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We developed a new class of inhibitors of protein-protein interactions of the SHP2 phosphatase, which is pivotal in cell signaling and represents a central target in the therapy of cancer and rare diseases. Currently available SHP2 inhibitors target the catalytic site or an allosteric pocket but lack specificity or are ineffective for disease-associated SHP2 mutants. Considering that pathogenic lesions cause signaling hyperactivation due to increased levels of SHP2 association with cognate proteins, we developed peptide-based molecules with nanomolar affinity for the N-terminal Src homology domain of SHP2, good selectivity, stability to degradation, and an affinity for pathogenic variants of SHP2 that is 2-20 times higher than for the wild-type protein. The best peptide reverted the effects of a pathogenic variant (D61G) in zebrafish embryos. Our results provide a novel route for SHP2-targeted therapies and a tool for investigating the role of protein-protein interactions in the function of SHP2.
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http://dx.doi.org/10.1021/acs.jmedchem.1c01371 | 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.