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song, q.

Publications and source records attributed to song, q..

2 recordsLinked to original sources

TRiC-assisted folding of class I HDAC family proteins regulated by distinct co-chaperone and cofactor networks

Class I histone deacetylases (HDACs), including HDAC1, HDAC2, HDAC3, and HDAC8, are essential for diverse cellular processes. Although the chaperonin TRiC is implicated in the activation of class I HDACs, the underlying mechanisms remain elusive. Using cryo-electron microscopy (cryo-EM), cross-linking mass spectrometry (XL-MS), and biochemistry analyses, we established class I HDACs as novel TRiC substrates and elucidate TRiC-assisted folding of HDAC1 and HDAC3 during its ATPase cycle, orchestrated by distinct co-chaperone and cofactor networks. In the closed TRiC chamber, both HDAC1 and HDAC3 adopt near-native states with shared binding interfaces. However, their open-state configurations diverge: Hsp70 and PDCD5 engage atop and within TRiC, respectively, for HDAC3, whereas prefoldin (PFD) binds atop TRiC for HDAC1, suggesting roles in substrate delivery and folding modulation. Furthermore, an unexpected bent conformation of CCT4, detected in TRiC-HDAC1 complex, may facilitate co-chaperone dissociation from TRiC. In contrast, HDAC8 folds independently of TRiC. Our study reveals the mechanism governing TRiC-assisted folding of class I HDACs in orchestration of dynamic co-chaperone/cofactor network, shielding new lights on the sophisticated regulatory landscape of TRiC, and open promising avenues for designing peptides or small molecules to selectively modulate TRiC-assisted folding of class I HDACs and other substrates.

molecular biology↗

Exploring the mechanisms and potential therapeutic targets of Ferroptosis Related Genes in ankylosing spondylitis

BackgroundFerroptosis is a novel type of regulated cell death, and there is growing evidence that it is directly associated with the disease. Therefore, this study aimed to investigate the relevance of iron Ferroptosis-related genes to ankylosing spondylitis (AS) to propose a novel targeted therapy for AS patients. MethodsAS samples were downloaded from the Gene Expression Omnibus (GEO) database (GSE41038). Ferroptosis-related genes were obtained from the FerrDb database, and differential expression analysis was performed using the GEO2R tool. Additionally, we constructed a protein-protein interaction (PPI) network and identified the central genes using Cytoscape. A neural network model was developed utilizing the data mining software Clementine. cMap technology was used to screen potential pharmacological compounds that target the central gene,and a predictive model was built by machine learning methods. ResultsWe discovered 786 differentially expressed genes in AS samples compared to normal tissue, including 359 up-regulated and 427 down-regulated genes. The intersection of ferroptosis-related genes and differential genes yielded 20 overlapping genes. We constructed a hub gene co-expression network with 20 nodes and 14 edges and obtained the ten most recommended drugs for AS. ConclusionBioinformatics analysis identified 20 potential genes associated with Ferroptosis in AS. Genes such as CAV1, NOX4, and NQO1 were revealed to influence the development of AS by regulating Ferroptosis. Our study provides new insights into the function of iron Ferroptosis-related genes in AS, suggesting that targeting Ferroptosis may be a potential therapeutic option for AS.

bioinformatics↗