Intrinsically disordered proteins (IDPs) lack a traditional three-dimensional structure or the so-called “native state fold,” unlike other structured proteins. IDPs, rather, exist in a dynamic ensemble in solution characterized by interchanging conformations. This inherent flexibility enables IDPs to perform diverse cellular functions, from signaling to regulation to molecular recognition, thereby playing important roles in molecular machines that include ribosomes, chromatin, nuclear pore transporters, cytoskeletal assembly, and phase-separated organelles. Because IDPs play a central role in several important biological pathways, pharmaceutical researchers have been trying to identify small-molecular ligands that target them. Finding such ligands, however, is not straightforward, because the structural characterization of IDPs is non-trivial. Even the residual structures in IDPs are difficult to characterize by routine structure determination techniques, including X-ray, cryo-EM, and NMR.

Other techniques that shed light on the flexibility of IDPs include measuring NMR relaxation parameters, chemical shift data, and translational diffusion. Diffusion measurements in solution, in particular, provide information about the compactness of a protein by linking diffusion coefficients with the hydrodynamic radii. NMR-based diffusion measurements have indeed allowed the successful characterization of IDPs of varied sizes, providing information about hydrophobic clusters and residual secondary structures. Unlike structured proteins, for which NMR experimental data are translated into three-dimensional models of proteins, for IDPs, the diffusion data are combined with the molecular dynamics (MD) pool of conformations to match the experimental and predicted relaxation rates.

In a study titled “Using NMR diffusion data to validate MD models of disordered proteins: Test case of N-terminal tail of histone H4” Skrynnikov and co-workers used the translational diffusion coefficient (obtained by NMR-based measurements) to validate the MD-simulated models of IDPs. The authors used the N-terminal tail of the histone H4 protein, which plays an important role in regulating gene transcription and chromatin restructure and remodeling, as a test case for this study. The authors found that the predicted values of diffusion coefficient, as obtained from the mean-square displacement of the peptide in the MD simulations, are largely determined by the viscosity of the MD water (which was also reinvestigated as a part of the study). The authors also discuss the issues in predicting translational diffusion coefficients for MD conformations, the corrections that need to be applied, issues with corrections, and applications of these empirical methods to IDPs. The first-principle approach used in this study for direct determination of the translation diffusion coefficient from MD simulations may provide a benchmark for further studies in IDPs.