Protein structure tokenizers have been limited by their focus on static structures, neglecting the dynamic conformational states of proteins. Ensembits addresses this shortcoming by introducing a novel tokenizer that captures the correlated motions and alternative conformational states revealed by protein ensembles. This innovation has significant implications for protein language modeling, function prediction, and evolutionary analysis. By accounting for the complex dynamics of protein structures, Ensembits enables a more nuanced understanding of protein behavior and function. The development of Ensembits marks a crucial step forward in the field of protein analysis, as it provides a more comprehensive representation of protein structures1. This matters to practitioners because it can lead to breakthroughs in fields such as drug discovery and disease research, where understanding protein behavior is critical.