Biology subjects

Fan, H.

Publications and source records attributed to Fan, H..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

Atomic Structure and Phospholipid Binding Properties of the Francisella Type VI Secretion System Effector Protein PdpC

Francisella tularensis, a gram-negative facultative intracellular pathogen, causes tularemia, a potentially fatal infection. The Francisella pathogenicity island (FPI) encodes a type VI secretion system (T6SS), critical for the bacteriums ability to replicate within host cells and cause disease. PdpC, an FPI-encoded T6SS effector protein, is essential for phagosomal escape, intracellular replication, and virulence in animals, yet its structure and function remain poorly understood. Here, we expressed PdpC recombinantly and determined the cryoEM structure of PdpC at 3.4 [A] resolution, revealing a monomeric 156 kDa protein with a seahorse-shaped architecture (80 [A] x 75 [A] x 120 [A]). PdpC comprises five domains: an N-terminal domain (NTD) forming a prominent lateral head lobe, a central body domain, a C-terminal tail domain, a small wedge domain at the groove between the body and tail, and an unmodeled "mouth" domain that completes the seahorse-like shape. Functional studies demonstrate that PdpC binds specific host cell phospholipids, including phosphatidylinositol-3-phosphate. These findings provide a foundation for elucidating PdpCs mechanism of action and developing strategies to prevent or treat tularemia.

microbiology↗

bioRxiv2025

Comparative study of protein X-ray and NMR structures: molecular docking-based virtual screening

Molecular docking-based virtual ligand screening is a powerful computational approach for identifying potential binders from large chemical libraries. Protein structures used in docking screens are commonly derived from X-ray crystallography or NMR spectroscopy, yet their impact on screening performance remains unclear. To address this, we conducted virtual screening using Glide against both apo and holo X-ray and NMR structures of 18 proteins. While no statistically significant difference in screening performance was observed for apo structures overall, X-ray apo structures tended to perform better in cases where better ligand enrichment than random selection was achieved. Similarly, single holo X-ray and NMR structures did not exhibited statistically significant difference in screening performance either. However, when multiple holo X-ray structures and NMR conformers (from one PDB ensemble) per protein were used, X-ray structures outperformed NMR conformers in most cases. In addition, for consensus enrichment which leverages multiple structures/conformers per protein to optimise ligand ranking, X-ray holo structures exhibited better performance than NMR holo conformers, suggesting that X-ray structures with chemically diverse co-crystalized ligands may introduce more relevant binding-site configurations than the NMR conformers with higher structural diversity but the same bound ligand. Overall, the better performance by X-ray holo structures could be partially attributed to the higher numbers of hydrogen bonds and hydrophobic contacts, formed between proteins and docked ligands.

bioinformatics↗

bioRxiv2025

Deep contrastive feature compression with classical machine learning enables ligand discovery through efficient triage of large chemical libraries

Improving in silico compound-protein interaction (CPI) predictability is critical for productive drug discovery. Current deep learning approaches largely rely on end-to-end models trained on limited labeled CPI datasets, overlooking the representational power of large-scale biochemical foundation models. We present COMRADE (Contrastive Multirepresentation Accelerated Docking Engine), a hybrid virtual screening framework that accelerates docking by triaging compounds using CE-Screen (Contrastive Embedding-Screen). CE-Screen leverages seven high-dimensional pretrained representations - including those from protein language models and molecular transformers, along with an original physics-based interaction potential encoding - for rapid first-pass screening [~]100x faster than docking. Its contrastive compression neural network maps these inputs onto a single compact, discriminative representation optimized for CPI prediction via a lightweight ensemble classifier. CE-Screen outperforms state-of-the-art end-to-end models by up to 111.11% on retrospective benchmarks and is successfully used to triage [~]10.8 million compounds against five targets, yielding novel hits for each one - including a new scaffold for the branched-chain ketoacid dehydrogenase kinase (BCKDK), an understudied yet high-value target in metabolic disease and oncology.

bioinformatics↗

bioRxiv2025

Chromatin remodeling integrates vertebrate body axis elongation and cell fate determination

The effective elongation of the vertebrate body axis depends on the precise coordination of cell movements and cell fate determination within the posterior tailbud region. However, the specific biological determinant that integrates these cellular processes during vertebrate tail bud elongation has remained unclear. Here, we demonstrate that the spatiotemporal heterogeneity of chromatin condensation states governs both cell fate and cell motility within the mesodermal progenitor zone (MPZ) and the presomitic mesoderm (PSM) during zebrafish tail bud elongation. By integrating biological experiments with computational modeling, we reveal that nuclear volume heterogeneity, mediated by chromatin remodeling, acts as an active driver of collective cell migration. Reducing chromatin condensation heterogeneity in the MPZ through modulation of chromatin modifications impairs collective cell movements and delays tailbud elongation. Single cell ATAC-seq and RNA-seq analyses reveal that global chromatin accessibility heterogeneity and region-specific chromatin remodeling differences in the PSM and MPZ are functionally associated with gene expression pathways involving in cell lineage specification. These findings establish a molecular connection between cell fate determination and tissue-scale cellular dynamics. Collectively, our findings unveil a unifying framework for understanding the coordination of cell fate determination and large-scale cellular movements during tissue morphogenesis.

developmental biology↗

bioRxiv2025

A Molecular Dynamics Protocol for Predicting EGFR Overactivation and Its Application to the Allosteric Mutations S768I, S768N, and D761N

Hyperactivation caused by mutations in the Epidermal Growth Factor Receptor (EGFR) kinase domain is implicated in various diseases, including cancer. However, the structural mechanisms underlying overactivation in many EGFR mutations remain poorly understood, and exploring these mechanisms through conventional experiments or in silico simulations is often labor- and cost-intensive. Here, we establish a Molecular Dynamics (MD) protocol capable of rapidly revealing EGFR mutant modes of action using multiple short simulations. We first simulated wild-type EGFR and the well-studied oncogenic mutations L858R and T790M/L858R under different simulation conditions, to derive a protocol which could recapitulate their experimentally established behavior. We then applied this protocol to three rare EGFR mutations: S768I, S768N, and D761N. Experimental studies have suggested that S768I and D761N are oncogenic, whereas S768N is likely a neutral mutation that does not significantly alter EGFR activity. Our simulation results were consistent with these functional indications and provided the corresponding molecular bases - S768I and S768N affect the orientation and stability of the catalytically important C-helix, while D761N introduces a new hydrogen bonding network between the C-helix and activation loop. Collectively, the protocol presented here provides a robust and rapid framework for characterizing EGFR mutation mechanisms and is readily adaptable to novel or uncharacterized variants.

bioinformatics↗

bioRxiv2025

Curvature generation and engineering principles from Shewanella oneidensis multi-flagellin flagellum

Motility driven by nanoscale flagella is vital to microbial survival and spread in fluid and structured environments. Absence of native flagellum structures, however, has limited our understanding of the mechanisms of microbial motility, hindering efforts to engineer microbe-based microbots for applications. Here, by cryogenic electron tomography (cryoET) and microscopy (cryoEM), we determined the structural basis of motility driven by the single flagellum anchored to one pole of Shewanella oneidensis MR-1 (S. oneidensis), an electrogenic bacterium commonly used in biotechnology. The structures of the curved flagellum, representing the conformation during motion, are captured, allowing delineation of molecular interactions among the subunits of its three components--filament, hook, and hook-filament junction. The structures of the filament, i.e., the propeller, reveal a varying composition of the flagellin isoforms FlaA and FlaB throughout the filament. Distinct inter-subunit interactions are identified at residues 129 and 134, which are the major determinants of functional differences in motility for the two isoforms. The hook--the universal joint--has a significantly larger curvature than that of the filament, despite both containing 11 curvature-defining conformers of their subunits. Transition between the propeller and universal joint is mediated by hook-filament junction, composed of 11 subunits of FlgK and FlgL, reconciling incompatibility between the filament and hook. Correlating these compositional and structural transitions with varying levels of curvature in flagellar segments reveals molecular mechanism enabling propulsive motility. Mechanistic understandings from S. oneidensis suggest engineering principles for nanoscale biomimetic systems. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/637127v1_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@17933forg.highwire.dtl.DTLVardef@1c44ab1org.highwire.dtl.DTLVardef@3d56dorg.highwire.dtl.DTLVardef@1b126b6_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

Lethal streptococcal infection is associated with widened lymph node bottlenecks

Streptococcus suis serotype 2 (SS2) infection causes streptococcal toxic shock-like syndrome (STSLS), which can be lethal in both pigs and humans. In mouse models, relatively subtle differences in the inoculum size result in drastically different infection outcomes, from clearance to acute death. Here, we leveraged barcoded SS2 in a murine model to define the bacterial population dynamics associated with death. Barcode sequencing analysis demonstrated that a 10-fold increase in inoculum size led to a 100-1,000-fold increase in the number of bacteria that initiated infection in certain lymph nodes, ultimately driving lethality. This lethal dose threshold was in part driven by suilysin (SLY), the major SS2 virulence factor. At higher doses, the clearance and replication kinetics of bacteria lacking SLY mimicked WT SS2 at sub-lethal doses. Our findings suggest that acute death in SS2 infection is caused by a wholesale failure of the immune system, enabling a large number of bacteria to initiate infection. These results demonstrate how subtle changes in inoculum size can have dramatic consequences for infection outcome and how lethal infection is driven by widened infection bottlenecks. Author SummaryLethal infections are often associated with a specific dose threshold, where increasing inoculum size is associated with an increased likelihood of death. However, a quantitative explanation how this numeric threshold is established is lacking. For example, lethal dose thresholds may reflect a dose where at least one microbe can pass through host-imposed barriers to infection. Alternatively, lethal dose thresholds may reflect a failure of the host immune system, leading to numerous microbes initiating infection. Here, using barcoded Streptococcus suis serotype 2 (SS2), we compare the within-host population dynamics associated between lethal and non-lethal infections. We find that lethal doses are associated with dramatic widening of infection bottlenecks, leading to a large number of bacteria that initiate infection. Lethal infection is also driven by suilysin, the major SS2 virulence factor. These observations demonstrate how lethal doses are quantitatively established by the relationship between host bottlenecks and bacterial virulence factors.

microbiology↗

bioRxiv2024

Chlamydia plasmid-encoded protein Pgp2 is a replication initiator with a unique beta-hairpin necessary for iteron-binding and plasmid replication

The virulence plasmid of the obligate intracellular bacterium Chlamydia encodes eight proteins. Among these, Pgp3 is crucial for pathogenicity, and Pgp4 functions as a transcriptional regulator of both plasmid and chromosomal genes. The remaining proteins, Pgp1, Pgp5, Pgp6, Pgp7, and Pgp8, are predicted to play various roles in plasmid replication or maintenance based on their amino acid sequences. However, the function of Pgp2 remains unknown, even though it is required for transformation. In this study, we utilized AlphaFold to predict the 3-dimensional (3-D) structure of C. trachomatis Pgp2. Despite a lack of apparent sequence homology, the AlphaFold structure exhibited high similarity to experimentally determined structures of several plasmid replication initiators. Notably, Pgp2 features a unique {beta}-hairpin motif near the DNA-binding domain, absent in other plasmid replication initiators with overall 3-D structures similar to Pgp2. This {beta}-hairpin motif was also present in AlphaFold models of Pgp2s across all 13 Chlamydia species. To assess its significance, we engineered a plasmid lacking the 11 amino acids constituting the {beta}-hairpin motif in C. trachomatis Pgp2. Although this deletion did not alter the overall structure of Pgp2, the mutated plasmid failed to transform plasmid-free C. trachomatis. These findings reveal that Pgp2 is a plasmid replication initiator, with the {beta}-hairpin motif playing a critical role in binding to its cognate iteron sequences in the replication origin of the chlamydial plasmid.

microbiology↗

bioRxiv2024

Serum metabolome profiling in patients with mild cognitive impairment reveals sex differences in lipid metabolism

Alzheimers disease (AD) affects more women than men. Although women live longer than men, it is not longevity alone, but other factors, including metabolic changes, that contribute to the higher risk of AD in women. Metabolic pathways have been implicated in AD progression, but studies to date examined targeted pathways, leaving many metabolites unmeasured. Sex is often a neglected biological variable, and most metabolomic studies were not designed to investigate sex differences in metabolomic profiles. Here, we performed untargeted metabolomic profiling of sera from male and female patients with mild cognitive impairment (MCI), a common precursor to AD, and matched controls. We discovered significant metabolic changes in individuals with MCI, and found several pathways that were strongly associated with sex. Peptide energy metabolism demonstrated sexual dimorphism. Lipid pathways exhibited the strongest differences between female and male MCI patients, including specific phosphatidylcholine lipids, lysophospholipids, long-chain fatty acids, and monoacylglycerols. 1-palmitoleoyl glycerol and 1-arachidonoyl glycerol were higher in female MCI subjects than in male MCI subjects with no differences between control males and females. Conversely, specific dicarboxylic fatty acids were lower in female MCI subjects than male MCI subjects. In cultured astrocytes, 1-arachidonoyl glycerol promoted phosphorylation of the transcriptional regulator sphingosine kinase 2, which was inhibited by the transient receptor potential vanilloid 1 receptor antagonists, as well as chromatin remodelling. Overall, we identified novel sex-specific metabolites in MCI patients that could serve as biomarkers of MCI in both sexes, help further define AD etiology, and reveal new potential prevention strategies for AD. Highlights{blacksquare} Individuals with MCI experience significant metabolic changes. {blacksquare}Lipid pathways demonstrated the strongest sexual dimorphism in MCI. {blacksquare}1-monoacylglycerols showed a robust sex association, being higher in MCI females. {blacksquare}Sex-specific metabolites may be MCI biomarkers in each sex.

neuroscience↗

bioRxiv2024

Unraveling transposable element-mediated regulatory landscape in diverse human immune cells

Transposable elements (TEs) are key contributors to genetic novelty. Despite increasing evidence of their importance, their roles in shaping the regulatory landscape of diverse immune cell populations remain largely unclear. Using single-cell multiome data from human peripheral blood mononuclear cells, we annotated the cell-specific cis-regulatory elements for major immune cell populations and identified a highly cell-specific signature of the overrepresented TE families. Focusing on monocytes that bear fast-evolving transcriptomes, we found that high proportions of their enhancers are TE-derived and bound by multiple pioneer transcription factors. Among them, we confirmed that the core myeloid regulator SPI1 can bind and regulate hundreds of TE-derived enhancers, which further affect the expression of adjacent immune genes. Additionally, interspecies comparison reveals that non-conserved monocyte enhancers are frequently generated by lineage-specific TE insertions, and correlate with the evolved gene expression between human and mouse. Overall, our study supports the importance of TEs in shaping the regulatory landscape of diverse immune cell populations.

genomics↗

bioRxiv2024

Mechanistic insights into the activity of SARS-CoV-2 RNA polymerase inhibitors using single-molecule FRET

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has resulted in significant global mortality and disruption. Despite extensive research, the precise molecular mechanisms underlying SARS-CoV-2 replication remain unclear. To address this, we developed a single-molecule Forster resonance energy transfer (smFRET) assay to directly visualize and analyse in vitro RNA synthesis by the SARS-CoV-2 RNA-dependent RNA polymerase (RdRp). We purified the minimal replication complex, comprising nsp12, nsp7, and nsp8, and combined it with fluorescently labelled RNA substrates, enabling real-time monitoring of RNA primer elongation at the single-molecule level. This platform allowed us to investigate the mechanisms of action of key inhibitors of SARS-CoV-2 replication. In particular, our data provides evidence for remdesivirs mechanism of action, which involves polymerase stalling and subsequent chain termination dependent on the concentration of competing nucleotide triphosphates. Our study demonstrates the power of smFRET to provide dynamic insights into SARS-CoV-2 replication, offering a valuable tool for antiviral screening and mechanistic studies of viral RdRp activity.

microbiology↗

bioRxiv2024

Differential Immunoregulation by Human Surfactant Protein A Variants Determines Severity of SARS-CoV-2-induced Lung Disease

AbstractCOVID-19 remains a significant threat to public health globally. Infection in some susceptible individuals causes life-threatening acute lung injury (ALI/ARDS) and/or death. Human surfactant protein A (SP-A) is a C-type lectin expressed in the lung and other mucosal tissues, and it plays a critical role in host defense against various pathogens. The human SP-A genes (SFTPA1 and SFTPA2) are highly polymorphic and comprise several common genetic variants, i.e., SP-A1 (variants 6A2, 6A4) and SP-A2 (variants 1A0, 1A3). Here, we elucidated the differential antiviral and immunoregulatory roles of SP-A variants in response to SARS-CoV-2 infection in vivo. Six genetically-modified mouse lines, expressing both hACE2 (SARS-CoV-2 receptor) and individual SP-A variants: (hACE2/6A2 (6A2), hACE2/6A4 (6A4), hACE2/1A0 (1A0), and hACE2/1A3(1A3), one SP-A knockout (hACE2/SP-A KO (KO) and one hACE2/mouse SP-A (K18) mice, were challenged intranasally with 103 PFU SARS-CoV-2 or saline (Sham). Infected KO and 1A0 mice had more weight loss and mortality compared to other mouse lines. Relative to other infected mouse lines, a more severe ALI was observed in KO, 1A0, and 6A2 mice. Reduced viral titers were generally observed in the lungs of infected SP-A mice relative to KO mice. Transcriptomic analysis revealed an upregulation in genes that play central roles in immune responses such as MyD88, Stat3, IL-18, and Jak2 in the lungs of KO and 1A0 mice. However, Mapk1 was significantly downregulated in 6A2 versus 1A0 mice. Analysis of biological pathways identified those involved in lung host defense and innate immunity, including pathogen-induced cytokine, NOD1/2, and Trem1 signaling pathways. Consistent with the transcriptomic data, levels of cytokines and chemokines such as G-CSF, IL-6 and IL-1{beta} were comparatively higher in the lungs and sera of KO and 1A0 mice with the highest mortality rate. These findings demonstrate that human SP-A variants differentially modulate SARS-CoV-2-induced lung injury and disease severity by differentially inhibiting viral infectivity and regulating immune-related gene expressions.

immunology↗

bioRxiv2024

Analyzing RNA-Seq Data from Chlamydia with Super Broad Transcriptomic Activation: Challenges, Solutions, and Implications for Other Systems

MotivationRNA sequencing (RNA-Seq) offers profound insights into the complex transcriptomes of diverse biological systems. However, standard differential expression analysis pipelines based on DESeq2 and edgeR encounter challenges when applied to the immediate early transcriptomes of Chlamydia spp., obligate intracellular bacteria. These challenges arise from their reliance on assumptions that do not hold in scenarios characterized by extensive transcriptomic activation and limited repression. Standard analyses using unique chlamydial RNA-Seq reads alone identify nearly 300 upregulated and about 300 downregulated genes, significantly deviating from actual RNA-Seq read trends. ResultsBy incorporating both chlamydial and host reads or adjusting for total sequencing depth, the revised normalization methods each detected over 700 upregulated genes and 30 or fewer downregulated genes, closely aligned with observed RNA-Seq data. Further validation through qRT-PCR analysis confirmed the effectiveness of these adjusted approaches in capturing the true extent of transcriptomic activation during the immediate early phase of chlamydial infection. While the strategies employed are developed in the context of Chlamydia, the principles of flexible and context-aware normalization may inform adjustments in other systems with unbalanced gene expression dynamics, such as bacterial spore germination. Availability and implementationThe code for reproducing the presented bioinformatic analysis is available at https://zenodo.org/records/11201379.

bioinformatics↗

bioRxiv2024

Five-layered robot (F-robot) based on functionally graded multilayer foam antiviral low-carbon (F-MAX) system for Pathogenic Microorganism Elimination

In this study, a revolutionary air filtration technology, the F-MAX multilayer composite plate, is introduced, offering high efficiency and environmental sustainability. This innovative system is designed to capture a wide range of pollutants, including harmful viruses and bacteria, enhancing air quality significantly. The F-MAX combines multiple layers, each tailored to target specific particles, with features like an electrostatically charged melt-blown fabric and eco-friendly materials like lithium brine by-product magnesia. Its durability, antiviral, and antibacterial properties make it a sustainable choice for air purification, suitable for both commercial and residential use. This system represents healthier living environments, effectively removing airborne contaminants, and demonstrating a commitment to a sustainable future. Additionally, the study introduces the F-robot specifically designed for laboratory environments to ensure pristine air quality. One-Sentence SummaryT-robot air filter, which use F-MAX, a multilayer composite consisted of self-healing cellular coating, Desert Rose (DR) coating, melt-blown cloth, and BMSC with high-efficiency, environmentally sustainable filtration, and antiviral properties, suitable for diverse environments.

microbiology↗

bioRxiv2024

Overcoming the preferred orientation problem in cryoEM with self-supervised deep-learning

While advances in single-particle cryoEM have enabled the structural determination of macromolecular complexes at atomic resolution, particle orientation bias (the so-called "preferred" orientation problem) remains a complication for most specimens. Existing solutions have relied on biochemical and physical strategies applied to the specimen and are often complex and challenging. Here, we develop spIsoNet, an end-to-end self-supervised deep-learning-based software to address the preferred orientation problem. Using preferred-orientation views to recover molecular information in under-sampled views, spIsoNet improves both angular isotropy and particle alignment accuracy during 3D reconstruction. We demonstrate spIsoNets capability of generating near-isotropic reconstructions from representative biological systems with limited views, including ribosomes, {beta}-galactosidases, and a previously intractable hemagglutinin trimer dataset. spIsoNet can also be generalized to improve map isotropy and particle alignment of preferentially oriented molecules in subtomogram averaging. Therefore, without additional specimen-preparation procedures, spIsoNet provides a general computational solution to the preferred orientation problem.

biophysics↗

bioRxiv2024

CPT1A Mediates Radiation Sensitivity in Colorectal Cancer

The prevalence and mortality rates of colorectal cancer (CRC) are increasing worldwide. Radiation resistance hinders radiotherapy, a standard treatment for advanced CRC, leading to local recurrence and metastasis. Elucidating the molecular mechanisms underlying radioresistance in CRC is critical to enhance therapeutic efficacy and patient outcomes. Bioinformatic analysis and tumour tissue examination were conducted to investigate the CPT1A mRNA and protein levels in CRC and their correlation with radiotherapy efficacy. Furthermore, lentiviral overexpression and CRISPR/Cas9 lentiviral vectors, along with in vitro and in vivo radiation experiments, were used to explore the effect of CPT1A on radiosensitivity. Additionally, transcriptomic sequencing, molecular biology experiments, and bioinformatic analyses were employed to elucidate the molecular mechanisms by which CPT1A regulates radiosensitivity. CPT1A was significantly downregulated in CRC and negatively correlated with responsiveness to neoadjuvant radiotherapy. Functional studies suggested that CPT1A mediates radiosensitivity, influencing reactive oxygen species (ROS) scavenging and DNA damage response. Transcriptomic and molecular analyses highlighted the involvement of the peroxisomal pathway. Mechanistic exploration revealed that CPT1A downregulates the FOXM1-SOD1/SOD2/CAT axis, moderating cellular ROS levels after irradiation and enhancing radiosensitivity. CPT1A downregulation contributes to radioresistance in CRC by augmenting the FOXM1-mediated antioxidant response. Thus, CPT1A is a potential biomarker of radiosensitivity and a novel target for overcoming radioresistance, offering a future direction to enhance CRC radiotherapy.

cancer biology↗

bioRxiv2024

Rapid High-Throughput Isolation and purification of Chicken Myoblasts Based on Deterministic Lateral Displacement Microfluidic Chips

Myoblasts are defined as stem cells containing skeletal muscle cell precursors. However, there are some challenges associated with the purification of myoblast samples, including long culture times and ease of bacterial contamination. In this study, we propose a microfluidic myoblast cell enrichment and purification platform based on the principle of deterministic lateral displacement (DLD). To achieve this, we designed a DLD chip with three outlets and tested it on 11-day-old Wenchang chicken pectoral muscle tissue. A cell suspension was prepared using the collagenase method, pretreated, and then passed into the designed DLD chip for myoblast enrichment and purification. In this study, the number of myoblasts and the diameter of myoblasts increased slowly before E9, and the diameter of myofibers decreased and the number of myofibers increased rapidly after E9. The period when the number of muscle fibers is highest is E12, and the period when the diameter of muscle fibers increases again after the lowest point is also E12. After E12, the diameter of the muscle fibers increased and the number of muscle fibers decreased. At E12, myoblasts clustered and fused, and the proliferation of myoblasts was greatly reduced. E12 is both intact myoblasts and the most vigorous proliferation period, so the best time to determine isolation is E12. We attained a myoblast cell recovery rate of 80%, a target outlet collection purity of 99%, and a chip throughput of 50 m/min. This study provides a novel and effective method for the isolation and purification of skeletal muscle myoblasts.

cell biology↗

bioRxiv2024

Revolutionizing GPCR-Ligand Predictions: DeepGPCR with experimental Validation for High-Precision Drug Discovery

G-protein coupled receptors (GPCRs), crucial in various diseases, are targeted of over 40% of approved drugs. However, the reliable acquisition of experimental GPCRs structures is hindered by their lipid-embedded conformations. Traditional protein-ligand interaction models falter in GPCR-drug interactions, caused by limited and low-quality structures. Generalized models, trained on soluble protein-ligand pairs, are also inadequate. To address these issues, we developed two models, DeepGPCR_BC for binary classification and DeepGPCR_RG for affinity prediction. These models use non-structural GPCR-ligand interaction data, leveraging graph convolutional networks (GCN) and mol2vec techniques to represent binding pockets and ligands as graphs. This approach significantly speeds up predictions while preserving critical physical-chemical and spatial information. In independent tests, DeepGPCR_BC surpassed Autodock Vina and Schrodinger Dock with an AUC of 0.72, accuracy of 0.68, and TPR of 0.73, whereas DeepGPCR_RG demonstrated a Pearson correlation of 0.39 and RMSE of 1.34. We applied these models to screen drug candidates for GPR35 (Q9HC97), yielding promising results with 3 (F545-1970, K297-0698, S948-0241) out of 8 candidates. Furthermore, we also successfully obtained 6 active inhibitors for GLP-1R. Our GPCR-specific models pave the way for efficient and accurate large-scale virtual screening, potentially revolutionizing drug discovery in the GPCR field.

bioinformatics↗