Journal: iScience

Article Title: Virus-host interactome reveals host cellular pathways perturbed by tick-borne encephalitis virus infection

doi: 10.1016/j.isci.2026.115821

Figure Lengend Snippet: TBEV NS5 interacts with P300 to modulate G0/G1 cell cycle progression (A) Cells were transfected with the plasmids of Flag-tagged EV and ten TBEV viral proteins, the cell distribution was analyzed by flow cytometry. (B) The expression plasmids of Flag-EV, 0.5 and 1.0 μg Flag-NS5 were transfected into A549 cells, the cell distribution was analyzed by flow cytometry. The experiment was repeated for three times, and the percentages of cells were shown in column graph. (C) Cells were transfected with Flag-EV or Flag NS5 together with HA-P300, the interaction between NS5 and P300 was analyzed by co-immunoprecipitation analysis. (D) The colocalization of P300 (green) and NS5 (red) were examined by immunofluorescence analysis. Scale bars, 10 μm. (E–G) Cells transfected with NS5 were collected after 48 h, the expression of CDK4, CDK6, and P16 was analyzed by immunoblot (E). (F) Quantification of protein levels from (E). Data are normalized to actin and presented as fold change relative to control (mean ± SD, n = 3). (G) qPCR analysis of mRNA expression of CDK4, CDK6, and P16 upon NS5 overexpression. Data are normalized to GAPDH using the 2ˆ(-ΔΔCt) method and shown as fold change relative to control (mean ± SD, n = 3). (H) A549 cells transfected with HA-EV, HA P300 and P300 Hm were further transfected with NS5, the distribution of cells was analyzed by flow cytometry. The experiments were repeated for three times, and the proportions of cells were shown in column graph, the expression of indicated proteins was assessed by immunoblot assay. (I) Cells transfected with P300 siRNA and NC siRNA (siNC) were further transfected with NS5, the distribution of cells was analyzed by flow cytometry, and the proportions of cells and the relative expression of P300 mRNA were shown in column graph. (J) Cells transfected with HA-EV, HA P300, and P300 Hm were mock-infected or infected TBEV, the distribution of cells was analyzed by flow cytometry. (K) Cells transfected with P300 siRNA and NC siRNA were mock-infected or infected TBEV, the distribution of cells was analyzed by flow cytometry. (L) Outline of G0/G1 cell-cycle arrest regulated by TBEV NS5. Data in column graphs are represented as mean ± SEM of three independent experiments. The p values are calculated and reported using one-way ANOVA.

Article Snippet: For small interfering RNA (siRNA) targeting P300, 5′-GGACUACCCUAUCAAGUAATT-3′, was synthesized at Sangon Biotech (Shanghai, China).

Techniques: Transfection, Flow Cytometry, Expressing, Immunoprecipitation, Immunofluorescence, Western Blot, Control, Over Expression, Infection

Journal: iScience

Article Title: Virus-host interactome reveals host cellular pathways perturbed by tick-borne encephalitis virus infection

doi: 10.1016/j.isci.2026.115821

Figure Lengend Snippet: P300 inhibitors and CDK4 agonist restrict viral gene expression by interfering with TBEV-induced cell-cycle arrest (A and B) A549 cells were either mock-infected or infected with TBEV, the cells were then treated with indicated concentration of C646 (A) and CPI-637 (B), the supernatants were collected at 48 hpi, and the mRNA level of TBEV E gene was analyzed by probe qPCR. (C–F) Cells mock-infected or infected with TBEV at the MOI of ten were treated with 10 μM C646 and CPI-637, the expression of TBEV NS1 protein was detected by immunoblot (C and D) and immunofluorescence analysis (E), and the cell cycle distribution was analyzed by flow cytometry (F). Scale bars, 50 μm. (G) Cells transfected with HA-EV, HA P300, and P300Hm were infected TBEV, the mRNA level of TBEV E gene in the supernatants was analyzed by probe qPCR. (H) Cells transfected with P300 siRNA and NC siRNA were infected TBEV, the mRNA level of TBEV E gene in the supernatants was analyzed by probe qPCR. (I) A549 cells were treated with the indicated concentrations of chrysin for 2 h, the cells were then infected with TBEV, the supernatants were collected at 48 hpi, and the mRNA level of TBEV E gene was analyzed by probe qPCR. (J–L) Cells were treated with 10 μM chrysin for 2 h, the cells were then mock-infected or infected with TBEV at the MOI of ten, the expression of TBEV NS1 protein was detected by immunoblot (J), and the cell distribution was analyzed by flow cytometry (K). The percentage of cells (L) upon chrysin treatment was shown in column graphs. Scale bars, 50 μm. Data in column graphs are represented as mean ± SEM of three independent experiments. The p values are calculated and reported using one-way ANOVA.

Article Snippet: For small interfering RNA (siRNA) targeting P300, 5′-GGACUACCCUAUCAAGUAATT-3′, was synthesized at Sangon Biotech (Shanghai, China).

Techniques: Gene Expression, Infection, Concentration Assay, Expressing, Western Blot, Immunofluorescence, Flow Cytometry, Transfection

Journal: bioRxiv

Article Title: CpG island density predicts CBP/p300 dependency across 3D chromatin clusters

doi: 10.64898/2026.05.04.722036

Figure Lengend Snippet: a. Overview of Pol2 HiChIP derived clusters. b. Clusters ranked by the percentage of their loop anchors overlapping CpG islands, broken into high, medium and low CpG content. c. Overlap of cluster features, including promoter-promoter loops, p300 and PAX3-FOXO1 ChIP-seq peak overlap, and target gene categories (Core Regulatory Transcription Factors and Housekeeping gene), at clusters ranked by percent CpG islands at anchors. d. Percentage of CpG islands at loop anchors within clusters, separated by gene category. e. Total Pol2 contacts per million (CPM) signal among clusters grouped by CpG content. f. Gene expression from RNA-seq (log2 transcripts per million, TPM) among clusters grouped by CpG content. g. Percentage of promoter-promoter loops among clusters grouped by CpG content. h. Frequency of PAX3-FOXO1 binding at loop anchors in clusters grouped by CpG content. i. Frequency of p300 binding at loop anchors in clusters grouped by CpG content. j. Gene expression changes in RMS cells after dual CRISPR mediated knockout of CBP and EP300, for genes in clusters grouped by CpG content. k. GAPDH and MYOD1 gene regulatory clusters, shown with Pol2 HiChIP clustering, CpG island abundance, P3F and p300 binding, H3K27ac and Pol2 ChIP-seq levels, and RNA-seq, revealing distinct cluster features. l. Model of CpG rich Housekeeping clusters vs. p300 rich Core Regulatory clusters.

Article Snippet: In 2022, a team at GlaxoSmithKline identified proline-based p300 inhibitors from a DNA-encoded library.

Techniques: HiChIP, Derivative Assay, ChIP-sequencing, Gene Expression, RNA Sequencing, Binding Assay, CRISPR, Knock-Out

Journal: bioRxiv

Article Title: CpG island density predicts CBP/p300 dependency across 3D chromatin clusters

doi: 10.64898/2026.05.04.722036

Figure Lengend Snippet: a. Molecular structure of IHK-44. b. IHK-44 docked to the HAT domain of p300. c-d. Dose-response ( c ) and time-course ( d ) Western blot of RH4 cells after IHK-44 treatment. Dose-response samples were treated for 6 h each. Time-course samples were treated at 100 nM each. H2B and H3 are shown as loading controls. e. Heatmaps of HBK16ac and H2BK20ac ChIP-seq shows that p300-bound enhancers are downregulated after 100 nM IHK-44 treatment over a 6 h time-course treatment period.

Article Snippet: In 2022, a team at GlaxoSmithKline identified proline-based p300 inhibitors from a DNA-encoded library.

Techniques: Western Blot, ChIP-sequencing

Journal: bioRxiv

Article Title: CpG island density predicts CBP/p300 dependency across 3D chromatin clusters

doi: 10.64898/2026.05.04.722036

Figure Lengend Snippet: a. Schematic of CHESS-DIA methodology. b. Violin plots of normalized protein abundance levels of CBP (left) and p300 (right) across nuclear compartments. c. Box plots of protein abundance levels between CBP (top) and p300 (bottom) in euchromatin fractions from RH4 cells treated with DMSO or increasing concentrations of IHK-44 (100 nM, 125 nM, 150 nM). Box plots represent median and quartiles, whiskers representing 1.5 x IQR. Statistical significance determined using a two-tailed Welch’s T-test. d. Box plots of protein abundance levels between PAX3-FOXO1, MYOD1, AND MYOG in euchromatin fractions from RH4 cells treated with DMSO or increasing concentrations of IHK-44 (100 nM, 125 nM, 150 nM). Box plots represent median and quartiles, whiskers representing 1.5 x IQR. Statistical significance determined using a two-tailed Welch’s T-test. e. Scatter plot comparing changes between RNA and protein abundance in RH4 cells treated with DMSO or 100 nM IHK-44 for 6 h. Lineage-specific TFs are highlighted and labeled in red, housekeeping genes in blue, other genes in gray.

Article Snippet: In 2022, a team at GlaxoSmithKline identified proline-based p300 inhibitors from a DNA-encoded library.

Techniques: Quantitative Proteomics, Two Tailed Test, Labeling

Journal: bioRxiv

Article Title: CpG island density predicts CBP/p300 dependency across 3D chromatin clusters

doi: 10.64898/2026.05.04.722036

Figure Lengend Snippet: a. Dose-response curves showing relative cell viability of FP-RMS (RH4), FN-RMS (RD), and normal myoblast (KM155C25DIST) cells after 72 h treatment with IHK-44. Values represent mean ± SEM of n = 4 technical replicates. b. Growth curves of % confluence over time (h) in FP-RMS (RH4, RH5), FN-RMS (CTR), and normal myoblast (HSMM) cell lines treated with DMSO or 185 nM IHK-44. Values represent mean ± SEM of n = 3 technical replicates. c. Heatmap summarizing IC 50 values (nM) for CBP/p300 bromodomain inhibitors (CCS1477, GNE-049), CBP/p300 HAT domain inhibitors (A-485, IHK-44), p300 degrader (JQAD1), and CBP/p300 degraders (dCBP-1, CBPD-409) across sensitive and resistant RMS cell lines. d. Bar plots summarizing cell-cycle arrest of RH4 cells treated with increasing doses (10, 100, 1000 nM) of IHK-44 for 72 h. e. Bar plots summarizing apoptosis Annexin V/PI staining of RH4 cells treated with increasing doses (10, 100, 1000 nM) of IHK-44 for 72 h. f. IC 50 values across 958 cell lines treated with IHK-44 from the PRISM screen grouped by primary disease. Box plot represents median and quartiles, whiskers showing 1.5 × IQR. Fusion-positive RMS is highlighted and labeled in red. Fusion-negative RMS in highlighted and labeled in red. g. Correlation between IHK-44 efficacy (log2.AUC) and other compounds in the DepMap Repurposing dataset. A-485 is highlighted and labeled in red. h. Correlation between IHK-44 efficacy (log2.AUC) and gene dependency scores in the DepMap CHRONOS dataset. p300 is highlighted and labeled in red. i. Western blots of non-treated histone acetylation levels in a panel of sensitive and resistant RMS cell lines. H2B and H3 are shown as loading controls

Article Snippet: In 2022, a team at GlaxoSmithKline identified proline-based p300 inhibitors from a DNA-encoded library.

Techniques: Staining, Labeling, Western Blot

Journal: bioRxiv

Article Title: CpG island density predicts CBP/p300 dependency across 3D chromatin clusters

doi: 10.64898/2026.05.04.722036

Figure Lengend Snippet: a. Design of a Random Forest machine learning model for predicting response to CBP/p300 inhibition at 6 hours, considering a mix of gene features, followed by SHAP permutation to learn the relative importance of each feature to predict responsiveness. b. The ROC (true positive versus false positive) curves for classification models from each gene feature group, and the combination of all features. Each line is colored according to the feature colors in ( a. ). AUC, area under the curve. c. The precision-recall curves for classification models from each gene feature group, and the combined all feature performance. Each line is colored according to the feature colors in ( a. ). AP, Average Precision. d. SHAP feature importance analysis colored by feature group across 100 regression runs. Each boxplot is colored according to the feature group colors in ( a. ).

Article Snippet: In 2022, a team at GlaxoSmithKline identified proline-based p300 inhibitors from a DNA-encoded library.

Techniques: Inhibition