An alternative, and readily available, source to reveal the structural basis of conformational entropy is ensemble modeling of X-ray crystallography and CryoEM data. These experiments collect ensembleaveraged data from tens of thousands to billions of individual molecules, capturing all conformations regardless of the exchange timescale. Heterogeneity of protein side chains, which contain the majority of protein conformational entropy, is often not disruptive to diffraction or alignment. While careful attention to experimental noise is needed , we have demonstrated that multiconformer modeling in high-resolution X-ray datasets can detect subtle and weak conformations, explaining statistically significant signals in the density map . The leucine side chain would have subtly different density surrounding it in each scenario. While a multiconformer model would help tease apart the contributions of different rotamers, a conventional single-state structure would almost certainly model all four examples the same way. A "crystallographic order parameter" that agrees reasonably with NMR relaxation experiments can be obtained by determining the distance between each alternative conformation and the weighted B-factor, a refined parameter to account for harmonic disorder, of each conformer . Importantly, it is not limited to methyl-containing side chains and, due to the timeaveraged nature of diffraction or single particle imaging, this metric extends to timescales beyond the pico-nanosecond timescale of NMR order parameters. Ideally, molecular dynamics (MD) simulations could directly observe the fluctuations of residue upon perturbation , but significant protein dynamics happen on a timescale inaccessible to MD , necessitating hybrid approaches that bias agreement to experimentally observed order parameters . Collectively, these techniques are beginning to quantify thstructural basis of conformational entropy. (B) Upon folding, the majority of the protein is structured. This results in a large loss of entropy in the leucine side chain. The leucine can only access two states, separated by an energy barrier. One conformation has significantly more harmonic entropy, as shown by a wider energy well (teal) relative to the other conformation (purple). B-factors model this harmonic motion in X-ray crystallography. The simplified energy landscape of the leucine side chain alone is shown. (C) When one ligand binds, the leucine loses an additional conformation, reducing its conformational entropy to one state (teal). This is also observed by narrowing the energy landscape well. (D) However, when a different ligand binds, with different interactions and no direct contact with the leucine residue, the leucine gains conformational entropy by accessing three of five rotamer states, but again with different widths due to differences in harmonic motion between each conformer. This leads to an increase in conformational entropy for this residue upon ligand binding relative to the unbound state. This would observed as an increased disorder in NMR order parameters, but 3 alternative conformations in X-ray or cryoEM data. (E) Another example of a leucine gaining conformational entropy upon ligand binding. While the leucine has the same number of accessible rotamer states as in the apo state (2), the harmonic motion in both rotamer states greatly increases. This would be observed as an increase in disorder in NMR order parameters, but 2 alternative conformations with increased B-factors in X-ray or cryoEM data.