Evidence map›Paper›PMID 41509221›Full record

ArticlebioRxiv : the preprint server for biology2026

Computational design of orthogonal TCR α/β interfaces for dual-TCR therapeutics.

Tomoaki Kinjo, Shawn Yu, Nathan Nicely, Andrew Leaver-Fay, William Y Kim, Brian Kuhlman

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Tomoaki KinjoDepartment of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.ORCID 0000-0003-0939-7756
Shawn YuLineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.ORCID 0000-0003-1951-2949
Nathan NicelyDepartment of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.ORCID 0000-0002-0025-2377
Andrew Leaver-FayDepartment of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.ORCID 0000-0003-4609-4340
William Y KimLineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.ORCID 0000-0001-7922-2156
Brian KuhlmanDepartment of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.ORCID 0000-0003-4907-9699

Funding

Virology Research Program (Program 4)P30CA016086 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI David Darr · 1985 to 2026
$201.5M
UNC-Duke Collaborative Clinical Pharmacology Postdoctoral Training Program-Evaluation SupplementT32GM086330 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KIM L.R. BROUWER, Daniel Gonzalez · 2011 to 2026
$8.5M
GPU workstation for deep learning-based protein design and cryo-EM data processingR35GM131923 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BRIAN A KUHLMAN · 2019 to 2026
$6.1M
NCI NIH HHS P30 CA016086NIGMS NIH HHS R35 GM131923NIGMS NIH HHS T32 GM086330
6 · The paper itself

Abstract

T-cell receptors (TCRs) recognize peptides presented by MHC, enabling access to intracellular targets that are largely inaccessible to antibodies and difficult to target with small molecules. Despite this potential, their inherent cross-reactivity limits tumor specificity, while single-antigen targeting provides limited coverage of intratumoral heterogeneity. Dual-TCR therapeutics comprising two distinct TCRs could enhance tumor specificity via combinatorial recognition while broadening coverage across heterogeneous antigens. However, practical development of dual-TCR therapeutics has been limited by α/β subunit mispairing that prevents efficient production and creates undesired binding properties. Here, we develop orthogonal TCR α/β interfaces that prevent subunit mispairing. Using computational multistate design and second-site suppressor strategies implemented in Rosetta, we identified over 250 TCR variants for experimental screening to assess protein stability and pairing fidelity. The top-performing designs achieved approximately 95% correct pairing, as validated by mass spectrometry and X-ray crystallography. Focusing mutations on constant domains and conserved framework regions of variable domains enabled broad applicability across diverse TCRs while preserving antigen recognition. Using these orthogonal interfaces, we developed trispecific T-cell engagers (TriTEs) that target two cancer-testis antigens and CD3 on T cells, demonstrating enhanced potency under dual-antigen engagement (EC50 of 380 fM) while maintaining high activity when targeting cells displaying a single antigen (EC50s of 48 pM and 20 pM). This orthogonal TCR interface technology establishes a generalizable platform for engineering multi-specific immune therapeutics targeting diverse cancer antigens.

Identifiers

PMID41509221
PMCPMC12776297

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.