Molecular Dynamics (MD) simulation has become an essential tool in biology since it was first attempted in 1977 on a folded globular protein, the bovine pancreatic trypsin inhibitor, by McCammon et al. MD simulations provide an unparalleled avenue for exploring biomolecules at the atomic level, affording researchers the opportunity to delve into the intricate details of their structure, dynamics, and interactions. This in-depth understanding, has proven invaluable in advancing our comprehension of biological processes. As a result, MD simulations now serve as valuable tools for various fields, specially in drug design. Accurately simulating the dynamics of large biomolecules in explicit solvent environments demands substantial computational resources. Recent advancements in computational resources, particularly the advent of highly efficient and cost-effective GPU-accelerated simulations, have significantly expanded the accessible timescales and broadened the scope of molecular dynamics (MD) simulations. To further extend the current reachable timescales, it is necessary to utilize various algorithmic techniques in MD simulations.