Biology subjects

Cao, C.

Publications and source records attributed to Cao, C..

At least 19 recordsLinked to original sources

bioRxiv2026

FLASH X-rays preserve neutrophil chromatin to boost antitumor immunity

Ultrahigh dose-rate FLASH radiotherapy spares normal tissue while preserving antitumor activity, positioning it as a promising technology in radiation oncology, but its immunomodulatory mechanisms remain elusive. Here, using a bilateral subcutaneous tumor model in mice, we show that 8-Gy FLASH X-rays, versus an equal dose of conventional dose-rate (CONV) X-rays, elicit a robust abscopal antitumor effect with anti-PD-1 therapy. Single-cell transcriptome and T cell receptor (TCR) profiling reveal that FLASH X-rays plus anti-PD-1 enhance antitumor immune infiltration and TCR clonal expansion in both irradiated and abscopal tumor lesions. Mechanistically, the ultrashort temporal continuity of FLASH dose delivery conserves chromatin compaction in neutrophils during exposure and inhibits neutrophil extracellular trap (NET) formation, thereby dismantling NET-mediated CD8+ T-cell exclusion within primary tumors. Conversely, CONV or split-dose FLASH X-rays induce marked chromatin modifications prior to dose completion, leading to chromatin hyper-relaxation which promotes NETosis and consequently abrogates systemic antitumor immunity. Notably, this detrimental effect can be reversed by pharmacologically suppressing PARylation-mediated chromatin modification and decondensation in neutrophils. These findings identify radiation-induced aberrant chromatin relaxation in neutrophils as a critical determinant of radioimmunotherapy outcomes, providing a rationale for redefining the FLASH effect and advancing its clinical translation.

cancer biology↗

bioRxiv2026

Allele-Resolved Hybrid Embryos Reveal the Fates of Regulatory Divergence

Developmental programs can remain conserved despite extensive regulatory divergence, but how evolved regulatory differences are transmitted through embryonic lineages remains unclear. Here we generate a time resolved, allele resolved single-cell atlas of hybrid embryogenesis between Ciona intestinalis and Ciona savignyi, enabling regulatory differences accumulated between species to be followed across defined developmental lineages. We find that allelic differences are maintained or remodeled in lineage specific ways, with their outcomes associated with regulatory origin and allele specific chromatin accessibility. Across multiple tissues, allelic divergence increases along gene regulatory network (GRN) hierarchy from upstream regulators toward downstream regulators and effector genes. In the cardiopharyngeal lineage, Foxf illustrates how allelic dominance provides partial compensation for highly divergent regulatory sequences and thereby contributes to developmental system drift. Together, our results reveal that regulatory divergence is dynamically sorted during development according to lineage context and GRN hierarchy. This lineage resolved framework provides a developmental basis for understanding how extensive regulatory evolution can accumulate while conserved embryonic programs are maintained.

developmental biology↗

bioRxiv2026

Intracranial Validation of Magnetoencephalography Across Oscillatory Frequency and Depth

Non-invasive, whole-brain neuroimaging methods such as functional magnetic resonance imaging, electroencephalography (EEG), and magnetoencephalography (MEG) are essential tools for studying the basis of human cognition in health and disease. MEG offers the opportunity to study neural activity at its intrinsic timescale, by recording the magnetic fields generated by electrical currents within the brain from outside the skull. Moreover, recently developed optically pumped magnetometers (OPMs) allow these recordings to take place in new settings, for example during naturalistic behaviour and in previously inaccessible populations. These breakthroughs have led to a shift in the neuroimaging landscape, with a global increase in the adoption of MEG. Crucially, however, the extent to which MEG recordings can measure different features of neural activity remains unclear. To address this issue, we leveraged a unique and rare dataset of concurrent MEG and intracranial EEG recordings from a cohort of epileptic patients. We found that group-level inferences of spontaneous oscillatory dynamics made with source-localised MEG, i.e. estimates of power and bursts, accurately reflected the underlying neural activity. As expected, the agreement was strongest for lower-frequency activity (delta, theta, and alpha) and superficial sources, and weakest in the gamma range. Crucially, however, MEG was also sensitive to deep structures: it captured oscillatory power and burst dynamics in the hippocampus, most robustly in the theta band. These findings demonstrate that MEG is sensitive to physiologically meaningful activity in cortical and subcortical regions and establish a foundation for the interpretation of future MEG studies across a wide range of research domains.

neuroscience↗

bioRxiv2026

What do satellite vegetation indices actually measure? Photosynthetic capacity rather than transient physiological function across 328 global FLUXNET sites

A direct empirical relationship between gross primary productivity (GPP) estimated by the eddy covariance method and satellite vegetation indices (VIs) has been widely observed across diverse ecosystems globally. Building on this observed covariation, VIs are frequently utilized as critical parameters - such as the fraction of absorbed photosynthetically active radiation (fPAR) - within light use efficiency (LUE) and greenness-based models for carbon cycle monitoring. However, actual canopy carbon assimilation is jointly governed by slowly evolving structural parameters and highly dynamic functional traits, such as physiological efficiency. The extent to which the macro-scale VI-GPP covariance is driven by structural scaffolding, and how this structural signal decouples from physiological function under environmental stress, remains to be systematically quantified. Here, we synthesized half-hourly eddy covariance measurements from 328 globally distributed sites and paired them with a rigorously angle-normalized Enhanced Vegetation Index (nadir view and fixed solar zenith angle at 30 degrees, EVI_SZA30). By applying a nonlinear light-response curve model across 54,720 high-frequency temporal windows, we mechanistically disentangled observed actual GPP (GPP_EC) into baseline photosynthetic capacity (P_c) and intrinsic quantum yield (alpha). Our results demonstrate that the macroscopic covariance between EVI_SZA30 and GPP_EC (R^2=0.554) is primarily driven by the index's robust ability to track structural capacity (P_c, R^2=0.538). In contrast, EVI_SZA30 exhibits limited sensitivity to high-frequency variations in functional traits like physiological efficiency (alpha, R^2=0.038). Particularly in water-limited biomes (e.g., open shrublands and woody savannas), intense environmental stress triggers rapid stomatal regulation while the physical canopy structure remains relatively stable. Consequently, the correlation between EVI and P_c becomes notably stronger than its correlation with actual GPP_EC, highlighting a pronounced structural-physiological decoupling. Because discrete overpasses by sun-synchronous polar-orbiting satellites face intrinsic temporal constraints in capturing sub-daily physiological down-regulation (e.g., midday photosynthetic depression), future monitoring paradigms could greatly benefit from the continuous, high-frequency observations provided by next-generation geostationary (GEO) satellites to bridge the gap between structural parameters and transient ecosystem function.

ecology↗

bioRxiv2026

Reconstructing sequence-grammar trajectories enables interpretable and tunable cis- regulatory element design

Designing synthetic cis-regulatory elements (CREs) with cell-type-specific activity remains challenging, and optimization is usually treated as a black box, obscuring how regulatory grammar emerges and why design trajectories fail. Here, we present GO-CRE (Guided Optimization of Cis-Regulatory Elements), which combines efficient sequence generation, predictor-guided reinforcement learning, and trajectory-level interpretation. GO-CRE reconstructs iterative sequence changes in a shared sequence-grammar landscape and identifies coordinated update programs corresponding to search, commitment, and optimization. Productive trajectories in HepG2 and K562 progressively acquired cell-type-associated grammar, whereas SK-N-SH trajectories remained confined to local basins. In HepG2, trajectory analysis revealed a low-complexity polyG trap; introducing a polyG penalty redirected optimization toward HNF/FOXA-associated features. Final designs retained sequence diversity while converging on cell-type-associated motif patterns. Lentiviral MPRA validated cell-type-specific activity in K562 and HepG2 and showed higher average activity of HepG2 designs than endogenous CREs. Together, these findings establish sequence-grammar trajectory reconstruction as a basis for interpretable and tunable synthetic CRE design.

genomics↗

bioRxiv2026

A superfolding sfPepper enables superresolution and single-molecule RNA imaging in live cells

Fluorescent RNAs (FRs) have emerged as powerful tools for the visualization of RNA in live cells. However, the poor folding of FRs is a major limiting factor in many advanced RNA imaging applications. Here, we describe a novel strategy to significantly increase the folding efficiency of FRs. By introducing a stabilizing stem and performing targeted mutagenesis at key junction regions, we develop a superfolder variant of the Pepper aptamer, termed sfPepper, that exhibits a striking twofold increase in folding efficiency compared with Pepper under physiological conditions. sfPepper exhibits much improved thermostability and reduced ion dependence and, most importantly, is substantially brighter than Pepper in live cells. sfPepper enables robust imaging of diverse noncoding RNAs and messenger RNAs with increased signal-to-background ratios and stimulated emission depletion (STED) superresolution imaging of CUG trinucleotide repeat-containing toxic RNAs. Remarkably, only four sfPepper repeats facilitate sensitive single-molecule mRNA tracking, revealing dynamic heterogeneity among ER-associated mRNA molecules. Together, this study establishes an efficient strategy for improving FR folding and offers a powerful tool for fluorescently labelling RNAs in live cells.

molecular biology↗

bioRxiv2026

Germline-mediated ubiquitous recombination in ScxCre male mice: implications for tendon research

Scleraxis (Scx), a basic helix-loop-helix (bHLH) transcription factor, is a primary marker for tendon and ligament lineages. Consequently, mouse models utilizing Cre recombinase under the control of the Scx locus represents a powerful tool for control of gene expression in tendon. The constitutive ScxCre mouse line is widely used for tendon-specific genetic manipulation. In this study, we demonstrate that ScxCre exhibits undesired significant off-target activity in the male germline, leading to ubiquitous recombination of floxed alleles in all tissues of the resulting offspring. This inheritance of recombined LoxP alleles occurs independently of Cre inheritance, indicating that ScxCre-induces recombination occurs prior to meiosis in diploid germ cells. This off-target activity is not observed in female germline. These findings highlight a critical need for stringent parental sex selection when using ScxCre lines to ensure tissue-specific targeting and avoid unintentional global gene deletion or transgene activation.

genetics↗

bioRxiv2026

Cardiac oxidative stress monitoring enabled by hierarchical mechanical adaptation

Soft bioelectronics have advanced cardiac monitoring through electrophysiological tracking, yet this alone cannot resolve the metabolic pathology essential to surgical decision-making. However, real-time molecular sensing on beating hearts remains unresolved due to deformation-induced sensor failure and stress-induced metabolite artifacts. This challenge is exemplified by ischemia-reperfusion injury (IRI), a major cardiac surgery complication characterized by reactive oxidative species (ROS) bursts, where true pathological ROS signals being confounded by mechanotransduction-induced ROS artifacts. Herein, we propose an enzymatic cardiac oxidative stress biosensor (E-cardiac) with hierarchical mechanical adaptation: macro-scale biofluid-mediated contact, micro-scale fiber reorganization, and nano-scale enzymatic confinement within gold nanoarches dissipate interfacial stress. This produces ultrathin ([~]460 nm), soft (0.79 kPa) E-cardiac with robust electrochemical stability (100% strain), low detection limit (380 nM), rapid adhesion (<3 s), stable biosensing on beating heart, as well as minimal invasive deployment capability. Mechanical analysis and cellular studies confirm mitigated stress-induced ROS and absent PIEZO channel activation. Validated across cardiomyocytes, ex vivo tissues, multi-species ischemia models (mouse, rat, rabbit, pig), rat ischemia-reperfusion injury, and Langendorff hearts simulating graded perfusion deficits, E-cardiac quantitatively differentiates IRI severity (sham < ischemia < reperfusion) as well as detecting the "ECG blind window". The E-cardiac platform provides real-time metabolic feedback for surgical guidance during cardiac procedures, enabling timely intervention before irreversible damage.

bioengineering↗

bioRxiv2026

Enhancing Pan-cancer Spatial Transcriptomics atSingle-cell Resolution with stPainter

Subcellular spatial transcriptomics technologies offer unprecedented views of tissue architecture but are fundamentally constrained by sparse gene panels and limited detection sensitivity. Current computational enhancement strategies typically rely on tissue-matched single-cell RNA sequencing (scRNA-seq) references and necessitate computationally intensive retraining for each dataset, impeding their scalability and clinical applicability. Here, we present STPAINTER, a conditional generative model that leverages a massive pretraining pan-cancer scRNA-seq atlas to universally enhance spatial transcriptomics data. Built upon a latent diffusion architecture with stochastic differential equation-guided generation, STPAINTER learns a universal manifold of cellular states to reconstruct genome-wide expression profiles from sparse spatial measurements. Uniquely, our pretraining paradigm enables zero-shot generalization and empowers downstream tasks by providing imputed transcriptomes and informative latent variables to enhance resolution at both the gene and cluster levels. Applied STPAINTER upon 6 spatial transcriptomics datasets of different cancer types, we demonstrate that our model empowers high-fidelity downstream analyses, including fine-grained subpopulation clustering and pathway enrichment. Furthermore, cross-validation with spatially resolved proteomics (CODEX) confirms the biological veracity of the imputed cellular landscapes. STPAINTER provides a robust, scalable framework for decoding complex tumor microenvironments without the need for auxiliary sequencing data.

bioinformatics↗

bioRxiv2026

Large-scale quantum computing framework enhances drug discovery in multiple stages

Coherent Ising machines (CIMs) excel at solving large-scale combinational optimization problems (COPs), but their insufficient long-term stability has hindered their applications in compute-intensive tasks like computer-aided drug discovery (CADD). By improving fiber vibration isolation and temperature control system, we have implemented a 2000-node CIM named QBoson-CPQC-3Gen achieving stable solutions over one hour on large-scale COPs. Graph-based encoding schemes were further introduced to realize a CIM-based CADD workflow including allosteric site detection, protein-peptide docking and intermolecular similarity calculation. CIM-based methods demonstrated superior speed and accuracy than heuristic algorithms. Especially, QBoson-CPQC-3Gen identified 2 novel druggable sites and bioactive compounds for 6 targets, which were further validated in vitro, in-cell and by crystal structures. Our contributions established a quantum-computing framework for multi-stage drug discovery, representing a significant advancement in both quantum computing applications and pharmaceutical research.

bioinformatics↗

bioRxiv2026

A Beneficial Endornavirus Enhances the Fitness of Phytopathogenic Fungus Rhizotonia solani

Although viruses are primarily characterized as pathogenic agents, certain viruses confer advantages to their hosts. The extent to which a virus can improve host biological performance, however, remains a fascinating topic in virology. An endornavirus, Rhizoctonia solani endornavirus IM (RsEV-IM), was identified as prevalent in Rhizoctonia solani isolates obtained from potato plants. Comparative analysis with a virus-free isogenic strain demonstrated that RsEV-IM infection enhances mycelial growth, sclerotium formation, stress tolerance, and fungal virulence across multiple plant species. Inoculation tests involving numerous R. solani strains confirmed that only RsEV-IM-infected strains exhibited high pathogenicity, independent of other mycovirus infections. Additionally, its secreted protein fraction of RsEV-IM-infected fungus contained elevated levels of various proteins, including those involved in cell wall degradation. This fraction not only facilitated R. solani infection but also suppressed the growth of other fungi and bacteria. These findings position RsEV-IM as a beneficial virus that widely enhances its hosts biological fitness. From both pathological and ecological perspectives, these observations are significant, as they reveal that a mycovirus can serve as a key virulence determinant in fungal populations and potentially shape microbial community dynamics in natural environments. ImportanceFungal pathogenicity and ecological traits have long been thought to be primarily governed by endogenous genetic factors. However, this study reveals a mutualistic relationship between an endornavirus (RsEV-IM) and Rhizoctonia solani, demonstrating that viral infection enhances fungal virulence and ecological fitness. RsEV-IM stimulates fungal growth and the secretion of cell wall-degrading enzymes, resulting in a severe disease phenotype. Ecologically, RsEV-IM-infected fungi potentially gain a competitive advantage over soil microbiota. These findings present a key example of a virus acting as an essential extrachromosomal determinant of fungal pathogenicity and ecosystem interactions. Our results advance the understanding of fungal virulence mechanisms and underscore the broader significance of beneficial virus-fungus associations in agriculture and microbial ecology.

microbiology↗

bioRxiv2026

Non-invasive tracking of hippocampal theta oscillations

Hippocampal theta oscillations play a crucial role in the formation of episodic memories by binding multisensory information into coherent episodes. Brain stimulation studies suggest that memory performance can be modulated by targeting these oscillations, offering a potential way of treating memory disorders. However, to effectively engage these rhythms, precise knowledge about their presence, frequency, phase and location is required, which has been a challenge, particularly for non-invasive methods such as magnetoencephalography (MEG). Here, we first asked if hippocampal signals are detectable in MEG recordings. Using simultaneous MEG-intracranial EEG (iEEG) data, we show that invasively recorded hippocampal activity is reflected in MEG sensor signals, demonstrating the feasibility of detecting deep-brain activity non-invasively. Building on this, we introduce a MEG-based analysis pipeline to track hippocampal theta frequency over time. Applied across three independent datasets, the pipeline captured characteristic hippocampal theta frequency patterns in both rodents and humans, and MEG-derived hippocampal frequencies were consistent with those observed simultaneously in intracranial EEG. These findings provide evidence that MEG can reliably track individual hippocampal oscillatory dynamics, paving the way for future non-invasive closed-loop interventions that adapt stimulation frequency and timing to ongoing oscillations.

neuroscience↗

bioRxiv2025

TXNDC5 Governs Extracellular Matrix Homeostasis in Pulmonary Hypertension

BACKGROUNDPulmonary hypertension (PH) is characterized by vascular remodeling without effective treatments. Thioredoxin domain containing 5 (TXNDC5), a member of the protein disulfide isomerases (PDI) family, regulates protein folding and vascular homeostasis, yet its role in PH remains unknown. METHODSLabel-free proteomics profiled protein expression in lungs from PH patients. TXNDC5 was analyzed by single-cell RNA sequencing, immunofluorescence, and Western blot. Endothelial gain- and loss-of-function approaches were applied in Sugen5416/hypoxia (SuHx)-induced rodent PH models. RNA sequencing and protein-protein interaction analysis were used to investigate underlying mechanisms. RESULTSTXNDC5 was significantly upregulated in the lungs of patients with PH and in experimental PH models, with predominant localization in endothelial cells (ECs) of remodeled distal pulmonary arteries. Endothelial TXNDC5 overexpression exacerbated pulmonary vascular remodeling, elevated right ventricular systolic pressure, and promoted right ventricular hypertrophy, whereas global or endothelial-specific TXNDC5 deficiency conferred protection against SuHx-induced PH. Hypoxia-induced factor (HIF)-2 transcriptionally activated TXNDC5 to drive PH development. Single-cell RNA sequencing identified a distinct subpopulation characterized by TXNDC5high extracellular matrix (ECM)-producing ECs. Bulk RNA sequencing combined with protein-protein interaction analysis revealed that TXNDC5 regulated ECM homeostasis through biglycan (BGN). Pharmacological inhibition of TXNDC5 with E64FC26 and endothelial-targeted TXNDC5 gene therapy significantly attenuated PH severity in rats. CONCLUSIONSOur study reveals that TXNDC5 is a main modulator to regulate ECM homeostasis and may serve as a promising target for the treatment of PH.

molecular biology↗

bioRxiv2025

Dynamic profiling of the aggresome processing pathway

Cellular homeostasis is maintained by the efficient degradation of proteins by the 26S proteasome, a key component of the ubiquitin proteasome system. When the proteasome function is impaired due to cellular stress like mutations, chemicals or epigenetic stressors, there is accumulation of unfolded or misfolded, ubiquitinated proteins leading to cellular toxicity. Cells combat this rise in cellular toxicity by sequestering ubiquinated proteins in a transient cellular structure called the aggresome. The transport of this ubquitinated protein cargo along the microtubules to form aggresomes and their clearance from cells by autophagy is called the aggresome processing pathway (APP). APP activation is a hallmark of several neurodegenerative diseases and has also been implicated in Influenza A Virus uncoating step. To study the dynamics of APP and the compositional diversity of the aggresome, we used time-dependent proximity labeling, mass spectrometry, and immunofluorescence microscopy. Here, we used vimentin (VIM) and histone deacetylase 6 (HDAC6), two established aggresome markers as baits to visualize aggresome formation and clearance in HeLa cells. We identified more than 75 novel components of mature aggresome. Further, we characterised the time-dependent protein-protein interactions in the neighbourhood of VIM and HDAC6 during APP progression. Our study identified new interactors of VIM and HDAC6 that maybe involved in aggresome clearance by autophagy. Together, our findings uncover novel APP-associated proteins that are central to advancing the understanding of this poorly characterized and highly complex pathway implicated in multiple diseases.

molecular biology↗

bioRxiv2025

Ultra-mild bisulfite outperforms EM-seq for 5-methylcytosine detection with low input DNA

We present Ultra-Mild Bisulfite Sequencing (UMBS-seq), a method for 5-methylcytosine (5mC) detection that minimizes DNA degradation and background noise. UMBS-seq outperforms conventional bisulfite and enzymatic methyl-sequencing (EM-seq) methods in library yield, complexity, and conversion efficiency when applied to low-input DNA samples. In particular, its effectiveness with low-input cell-free DNA (cfDNA) and hybridization-based target capture highlight its potential for clinical applications, including 5mC biomarker detection and early disease diagnosis.

genomics↗

bioRxiv2025

Illuminating the Virosphere's Dark Matter using Hierarchical Deep Learning

Systematic discovery of novel viruses is essential for pandemic preparedness, understanding tumor-associated viruses, developing viral delivery systems, and advancing biomedical applications. Yet, the majority of sequences in metagenomic datasets lack close relatives in existing references, representing a vast viral "dark matter" whose biology and evolution remain largely unknown. The central task is threefold: 1) to determine whether a genome is viral or non-viral, 2) to correctly assign viral genomes to known lineages when possible, and, critically, 3) to recognize when no existing lineage applies and thereby identify candidates for entirely novel viral groups. Existing approaches, which depend on sequence homology or narrow markers, struggle to capture this uncharted viral space. Here we present DeepVirus, a hierarchical transformer-based framework that models viral genomes as structured sequences of protein-coding genes. By combining protein-level embeddings from a foundation model with genome-aware representations, DeepVirus not only achieves accurate classification across deep taxonomic hierarchies, but also extends beyond conventional classification to detect and organize candidate novel viral lineages through open-set recognition. Applied to large-scale metagenomic resources, DeepVirus uncovered extensive viral diversity, including previously uncharacterized RNA-dependent RNA polymerases (RdRps), thereby expanding the known evolutionary space of RNA viruses. DeepVirus integrates deep learning with genome-aware open-set discovery to illuminate viral dark matter, providing a foundation for systematic viral taxonomy and advancing exploration of the global virosphere, with broad implications for safeguarding human health.

bioinformatics↗

bioRxiv2025

Development of LYTACs via incorporating a nucleolin-targeting and lysosome-directed aptamer

Lysosomal targeting chimeras (LYTACs) represent an emerging class of bifunctional molecules that bridge extracellular target proteins with intrinsic lysosome-targeting receptors (LTRs) on the cell surface, facilitating endocytic internalization and subsequent lysosomal degradation of the targets. However, the therapeutic potential of LYTACs has been limited by the scarcity of suitable intrinsic LTRs. We previously identified an aptamer, SAPT8, that selectively targets nucleolin, a shuttling protein overexpressed on the surface of pathogenic FLSs in rheumatoid arthritis (RA), and induced its lysosomal degradation. In this study, we repurposed SAPT8 as a tumor-targeting and lysosome-directed ligand, leveraging the elevated expression of NCL on tumor cell surfaces. By conjugating SAPT8 with either the c-Met-binding aptamer SL1 or the small molecule inhibitor Tepotinib, we engineered novel LYTACs that demonstrated potent tumor-targeting capability and induced concurrent degradation of both c-Met and NCL, leading to significant antitumor effects. Furthermore, fusion of SAPT8 with VEGFR-2-targeting aptamer Apt02 generated LYTACs that simultaneously degraded VEGFR-2 and NCL, effectively suppressing RA-FLS activity. These results establish SAPT8 as a versatile platform for developing next-generation LYTACs, overcoming current limitations in extracellular protein degradation by circumventing dependence on endogenous LTRs. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=69 SRC="FIGDIR/small/672993v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@975b74org.highwire.dtl.DTLVardef@f55565org.highwire.dtl.DTLVardef@b9639corg.highwire.dtl.DTLVardef@13aaba7_HPS_FORMAT_FIGEXP M_FIG C_FIG

pathology↗

bioRxiv2025

Protective Effect of Cannabinoid Type II Receptor Ligand on Bleomycin-Induced Pulmonary Fibrosis in Mice

This study aimed to investigate the protective effects of the CB2R ligand compound COCA (N-(3-chloro-2-methylphenyl)-5-(4-hydroxyphenyl)-1,2-oxazole-3-carboxamide) against bleomycin (BLM)-induced pulmonary fibrosis in mice. Compound COCA was identified via AI-driven virtual screening from the ChEMBL database. Forty male C57BL/6J mice were randomly divided into five groups: control, model (BLM), low-dose COCA, high-dose COCA, and pirfenidone. Pulmonary fibrosis was induced by intratracheal BLM administration in the model and treatment groups. Pathological evaluation, ELISA, immunofluorescence, and Western blot were conducted.The results showed that COCA significantly alleviated BLM-induced inflammation and fibrosis. ELISA demonstrated decreased serum levels of TNF- and IL-6 in the treated groups compared to the BLM group (P < 0.01). Immunofluorescence indicated reduced expression of Col-I and Col-III in the treated groups (P < 0.01). Western blot analysis revealed an upregulation of CB2R in the BLM group, and enhanced expressions of Nrf2 and Smad7 in the treated groups (P < 0.01).In conclusion, AI-driven virtual screening enabled the identification of the CB2R ligand COCA, which binds to CB2R, activates the Nrf2/Smad7 pathway, downregulates related cytokines, and plays a therapeutic and protective role in pulmonary fibrosis.

pharmacology and toxicology↗