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Protein-protein interactions in the cell membrane are typically mediated by glycans, with terminal sialic acid often involved in these interactions. To probe the nature of the interactions, we developed quantitative cross-linking methods involving the glycans of the glycoproteins and the polypeptide moieties of proteins. We designed and synthesized biotinylated enrichable cross-linkers that were click-tagged to metabolically incorporate azido-sialic acid on cell surface glycans to allow cross-linking of the azido-glycans with lysine residues on proximal polypeptides. The glycopeptide-peptide cross-links (GPx) were enriched using biotin groups through affinity purification with streptavidin resin beads. Workflows using two linkers, one photocleavable and the other disulfide, were developed and applied to reveal the sialic acid-mediated cell-surface protein networks of PNT2 (prostate) cells. Glycopeptide-peptide pairs were identified, with 12000 GPx linked by sialylated glycoforms revealing interactions between source glycoproteins and nearly 700 target proteins. Protein-protein interactions were characterized by as many as 40 peptide pairs, and the extent of the interactions between proteins was prioritized by the number of GPx. Quantitation was performed by counting the number of GPx that identify the protein pairs. Abundant membrane proteins such as ITGB1 yielded an interactome consisting of around 400 other proteins, which were ranked from the most extensive interaction, having the largest number of GPx, to at least one. The interactome was further confirmed separately by published databases. This tool will enhance our understanding of glycosylation on protein-protein interactions and provide new potential targets for therapeutics.
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http://dx.doi.org/10.1021/acs.analchem.4c04134 | DOI Listing |
IEEE Trans Comput Biol Bioinform
September 2025
Accurately identifying associations between human genes (proteins) and clinical phenotypes is critical for advancing drug development and precision medicine. While the human phenotype ontology (HPO) standardizes clinical phenotypes, current computational approaches for predicting human protein-phenotype associations suffer from two limitations: (1) underutilization of multimodal protein-related information and (2) lack of state-of-the-art deep learning representations tailored to diverse data modalities, such as text and sequence. To overcome these limitations, we introduce MultiFusion2HPO, a novel multimodal model that integrates diverse features and advanced learning methods from multiple data sources to enhance the prediction of human protein-HPO associations.
View Article and Find Full Text PDFBiomed Environ Sci
August 2025
Gastrointestinal Disease Centre, Hebei Key Laboratory of Colorectal Cancer Precision Diagnosis and Treatment, The First Hospital of Hebei Medical University, Shijiazhuang 050031, Hebei, China.
Objective: To explore the correlation between chromosome 8 open reading frame 76 (C8orf76) and cyclin-dependent kinase 4 (CDK4) and the potential predictive effect of C8orf76 and CDK4 on the prognosis of colorectal cancer (CRC).
Methods: We constructed a protein-protein interaction network of C8orf76-related genes and analyzed the prognostic signatures of C8orf76 and CDK4. Clinicopathological features of C8orf76 and CDK4 were visualized using a nomogram.
Front Immunol
September 2025
Department of Thoracic Surgery, Shenzhen People's Hospital (The First Affiliated Hospital, Southern University of Science and Technology; The Second Clinical Medical College, Jinan University), Shenzhen, Guangdong, China.
Background: Lung cancer remains the leading cause of cancer-related mortality globally, primarily due to late-stage diagnosis, molecular heterogeneity, and therapy resistance. Key biomarkers such as EGFR, ALK, KRAS, and PD-1 have revolutionized precision oncology; however, comprehensive structural and clinical validation of these targets is crucial to enhance therapeutic efficacy.
Methods: Protein sequences for EGFR, ALK, KRAS, and PD-1 were retrieved from UniProt and modeled using SWISS-MODEL to generate high-confidence 3D structures.
Biochem Biophys Rep
December 2025
Division of Breast Surgery, Department of Surgery, Taipei Veterans General Hospital, Taipei, 112, Taiwan.
Purpose: This study aimed to conduct functional proteomics across breast cancer subtypes with bioinformatics analyses.
Methods: Candidate proteins were identified using nanoscale liquid chromatography with tandem mass spectrometry (NanoLC-MS/MS) from core needle biopsy samples of early stage (0-III) breast cancers, followed by external validation with public domain gene-expression datasets (TCGA TARGET GTEx and TCGA BRCA).
Results: Seventeen proteins demonstrated significantly differential expression and protein-protein interaction (PPI) found the strong networks including COL2A1, COL11A1, COL6A1, COL6A2, THBS1 and LUM.
Biochem Biophys Rep
June 2025
Department of Public Health, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Background: Synaptic dysfunction and synapse loss occur in Alzheimer's disease (AD). The current study aimed to identify synaptic-related genes with diagnostic potential for AD.
Methods: Differentially expressed genes (DEGs) were overlapped with phenotype-associated module selected through weighted gene co-expression network analysis (WGCNA), and synaptic-related genes.