Improved structural characterizations of the drkN SH3 domain unfolded state suggest a compact ensemble with native-like and non-native structure

Due to their dynamic ensemble nature and a deficiency of experimental restraints, disordered states of proteins are difficult to characterize structurally. Here, we have expanded upon our previous work on the unfolded state of the Drosophila drk N-terminal (drkN) SH3 domain with our program ENSEMBLE, which assigns population weights to pregenerated conformers in order to calculate ensembles of structures whose properties are collectively consistent with experimental measurements. The experimental restraint set has been enlarged with newly measured paramagnetic relaxation enhancements from Cu2+ bound to an amino terminal Cu2+-Ni2+ binding (ATCUN) motif as well as nuclear Overhauser effect (NOE) and hydrogen exchange data from recent studies. In addition, two new pseudo-energy minimization algorithms have been implemented that have dramatically improved the speed of ENSEMBLE population weight assignment. Finally, we have greatly improved our conformational sampling by utilizing a variety of techniques to generate both random structures and structures that are biased to contain elements of native-like or non-native structure. Although it is not possible to uniquely define a representative structural ensemble, we have been able to assess various properties of the drkN SH3 domain unfolded state by performing ENSEMBLE minimizations of different conformer pools. Specifically, we have found that the experimental restraint set enforces a compact structural distribution that is not consistent with an overall native-like topology but shows preference for local non-native structure in the regions corresponding to the diverging turn and the beta 5 strand of the folded state and for local native-like structure in the region corresponding to the beta 6 and beta 7 strands. We suggest that this approach could be generally useful for the structural characterization of disordered states. (c) 2007 Elsevier Ltd. All rights reserved.