Chemical Biology & Drug Design最新文献

A novel series of covalent pyrrolo[2,3-d]pyrimidine cinnamamides was synthesized and evaluated for anticancer activity. The compounds were tested against three cancer cell lines—MDA-MB-231 (triple-negative breast cancer), A549 (non-small cell lung cancer), and U-87 MG (glioblastoma), alongside a cytotoxicity assessment on non-tumor NIH/3 T3 mouse embryonic fibroblast cell line. Compound 5k (IC₅₀ = 0.99 ± 0.45 μM) and 5i (IC₅₀ = 1.15 ± 0.14 μM) demonstrated markedly higher potency against MDA-MB-231 cells compared to cisplatin (IC₅₀ = 34.36 ± 0.16 μM), whereas 5e was found active against A549 cells (IC₅₀ = 1.41 ± 1.13 μM). None of the active compounds exhibited significant toxicity against normal NIH/3 T3 cells. Molecular docking studies involving covalent modification at the ATP-binding sites of EGFR (L858R/T790M), HER2, and JAK3 via key interactions with Cys797 (EGFR/HER2) and Cys909 (JAK3) supported their irreversible mechanism of action. Glutathione-binding assay confirmed the covalent adduct formation with a prominent molecular ion peak corresponding to the adduct. Density Functional Theory analyses of the leading compounds revealed low HOMO-LUMO energy gaps, which correlated with elevated electronic reactivity and biological capability. Electrostatic surface potential maps further highlighted distinct electrophilic character around the acrylamide warhead, facilitating potential covalent bond formation with nucleophilic Cys residues in the target proteins. In silico ADMET profiling confirmed favorable drug-likeness and safety attributes. Together, these findings support the discovery of this novel class of covalent pyrrolo[2,3-d] pyrimidine cinnamamides as promising and safer lead candidates for anticancer therapy, particularly against triple-negative breast cancer.

Glioma, a prevalent malignancy globally, presents a serious threat to human health. Recent research has highlighted the significant anti-tumor properties of 6-gingerol (6-G), an active component of the traditional Chinese medicine ginger, though its precise mechanisms in glioma remain to be fully elucidated. This study employed network pharmacology, molecular docking, and dynamic simulation to explore the targets and underlying mechanisms of 6-G's anti-glioma effects, followed by in vitro validation of the key pathways. Drug-related targets were identified via PharmMapper and Swiss target prediction databases, while disease-related targets were sourced from GeneCards, OMIM, and TTD. The intersection of these datasets yielded potential therapeutic targets. Subsequent PPI network analysis using STRING11.5 and core gene screening with Cytoscape 3.9.1 led to the construction of a “drug-target network” and the identification of central genes. GO and KEGG enrichment analyses were conducted on potential therapeutic targets. Molecular docking and dynamic simulations were utilized to analyze the interactions between core genes and 6-G. Ultimately, the primary mechanism underlying 6-G's anti-GC effects was validated through in vitro experiments. A total of 183 potential targets for 6-G treatment of glioma were identified, with PPI analysis and core target screening revealing 10 critical targets. Enrichment analyses underscored the PI3K/AKT pathway as the primary signaling mechanism through which 6-G exerts its therapeutic effects. Molecular docking results showed that AKT1, HSP90AA1, EGFR, and MAPK3 were the key targets of 6-G in the treatment of glioma, and dynamic simulations further verified these findings. In vitro findings demonstrated that 6-G effectively inhibits the proliferation of U87 and U251 glioma cells, induces apoptosis, arrests the G1 phase of the cell cycle, and suppresses migration and invasion. Western blot analysis confirmed a significant downregulation of p-AKT in the PI3K/AKT pathway. In conclusion, 6-G impairs glioma cell proliferation, promotes apoptosis, induces G1 phase arrest, and inhibits migration and invasion, primarily through the suppression of the PI3K-AKT pathway. This finding provides a robust foundation for further research and clinical application.

Quinazolin-4-one scaffolds offer rich anticancer chemistry but often trade potency for selectivity. Building on a tubulin-targeting lead (MJ-65), 12 new derivatives (26–37) were synthesized to dissect geometry–activity relationships and enhance the polarity of C2-substituents. Cytotoxicity was profiled against cancerous (HCT116 and CAL27) and normal (FHC) cells. In silico studies employed CDOCKER against tubulin (PDB 5NJH), GROMACS for molecular dynamics (MD), and ProTox-3.0 for toxicity estimation. The previously synthesized geometry-matched pairs 21–25 were active at 10 μM. In contrast, their isomers 26–30 were largely inactive, revealing a configuration-dependent binding mechanism. Optimizing polarity yielded Holu-7 (compound 35; 2,4-dihydroxyphenyl at the C2-position), which exhibited sub-50 nM IC₅₀ in HCT116/CAL27 cells and > 10 μM in FHC cells and induced robust G₂/M arrest. Docking/MD supported stable vinca-site engagement, with hydrogen bonds to ASP179/ASN206 and π-stacking with TYR224. ProTox-3.0 predicted a higher LD₅₀ and absence of major organ toxicities relative to MJ-65. This data indicates that configuration-aware, polarity-tuned design can deliver selective quinazolinone anticancer candidates; therefore, Holu-7 merits further preclinical evaluation.

Coronavirus Disease-2019 (COVID-19) caused by SARS-CoV-2 remains a serious health concern worldwide. Inhibitors of the protein–protein interaction (iPPI) between the SARS-CoV-2 spike protein (S) and human Angiotensin-Converting Enzyme-2 (ACE2) are promising as potential antiviral agents. This study aimed to identify and evaluate novel compounds as inhibitors of the S receptor-binding domain (RBD) and ACE2 interaction through Eugenol- and Structure-Based virtual screening approaches. The hit compounds were corroborated as protein–protein interaction inhibitors using an ELISA-based enzyme assay. Molecular docking and molecular dynamics (MD) studies of the selected compounds showed that they maintained a molecular interaction and stability (RMSD fluctuations less than 4 Å) with essential residues of the S protein. The best compound, Eu-1 (IC₅₀ = 16 μM), prevented the interaction between the S protein and ACE2 receptor efficiently with an 83.7% inhibition at 50 μM. In addition, Eu-1 had an adequate value of cytotoxicity (CC₅₀ > 200 μM). Therefore, Eu-1 is a candidate compound for further SARS-CoV-2 preclinical experiments.

Diabetic nephropathy (DN) is a severe microvascular complication of diabetes. This study aimed to identify hub genes and explore potential therapeutic drugs for DN. Differentially expressed genes were analyzed between DN and normal samples from the GSE104948 and GSE47183 datasets. Hub genes were identified through weighted gene coexpression network analysis and protein–protein interaction network analysis and validated using two external datasets. Receiver operating characteristic curves were employed to assess the diagnostic accuracy of the hub genes. Virtual screening identified potential small-molecule compounds targeting the hub genes CD163 and transmembrane immune signaling adaptor TYROBP (TYROBP). High-glucose (HG)-induced human glomerular mesangial cells (HGMCs) were used to construct an in vitro DN model. Cell viability was assessed using a cell counting kit-8, and inflammatory factors were measured by enzyme-linked immunosorbent assay, and mesangial extracellular matrix-related protein levels were detected by Western blot. Two hub genes, CD163 and TYROBP, were identified as significantly upregulated in DN samples and HG-induced HGMCs, demonstrating high specificity and sensitivity for DN diagnosis. Demethyleneberberine (DMB) and dehydroevodiamine (DHE) exhibited strong binding affinity to CD163 and TYROBP and effectively suppressed HG-induced HGMC proliferation, inflammatory responses, and extracellular matrix deposition. In conclusion, CD163 and TYROBP serve as key biomarkers and therapeutic targets for DN, while DMB and DHE show promise as natural compounds for DN treatment.

Psoriasis is a prevalent chronic skin disease. Cycloastragenol (CAG) has been shown to activate autophagy and alleviate epidermal keratinocyte hyperproliferation in psoriasis. This study aimed to clarify the mechanism of CAG-mediated autophagy in psoriasis-like models. We treated C57BL/6 mice with imiquimod cream and stimulated HaCaT cells with a cytokine mixture (C-mix) to establish mouse and cell models. Psoriasis area and severity index scores were used to evaluate pathological changes. Autophagy flux was monitored using a monomeric red fluorescent protein–green fluorescent protein–microtubule-associated protein 1 light chain 3 assay. The interaction between sirtuin 1 (SIRT1) and zinc finger containing Krüppel-associated box and SCAN domain 3 (ZKSCAN3), as well as ZKSCAN3 acetylation, was examined using co-immunoprecipitation. Our results found that CAG alleviated autophagy inhibition in the imiquimod-induced psoriasis-like mouse model and enhanced autophagy by upregulating SIRT1 expression. ZKSCAN3 inhibited autophagy in the C-mix-stimulated psoriasis-like cellular model, while SIRT1 reduced the nuclear localization of ZKSCAN3 through deacetylation. ZKSCAN3 overexpression reversed SIRT1-mediated autophagy enhancement, whereas CAG promoted autophagy by regulating the nuclear localization of ZKSCAN3. In conclusion, our findings demonstrate that CAG ameliorates autophagy inhibition by modulating the SIRT1/ZKSCAN3 axis in psoriasis.

To develop and validate an interpretable machine-learning model for early prediction of biochemical recurrence (BCR) by fusing multiparametric MRI radiomics, clinical variables, and hematological biomarkers. A total of 172 patients (115 BCR-positive, 57 BCR-negative), who underwent RP with a median follow-up of 37 months, from Taizhou People's Hospital were retrospectively enrolled. Preoperative ADC and T2-weighted images were manually segmented to extract radiomic features; laboratory and clinical data included PSA, routine blood counts, lipid profile, and coagulation indices. After LASSO selection, seven machine-learning algorithms were trained and internally validated. The best-performing model was interpreted with SHAP analysis to quantify feature contributions. PSA emerged as the dominant predictor, exhibiting the highest mean absolute SHAP value and thereby exerting the greatest influence on model output. Among coagulation parameters, D-dimer and APTT were significantly associated with BCR (p = 0.007 and p = 0.036, respectively). Integration of ADC + T2 radiomics with clinical/hematological variables via a SVM classifier yielded the highest performance: AUC 0.916 (95% CI: 0.891–0.941) in the training set and 0.820 (95% CI: 0.762–0.878) in the validation set. SHAP revealed that ADC/T2 radiomic features constituted 60% of the top-ten predictors, while D-dimer exhibited a paradoxical negative SHAP value, suggesting a potential protective association. Multimodal fusion of mpMRI radiomics, clinical feature, and hematological biomarkers substantially improves BCR prediction. The interpretable model highlights PSA, and coagulation dysfunction, as key recurrence drivers, offering a clinically actionable tool for personalized management.

Chronic rhinosinusitis with nasal polyps (CRSwNP) is a multifaceted inflammatory condition that significantly affects patients clinically. It is vital to comprehend the basic molecular mechanisms and to discover new biomarkers. This research combines multi-omics data, molecular docking, and dynamic simulations to investigate gene functions and possible biomarkers related to CRSwNP. Initially, we discovered 555 differentially expressed genes (DEGs) induced by alpha-toxin (Hla) and 8119 DEGs associated with CRSwNP obtained from the Gene Expression Omnibus (GEO) database. Utilizing GO/KEGG enrichment analysis, we identified the NF-κB signaling pathway as significant. We identified 16 genes associated with TGF-β receptor signaling in epithelial–mesenchymal transition (EMT) through PathCards and subsequently intersected these with the differentially expressed genes from two datasets. This analysis revealed the presence of one gene, PRKCZ. Additionally, single-cell sequencing offered deeper insights into cellular diversity, elucidating the expression patterns of PRKCZ across various cell types. Molecular docking and dynamics simulations established that the proteasome inhibitor MG132 can create a stable complex with PRKCZ. In conclusion, qRT-PCR, Western blot, immunohistochemistry, and fluorescence assays validated that Hla stimulation markedly heightened the levels of inflammatory pathway markers in human nasal mucosal epithelial cells. Importantly, the inhibition of PRKCZ by MG132 resulted in a significant reduction of these marker expression levels, offering a foundation for targeted therapeutic interventions. The current research demonstrates that alpha-toxin from Staphylococcus aureus promotes EMT in CRSwNP via the NF-κB/TGF-β signaling axis. A significant gene that may serve as a potential therapeutic target is PRKCZ.