Biology subjects

Zha, J.

Publications and source records attributed to Zha, J..

11 recordsLinked to original sources

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↗

bioRxiv2025

Sampling Function-Related Metastable States of Proteins With DASH

Rational discovery of function-specific protein modulators as well as activity-enhanced engineering proteins underscore the need to identify function-related metastable states (FMSs) of proteins. However, current experimental and computational methods struggle to generate these states directly from their native state (NS), likely because the NS [->] FMS transition is non-spontaneous. To address this challenge, we introduce Deep learning guided Adaptive sampling with seed Selection and Hopping (DASH), integrating both deep learning and physical functions to guide molecular dynamics (MD) simulation towards FMS. DASH successfully sampled NS [->] FMS transitions in 18 cases across two tasks: protein activation and cryptic allosteric site opening. DASH combined with secondary-structure collective variables is further able to sample folding of disordered regions. Compared to existing methods, DASH demonstrates superior performance while requiring comparable simulation time. Crucially, we applied DASH to sample new conformations of proteins, by which revealing new folding states, previously unknown allosteric sites, and potential activators. These predictions have been further verified in wet-lab experiments and crystal structures determinations. Collectively, our framework provides a robust strategy for function-specific pharmacy research and could accelerate future drug discovery efforts.

bioinformatics↗

bioRxiv2025

Potent Efficacy of Computer-Aided Designed Peptide Degrader Drug on PCSK9-Mediated Hypercholesterolemia

Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a key regulator of low-density lipoprotein receptor (LDLR) degradation, which leads to increased levels of low-density lipoprotein cholesterol (LDL-C) and a heightened risk of hypercholesterolemia. Existing therapeutic strategies--such as monoclonal antibodies and gene-editing approaches--are limited by high production costs, potential safety concerns, and limited effectiveness in targeting intracellular PCSK9. Targeted protein degradation (TPD) represents a promising alternative capable of overcoming these limitations. In this study, we utilized computer-aided drug design (CADD) to develop a peptide-based degrader, Cadd4, aimed at selectively reducing PCSK9 levels. Through molecular docking and structural refinement, a peptide sequence with strong binding affinity to PCSK9 was identified. Functional evaluation was conducted both in vitro using human LX-2 cells and in vivo in high-fat diet (HFD)-induced hypercholesterolemic mouse models. Cellular uptake, PCSK9 degradation, and LDLR restoration were assessed via confocal microscopy, western blotting, and biochemical analysis. Safety was evaluated by monitoring liver enzyme levels and general physiological parameters. Cadd4 exhibited efficient intracellular delivery and selective PCSK9 degradation in LX-2 cell. In HFD-fed mice, hepatic PCSK9 expression was reduced by 38%, accompanied by a marked increase in LDLR levels. These changes translated into a 25% reduction in total plasma cholesterol and a 29% decrease in LDL-C concentrations. Biodistribution studies indicated liver-specific accumulation of Cadd4, consistent with its intended site of action. Experiments using human liver tissue further confirmed its ability to decrease PCSK9 and enhance LDLR levels. No signs of liver toxicity or adverse systemic effects were observed throughout the study. This work introduces Cadd4 as a CADD-designed peptide-based degrader capable of lowering plasma cholesterol by promoting LDLR recovery via PCSK9 degradation. Its intracellular mechanism of action addresses key gaps in current PCSK9-targeted therapies and supports the broader utility of TPD platforms in managing hypercholesterolemia. These findings offer a foundation for developing cost-effective, scalable therapies within the context of precision cardiovascular medicine.

pharmacology and toxicology↗

bioRxiv2025

The RNA splicing factor PRPF8 is required for left-right organiser cilia function and determination of cardiac left-right asymmetry via regulation of Arl13b splicing

Cilia function in the left-right organizer (LRO) is critical for determining internal organ asymmetry in vertebrates. To further understand the genetics of left-right asymmetry, we isolated a mouse mutant with laterality defects, l11Jus27, from a random mutagenesis screen. l11Jus27 mutants carry a missense mutation in the pre-mRNA processing factor, Prpf8. cephaloph[o]nus (cph) mutant zebrafish, carrying a protein truncating mutation in prpf8, phenocopy the laterality defects of l11Jus27 mutants. Prpf8 mutant mouse and fish embryos have increased expression of an alternative transcript encoding the cilium-associated protein, ARL13B, that lacks exon 9. In zebrafish, over-expression of the arl13b transcript lacking exon 9 perturbed cilium formation and caused laterality defects. The shorter ARL13B protein isoform lacked interactions with intraflagellar transport proteins. Our data suggest that PRPF8 plays a prominent role in LRO cilia by through the regulation of alternative splicing of ARL13B, thus uncovering a new mechanism for cilia-linked developmental defects.

developmental biology↗

bioRxiv2024

BayVarC: an ultra-sensitive ctDNA variant caller using Bayesian approach

In liquid biopsy, it is critical to detect variants of allele frequencies as low as 0.1% or even lower, especially when used to monitor secondary resistant mutations and minimal residual disease. Despite the efforts on improving experimental design, it remains challenging to distinguish low-frequency variants from technical noises in the downstream bioinformatic analysis. Here, we introduce BayVarC, a novel variant caller specifically designed for variant calling in liquid biopsy. It applies Bayesian inference to accurately quantify noise level in a locus-specific manner, enabling the discrimination between technical noise and low-frequency cancer variants. Detailed in-silico simulation and in-vitro experiments demonstrated BayVarC superior performance over existing state-of-the-art tools. BayVarC can effectively detect low frequency variants while maintaining low false positive rate (0.05 FP/KB). Meanwhile, it achieves Limit of Detection (LoD) as low as 0.1%. Furthermore, empowered by its architecture, BayVarC shows promising applicability in Minimal Residual Disease (MRD) detection. BayVarC is freely available at https://github.com/GenetronBioinfomatics/BayVarC.

bioinformatics↗

bioRxiv2022

Selective perijunctional MLCK1 recruitment in Crohn's disease: Identification of essential structural domains

Intestinal epithelia express two long myosin light chain kinase (MLCK) splice variants, MLCK1 and MLCK2. Unlike MLCK2, MLCK1 is concentrated at the perijunctional actomyosin ring and this localization is enhanced by tumor necrosis factor (TNF) signaling. Here we sought to identify and characterize the domain(s) that direct basal and TNF-induced MLCK1 subcellular localization. Quantitative morphometry demonstrated specific increases in MLCK1 expression and perijunctional localization in Crohns disease patient biopsies, relative to controls. TNF induced perijunctional recruitment of MLCK1-EGFP but did not affect localization of MLCK2-EGFP, which was predominantly associated with basal stress fibers. Recombinant N-terminal MLCK1 and MLCK2 regions accelerated actin polymerization in vitro but were not different from one another. In contrast, the affinity of N-terminal MLCK1 binding to F-actin was greater than that of MLCK2. Perijunctional MLCK1 and MLCK2 domain recruitment in intestinal epithelial cells paralleled in vitro F-actin binding. The unique MLCK1 Ig3 domain was necessary, but not sufficient, for both F-actin binding and perijunctional recruitment, but, nevertheless, displaced perijunctional MLCK1, enhanced steady-state barrier function, and limited TNF-induced MLCK1 recruitment and barrier loss. These data demonstrate selective perijunctional MLCK1 recruitment in Crohns disease, suggest that F-actin binding contributes to perijunctional recruitment, and show that Ig3 can act as a dominant negative effector that limits TNF-induced MLCK1 recruitment and barrier loss. These results data provide key mechanistic detail that will enable development of therapeutics that target Ig3, or its intercellular binding partners, to reverse inflammation-induced barrier loss and limit disease progression.

cell biology↗

bioRxiv2022

Single-Cell RNA-seq of Heart Reveals Intercellular Communication Drivers of Myocardial Fibrosis in Diabetic Mice

Diabetes-induced cardiomyopathy is characterized by myocardial fibrosis as a main pathology. In-depth study of cardiac heterogeneity and cell-to-cell interactions will help to reveal the pathogenesis of diabetic myocardial fibrosis and provide potential targets for the treatment of this disease. Here, we insighted into the intercellular communication drivers underlying myocardial fibrosis in mouse heart with high-fat-diet (HFD)/streptozotocin (STZ)-induced diabetes at single-cell resolution. Intercellular and protein-protein interaction networks of fibroblasts and macrophages, endothelial cells, as well as fibroblasts and epicardial cells reveal critical changes in ligand-receptor interactions such as Pdgf(s)-Pdgfra and Efemp1-Egfr, which promote the development of a profibrotic microenvironment during diabetes progression and confirm that specific inhibition of Pdgfra axis can significantly improve diabetic myocardial fibrosis. We further identified the phenotypically distinct Hrchi and Postnhi fibroblast subpopulations that are associated with pathological extracellular matrix remodeling, of which Hrchi fibroblasts are the most profibrogenic under diabetic conditions. Finally, we validated the role of Itgb1 hub gene mediated intercellular communication drivers of diabetic myocardial fibrosis in Hrchi fibroblasts, and confirmed the result by AAV9-mediated Itgb1 knockdown in the heart of diabetic mice. In summary, cardiac cell mapping provides novel insights into intercellular communication drivers underlying pathological extracellular matrix remodeling during diabetic myocardial fibrosis.

cell biology↗

bioRxiv2021

Pancreatic ductal adenocarcinoma cells employ integrin α6β4 to form hemidesmosomes and regulate cell proliferation

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis due to its aggressive progression, late detection and lack of druggable driver mutations, which often combine to result in unsuitability for surgical intervention. Together with activating mutations of the small GTPase KRas, which are found in over 90% of PDAC tumours, a contributory factor for PDAC tumour progression is formation of a rigid extracellular matrix (ECM) and associated desmoplasia. This response leads to aberrant integrin signalling, and accelerated proliferation and invasion. To identify the integrin adhesion systems that operate in PDAC, we analysed a range of pancreatic ductal epithelial cell models using 2D, 3D and organoid culture systems. Proteomic analysis of isolated integrin receptor complexes from human pancreatic ductal epithelial (HPDE) cells predominantly identified integrin 6{beta}4 and hemidesmosome components, rather than classical focal adhesion components. Electron microscopy, together with immunofluorescence, confirmed the formation of hemidesmosomes by HPDE cells, both in 2D and 3D culture systems. Similar results were obtained for the human PDAC cell line, SUIT-2. Analysis of HPDE cell secreted proteins and cell-derived matrices (CDM) demonstrated that HPDE cells secrete a range of laminin subunits and form a hemidesmosome-specific, laminin 332-enriched ECM. Expression of mutant KRas (G12V) did not affect hemidesmosome composition or formation by HPDE cells. Cell-ECM contacts formed by mouse and human PDAC organoids were also assessed by electron microscopy. Organoids generated from both the PDAC KPC mouse model and human patient-derived PDAC tissue displayed features of acinar-ductal cell polarity, and hemidesmosomes were visible proximal to prominent basement membranes. Furthermore, electron microscopy identified hemidesmosomes in normal human pancreas. Depletion of integrin {beta}4 using siRNA reduced cell proliferation in both SUIT-2 and HPDE cells, reduced the number of SUIT-2 cells in S-phase, and induced G1 cell cycle arrest, indicating a requirement for 6{beta}4-mediated adhesion for cell cycle progression and growth. Taken together, these data suggest that laminin-binding adhesion mechanisms in general, and hemidesmosome-mediated adhesion in particular, may be under-appreciated in the context of PDAC. Proteomic data are available via ProteomeXchange with the identifiers PXD027803, PXD027823 and PXD027827.

cancer biology↗

bioRxiv2021

Bayesian metamodeling of complex biological systems across varying representations

Comprehensive modeling of a whole cell requires an integration of vast amounts of information on various aspects of the cell and its parts. To divide-and-conquer this task, we introduce Bayesian metamodeling, a general approach to modeling complex systems by integrating a collection of heterogeneous input models. Each input model can in principle be based on any type of data and can describe a different aspect of the modeled system using any mathematical representation, scale, and level of granularity. These input models are (i) converted to a standardized statistical representation relying on Probabilistic Graphical Models, (ii) coupled by modeling their mutual relations with the physical world, and (iii) finally harmonized with respect to each other. To illustrate Bayesian metamodeling, we provide a proof-of-principle metamodel of glucose-stimulated insulin secretion by human pancreatic {beta}-cells. The input models include a coarse-grained spatiotemporal simulation of insulin vesicle trafficking, docking, and exocytosis; a molecular network model of glucose-stimulated insulin secretion signaling; a network model of insulin metabolism; a structural model of glucagon-like peptide-1 receptor activation; a linear model of a pancreatic cell population; and ordinary differential equations for systemic postprandial insulin response. Metamodeling benefits from decentralized computing, while often producing a more accurate, precise, and complete model that contextualizes input models as well as resolves conflicting information. We anticipate Bayesian metamodeling will facilitate collaborative science by providing a framework for sharing expertise, resources, data, and models, as exemplified by the Pancreatic {beta}-Cell Consortium. Significance StatementCells are the basic units of life, yet their architecture and function remain to be fully characterized. This work describes Bayesian metamodeling, a modeling approach that divides-and-conquers a large problem of modeling numerous aspects of the cell into computing a number of smaller models of different types, followed by assembling these models into a complete map of the cell. Metamodeling enables a facile collaboration of multiple research groups and communities, thus maximizing the sharing of expertise, resources, data, and models. A proof-of-principle is provided by a model of glucose-stimulated insulin secretion produced by the Pancreatic {beta}-Cell Consortium.

cell biology↗

bioRxiv2018

Localization of balanced chromosome translocation breakpoints by long-read sequencing on the Oxford Nanopore platform

Structural variants (SVs) in genomes, including translocations, inversions, insertions, deletions and duplications, remain difficult to be detected reliably by traditional genomic technologies. In particular, balanced translocations and inversions cannot be detected by microarrays since they do not alter chromosome copy numbers; they cannot be reliably detected by short-read sequencing either, since many breakpoints are located within repetitive regions of the genome that are unmappable by short reads. However, the detection and the precise localization of breakpoints at the nucleotide level are important to study the genetic causes in patients carrying balanced translocations or inversions. Long-read sequencing techniques, such as the Oxford Nanopore Technology (ONT), may detect these SVs in a more direct, efficient and accurate manner. In this study, we applied whole-genome long-read sequencing on the Oxford Nanopore GridION sequencer to detect the breakpoints from 6 carriers of balanced translocations and one carrier of inversion, where SVs had initially been detected by karyotyping at the chromosome level. The results showed that all the balanced translocations were detected with [~]10X coverage and were consistent with the karyotyping results. PCR and Sanger sequencing confirmed 8 of the 14 breakpoints to single base resolution, yet other breakpoints cannot be refined to single-base due to their localization at highly repetitive regions or pericentromeric regions, or due to the possible presence of local deletions/duplications. Our results indicate that low-coverage whole-genome sequencing is an ideal tool for the precise localization of most translocation breakpoints and may provide haplotype information on the breakpoint-linked SNPs, which may be widely applied in SV detection, therapeutic monitoring, assisted reproduction technology (ART) and preimplantation genetic diagnosis (PGD).

genetics↗

bioRxiv2018

HSP-4/BiP expression in secretory cells is regulated by a lineage-dependent differentiation program and not by the unfolded protein response

Differentiation of secretory cells leads to sharp increases in protein synthesis, challenging ER proteostasis. Anticipatory activation of the unfolded protein response (UPR) prepares cells for the onset of secretory function by expanding the ER size and folding capacity. How cells ensure that the repertoire of induced chaperones matches their post-differentiation folding needs is not well understood. We find that during differentiation of stem-like seam cells, a typical UPR target, the C. elegans BiP homologue HSP-4, is selectively induced in alae-secreting daughter cells, but is repressed in hypodermal daughter cells. Surprisingly, this lineage-dependent induction bypasses the requirement for UPR signaling, and instead is controlled by a specific developmental program. The repression of HSP-4 in hypodermal-fated cells requires a transcriptional regulator BLMP-1/BLIMP1, involved in differentiation of mammalian secretory cells. The HSP-4 induction is anticipatory, and is required for the integrity of secreted alae. Thus, differentiation programs can directly control a broad-specificity chaperone that is normally stress-dependent, to ensure the integrity of secreted proteins.

cell biology↗