Control of p53 turnover is critical to p53 function. E1A binding to p300/CBP translates into enhanced p53 stability, implying that these coactivator proteins normally operate in p53 turnover control. In this regard, the p300 C/H1 region serves as a specific in vivo binding site for both p53 and MDM2, a naturally occurring p53 destabilizer. Moreover, most of the endogenous MDM2 is bound to p300, and genetic analysis implies that specific interactions of p53 and MDM2 with p300 C/H1 are important steps in the MDM2-directed turnover of p53. A specific role for p300 in endogenous p53 degradation is underscored by the p53-stabilizing effect of overproducing the p300 C/H1 domain. Taken together, the data indicate that specific interactions between p300/CBP C/H1, p53, and MDM2 are intimately involved in the MDM2-mediated control of p53 abundance.

As the number of elucidated protein structures is rapidly increasing, the growing data call for methods to efficiently exploit the structural information for biological and pharmaceutical purposes. Given the three-dimensional (3D) structure of a protein and a ligand, predicting their binding sites and affinity are a key task for computer-aided drug discovery. To address this task, a variety of docking tools have been developed. Most of them focus on docking in the preset binding sites given by users. To automatically predict binding modes without information about binding sites, we developed a user-friendly blind docking web server, named CB-Dock, which predicts binding sites of a given protein and calculates the centers and sizes with a novel curvature-based cavity detection approach, and performs docking with a popular docking program, Autodock Vina. This method was carefully optimized and achieved ~70% success rate for the top-ranking poses whose root mean square deviation (RMSD) were within 2 Å from the X-ray pose, which outperformed the state-of-the-art blind docking tools in our benchmark tests. CB-Dock offers an interactive 3D visualization of results, and is freely available at http://cao.labshare.cn/cb-dock/ .

Protein-ligand blind docking is a powerful method for exploring the binding sites of receptors and the corresponding binding poses of ligands. It has seen wide applications in pharmaceutical and biological researches. Previously, we proposed a blind docking server, CB-Dock, which has been under heavy use (over 200 submissions per day) by researchers worldwide since 2019. Here, we substantially improved the docking method by combining CB-Dock with our template-based docking engine to enhance the accuracy in binding site identification and binding pose prediction. In the benchmark tests, it yielded the success rate of ∼85% for binding pose prediction (RMSD < 2.0 Å), which outperformed original CB-Dock and most popular blind docking tools. This updated docking server, named CB-Dock2, reconfigured the input and output web interfaces, together with a highly automatic docking pipeline, making it a particularly efficient and easy-to-use tool for the bioinformatics and cheminformatics communities. The web server is freely available at https://cadd.labshare.cn/cb-dock2/.

Cdc48/p97, a ubiquitin-selective chaperone, orchestrates the function of E3 ligases and deubiquitylases (DUBs). Here, we identify a new function of Cdc48 in ubiquitin-dependent regulation of mitochondrial dynamics. The DUBs Ubp12 and Ubp2 exert opposing effects on mitochondrial fusion and cleave different ubiquitin chains on the mitofusin Fzo1. We demonstrate that Cdc48 integrates the activities of these two DUBs, which are themselves ubiquitylated. First, Cdc48 promotes proteolysis of Ubp12, stabilizing profusion ubiquitylation on Fzo1. Second, loss of Ubp12 stabilizes Ubp2 and thereby facilitates removal of ubiquitin chains on Fzo1 inhibiting fusion. Thus, Cdc48 synergistically regulates the ubiquitylation status of Fzo1, allowing to control the balance between activation or repression of mitochondrial fusion. In conclusion, we unravel a new cascade of ubiquitylation events, comprising Cdc48 and two DUBs, fine-tuning the fusogenic activity of Fzo1.

Metabolic syndrome (MetS), characterized as obesity, insulin resistance, and non-alcoholic fatty liver diseases (NAFLD), is associated with vitamin D insufficiency/deficiency in epidemiological studies, while the underlying mechanism is poorly addressed. On the other hand, disorder of gut microbiota, namely dysbiosis, is known to cause MetS and NAFLD. It is also known that systemic inflammation blocks insulin signaling pathways, leading to insulin resistance and glucose intolerance, which are the driving force for hepatic steatosis. Vitamin D receptor (VDR) is highly expressed in the ileum of the small intestine, which prompted us to test a hypothesis that vitamin D signaling may determine the enterotype of gut microbiota through regulating the intestinal interface. Here, we demonstrate that high-fat-diet feeding (HFD) is necessary but not sufficient, while additional vitamin D deficiency (VDD) as a second hit is needed, to induce robust insulin resistance and fatty liver. Under the two hits (HFD+VDD), the Paneth cell-specific alpha-defensins including α-defensin 5 (DEFA5), MMP7 which activates the pro-defensins, as well as tight junction genes, and MUC2 are all suppressed in the ileum, resulting in mucosal collapse, increased gut permeability, dysbiosis, endotoxemia, systemic inflammation which underlie insulin resistance and hepatic steatosis. Moreover, under the vitamin D deficient high fat feeding (HFD+VDD), Helicobacter hepaticus, a known murine hepatic-pathogen, is substantially amplified in the ileum, while Akkermansia muciniphila, a beneficial symbiotic, is diminished. Likewise, the VD receptor (VDR) knockout mice exhibit similar phenotypes, showing down regulation of alpha-defensins and MMP7 in the ileum, increased Helicobacter hepaticus and suppressed Akkermansia muciniphila. Remarkably, oral administration of DEFA5 restored eubiosys, showing suppression of Helicobacter hepaticus and increase of Akkermansia muciniphila in association with resolving metabolic disorders and fatty liver in the HFD+VDD mice. An in vitro analysis showed that DEFA5 peptide could directly suppress Helicobacter hepaticus. Thus, the results of this study reveal critical roles of a vitamin D/VDR axis in optimal expression of defensins and tight junction genes in support of intestinal integrity and eubiosis to suppress NAFLD and metabolic disorders.

SETDB1 is a histone H3K9 methyltransferase that has a critical role in early development. It is located within a melanoma susceptibility locus and facilitates melanoma formation. However, the mechanism by which SETDB1 regulates tumorigenesis remains unknown. Here we report the molecular interplay between SETDB1 and the well-known hotspot gain-of-function (GOF) TP53 R249S mutation. We show that in hepatocellular carcinoma (HCC) SETDB1 is overexpressed with moderate copy number gain, and GOF TP53 mutations including R249S associate with this overexpression. Inactivation of SETDB1 in HCC cell lines bearing the R249S mutation suppresses cell growth. The TP53 mutation status renders cancer cells dependent on SETDB1. Moreover, SETDB1 forms a complex with p53 and catalyses p53K370 di-methylation. SETDB1 attenuation reduces the p53K370me2 level, which subsequently leads to increased recognition and degradation of p53 by MDM2. Together, we provide both genetic and biochemical evidence for a mechanism by which SETDB1 regulates cancer cell growth via methylation of p53.

(14,18,19,39), CDEIII is essential for function (15,34,40).A protein (CP1, CPF1, or CBF1) that binds to CDEI has been identified (1,7,31). Disruption of the gene encoding this protein causes pleiotropic effects, including a 10-fold increase in mitotic chromosome missegregation (2,8,36

Background: The molecular mechanism of coronavirus PLPs suppressing the innate immune response remains unclear. Results: PLP2 induces the degradation of p53 through stabilizing MDM2, and IRF7 is a novel target gene of p53. Conclusion: PLP2 inhibits the p53-mediated production of type I IFN and apoptosis to ensure viral growth. Significance: We identify the mechanism with which coronavirus induces the low dosage IFN production.