Alchemical Free Energy (AFE) simulations have emerged as a powerful computational approach for lead optimization in drug design, offering precise predictions of protein-ligand binding affinity. The selection of an appropriate timestep is critically important in these simulations due to their complex nature involving non-physical intermediate states. While traditional approaches have relied on subjective criteria such as ensuring stable trajectories or arbitrary numerical comparisons, current recommendations range from a 1 fs timestep when constraints cannot be applied to alchemical regions to a 4 fs timestep when using the SHAKE algorithm and Hydrogen Mass Repartitioning (HMR). Despite these recommendations, a significant gap remains in the systematic evaluation of timestep selection for AFE simulations. The existing literature lacks a comprehensive and quantitative examination of optimal temporal resolution, particularly for the proposed 4 fs timestep using SHAKE and HMR. This absence of rigorous guidelines is particularly problematic given the nuanced interplay between computational precision and efficiency in AFE calculations, where the choice of timestep can substantially influence the accuracy of protein-ligand binding affinity predictions.