Ebenezer, A. | bioRxiv Science

bioRxiv2026

19F Ultrafast MAS NMR Reveals the Dynamic Basis of pH-Dependent Regulation in Proteorhodopsin

19F NMR spectroscopy is a powerful approach for studying complex biomolecular systems because of its high sensitivity, exceptional responsiveness to local structural changes, and simplified spectra. Here, we demonstrate the application of 19F ultrafast MAS NMR to 5-fluorotryptophan-labelled proteorhodopsin reconstituted in lipid bilayers. By assigning 9 of the 10 tryptophan resonances, pH-dependent analyses of chemical shifts, line shapes, and conformational exchange reveal the dynamics of two functionally important residues: W34 in the interprotomer His-Asp-Trp triad and W98 within the retinal-binding pocket. The results identify W34 as a dynamic regulator of proton transport and support a model in which slow ring flipping on the seconds timescale transiently modulates the W34-H75 interaction, thereby acting as a pH-dependent molecular throttle. The spectral characteristics of W98 further suggest that it functions as a dynamic regulator of the photocycle within the retinal-binding pocket. Beyond these mechanistic insights, we show that a MAS rate of 100 kHz markedly enhances the resolution of this 19F-labelled membrane protein. Combined with a simple chemical-shift scoring metric and advanced, linear-scaling AF-QM/MM-based 19F chemical shift calculations of all sites within this protein, this workflow provides a robust and broadly applicable framework for characterizing membrane protein structure and dynamics in native-like lipid environments. TABLE OF CONTENT GRAPHICS O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/739351v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@18cc7bborg.highwire.dtl.DTLVardef@18cf6fforg.highwire.dtl.DTLVardef@1abe960org.highwire.dtl.DTLVardef@166a39c_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2025

Targeting peptide-MHC complexes with designed T cell receptors and antibodies

Class I major histocompatibility complexes (MHCs), expressed on the surface of all nucleated cells, present peptides derived from intracellular proteins for surveillance by T cells. The precise recognition of foreign or mutated peptide-MHC (pMHC) complexes by T cell receptors (TCRs) is central to immune defense against pathogens and tumors. Although patient-derived TCRs specific for cancer-associated antigens have been used to engineer tumor-targeting therapies, their reactivity toward self- or near-self antigens may be constrained by negative selection in the thymus. Here, we introduce a structure-based deep learning framework, ADAPT (Antigen-receptor Design Against Peptide-MHC Targets), for the design of TCRs and antibodies that bind to pMHC targets of interest. We evaluate the ADAPT pipeline by designing and characterizing TCRs and antibodies against a diverse panel of pMHCs. Cryogenic electron microscopy structures of two designed antibodies bound to their respective pMHC targets demonstrate atomic-level accuracy at the recognition interface, supporting the robustness of our structure-based approach. Computationally designed TCRs and antibodies targeting pMHC complexes could enable a broad range of therapeutic applications, from cancer immunotherapy to autoimmune disease treatment, and insights gained from TCR-pMHC design should advance predictive understanding of TCR specificity with implications for basic immunology and clinical diagnostics.

immunology↗