Significant progress has been made in computational biophysics since the 1970s with the advent of powerful computers and the development of molecular dynamics (MD) simulations and other computational techniques, enabling researchers to understand complex biological processes at the atomic level. Capitalizing on large-scale MD simulations and advanced computational approaches, this field provides useful perspectives into the molecular complexities of biological entities. From visualizing MD in real-time to predicting protein structures and drug-receptor interactions, the tools at our disposal have expanded precipitously. Techniques such as enhanced MD dynamics sampling and multiscale modeling emphasize the extent of its capabilities . Such advancements not only elucidate kinetic and thermodynamic properties of interest in complex systems but also pave the way for transformative drug design and molecular biology breakthroughs . Among the recent advances, SEEKR2 (Simulation enabled estimation of kinetic rates v. 2) has emerged as a powerful tool to compute the kinetics and thermodynamics of complex biological processes, such as receptor-ligand binding and unbinding . SEEKR2 is a multiscale simulation method that combines MD and Brownian dynamics (BD) simulations to compute the receptor-ligand binding (kon) and unbinding (k off ) rates while providing valuable insights into the underlying mechanisms.