Biology subjects

Ying, T.

Publications and source records attributed to Ying, T..

14 recordsLinked to original sources

bioRxiv2026

Decoding antibody-antigen recognition: the BL8 language and its application in calibrating deep learning predictions

Antibodies are central to immunology and therapeutics, and understanding how they recognize antigens is essential to rational drug design. This recognition depends on the interplay of interface geometry, physicochemical interactions, sequence context, and complementarity-determining region (CDR) conformation. However, traditional analyses often oversimplify this complexity, which becomes particularly problematic when evaluating the massive and frequently overconfident structural hypotheses generated by modern deep learning models. Here, we introduce BL8, an interpretable, eight-view structural language that comprehensively parameterizes interfaces across topology, shape, interaction, CDR conformation, flexibility, interfacial area, amino-acid-pair composition, and sequence background. Using 15,396 experimental interface records from the Structural Antibody Database (SAbDab), we built a fixed reference atlas containing 1,498 discrete BL8 signatures. The atlas shows that natural interfaces occupy a diverse, long-tailed structural space in which similar geometric scaffolds can be associated with different chemical and sequence features. Furthermore, we projected 28,501 predicted complexes involving programmed death-ligand 1 (PD-L1), the SARS-CoV-2 receptor-binding domain (RBD), and programmed cell death protein 1 (PD-1), generated using AlphaFold 3 (AF3), Protenix-v2, and OpenDDE, into the reference space. Acting as a robust underlying calibration layer, BL8 successfully decoupled physical viability from native confidence illusions, revealing cross-target hallucinations and filtering out 15.3% to 20.1% of highly deceptive false-positive predictions. Crucially, by benchmarking distinct generative behaviors across models, it enabled the extraction of highly reliable, multi-model consensus out-of-distribution binding paradigms. Together, BL8 bridges foundational biophysics with large-scale computational predictions, providing an essential benchmarking framework for discovering novel mechanisms in the era of artificial intelligence.

immunology↗

bioRxiv2025

A Generative Foundation Model for Antibody Design

Antibodies are indispensable components of the immune system, yet the design of high-affinity antibodies remains a time-consuming and experimentally intensive process. To address this challenge, we present IgGM, a novel generative foundation model designed to accelerate high-affinity antibody engineering. IgGM learns the complex relationships underlying the binding interactions between antigens and antibodies, as well as the mapping between antibody sequences and structures. By conditioning on different inputs, IgGM supports a wide range of antibody design tasks, including complex structure prediction, inverse design, affinity maturation, framework optimization, humanization, and de novo antibody design. It is compatible with both conventional antibodies and nanobodies, and allows user-defined CDR loop lengths for flexible design. To prioritize candidates, we introduce a frequency-based computational screening strategy that enhances design efficiency. Extensive evaluation through both in silico benchmarks and in vitro experiments across diverse antigens such as PD-L1, Protein A, TNF-, IL-33, SARS-CoV-2 RBD and its variants demonstrates that IgGM consistently generates antibodies or nanobodies with high measured affinity. These results underscore IgGMs versatility and effectiveness as a powerful tool for next-generation antibody discovery and optimization.

bioinformatics↗

bioRxiv2025

CircRNA-based, non-integrated, in vivo panCAR-mediated B cell immune resetting in mouse models and non-human primates

B cell immune resetting, defined as the comprehensive depletion and subsequent reconstitution of B cells, represents a pivotal therapeutic approach for B cell-associated disorders. Recently, chimeric antigen receptor T cell (CAR-T) therapy has demonstrated substantial clinical efficacy in treating B cell malignancies and autoimmune diseases. However, this approach remains constrained by its reliance on lymphodepleting conditioning regimens, high invasiveness, high costs, and the risk of severe cytokine release syndrome (CRS). Antibody-based therapies, including monoclonal antibodies and T cell-engager (TCE) bispecific antibodies, suffer from suboptimal tissue penetration, resulting in inadequate B cell depletion in lymphoid and peripheral tissues, and subsequent rapid resurgence of pathogenic B cells. Here, we engineered highly stable circular RNAs (circRNAs) encoding anti-CD19 CAR (circRNA-CAR), which demonstrated prolonged and enhanced CAR protein expression compared to conventional linear mRNAs. By employing immune cell-tropic lipid nanoparticles (LNPs) for in vivo delivery, circRNA-CAR facilitated the generation of panCAR immune cells (including CAR-T, CAR-NK, and CAR-macrophages) in both murine models and cynomolgus monkeys. Compared to rituximab or teclistamab, in vivo panCAR induced more extensive B cell depletion across multiple tissue compartments in mice. Moreover, in vivo panCAR mediated robust B cell depletion, eliminated autoreactive antibodies, and restored renal function by alleviating proteinuria in a systemic lupus erythematosus (SLE) murine model. It also effectively reduced IgE antibody levels, decreased eosinophil activity, and improved lung pathology in an asthma murine model. Notably, in vivo panCAR-mediated B cell depletion significantly attenuated aging-associated phenotypes in 17- month-old aging mice, remarkably outperforming both rituximab and teclistamab. In cynomolgus monkeys, in vivo panCAR achieved sustained B cell depletion lasting approximately 40 to 50 days, followed by reconstitution of a naive B cell repertoire. Collectively, circRNA-based in vivo panCAR enables complete B cell immune resetting, offering a versatile and promising therapeutic platform for a broad spectrum of B cell- and antibody-mediated disorders.

immunology↗

bioRxiv2025

Complement C3 recognition by C3 convertases

The complement system plays a fundamental role in human immunity, and its dysregulation is implicated in numerous diseases. Activation of the complement occurs through three main pathways: classical, lectin, and alternative; which converge at the central component, C3. The classical and lectin pathways utilize the C4b2a convertase to cleave C3 and initiate complement activation, while the alternative pathway employs the C3bBb convertase, which is further stabilized by properdin. The molecular mechanisms governing C3 recognition by these convertase complexes remain incompletely understood. Here, we first present a 3.1 [A] cryo-electron microscopy (cryo-EM) structure of the C4b2a-C3 complex, alongside the 2.9 [A] and 3.1 [A] structures of the C4b2 zymogen in the loading and activation states. These structural snapshots elucidate the structural basis for C3 engagement by C4b2a, and illustrate sequential conformational changes during the classical/lectin pathway convertase maturation. Furthermore, we determine a 2.6 [A] cryo-EM structure of the C3bBb-properdin-C3 complex, which uncovers unique substrate-binding features of C3bBb and sheds light on how properdin stabilizes the alternative pathway convertase. These results offer comprehensive mechanistic insights into complement activation.

molecular biology↗

bioRxiv2025

A synergistic generative-ranking framework for tailored design of therapeutic single-domain antibodies

Single-domain antibodies (sdAbs) have emerged as powerful therapeutic agents due to their small size, high stability, and superior tissue penetration. However, unlike conventional monoclonal antibodies (mAbs), sdAbs lack an Fc domain, limiting their functional versatility and manufacturability. To address this challenge, we developed TFDesign-sdAb, a deep learning-based generative-ranking framework that enables rational engineering of sdAbs with tailored functionalities. Our framework integrates a structure-aware diffusion model (IgGM) for large-scale candidate generation and a fine-tuned sorter (A2binder) that evaluates and prioritizes them based on predicted functionality. Unlike traditional CDR-focused approaches, TFDesign-sdAb optimizes both complementarity-determining regions (CDRs) and framework regions (FRs), allowing sdAbs to acquire new functional properties while maintaining antigen specificity. We validated our approach by conferring Protein A binding to human VHs and nanobodies that originally lacked this feature, achieving high expression rates, strong binding affinities, and successful purification via industry-standard Protein A affinity chromatography. High-resolution structural characterization (1.49 [A] and 2.0 [A]) of the redesigned sdAb-Protein A complexes revealed conserved FR-mediated binding motifs that recapitulate natural Fc-Protein A interactions, validating the accuracy of our model. Furthermore, our pipeline streamlined the antibody engineering process, achieving a 100% success rate in generating Protein A-binding sdAbs while maintaining their original antigen-binding affinity. This work demonstrates the power of AI-driven design in overcoming long-standing limitations in antibody engineering and presents a scalable, generalizable solution for enhancing sdAb functionality.

bioinformatics↗

bioRxiv2023

Pretrainable Geometric Graph Neural Network for Antibody Affinity Maturation

Increasing the binding affinity of an antibody to its target antigen is a crucial task in antibody therapeutics development. This paper presents a pretrainable geometric graph neural network, GearBind, and explores its potential in in silico affinity maturation. Leveraging multi-relational graph construction, multi-level geometric message passing and contrastive pretraining on mass-scale, unlabeled protein structural data, GearBind outperforms previous state-of-the-art approaches on SKEMPI and an independent test set. A powerful ensemble model based on GearBind is then derived and used to successfully enhance the binding of two antibodies with distinct formats and target antigens. ELISA EC50 values of the designed antibody mutants are decreased by up to 17 fold, and KD values by up to 6.1 fold. These promising results underscore the utility of geometric deep learning and effective pretraining in macromolecule interaction modeling tasks.

bioinformatics↗

bioRxiv2023

Vaccinia virus induces EMT-like transformation and RhoA-mediated mesenchymal migration

The emerging outbreak of monkeypox is closely associated with the viral infection and spreading, threatening global public health. Virus-induced cell migration facilitates viral transmission. However, high-resolution dynamics and mechanisms underlying this type of cell migration remain unclear. Here, we investigate the motility of cells infected by vaccinia virus (VACV), a close relative of monkeypox, through combining multi-omics analyses and high-resolution live-cell imaging. We find that, upon VACV infection, the epithelial cells undergo EMT-like transformation, during which they lose intercellular junctions and acquire the migratory capacity to promote viral spreading. After transformation, VACV-induced mesenchymal migration is highly dependent on the actin cytoskeleton and RhoA signaling, which is responsible for the depolymerization of robust actin stress fibers, the leading-edge protrusion formation, and the rear-edge recontraction. Our study reveals how poxviruses alter the epithelial phenotype and regulate RhoA signaling to induce fast migration, providing a unique perspective to understand the pathogenesis of poxviruses.

cell biology↗

bioRxiv2022

A potent SARS-CoV-2 antibody neutralizes Omicron variant by disassembling the spike trimer

The continuous emergence of novel SARS-CoV-2 variants poses new challenges to the fight against the COVID-19 pandemic. The newly emerging Omicron strain caused serious immune escape and raised unprecedented concern all over the world. The development of antibody targeting conserved and universal epitope is urgently needed. A subset neutralizing antibody(nAbs) against COVID-19 from convalescent patients were isolated in our previous study. Here in this study, we investigated the accommodation of these nAbs to SARS-CoV-2 variants of concerns (VOCs), revealing that IgG 553-49 neutralizes pseudovirus of SARS-CoV-2 Omicron variant. In addition, we determined the cryo-EM structure of SARS-CoV-2 spike complexed with three antibodies targeting different epitopes, including 553-49, 553-15 and 553-60. Notably, 553-49 targets a novel conserved epitope and neutralizes virus by disassembling spike trimers. 553-15, an antibody that neutralizes all the other VOCs except omicron, cross-links two spike trimers to form trimer dimer, demonstrating that 553-15 neutralizes virus by steric hindrance and virion aggregation. These findings suggest the potential to develop 49 and other antibody targeting this highly conserved epitope as promising cocktail therapeutics reagent for COVID-19. ImportanceThe newly emergence of Omicron strain caused higher immune escape, raising unprecedented concerns about the effectiveness of antibody therapies and vaccines. In this study, we identified a SARS-CoV-2 Omicron neutralizing antibody 553-49, which neutralizes Omicron variant by targeting a completely conserved novel epitope. Besides, we revealed that IgG 553-15 neutralizes SARS-CoV-2 by crosslinking virions and 553-60 functions by blocking receptor binding. Comparison of different RBD epitopes revealed that the epitope of 553-49 is hidden in the S trimer and keeps high conservation during SARS-CoV-2 evolution, making 553-49 a promising therapeutics reagent to fight against the emerging Omicron and future variant of SARS-CoV-2.

microbiology↗

bioRxiv2021

Broad neutralization of SARS-CoV-2 variants by an inhalable bispecific single-domain antibody

The effectiveness of SARS-CoV-2 vaccines and therapeutic antibodies has been limited by the continuous emergence of viral variants, and by the restricted diffusion of antibodies from circulation into the sites of respiratory virus infection. Here, we report the identification of two highly conserved regions on Omicron variant RBD recognized by broadly neutralizing antibodies. Based on this finding, we generated a bispecific single-domain antibody that was able to simultaneously and synergistically bind these two regions on a single Omicron variant RBD as revealed by Cryo-EM structures. This inhalable antibody exhibited exquisite neutralization breadth and therapeutic efficacy in mouse models of SARS-CoV-2 infections. The structures also deciphered an uncommon cryptic epitope within the spike trimeric interface that may have implications for the design of broadly protective SARS-CoV-2 vaccines and therapeutics.

immunology↗

bioRxiv2021

Antibody Cocktail Exhibits Broad Neutralization against SARS-CoV-2 and SARS-CoV-2 variants

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has precipitated multiple variants resistant to therapeutic antibodies. In this study, 12 high-affinity antibodies were generated from convalescent donors in early outbreaks using immune antibody phage display libraries. Of them, two RBD-binding antibodies (F61 and H121) showed high affinity neutralization against SARS-CoV-2, whereas three S2-target antibodies failed to neutralize SARS-CoV-2. Following structure analysis, F61 identified a linear epitope located in residues G446 -S494, which overlapped with angiotensin-converting enzyme 2 (ACE2) binding sites, while H121 recognized a conformational epitope located on the side face of RBD, outside from ACE2 binding domain. Hence the cocktail of the two antibodies achieved better performance of neutralization to SARS-CoV-2. Importantly, F61 and H121 exhibited efficient neutralizing activity against variants B.1.1.7 and B.1.351, those showed immune escape. Efficient neutralization of F61 and H121 against multiple mutations within RBD revealed a broad neutralizing activity against SARS-CoV-2 variants, which mitigated the risk of viral escape. Our findings defined the basis of therapeutic cocktails of F61 and H121 with broad neutralization and delivered a guideline for the current and future vaccine design, therapeutic antibody development, and antigen diagnosis of SARS-CoV-2 and its novel variants.

immunology↗

bioRxiv2020

A single dose SARS-CoV-2 simulating particle vaccine induces potent neutralizing activities

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for which a vaccine is urgently needed to control its spreading. To facilitate the representation of a native-like immunogen without being infectious, here, we reported a SARS-CoV-2 vaccine candidate (designated ShaCoVacc) by incorporating spike-encoding mRNA inside and decorating spike protein on the surface of the virus simulating particles (VSPs) derived from lentiviral particles. We characterized the mRNA copy number, glycosylation status, transduction efficiency, and innate immune property of the new vaccine platform. Importantly, we showed the ShaCoVacc induced strong spike-specific humoral immune responses and potent neutralizing activities by a single injection. Additionally, we disclosed the epitopes of spike-specific antibodies using peptide microarray and revealed epitopes susceptible to specific neutralizing antibodies. These results support further development of ShaCoVacc as a candidate vaccine for COVID-19 and VSP may serve as a new vaccine platform for emerging infectious diseases.

bioengineering↗

bioRxiv2020

Fully human single-domain antibodies against SARS-CoV-2

The COVID-19 pandemic is spreading rapidly, highlighting the urgent need for an efficient approach to rapidly develop therapeutics and prophylactics against SARS-CoV-2. We describe here the development of a phage-displayed single-domain antibody library by grafting naive CDRs into framework regions of an identified human germline IGHV allele. This enabled the isolation of high-affinity single-domain antibodies of fully human origin. The panning using SARS-CoV-2 RBD and S1 as antigens resulted in the identification of antibodies targeting five types of neutralizing or non-neutralizing epitopes on SARS-CoV-2 RBD. These fully human single-domain antibodies bound specifically to SARS-CoV-2 RBD with subnanomolar to low nanomolar affinities. Some of them were found to potently neutralize pseudotyped and live virus, and therefore may represent promising candidates for prophylaxis and therapy of COVID-19. This study also reports unique immunogenic profile of SARS-CoV-2 RBD compared to that of SARS-CoV and MERS-CoV, which may have important implications for the development of effective vaccines against SARS-CoV-2.

microbiology↗

bioRxiv2020

Public broadly neutralizing antibodies against hepatitis B virus in individuals with elite serologic activity

SUMMARYAlthough there is no effective cure for chronic hepatitis B virus (HBV) infection, antibodies are protective and constitute clinical correlates of recovery from infection. To examine the human neutralizing antibody response to HBV in elite neutralizers we screened 144 individuals. The top individuals produced shared clones of broadly neutralizing antibodies (bNAbs) that targeted 3 non-overlapping epitopes on the HBV S antigen (HBsAg). Single bNAbs protected humanized mice against infection, but selected for resistance mutations in mice with established infection. In contrast, infection was controlled by a combination of bNAbs targeting non-overlapping epitopes with complementary sensitivity to mutations that commonly emerge during human infection. The co-crystal structure of one of the bNAbs with a peptide epitope containing residues frequently mutated in human immune escape variants revealed a loop anchored by oppositely charged residues. The structure provides a molecular explanation for why immunotherapy for HBV infection may require combinations of complementary bNAbs.

immunology↗

bioRxiv2020

Potent binding of 2019 novel coronavirus spike protein by a SARS coronavirus-specific human monoclonal antibody

The newly identified 2019 novel coronavirus (2019-nCoV) has caused more than 800 laboratory-confirmed human infections, including 25 deaths, posing a serious threat to human health. Currently, however, there is no specific antiviral treatment or vaccine. Considering the relatively high identity of receptor binding domain (RBD) in 2019-nCoV and SARS-CoV, it is urgent to assess the cross-reactivity of anti-SARS-CoV antibodies with 2019-nCoV spike protein, which could have important implications for rapid development of vaccines and therapeutic antibodies against 2019-nCoV. Here, we report for the first time that a SARS-CoV-specific human monoclonal antibody, CR3022, could bind potently with 2019-nCoV RBD (KD of 6.3 nM). The epitope of CR3022 does not overlap with the ACE2 binding site within 2019-nCoV RBD. Therefore, CR3022 has the potential to be developed as candidate therapeutics, alone or in combination with other neutralizing antibodies, for the prevention and treatment of 2019-nCoV infections. Interestingly, some of the most potent SARS-CoV-specific neutralizing antibodies (e.g., m396, CR3014) that target the ACE2 binding site of SARS-CoV failed to bind 2019-nCoV spike protein, indicating that the difference in the RBD of SARS-CoV and 2019-nCoV has a critical impact for the cross-reactivity of neutralizing antibodies, and that it is still necessary to develop novel monoclonal antibodies that could bind specifically to 2019-nCoV RBD.

microbiology↗