Journal: Advanced Science

Article Title: β‐Elemene Rescues Radiation‐Induced Enteritis by Orchestrating a Host‐Microbiome Circuit That Fuels Epigenetic DNA Repair

doi: 10.1002/advs.202521445

Figure Lengend Snippet: EP300 Functions as the Lactyl‐transferase for RBBP4 to Establish a Positive Feedback Loop (A) Molecular docking model. Left: Overall predicted structure of the interaction between a lactylated RBBP4 peptide (light blue) and the EP300 protein (cyan). Right: Magnified view showing that the K26 lactylation (Lys 26) on RBBP4 can form hydrogen bonds with key residues such as Glutamic Acid (GLU 1519) in the EP300 catalytic domain, thereby stabilizing the interaction. (B,C) Western blot (WB) analysis. (D,E) Co‐immunoprecipitation (Co‐IP) experiments with IP performed using an anti‐RBBP4 antibody (D) and an anti‐EP300 antibody (E). The results indicate that The EP300 agonist CTB enhanced (D), while the inhibitor C646 reduced (E), the interaction between EP300 and RBBP4. (F) Multiplex immunofluorescence staining of mouse ileal tissues. Compared to the radiation‐only group (IR+PBS), the β‐elemene treatment group (IR+β‐elemene) showed significantly enhanced expression and co‐localization of MCT1 (cyan), CD147 (green), RBBP4‐K26la (yellow), POLD1 (red), and POLD3 (purple) in the intestinal crypt regions. (G) Summary and schematic model of the mechanism. This study elucidates that β‐elemene promotes cellular uptake of L. gasseri ‐derived lactate by enhancing the membrane translocation of MCT1 in a CD147‐dependent manner. Intracellular lactate, through the lactylation of RBBP4 at the K26 site, recruits EP300 to the promoter regions of downstream genes ( POLD1 / POLD3 ), catalyzing H3K27ac modification. This ultimately activates the DNA damage repair pathway, protecting intestinal epithelial cells from radiation injury. Original full and unaltered blots can be found in Figure .

Article Snippet: The EP300 inhibitor C646 and agonist CTB were purchased from MedChemExpress.

Techniques: Western Blot, Immunoprecipitation, Co-Immunoprecipitation Assay, Multiplex Assay, Immunofluorescence, Staining, Expressing, Derivative Assay, Membrane, Translocation Assay, Modification

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