Proteins are inherently dynamic systems whose motions cover large ranges in both magnitude and timescale. Because of the omnipresence of motion, it is likely that dynamics have important roles in the function of biomolecules. For detailed understanding of a protein's function, the three-dimensional structure and description of its dynamics are therefore required. Structure determination methods are well established, and NMR-relaxation phenomena provide insights into local molecular dynamics; moreover, recently several attempts have been made to detect concerted motion. Here, we present an ensemble-based structure-determination protocol using ensemble-averaged distance restraints obtained from exact NOE rates. Application to the model protein GB3 establishes an ensemble of structures that reveals correlated motion across the β-sheet, concerted motion between the backbone and side chains localized in the structure core, and a lack of concerted conformational exchange between the β-sheet and the α-helix.

Despite high sequence homology among the p53 family members, the regulation of their transactivation potential is based on strikingly different mechanisms. Previous studies revealed that the activity of TAp63α is regulated via an autoinhibitory mechanism that keeps inactive TAp63α in a dimeric conformation. While all p73 isoforms are constitutive tetramers, their basal activity is much lower compared with tetrameric TAp63. We show that the dimeric state of TAp63α not only reduces DNA binding affinity, but also suppresses interaction with the acetyltransferase p300. Exchange of the transactivation domains is sufficient to transfer the regulatory characteristics between p63 and p73. Structure determination of the transactivation domains of p63 and p73 in complex with the p300 Taz2 domain further revealed that, in contrast to p53 and p73, p63 has a single transactivation domain. Sequences essential for stabilizing the closed dimer of TAp63α have evolved into a second transactivation domain in p73 and p53.

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The highly flexible nature of RNA provides a formidable challenge for structure-based drug design approaches that target RNA. We introduce an approach for modeling target conformational changes in RNA−ligand docking based on potential grids that are represented as elastic bodies using Navier's equation. This representation provides an accurate and efficient description of RNA−ligand interactions even in the case of a moving RNA structure. When applied to a data set of 17 RNA−ligand complexes, filtered out of the largest validation data set used for RNA−ligand docking so far, the approach is twice as successful as docking into an apo structure and still half as successful as redocking to the holo structure. The approach allows considering RNA movements of up to 6 Å rmsd and is based on a uniform and robust parametrization of the properties of the elastic potential grids, so that the approach is applicable to different RNA−ligand complex classes.