Well-defined, stereospecific states in protein complexes are often in exchange with an ensemble of more dynamic orientations: the encounter states. The structure of the stereospecific complex between cytochrome P450cam and putidaredoxin was solved recently by X-ray diffraction as well as paramagnetic NMR spectroscopy. Other than the stereospecific complex, the NMR data clearly show the presence of additional states in the complex in solution. In these encounter states, populated for a small percentage of the time, putidaredoxin assumes multiple orientations and samples a large part of the surface of cytochrome P450cam. To characterize the nature of the encounter states, an extensive paramagnetic NMR dataset has been analyzed using the Maximum Occurrence of Regions methodology. The analysis reveals the location and maximal spatial extent of the additional states needed to fully explain the NMR data. Under the assumption of sparsity of the size of the conformational ensemble, several minor states can be located quite precisely. The distribution of these minor states correlates with the electrostatic potential map around cytochrome P450cam. Whereas some minor states are on isolated positively charged patches, others are connected to the stereospecific site via positively charged paths. The existence of electrostatically favorable pathways between the stereospecific interaction site and the different minor states or lack thereof suggests a means to discriminate between productive and futile encounter states.paramagnetic NMR | encounter complex | cytochrome P450cam | putidaredoxin | maximum occurrence C rystal structures suggest that proteins assume unique, stereospecific orientations within protein-protein complexes. However, a number of studies in solution have made clear that encounter states are an inherent element of protein complexes (1-8), especially in electron transfer (ET), where the interactions are often extremely fast (9). In the encounter complex, the proteins assume multiple other orientations, often in equilibrium with the major stereospecific state. In low-affinity complexes with dissociation constant (K d ) values > 10 μM, the encounter complex can represent a sizeable fraction, and in some cases, a well-defined, stereospecific complex may even be absent (10-15). The presence of encounter states may be a consequence of the chemical nature of proteins. In nonobligate stereospecific complexes, the interface represents a small fraction of the total protein surface, and therefore, it is reasonable to assume that weak interactions also occur elsewhere. In the case in which protein pairs have evolved to exhibit a high association rate by using electrostatic preorientation, electrostatic patches seem to enhance the presence of encounter states (16,17). On the one hand, the preorientation reduces the surface area that is visited by the partner, thus enhancing the number of productive encounters, but on the other hand, highly charged patches can bind the oppositely charged protein in many orientations with a...

Long-range NMR data, namely residual dipolar couplings (RDCs) from external alignment and paramagnetic data, are becoming increasingly popular for the characterization of conformational heterogeneity of multidomain biomacromolecules and protein complexes. The question addressed here is how much information is contained in these averaged data. We have analyzed and compared the information content of conformationally averaged RDCs caused by steric alignment and of both RDCs and pseudocontact shifts caused by paramagnetic alignment, and found that, despite the substantial differences, they contain a similar amount of information. Furthermore, using several synthetic tests we find that both sets of data are equally good towards recovering the major state(s) in conformational distributions.

The presence of heterogeneity in the interdomain arrangement of several biomolecules is required for their function. Here we present a method to obtain crucial clues to distinguish between different kinds of protein conformational distributions based on experimental NMR data. The method explores subregions of the conformational space and provides both upper and lower bounds of probability for the system to be in each subregion.