types of computational tasks.