“…There have been strides to incorporate experimental techniques with computation, with efforts spanning back to the 1980s with NMR and X-ray crystallography and more recently EPR, MS, and cryo-EM among others. − HDX experiments, originally probed in the 1970s, have been used to map exchange rates onto atomic-resolution structures to assign dynamic properties to otherwise static representations. ,− In the general case, HDX rates have also been coupled to molecular dynamics simulations to explain variation in different regions of a protein. ,− Additionally, these data have been incorporated into protein–protein docking of complexes with known tertiary structure to elucidate quaternary structure. − However, importantly, HDX rates have not yet been used to predict de novo tertiary structure. Previous implementations for structural characterization rely on either homology modeling or some starting structures such as an alternative conformation of a protein or a designed protein. − While there are multiple software packages with impressive results that exist for ab initio structure prediction, such as the co-evolution-dependent neural network AlphaFold, the secondary structure assembling BCL, or iterative threading I-TASSER, none have been coupled to experimental data as frequently or diversely as the Rosetta Modeling Software. ,,,,,− Rosetta ab initio structure prediction allows for the generation of models from amino acid sequence alone, assembling fragments generated from short segments with similar sequences using Monte Carlo sampling combined with a hybrid classical physics and probabilistic knowledge-based scoring function in both coarse-grained and full-atom modeling, similar to other multiscale modeling methods. ,…”