Research Highlights

De Novo Design and Structure of a Peptide-centric TCR Mimic Binding Module Householder KD, Xiang X, Jude KM, et al. Science. 2025;389:375 Peptide antigens presented on major histocompatibility complexes (pMHC molecules) engage T-cell receptors (TCRs) to trigger T-cell responses. Because such pMHCs are frequently excellent cancer antigens, great efforts have been made in generating TCR mimics with high affinity toward such pMHCs for cancer immunotherapeutics. To date, such TCR mimics are primarily antibody-based, which are limited by a significant off-target toxicity profile due to their high affinities to the MHCs, rather than the peptides, in the pMHC targets.1 Fine-tuning such antibodies to reduce their toxicity profile can be laborious and time-consuming, thereby limiting the impact of this approach. In the present study, Householder et al2 took a de novo design approach to develop α-helical TCR mimics possessing structural advantages over antibody-based TCR mimics. Such a design approach was further aided by current state-of-the-art protein design tools, such as RFdiffusion and ProteinMPNN, to significantly enhance the discovery rate. As a proof of principle, they first generated 50 monomer helices using RFdiffusion and empirically selected the top helix, based on compactness and ease of expression as a recombinant protein, as the backbone scaffold for subsequent experiments. They used a well-known melanoma peptide antigen NY-ESO-1157-165(C9V) presented on the HLA-A*02 allele as their pMHC target and used AlphaFold to predict its structure and critical amino acid residues as hotspots for design. They then produced 100 distinct 4-helix bundles capable of docking NY-ESO-1 HLA-A*02 and used AlphaFold2 to predict a parameter called “interface predicted aligned error (iPAE).” In prior studies, there is a correlation between iPAE values of ≤10.0 and increased experimental success. By doing so, they found 4 “hit” scaffolds from the 100 designs and identified 1 scaffold (called “scaffold 1”) as adopting a centered, TCR-like docking mode, therefore best meeting their design criteria. Simultaneously, 500 more sequences per scaffold were generated to expand sequence variant diversity and scored with AlphaFold2 for iPAE. The top 5 sequences were next displayed as single clones on yeast cells and examined by NY-ESO-1-HLA-A*02 tetramer staining. The strongest binder by tetramer staining was designated as “mini-TCRm1.1,” which, compared with an actual TCR, exhibited significantly enhanced compactness and rigidity. Subsequent structural validation was performed by comparing AlphaFold2 results to actual crystallization and revealed overall agreement. Additionally, an “off-target” peptide search of 14 363 peptides from the MHC Motif Atlas by Hamming distance search identified only 2 peptides predicted to bind to mini-TCRm1.1, and with significantly decreased affinities. Finally, they tested the ability of mini-TCRm1.1 to engage T cells in an antigen-specific manner by generating a construct fusing the sequence of mini-TCRm1.1 to that of anti-CD3εscFv from blinatumomab (a Food and Drug Administration–approved bispecific T-cell engager) via a 5-amino acid linker. They found that their engineered mini-TCRm1.1-anti-CD3εscFv stimulated the activation of reporter Jurkats T cells as well as induced cytotoxicity of primary human T cells in a peptide antigen-specific manner. When expressed in a chimeric antigen receptor context, mini-TCRm1.1 drove T-cell activation and cytotoxicity against the A375 human melanoma cell line (which presents the NY-ESO-1157-165 peptide on HLA-A*02). This study demonstrates the significant advantages of de novo design of TCR mimics over conventional antibody-based TCR mimics: (1) the rapidity of candidate discovery via deep learning tools; (2) the rigidity of the α-helical platform allowing exceptional design accuracy; (3) the flexibility permitting engineering of multivalency; and (4) the solubility supporting clinically feasible administrations. Minimizing off-target interactions and unwanted immunogenicity in future studies will significantly enhance their clinical applications. Specific to transplantation, the prospect of engineering negative T-cell signaling components into such pMHC TCR mimics could conceivably contribute to the inhibition of donor-specific T-cell responses. Donor–recipient Mismatch at the SIRPA Locus Adversely Affects Kidney Allograft Outcomes Zhao D, Dai H, Macedo C, et al. Sci Transl Med. 2025;17:eady1135 A mismatch in the polymorphic SIRPA gene, encoding the signal regulatory protein α (SIRPα), between donors and recipients can initiate myeloid-mediated alloresponses as part of the innate allorecognition process. The interaction between SIRPα and its ligand, CD47, on myeloid cells conveys a “don’t eat me” signal through SH2-containing tyrosine phosphatase (SHP-1/2) activation.1 Donor–recipient SIRPA mismatches alter CD47–SIRPα binding affinity and drive monocyte differentiation into dendritic cells with a potential to compromise transplant outcomes.2 In the current study, Zhao et al3 used a translational mouse-to-human approach to examine the effects of SIRPA mismatch on histological and clinical outcomes in kidney transplantation. In their mouse model, kidney transplants from SIRPα- and major histocompatibility complex (MHC)-mismatched donors (group 1) developed chronic rejection by 10–12 mo posttransplant, characterized by nodular immune cell infiltrates and fibrosis. Grafts from MHC-mismatched but SIRPα-matched donors (group 2) exhibited a significant reduction in chronic rejection markers, highlighting the contribution of SIRPα mismatch to chronic rejection. Furthermore, recipients lacking CD47 (group 3) revealed substantially decreased chronic rejection and fibrosis, suggesting that the SIRPα-mismatch effect is facilitated by SIRPα–CD47 signaling. Moreover, the authors conducted an in silico analysis using whole-genome sequencing data to characterize all annotated single-nucleotide polymorphisms in SIRPA. Seventy-seven single-nucleotide polymorphisms were recognized across SIRPA exons corresponding to approximately 150 haplotypes. Among these, 10 haplotypes represented about 92% of the global variation. Based on the amino acid variations in the IgV domain, these haplotypes were divided into 2 major allelic groups: v1-like (“A”; with leucine at position 66 and proline at position 99), being more prevalent in Africans and Europeans and v2-like (“B”; with serine at position 66 and a proline deletion at position 99), being more common in East Asians. The human part of the study comprised 2 separate groups of kidney transplant recipients. The first cohort, comprising 455 recipients followed for 55.5 ± 21 mo, was classified into 3 groups: SIRPA-matched, A→B mismatched (recipient genotype carries more B alleles), and B→A mismatched (donor genotype carries more B alleles). Mismatched groups had higher acute rejection rates. The B→A mismatch was associated with delayed graft function, persistent allograft inflammation, premature interstitial fibrosis and tubular atrophy (score ≥3), and shortened allograft survival. The A→B mismatch was only associated with early acute rejection and increased interstitial fibrosis and tubular atrophy within the first year. In the second cohort of 258 recipients (mean follow-up: 53 ± 15 mo), graft survival was similarly significantly lower in the B→A mismatched group. The authors also reported a shift toward an activated monocyte phenotype in B→A mismatched patients at 3 mo posttransplant, independent of rejection status. Renal biopsies with acute cellular rejection showed a higher density of M2-polarized macrophages in the matched group, indicating an increase in regulatory macrophage populations. In addition to the innate immune system involvement in ischemia/reperfusion injury and CD47 signaling, this study demonstrated a trend toward increased de novo donor-specific antibody formation through monocyte-derived dendritic cell activation and subsequent T cell–mediated B-cell responses in the B→A mismatched groups.3 They showed that B→A mismatch resulted in allograft deterioration mainly via fibrosis, independent of delayed graft function or donor-specific antibodies. This study underscores SIRPA genotyping as a potential immunogenetic biomarker for donor–recipient matching in kidney transplantation. Prospective studies are now needed to investigate the effect of SIRPA mismatch effects on antibody responses, its role in patients on maintenance corticosteroids, and its relevance across different populations and ethnic groups.