Peptide modulation of class I major histocompatibility complex protein molecular flexibility and the implications for immune recognition.

T cells use the αß T cell receptor (TCR) to recognize antigenic peptides presented by class I major histocompatibility complex proteins (pMHCs) on the surfaces of antigen-presenting cells. Flexibility in both TCRs and peptides plays an important role in antigen recognition and discrimination. Less clear is the role of flexibility in the MHC protein; although recent observations have indicated that mobility in the MHC can impact TCR recognition in a peptide-dependent fashion, the extent of this behavior is unknown. Here, using hydrogen/deuterium exchange, fluorescence anisotropy, and structural analyses, we show that the flexibility of the peptide binding groove of the class I MHC protein HLA-A*0201 varies significantly with different peptides. The variations extend throughout the binding groove, impacting regions contacted by TCRs as well as other activating and inhibitory receptors of the immune system. Our results are consistent with statistical mechanical models of protein structure and dynamics, in which the binding of different peptides alters the populations and exchange kinetics of substates in the MHC conformational ensemble. Altered MHC flexibility will influence receptor engagement, impacting conformational adaptations, entropic penalties associated with receptor recognition, and the populations of binding-competent states. Our results highlight a previously unrecognized aspect of the "altered self" mechanism of immune recognition and have implications for specificity, cross-reactivity, and antigenicity in cellular immunity.

Simulating inadequate dialysis and its correction using an individualized patient-derived nomogram.

Computerized kinetic modeling is a valuable automated peritoneal dialysis (APD) prescription tool for optimizing dialysis adequacy. However, non-compliance results in failure to achieve adequacy targets. The aim of this study was to determine if a nomogram could estimate dialysis compensations for shortfalls in simulated non-compliant patients, such that total weekly urea clearance (Kt/V(urea)) targets are met. Individualized nomograms comprising a series of curves were derived from PD Adequest (ver. 2.0)-predicted Kt/V(urea) data (r (2 ) > 0.99) for different APD prescriptions. The nomogram was then used to estimate the (Nomogram-computed) average of the daily Kt/V(urea) in 14 patients. The study comprised three 1-month phases. Patients were compliant to dialysis in phase I, where Adequest-predicted Kt/V(urea) showed good agreement with both measured (r (I) = 0.72), and Nomogram-computed values (r (I) > 0.99) (p < 0.001). Conversely, in non-compliant phase II, Nomogram-computed values were lower than Adequest-predicted values (p < 0.002). In phase III, the nomogram estimated prescription adjustments required to compensate for shortfalls, such that there was significantly less difference between Nomogram-computed and Adequest-predicted Kt/V(urea) than in phase II (p = 0.005). Thus, despite non-compliance, predicted Kt/V(urea) targets were attained using the nomogram to adjust the daily APD prescriptions. This concept is potentially useful for patients desiring to compensate for inadvertent shortfalls, rather than for 'truly non-compliant' patients.