Grapevine leafroll disease (GLD) is a globally important disease that affects the metabolic composition and biomass of grapes, leading to a reduction in grape yield and quality of wine produced. Grapevine leafroll-associated virus 3 (GLRaV-3) is the main causal agent for GLD. This study aimed to identify protein-protein interactions between GLRaV-3 and its host. A yeast two-hybrid (Y2H) library was constructed from mRNA and screened against GLRaV-3 open reading frames encoding structural proteins and those potentially involved in systemic spread and silencing of host defense mechanisms. Five interacting protein pairs were identified, three of which were demonstrated in planta. The minor coat protein of GLRaV-3 was shown to interact with 3-deoxy-D-arabino-heptulosonate 7-phosphate synthase 02, a protein involved in primary carbohydrate metabolism and the biosynthesis of aromatic amino acids. Interactions were also identified between GLRaV-3 p20A and an 18.1-kDa class I small heat shock protein, as well as MAP3K epsilon protein kinase 1. Both proteins are involved in the response of plants to various stressors, including pathogen infections. Two additional proteins, chlorophyll a-b binding protein CP26 and a SMAX1-LIKE 6 protein, were identified as interacting with p20A in yeast but these interactions could not be demonstrated in planta. The findings of this study advance our understanding of the functions of GLRaV-3-encoded proteins and how the interaction between these proteins and those of could lead to GLD.
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http://dx.doi.org/10.1094/PHYTO-03-23-0107-R | DOI Listing |
Front Oncol
January 2025
The Translational Research Institute for Neurological Disorders of Wannan Medical College, Department of Neurosurgery, The First Affiliated Hospital of Wannan Medical College (Yijishan Hospital of Wannan Medical College), Wuhu, Anhui, China.
Introduction: Gliomas, particularly glioblastomas (GBM), are highly aggressive with a poor prognosis and low survival rate. Currently, deoxyelephantopin (DET) has shown promising anti-inflammatory and anti-tumor effects. Using clinical prognostic analysis, molecular docking, and network pharmacology, this study aims to explore the primary targets and signaling pathways to identify novel GBM treatment approaches.
View Article and Find Full Text PDFFront Mol Biosci
January 2025
Department of Obstetrics and Gynecology, Fujian Maternity and Child Health Hospital College of Clinical Medicine for Obstetrics Gynecology and Pediatrics, Fujian Medical University, Fuzhou, China.
Background: Polycystic ovary syndrome (PCOS) is a common endocrine and metabolic condition impacting millions of women worldwide. This study sought to identify granulosa cell endoplasmic reticulum stress (GCERS)-related differentially expressed genes (DEGs) between women with PCOS and those without PCOS using bioinformatics and to investigate the related molecular mechanisms.
Methods: Two datasets were downloaded from GEO and analysed using the limma package to identify DEGs in two groups-PCOS and normal granulosa cells.
Comput Struct Biotechnol J
December 2024
Department of Computer Science, Virginia Tech, Blacksburg, 24061, VA, USA.
Quality estimation of the predicted interaction interface of protein complex structural models is not only important for complex model evaluation and selection but also useful for protein-protein docking. Despite recent progress fueled by symmetry-aware deep learning architectures and pretrained protein language models (pLMs), existing methods for estimating protein complex quality have yet to fully exploit the collective potentials of these advances for accurate estimation of protein-protein interface. Here we present EquiRank, an improved protein-protein interface quality estimation method by leveraging the strength of a symmetry-aware E(3) equivariant deep graph neural network (EGNN) and integrating pLM embeddings from the pretrained ESM-2 model.
View Article and Find Full Text PDFHeliyon
January 2025
Department of Infectious Diseases, Affiliated Hospital, Southwest Medical University, Luzhou, 646000, China.
Background: Hepatocellular carcinoma (HCC) is a significant global health concern, with chronic hepatitis B virus (HBV) infection being a major contributor. Understanding the mechanisms of HBV-associated HCC is crucial to improving the prognosis and developing effective treatments.
Methods: HBV-associated HCC datasets (GSE19665, GSE121248, GSE55092, GSE94660, and TCGA-LIHC) acquired from public databases were mined to identify key driver genes by differentially expressed gene analysis, weighted gene co-expression network analysis (WGCNA), followed by protein-protein interaction network analysis, Lasso-Cox regression analysis, and randomforestSRC algorithm.
Tzu Chi Med J
July 2024
Pharmacy College, Gannan Medical University, Ganzhou, Jiangxi, China.
Objectives: This study aimed to explore the potential mechanisms of TMF (5,7,3',4'-tetramethoxyflavone) in treating osteoarthritis (OA) using network pharmacology and molecular docking.
Materials And Methods: Databases including SwissTargetPrediction, BATMAN-TCM, PharmMapper, TargetNet, SuperPred, and SEA were utilized to screen the targets of TMF. "OA" was used as the disease keyword to predict OA-related genes through GeneCards, Therapeutic Target Database, PharmGKB, Online Mendelian Inheritance in Man, and Comparative Toxicogenomics Database.
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