Enhanced antigen presentation in the absence of the invariant chain endosomal localization signal.

The cytosolic tail of the major histocompatibility complex class II-associated invariant chain (Ii) molecule is thought to contain the endosomal localization signal that directs and/or retains newly synthesized class II within the endosomal antigen processing compartment. To determine the role of this signal in class II transport and antigen presentation we have generated class II-positive L cell transfectants that coexpress wild type or truncated forms of Ii. Deletion of the endosomal localization signal from Ii results in rapid transport of class II-Ii complexes to the cell surface. Once at the cell surface, the complex is efficiently internalized, Ii is degraded, and class II free of Ii is recycled back to the plasma membrane. Interestingly, the truncated form of Ii is still able to increase the efficiency of antigen presentation to T cells. These data suggest that the ability of Ii to enhance antigen presentation is not limited to Golgi apparatus-endosomal sorting and raise the possibility that endocytosed class II can form immunogenic complexes with newly processed antigen

Calculating Ensemble Averaged Descriptions of Protein Rigidity without Sampling

Previous works have demonstrated that protein rigidity is related to thermodynamic stability, especially under conditions that favor formation of native structure. Mechanical network rigidity properties of a single conformation are efficiently calculated using the integer body-bar Pebble Game (PG) algorithm. However, thermodynamic properties require averaging over many samples from the ensemble of accessible conformations to accurately account for fluctuations in network topology. We have developed a mean field Virtual Pebble Game (VPG) that represents the ensemble of networks by a single effective network. That is, all possible number of distance constraints (or bars) that can form between a pair of rigid bodies is replaced by the average number. The resulting effective network is viewed as having weighted edges, where the weight of an edge quantifies its capacity to absorb degrees of freedom. The VPG is interpreted as a flow problem on this effective network, which eliminates the need to sample. Across a nonredundant dataset of 272 protein structures, we apply the VPG to proteins for the first time. Our results show numerically and visually that the rigidity characterizations of the VPG accurately reflect the ensemble averaged properties. This result positions the VPG as an efficient alternative to understand the mechanical role that chemical interactions play in maintaining protein stability