In recent years there has been an increasing emphasis on making bona fide predictions and then testing these predictions with wetlab experiments. Multiple studies demonstrate quantitative agreement between MSMs, simulation-based predictions, and a variety of experiments . These results demonstrate that existing force fields are accurate enough for many applications, given that sufficiently large datasets are collected. For example, we have shown that the agreement between different 10 ns simulations and NMR experiments is highly variable, but that 10 µs simulations reliably yield quantitative agreement with these experiments . In agreement with NMR and room-temperature crystallography, MSMs also reveal substantial dynamics in protein cores despite the tight packing that one could imagine would prevent conformational changes . Given the advancement in modern force fields that enable large datasets to be directly compared to experiment, it is important to consider what experimental measurements one will make to test the predictions generated from your analysis. A classic avenue to compare simulations to experiments involves the use of computing binding affinities from large-scale simulation datasets and comparing them with measured quantities from experimental assays. Some methods, like Free Energy calculations (described later) provide a direct estimation of binding affinity, while other methods can extract these affinities from equilibrium datasets. Such methods leverage scoring functions from docking methods to predict the binding affinity of a protein-ligand complex; these methods estimate on a singular protein conformation. By having mulitple structures from MD simulations, one can asssess the impact of multiple likely conformations on binding and identify multiple new binding modes. By using populations information from an MSM, one can reweight the binding affinities directly by scaling each protein-ligand binding score by the population of that conformation from an MSm. Recent papers have shown that using large equilibrium MD conformations and their population derived MSMs improve binding affinity predictions from docking scores by reweighting the score per conformation . Future methods have demonstrated their capability to not just improve docking scores using multiple conformations, but in turn provide the necessary framework to estimate population shifts caused by inhibitor binding .