Additionally, consider the number of useful biological constructs being simulated: Is the fluctuation of a single wild-type protein sufficient to answer the scientific question, or would multiple mutants or different ligand-bound states need to be observed? The number of constructs multiplies the number of parallel simulations needed to run, which impacts the computational requirements to generate the dataset. With biomolecular simulations, one must also consider biochemical details such as the protonation states of your system. The protonation state of residues such histidine, cysteine, and others, can have a large impact on biochemical properties such as binding affinity or enzymatic activity . Some titratable systems may also contain multiple highly populated tautomers, requiring one to consider multiple possible protonation states simultaneously, multiplying the required sampling .