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O-GlcNAc modification plays critical roles in regulating the stress response program and cellular homeostasis. However, systematic and multi-omics studies on the O-GlcNAc regulated mechanism have been limited. Here, comprehensive data are obtained by a chemical reporter-based method to survey O-GlcNAc function in human breast cancer cells stimulated with the genotoxic agent adriamycin. We identify 875 genotoxic stress-induced O-GlcNAc chromatin-associated proteins (OCPs), including 88 O-GlcNAc chromatin-associated transcription factors and cofactors (OCTFs), subsequently map their genomic loci, and construct a comprehensive transcriptional reprogramming network. Notably, genotoxicity-induced O-GlcNAc enhances the genome-wide interactions of OCPs with chromatin. The dynamic binding switch of hundreds of OCPs from enhancers to promoters is identified as a crucial feature in the specific transcriptional activation of genes involved in the adaptation of cancer cells to genotoxic stress. The OCTF nuclear factor erythroid 2-related factor-1 (NRF1) is found to be a key response regulator in O-GlcNAc-modulated cellular homeostasis. These results provide a valuable clue suggesting that OCPs act as stress sensors by regulating the expression of various genes to protect cancer cells from genotoxic stress., Protein O-GlcNAcylation is involved in regulating gene expression and maintaining cellular homeostasis. Here, the authors develop a chemical reporter-based strategy for the proteomic profiling and genome-wide mapping of genotoxic stress-induced O-GlcNAcylated chromatin-associated proteins.

Background: Hypericin is the main active ingredient of St. John’s wort, a Chinese herb commonly used for treating depression. Previous studies shown that hypericin can strongly inhibit human cytochrome P450 (CYP) enzyme activities; however, its potential interactions that inhibit human carboxylesterases 2 (hCE2) are unclear. Purpose: This study aimed to investigate the inhibitory effect of hypericin on hCE2. Methods: The inhibition mechanism of hypericin on hCE2 was studied by using N-(2-butyl-1,3-dioxo-2,3-dihydro- 1H-phenalen-6-yl)-2-chloroacetamide (NCEN). The type of inhibition of hypericin on hCE2 and the corresponding inhibition constant (Ki) value were determined. The inhibition of hypericin on hCE2 in living cells was discussed. The risk of herb-drug interactions (HDI) of hypericin in vivo was predicted by estimating the area under the drug concentration-time curve (AUC) in the presence or absence of hypericin. To understand the inhibition mechanism of hypericin on the activity of hCE2 in-depth, molecular docking was performed. Results: The half-maximal inhibitory concentration (IC50) values of hypericin against the hydrolysis of NCEN and irinotecan (CPT-11) were calculated to be 26.59 μM and 112.8 μM, respectively. Hypericin inhibited the hydrolysis of NCEN and CPT-11. Their Ki values were estimated as 10.53 μM and 81.77 μM, respectively. Moreover, hypericin distinctly suppressed hCE2 activity in living cells. In addition, the AUC of hCE2 metabolic drugs with metabolic sites similar to NCEN was estimated to increase by up to 5 % in the presence of hypericin. More importantly, the exposure of CPT-11 in the intestinal epithelium was predicted to increase by 2 % - 69 % following the oral coadministration of hypericin. Further, molecular simulations indicated that hypericin could strongly interact with ASP98, PHE307, and ARG355 to form four hydrogen bonds within hCE2. Conclusion: These findings regarding the combination of hypericin-containing herbs and drugs metabolized by hCE2 are of considerable clinical significance.

Inversion of chromosome 16 is a consistent finding in patients with acute myeloid leukemia subtype M4 with eosinophilia (AML M4Eo), which generates a CBFB-MYH11 fusion gene. We recently showed that RUNX1 is indispensable for Cbfb-MYH11-induced leukemogenesis in a mouse model. We found that RUNX1 interacted with CBFβ-SMMHC, the fusion protein encoded by CBFB-MYH11, to directly regulate critical genes for leukemogenesis (Zhen et al., Blood, 2020). However, our current understanding of the interaction between CBFβ-SMMHC and RUNX1 does not provide adequate explanation on how the RUNX1-CBFβ-SMMHC complex forms and how the complex interacts with DNA for leukemogenesis as CBFβ-SMMHC without the RUNX1 high-affinity-binding-domain (CBFβ-SMMHC-ΔHABD) is also able to induce leukemia while CBFβ-SMMHC with mutations in the C-terminal multimerization domain (CBFβ-SMMHC-mDE) is not able to induce leukemia in mice. To address this question, we used RHD domain of RUNX1, CBFβ, CBFβ-SMMHC, CBFβ-SMMHC-ΔHABD and CBFβ-SMMHC-mDE proteins, which were purified from E. coli overexpressing these proteins, to explore how the HABD and DE domains affect the interactions between CBFβ-SMMHC, RHD and RUNX1-target DNA Bio-Layer Interferometry (BLI) and negative staining. As expected, deletion of the HABD domain significantly reduced CBFβ-SMMHC's binding affinity to RHD by BLI assay. Interestingly, differences in binding affinity between RHD and different versions of CBFβ-SMMHC did not correlate with their leukemogenic capability. On the other hand, the binding affinity between RHD and its target oligo was more significantly enhanced by CBFβ-SMMHC and CBFβ-SMMHC-ΔHABD that can induce leukemia than CBFβ-SMMHC-DE, which cannot. We also found that both CBFβ-SMMHC and CBFβ-SMMHC-ΔHABD, but not CBFβ-SMMHC-mDE, could form a filament structure by negative staining, suggesting the filament formation ability is important for leukemogenesis by CBFβ-SMMHC. In addition, RHD reduces filament formation by CBFβ-SMMHC, which was overcome when target oligo was added. In contrast, RHD could not inhibit filament formation by CBFβ-SMMHC-ΔHABD, suggesting that HABD interaction is required for RHD to disrupt filament formation by CBFβ-SMMHC. Overall, we found that leukemogenic capability of CBFβ-SMMHC correlates with its ability to enhance binding between RHD and its target DNA and to form multimerized filaments. The results also suggest that HABD and DE domains of CBFβ-SMMHC are required for the formation of the RUNX1-CBFβ-SMMHC complex with higher binding affinity to target DNA. Disclosures No relevant conflicts of interest to declare.

Herein we provide a mass spectrometry-based lysine reactivity profiling strategy to monitor the ligand modulation of protein receptors, which is achieved by active dimethyl labeling of lysine residues and comparison of the alterations of labeling reactivity during ligand binding. The small-molecule ligand modulation patterns on the catechol-O-methyltransferase and the N-methyl-d-aspartate receptors have been predicted, including both binding regions and related conformational changes.

Table S7. The 241 potential miRNAs predicted by both RF model and 1D-CNN model. (DOCX 23 kb)

Table S3. Feature list. (DOCX 14 kb)

Table S1. Positive samples. (DOCX 20 kb)

Table S5. The top 10% most important features evaluated by RF model using mean decrease accuracy (left) and mean decrease Gini (right), respectively. (DOCX 14 kb)

Table S2. Negative samples. (DOCX 50 kb)

Compared with coumarin, 7-hydroxycoumarin could serve as a better hit for developing CYP2A6 inhibitors. In this study, a series of 7-hydroxycoumarin and its structural analogues were collected to study their structure-activity relationship (SAR) and isoform selectivity for inhibiting CYP2A6. All tested coumarins except a C4 phenyl derivative (11) showed higher inhibitory activities for CYP2A6 over the other CYP isoforms, including CYP1A2, CYP2D6, CYP2E1, CYP3A4, CYP2C8, and CYP2C9. Of these coumarins, 6,7-dihydroxycoumarin (1) and 7,8-dihydroxycoumarin (9) were found to be potent inhibitors of CYP2A6 with IC50/Ki value of 0.39/0.25 and 4.61/3.02 μM, respectively, compared to methoxalen as positive control (IC50/Ki = 0.43/0.26 μM). In contrast, other coumarins showed low or decreased CYP2A6-inhibiting activities. SAR analysis showed that hydroxy groups might be important for CYP2A6 inhibition, and the rank order of sites for hydroxy substitution was C6 > C7 > C8. In addition, either hydrophobic or hydrophilic substituents introduced into C4, C6 and C8 led to a reduction in CYP2A6-inhibiting activity, and the degree of influence was dependent on the size and electrical charge of substituents. Furthermore, inhibition kinetic analysis and docking simulations demonstrated that the 8-O-glucosylated coumarin derivative (17) exhibited noncompetitive inhibition against CYP2A6, while competitive inhibition patterns were noted for the other tested coumarins. The mechanisms underlying the inhibitors binding to CYP2A6 were further investigated by molecular docking study. The findings presented herein are very helpful for developing highly selective and more potent CYP2A6 inhibitors.