Biology subjects

Duan, H.

Publications and source records attributed to Duan, H..

At least 19 recordsLinked to original sources

bioRxiv2026

Relation-Aware Graph-Hypergraph Networks for Antibody Sequence-Structure Co-Design

Motivation: The design of antibody complementarity-determining regions (CDRs) is pivotal for therapeutic development, yet remains challenged by the complexity of the antibody-antigen interface. Existing methods, which largely rely on pairwise relationships, struggle to capture intrinsic multi-body interactions and global structural constraints. Results: We propose the Relation-Aware Graph-Hypergraph Network (RA-GHN), a framework that unifies graph-based pairwise modeling with biophysical hypergraphs to capture high-order cooperative effects. Its heterogeneous hypergraph uses epitope-paratope interaction patches, spatial structural clusters, and high-degree hub structures. A dual-pathway architecture integrates a Relation-Aware Equivariant Graph Network with an Equivariant Hypergraph Encoder while preserving SE(3)-equivariance. We also introduce the Structure-Sequence Decoupling Index, which balances structural reliability with sequence novelty. Experiments show that RA-GHN outperforms state-of-the-art baselines across standard benchmarks and affinity optimization tasks.

bioinformatics↗

bioRxiv2026

HighFold-Lasso: Topology-Guided Prediction of Lasso Peptide Structures Using AlphaFold3

Lasso peptides are a class of ribosomally synthesized and post-translationally modified peptides (RiPPs) characterized by a mechanically interlocked topology, in which the C-terminal tail is threaded through an N-terminal macrolactam ring formed by an isopeptide bond. This unique topology often confers high thermal stability and resistance to proteolytic degradation. However, the isopeptide linkage, threaded topology, and class-specific disulfide connectivity make lasso peptide structures difficult to reconstruct reliably using general-purpose structure prediction models. Here, we developed HighFold-Lasso, which combines custom covalent connectivity with lasso scaffold-guided adaptive low-noise initialization to enable conditional structure generation guided by lasso conformational priors. On a test set of 52 experimentally determined structures, HighFold-Lasso achieved a 100% lasso topology success rate, with a mean RMSD C-alpha of 1.942 Angstrom for the ring-loop region and 2.375 Angstrom for the full peptide. The framework supports modeling of the four classical lasso peptide classes (I-IV) and can represent noncanonical amino acids, providing computational support for structure-function studies and molecular engineering of lasso peptides.

bioinformatics↗

bioRxiv2026

MINT: Predicting Enzyme-Cofactor Specificity by Multimodal Knowledge Transfer from Protein-Ligand Interactions

Protein-cofactor selectivity prediction is important for enzyme annotation, metabolic engineering, and biocatalyst discovery, but it remains challenging because experimentally supported associations are limited and unevenly distributed, and because biologically relevant differences can be subtler than those captured by general protein-ligand interaction models. Here, we present MINT (Multimodal Interaction Network with Teacher supervision), a multimodal framework for cofactor specificity prediction. MINT combines protein sequence features with cofactor sequence and graph representations and is trained with a gradual adaptation strategy that transfers useful information from a pretrained protein-ligand interaction model to the cofactor prediction task. On a fixed balanced held-out test set, MINT achieved the best overall performance among all compared methods (AUC = 0.932), and this ranking was reproduced in an independent family-stratified evaluation at the natural positive rate (pooled AUC = 0.939). Further analyses suggest that the pretrained model provides transferable structural information, while the gradual training scheme helps adapt that information to cofactor specificity. In a case study of the chemically near-identical NAD/NADP pair, MINT recovered 95.0-98.6% of true binders and resolved a single-phosphate-level distinction with direct relevance to engineering enzyme cofactor specificity. These results show that gradual transfer learning is an effective approach to cofactor specificity prediction when annotation is limited.

bioengineering↗

bioRxiv2026

A First-in-Class, Brain-Penetrant Small Molecule Inhibitor of the NOS1AP-Tau Interaction Rescues Tau Pathology In Vivo and Improves Cognition

NOS1AP is a genetically validated driver of tau pathology in Alzheimer's disease (AD), yet the NOS1AP-tau interaction itself has remained pharmacologically untargeted. We report CAPTOR-1, a first-in-class small molecule that disrupts this interaction by binding a pocket in the N-terminal region of NOS1AP (residues 1-126). A drug-resistant NOS1AP Y16A/F42A variant that retained tau binding but exhibited a 78-fold reduction in CAPTOR-1 affinity provides genetic evidence supporting an on-target mechanism. In human iPSC-derived neurons, CAPTOR-1 dose-dependently reduces endogenous NOS1AP-tau association, tau seeding activity, and pathogenic tau phosphorylation, phenocopying genetic NOS1AP knockdown; these effects extend to neurons from patients with sporadic AD. Orally dosed CAPTOR-1 crosses the blood-brain barrier and engages NOS1AP in brain dose-dependently. Chronic oral dosing rescues pathology, synaptic function, and memory in a tauopathy model (PS19) and an amyloidosis model (APP/PS1), sparing wild-type littermates in both. This work establishes pharmacological disruption of the NOS1AP-tau interaction as a viable, disease-modifying strategy for AD and positions CAPTOR-1 as a biomarker-ready chemical probe (pTau217, neurofilament light) for translational studies.

pharmacology and toxicology↗

bioRxiv2026

Smallpox Vaccine Elicits CD8+ T Cell Immunity Persisting Over Four Decades with Cross-Recognition of Monkeypox Virus

Monkeypox, caused by MPXV, has become a global public health concern; however, the T-cell immunity against MPXV following smallpox vaccination remains unclear. In this study, we screened the immunogenicity of 21 predicted MPXV epitopes and compared immune responses between young and elderly groups. Two immunogenic CD8 T-cell epitopes, M15 and M17, were identified, both of which effectively stimulated specific immune responses, with significantly stronger responses observed in the young group. Notably, this study provides the first evidence that smallpox vaccination induces CD8 T-cell immunity that cross-recognizes the MPXV epitopes M15 and M17 and remains detectable for more than four decades after vaccination, as demonstrated in vaccinated individuals aged 53-75. These findings provide experimental evidence for understanding the cross-protective mechanisms of the smallpox vaccine and informing monkeypox vaccine development.

immunology↗

bioRxiv2026

Symptomatic human norovirus infection in zebrafish embryos uncovers neural infection and extracellular vesicle-mediated transmission dynamics

Human norovirus (hNoV) is the leading global cause of acute gastroenteritis, imposing a substantial health and economic burden worldwide. Progress in understanding hNoV pathogenesis has been hindered by the lack of tractable small-animal models that recapitulate symptomatic infection. Although zebrafish larvae support hNoV replication, infection remains asymptomatic, limiting their utility for studying disease mechanisms and host-pathogen interactions. In this study, we report that the zebrafish embryo infection model, in which microinjection of hNoV at the early cell stage, resulted in robust systemic viral replication accompanied by overt pathological manifestations, including pericardial and renal edema, yolk and cranial opacity, and mortality by 3 days post-infection. Disease severity displayed marked individual variability and correlated closely with viral burden. Integrated multi-omics analyses, including bulk transcriptomics, untargeted metabolomics, and single-cell RNA sequencing, demonstrated that embryonic infection elicits a stronger and more coordinated antiviral response than larval-stage infection, while enabling widespread viral dissemination across diverse cell lineages. Approximately two-thirds of infected cells were derived from the nervous system or neural crest lineages, providing a potential mechanistic basis for the neurological complications occasionally reported in hNoV-infected patients. Furthermore, we identified a developmental stage-dependent role for extracellular vesicle (EV)-associated hNoV transmission: free virions mediated more efficient infection and higher symptomatic incidence in immunologically immature embryos, whereas EV-associated virions exhibited enhanced infectivity in more immunocompetent larvae. Together, these findings establish the zebrafish embryo as a versatile and accessible in vivo platform for studying symptomatic hNoV infection, reveal host maturity-dependent viral transmission strategies, and provide new opportunities for mechanistic studies and high-throughput evaluation of antiviral and vaccine candidates. Author summaryHuman norovirus is the leading cause of stomach flu worldwide but studying it has been difficult because the lack of a simple, small-animal model that actually gets sick from the virus. While older zebrafish larvae can harbor the virus, they do not show symptoms. In this study, we successfully created a new model by injecting human norovirus into zebrafish embryos at their early cell stage. Unlike the older larvae, these embryos developed clear symptoms, including fluid buildup around the heart and kidneys, tissue cloudiness, and death within three days. Using advanced genetic and metabolic tracking, we discovered that the virus spreads widely throughout the embryos body, particularly targeting cells in the nervous system. This link might explain why human patients occasionally suffer from neurological symptoms. Additionally, our study revealed that the virus changes its transmission strategy based on the animals age: it travels freely to infect vulnerable embryos but hides inside lipid vesicles to infect older, more immune-developed larvae. Ultimately, these findings provide a practical, efficient animal model to better understand norovirus sickness and rapidly test new vaccines and treatments.

microbiology↗

bioRxiv2026

The Origin and Evolution of Protein Synthesis: A Co-Adaptation Flexible-Rigid Docking Model Based on First-Principles Reasoning

Although the "RNA world" hypothesis suggests that RNA played a crucial role in the origin of life [7], the functional framework of RNA in prebiotic protein synthesis and the mechanisms of genetic code formation during the prebiotic period remain poorly understood. Here, using the prebiotic "primordial soup" as a model, we reconstructed the detailed steps that would yield a protein with a stable ordered amino-acid sequence in the "primordial soup" at the prebiotic period. In the "primordial soup", a large number of medium- to large-sized biomolecule-like substances--such as RNA-like and protein-like molecules of various sizes and shapes, as well as related polymers like amino-acid-RNA-like etc.--did generate and accumulate. Moreover, protein-like and RNA-like molecules formed even more intricate complexes. These complexes bound free mRNA-like molecules through complementary base pairing. Subsequently, with an extremely low probability, two adjacent amino-acid-RNA-like molecules became bound to this free mRNA-like molecule, and their amino acids underwent a condensation reaction by the complexes, producing peptides and eventually proteins or polypeptides. This free mRNA-like molecule exhibits a certain flexible structure, whereas the super-large complexes formed by protein-like and RNA-like molecules (which possess certain activities) and the amino-acid-RNA molecules exhibit relatively rigid structures. Long-term evolution and mutual selection led to the emergence of proteins with stable amino acid sequences and moderate catalytic activity. In this way, the nucleotide information embedded in such mRNA-like molecules indirectly express through protein synthesis--a process we term the "A Co-Adaptation Flexible-Rigid Docking Model", where flexible mRNA-like molecules dock onto rigid complexes to enable ordered peptide formation. Finally, we show how trinucleotide codons emerge naturally from the flexible-rigid docking constraints.

evolutionary biology↗

bioRxiv2026

EEG-Neurofeedback Targeting Gamma Oscillations at the Parieto-Occipital Region Reduces Pain Perception

Pain is closely associated with both spontaneous and stimulus-evoked gamma oscillations, which differ in their phenomenology and their relationship to pain perception. These associations make gamma oscillations a promising target for pain interventions, such as closed-loop real-time neurofeedback (NFB). While modulating stimulus-evoked gamma oscillations is technically challenging due to their concurrent occurrence with pain perception, targeting spontaneous gamma oscillations is both feasible and practical, as it could influence subsequent cortical nociceptive processing and reduce pain. To test this mechanistic hypothesis, we developed a novel NFB training protocol aimed at increasing spontaneous gamma oscillations in the parieto-occipital region to alleviate pain. Eight-eight healthy, right-handed subjects were randomly assigned to either an active or sham NFB group and completed three sessions of NFB training. During each session, subjects underwent EEG recording and received randomized laser stimulation while watching a video. After three training sessions, approximately 52% of subjects in the active group successfully increased the spectral power of spontaneous gamma oscillations in the parieto-occipital region. Crucially, the spectral power of spontaneous gamma oscillations was significantly and negatively correlated with subjective pain intensity after the third NFB session. Additionally, subjects who responded successfully to active NFB showed significant reductions in pain intensity, unpleasantness, and laser-evoked potentials compared to the sham group. Together, these findings establish a causal relationship between spontaneous gamma oscillations in the parieto-occipital region and pain perception, potentially offering a novel NFB-based therapeutic strategy for pain management.

neuroscience↗

bioRxiv2026

Cyclic Peptides Target CAPON and Modulate Cellular Responses under Alzheimers Disease-Relevant Stress

CAPON (NOS1AP) is an adaptor protein involved in neuronal nitric oxide synthase (nNOS) signaling and has been implicated in Alzheimers disease (AD), excitotoxicity, and tau-associated neurodegeneration. Here, we report the identification of cyclic peptide ligands targeting CAPON using phage display screening of a disulfide-constrained peptide library. Phage enrichment, ELISA validation, microscale thermophoresis (MST), and biolayer interferometry (BLI) identified CAP1 as the lead peptide, exhibiting low micromolar binding affinity toward CAPON. Computational studies further supported stable CAPON-CAP1 interactions through complementary hydrophobic and electrostatic contacts. Functionally, CAP1 attenuated A{beta}42-induced neuronal toxicity, suppressed NMDA-driven nitric oxide production, and reduced pathological tau phosphorylation in neuronal models under AD-relevant stress conditions. In addition, CAP1 demonstrated favorable preliminary pharmacokinetic properties, including good aqueous solubility, plasma stability, and measurable membrane permeability. Collectively, these findings establish the first cyclic peptide ligands targeting CAPON and identify CAP1 as a promising scaffold for modulation of CAPON-dependent neurodegenerative signaling.

pharmacology and toxicology↗

bioRxiv2026

sxRaep: A Rapid and Accurate Enzyme Predictor for high-throughput mining of enzymatic sequences

MotivationMetagenomic sequencing generates petabyte-scale sequence datasets that strain both deep learning and alignment based enzyme annotation tools. A lightweight rapid and accurate filter tool is needed to filter and identify enzymatic sequences prior to resource-intensive functional prediction. ResultsWe present sxLaep (Lightweight and Accurate Enzyme Predictor), a resource-efficient framework using lightweight physicochemical features for enzyme pre-screening. On the external validation set, sxLaep completed prediction in only 0.002 s/sequence, which is 22.9-fold faster than Diamond (0.0457 s/sequence). It used 372.16 MB peak memory, corresponding to a 54.4% memory reduction relative to Diamond (815.64 MB). sxLaep achieved an accuracy of 99.34% and the highest recall in remote homology detection, including enzyme candidates missed by alignment-based methods. We further successfully applied sxLaep to a marine metagenomic enzyme-mining workflow, demonstrating its utility for high-throughput discovery from large-scale metagenomic sequences. Availability and ImplementationsxLaep is available as a Python package at https://pypi.org/project/sxlaep and is maintained as an open-source software repository at https://github.com/labxscut/sxLaep. Detailed installation, usage, and Docker deployment instructions are provided in the GitHub repository to support reproducible enzyme prediction and model execution. Contactlcxia@scut.edu.cn

bioinformatics↗

bioRxiv2026

Multimodal immunopharmacologic screens identify drugs rewiring the cancer-immune interface

Natural killer (NK) cell-based therapies are a promising approach in cancer, but their efficacy is limited by impaired effector function and tumor-intrinsic resistance. To systematically identify therapeutic strategies that target both sides of the cancer-immune interface, we designed a multimodal immunopharmacologic screening platform comprising high-throughput co-culture drug screens, cytokine secretome profiling, single-cell perturbation screens, and genome-scale CRISPR screening, followed by validation in biobanked patient-derived models. Applying the platform across five blood cancer types, we identified protein kinase C (PKC) activation to simultaneously increase effector cytotoxicity and cytokine secretion through transcriptomic rewiring, and tumor susceptibility to NK cell killing through tumor-intrinsic PKC-{delta}. In patient samples, PKC activation sensitized NK-resistant leukemic progenitors to NK cell killing. In addition, NEDD8 inhibition enhanced NK function and shifted tumor TNF signaling towards pro-apoptotic pathways. Our platform provides a systematic approach to identify drugs rewiring both sides of the cancer-immune interface to circumvent tumor immune resistance.

cancer biology↗

bioRxiv2026

Reversible CD28 checkpoint modulation by cyclic peptides outperforms biologic blockade under exposure-limited conditions

CD28 co-stimulatory blockade is an established therapeutic strategy in autoimmune disease, yet every clinical-stage agent shares a structural limitation: high-affinity, long-lived receptor occupancy that precludes dynamic control of immune suppression. In chronic inflammatory conditions, where prolonged immunosuppression carries infection risk and necessitates treatment interruptions, no existing agent permits rapid restoration of immune function. We report CP8, a disulfide-constrained cyclic peptide antagonist that matches the inhibitory potency of clinical-stage CD28 biologics (FR104, Acazicolcept, and Lulizumab) across primary human immune cells from healthy and ulcerative colitis donors, suppressing IL-2 and IFN-{gamma} production without agonist activity. Unlike these biologics, CP8 enables rapid and near-complete restoration of T-cell function upon compound removal, a property mechanistically inaccessible to antibody-based therapeutics and demonstrated here for the first time for any CD28-targeting agent. In a T-cell transfer colitis model, CP8 maintains efficacy under intermittent dosing and outperforms Acazicolcept, a dual CD28/ICOS inhibitor, under exposure-limited conditions, achieving superior disease suppression, tissue preservation, and cytokine reduction. These results demonstrate that potency and pharmacological persistence are decoupled properties, and reframe cyclic peptides as a superior modality for immune checkpoints where temporal control of signaling is essential to balance efficacy with the risks of chronic immune suppression.

pharmacology and toxicology↗

bioRxiv2026

BioReason-Pro: Advancing Protein Function Prediction with Multimodal Biological Reasoning

Protein function annotation is fundamental to understanding biological mechanisms, designing therapeutics, and advancing biomedical research. Current computational methods either rely on shallow sequence similarity or treat function prediction as isolated classification tasks, failing to capture the integrative reasoning across sequence, structure, domains, and interactions that expert biologists perform to infer function. We introduce BioReason-Pro, the first multimodal reasoning large language model (LLM) for protein function prediction that integrates protein embeddings with biological context to generate structured reasoning traces. A key input into BioReason-Pro is the set of GO term predictions made by GO-GPT, our autoregressive transformer that captures hierarchical and cross-aspect dependencies of GO terms. BioReason-Pro is trained via supervised fine-tuning on synthetic reasoning traces generated by GPT-5 for over 130K proteins and further optimized through reinforcement learning. It achieves 73.6% Fmax on GO term prediction and an LLM judge score of 8/10 on functional summaries, substantially outperforming previous methods. Evaluations with human protein experts show that BioReason-Pro annotations are preferred over ground truth UniProt annotations in 79% of cases. Remarkably, BioReason-Pro predicted a novel interaction partner for the renal cancer biomarker RCDG1, which we confirmed in the lab by co-immunoprecipitation. In other binding-partner predictions, its per-residue attention localized to the exact contact residues resolved in cryo-EM structures. Together, GO-GPT and BioReason-Pro establish a framework for protein function prediction that combines precise ontology modeling with interpretable biological reasoning.

molecular biology↗

bioRxiv2026

AI-designed cyclic peptides enable controllable modulation of the CD28 immune checkpoint

Immune checkpoint therapies have transformed immunotherapy but remain dominated by biologic agents characterized by prolonged receptor occupancy and limited pharmacologic controllability. Synthetic modalities capable of targeting protein-protein interaction interfaces while enabling tunable immune regulation remain largely unexplored. Here, we report an AI-guided strategy for discovering cyclic peptide antagonists of the costimulatory receptor CD28. The lead peptide, CIP-3, binds the CD28 extracellular domain with nanomolar affinity and competitively disrupts CD28-ligand interactions. In primary human immune systems, CIP-3 suppresses CD28-dependent T-cell activation without intrinsic agonist activity and exhibits rapid pharmacologic reversibility, enabling exposure-dependent control of immune signaling. In a T-cell transfer model of chronic colitis, CIP-3 confers dose-dependent therapeutic efficacy and reduces systemic inflammatory cytokines. CIP-3 also suppresses cytokine production across independent healthy donors and patient-derived PBMCs from individuals with ulcerative colitis with efficacy comparable to a benchmark anti-CD28 biologic. Together, these findings establish AI-designed cyclic peptides as a controllable synthetic modality for immune checkpoint modulation.

pharmacology and toxicology↗

bioRxiv2026

A biofidelic Goat Model of Traumatic Optic Neuropathy with Optic Canal Fracture via Transnasal Endoscopy

Traumatic optic neuropathy (TON) is a major cause of irreversible vision loss following blunt cranial trauma, yet the absence of clinically relevant large animal models that faithfully recapitulate human TON has significantly impeded translational research. Current rodent models do not reproduce optic canal fracture, a key injury mechanism in many patients with TON. Here, we combined high-fidelity finite element analysis (FEA) with iterative engineering to establish a reproducible goat model of TON. We first built a high-resolution human-head finite element model to characterize force transmission to the optic nerve. Across clinically relevant periorbital impacts, stress preferentially concentrated in the intracanalicular segment, reaching a peak force density of approximately 500 N/m2 at 50.6 ms, about fivefold higher than in the intraorbital segment. Simulations further showed that direct optic canal impact reproduced comparable intracanalicular stress with a markedly lower input force: 195 N, compared with 3900 N for periorbital impact. Guided by these insights, we developed transnasal endoscopic impact systems capable of inducing optic canal fractures in goats. TON was confirmed within 24 hours by a characteristic relative afferent pupillary defect (RAPD), and at 1 month post-injury goats (n = 14) exhibited a 10%-20% reduction in ganglion cell complex (GCC) thickness and 40%-65% reductions in flash visual evoked potential (FVEP) and pattern electroretinogram (PERG) amplitude ratios (all P [≤] 0.001), with structural and functional preservation of the fellow eye. This study presents a robust, standardized, and clinically relevant large-animal platform for investigating TON pathophysiology.

neuroscience↗

bioRxiv2026

Nanoscale Protonation Limits and Charge Density in Polymer Films Govern the Activity of Immobilized LacZ under Acid Stress

Under acidic conditions, polycationic polymer coatings function as protective immobilization supports through protonation-mediated local pH buffering. However, it remains unclear how polymer support design parameters, such as film thickness and charge density, govern that vital protonation process. Leveraging the precise control of film thickness and copolymer composition enabled by initiated chemical vapor deposition (iCVD), we systematically investigated how these parameters govern the protonation behavior of poly[glycidyl methacrylate-co-2-(dimethylamino)ethyl methacrylate] (pGD) thin films and, in turn, the activity of immobilized {beta}-galactosidase (LacZ). Infrared spectroscopy suggests that proton penetration was capped at a depth of [~]250 nm in pGD with 65% DMAEMA, limiting the polycationic thickness in pGD films thicker than this value. Consistent with this limit, immobilized LacZ activity under acidic stress (pH 4) increased with protonated thickness up to [~]250 nm and then plateaued. Raising the polycationic monomer content from 25 to 65 mol% increased LacZ activity at pH 4 by up to 83%, consistent with a higher positive charge density providing stronger local pH buffering. To test whether this behavior depends on immobilization sites, we evaluated two approaches: random immobilization (via amine-epoxy ring-opening reactions) and site-directed immobilization (via SpyCatcher/SpyTag binding). Directed immobilization preserved higher LacZ activity than random immobilization, but the protonation-dependent protection trend remained consistent for both strategies. These findings establish protonation depth and charge density as tunable design parameters for polycationic immobilization supports that stabilize enzymes under acidic conditions.

bioengineering↗

bioRxiv2026

High-PepBinder: A pLM-Guided Latent Diffusion Framework for Affinity-Aware Target-Specific Peptide Design

Peptides, as therapeutic molecules, offer unique advantages in targeting complex protein surfaces, yet their rational design remains limited by the vastness of the sequence space and the constraints of traditional approaches. Here, we propose High-PepBinder, a sequence-only conditional diffusion framework for target-specific peptide generation. Guided by the target protein sequence, High-PepBinder adopts a dual encoder architecture that integrates protein language models (pLMs) with the diffusion model. This approach cascades the peptide generation model with an affinity classifier and enables the generation process to capture affinity-related features of the peptides through lightweight joint optimization. Due to the scarcity of protein-peptide affinity data, we constructed PepPBA, to our knowledge the most comprehensive dataset to date, and established a structure- and physics-based screening pipeline to prioritize top candidates. Results show that High-PepBinder demonstrates competitive performance across multiple peptide generation and affinity-related tasks. For representative targets, including KEAP1, XIAP, and EGFR, the generated peptides preserve key binding geometries and interface patterns of reference peptides in predicted complexes, while maintaining sequence diversity and favorable predicted properties. Overall, High-PepBinder contributes toward a general and sequence-only strategy for peptide design, offering a computational framework for expanding peptide discovery against challenging targets.

bioinformatics↗

bioRxiv2025

A programmable mRNA platform for miRNA detection via miRNA-mRNA2 triplex-mediated ribosomal frameshifting

Programmed -1 ribosomal frameshifting (-1 PRF) is a recoding mechanism utilized by viruses to expand their coding capacity and modulate the stoichiometric ratio of -1 frame and 0 frame translation products. The stability of mRNA secondary structure at the ribosomal entry site within the frameshifting stimulating elements (FSEs) determines the frameshifting efficiency. Here, we report the development of a programmable mRNA-based platform that detects specific mature microRNA (miRNA or miR) by converting their presence into a quantifiable protein output through miRNA-triggered -1 PRF. We designed a triplex-forming mRNA (TF-mRNA) platform to selectively trap target miRNAs through the formation of major-groove mRNA-miRNA-mRNA (miR-mRNA2) triplexes. Bio-layer interferometry and fluorescence binding studies confirmed that TF-mRNA forms stable complexes with cognate miRNAs with low nanomolar affinity and prolonged dissociation rate. Critically, the formation of miR-mRNA2 triplex robustly stimulated ribosomal frameshifting in a cell-free dual-luciferase translation system, acting as a miRNA-dependent molecular switch. The generality of this TF-mRNA platform has been verified for several disease-associated purine-rich miRNAs, and it is suitable for targeting a wide range of other purine-enriched miRNAs. This programmable TF-mRNA platform establishes a foundation for developing novel diagnostic tools and synthetic biology circuits that convert the presence of miRNA into a quantifiable protein output. TOC Figure O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/690164v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@1d6d9f7org.highwire.dtl.DTLVardef@8008e6org.highwire.dtl.DTLVardef@1c8344borg.highwire.dtl.DTLVardef@e153ec_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗