Drug-metabolizing enzymes, particularly the cytochrome P450 (CYP450) monooxygenases, play a pivotal role in pharmacokinetics. CYP450 enzymes can be affected by various xenobiotic substrates, which will eventually be responsible for most metabolism-based herb–herb or herb–drug interactions, usually involving competition with another drug for the same enzyme binding site. Compounds from herbal or natural products are involved in many scenarios in the context of such interactions. These interactions are decisive both in drug discovery regarding the synergistic effects, and drug application regarding unwanted side effects. Herein, this review was conducted as a comprehensive compilation of the effects of herbal ingredients on CYP450 enzymes. Nearly 500 publications reporting botanicals’ effects on CYP450s were collected and analyzed. The countries focusing on this topic were summarized, the identified herbal ingredients affecting enzyme activity of CYP450s, as well as methods identifying the inhibitory/inducing effects were reviewed. Inhibitory effects of botanicals on CYP450 enzymes may contribute to synergistic effects, such as herbal formulae/prescriptions, or lead to therapeutic failure, or even increase concentrations of conventional medicines causing serious adverse events. Conducting this review may help in metabolism-based drug combination discovery, and in the evaluation of the safety profile of natural products used therapeutically.

Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease with limited treatment options. Despite endothelial cells (ECs) comprising 30% of the lung cellular composition, the role of EC dysfunction in pulmonary fibrosis (PF) remains unclear. We hypothesize that sterol regulatory element-binding protein 2 (SREBP2) plays a critical role in the pathogenesis of PF via EC phenotypic modifications. Transcriptome data demonstrate that SREBP2 overexpression in ECs led to the induction of the TGF, Wnt, and cytoskeleton remodeling gene ontology pathways and the increased expression of mesenchymal genes, such as snail family transcriptional repressor 1 (snai1), α -smooth muscle actin, vimentin, and neural cadherin. Furthermore, SREBP2 directly bound to the promoter regions and transactivated these mesenchymal genes. This transcriptomic change was associated with an epigenetic and phenotypic switch in ECs, leading to increased proliferation, stress fiber formation, and ECM deposition. Mice with endothelial-specific transgenic overexpression of SREBP2 (EC-SREBP2[N]-Tg mice) that were administered bleomycin to induce PF demonstrated exacerbated vascular remodeling and increased mesenchymal transition in the lung. SREBP2 was also found to be markedly increased in lung specimens from patients with IPF. These results suggest that SREBP2, induced by lung injury, can exacerbate PF in rodent models and in human patients with IPF.

Background: Dysregulated BMP (bone morphogenetic protein) or TGF-β (transforming growth factor beta) signaling pathways are imperative in idiopathic and familial pulmonary arterial hypertension (PAH) as well as experimental pulmonary hypertension (PH) in rodent models. MED1 (mediator complex subunit 1) is a key transcriptional co-activator and KLF4 (Krüppel-like factor 4) is a master transcription factor in endothelium. However, MED1 and KLF4 epigenetic and transcriptional regulations of the BMP/TGF-β axes in pulmonary endothelium and their dysregulations leading to PAH remain elusive. We investigate the MED1/KLF4 co-regulation of the BMP/TGF-β axes in endothelium by studying the epigenetic regulation of BMPR2 (BMP receptor type II), ETS-related gene ( ERG ), and TGFBR2 (TGF-β receptor 2) and their involvement in the PH. Methods: High-throughput screening involving data from RNA-seq, MED1 ChIP-seq, H3K27ac ChIP-seq, ATAC-seq, and high-throughput chromosome conformation capture together with in silico computations were used to explore the epigenetic and transcriptional regulation of BMPR2, ERG, and TGFBR2 by MED1 and KLF4. In vitro experiments with cultured pulmonary arterial endothelial cells (ECs) and bulk assays were used to validate results from these in silico analyses. Lung tissue from patients with idiopathic PAH, animals with experimental PH, and mice with endothelial ablation of MED1 (EC- MED1 ^−/− ) were used to study the PH-protective effect of MED1. Results: Levels of MED1 were decreased in lung tissue or pulmonary arterial endothelial cells from idiopathic PAH patients and rodent PH models. Mechanistically, MED1 acted synergistically with KLF4 to transactivate BMPR2, ERG, and TGFBR2 via chromatin remodeling and enhancer-promoter interactions. EC- MED1 ^−/− mice showed PH susceptibility. In contrast, MED1 overexpression mitigated the PH phenotype in rodents. Conclusions: A homeostatic regulation of BMPR2, ERG, and TGFBR2 in ECs by MED1 synergistic with KLF4 is essential for the normal function of the pulmonary endothelium. Dysregulation of MED1 and the resulting impairment of the BMP/TGF-β signaling is implicated in the disease progression of PAH in humans and PH in rodent models.

In recent years, drug repositioning has emerged as a promising alternative to the time-consuming, expensive and risky process of developing new drugs for diseases. However, the current database for drug repositioning faces several issues, including insufficient data volume, restricted data types, algorithm inaccuracies resulting from the neglect of multidimensional or heterogeneous data, a lack of systematic organization of literature data associated with drug repositioning, limited analytical capabilities and user-unfriendly webpage interfaces. Hence, we have established the first all-encompassing database called DrugRepoBank, consisting of two main modules: the ‘Literature’ module and the ‘Prediction’ module. The ‘Literature’ module serves as the largest repository of literature-supported drug repositioning data with experimental evidence, encompassing 169 repositioned drugs from 134 articles from 1 January 2000 to 1 July 2023. The ‘Prediction’ module employs 18 efficient algorithms, including similarity-based, artificial-intelligence-based, signature-based and network-based methods to predict repositioned drug candidates. The DrugRepoBank features an interactive and user-friendly web interface and offers comprehensive functionalities such as bioinformatics analysis of disease signatures. When users provide information about a drug, target or disease of interest, DrugRepoBank offers new indications and targets for the drug, proposes new drugs that bind to the target or suggests potential drugs for the queried disease. Additionally, it provides basic information about drugs, targets or diseases, along with supporting literature. We utilize three case studies to demonstrate the feasibility and effectiveness of predictively repositioned drugs within DrugRepoBank. The establishment of the DrugRepoBank database will significantly accelerate the pace of drug repositioning. Database URL:https://awi.cuhk.edu.cn/DrugRepoBank

Drug–target interactions (DTIs) are considered a crucial component of drug design and drug discovery. To date, many computational methods were developed for drug–target interactions, but they are insufficiently informative for accurately predicting DTIs due to the lack of experimentally verified negative datasets, inaccurate molecular feature representation, and ineffective DTI classifiers. Therefore, we address the limitations of randomly selecting negative DTI data from unknown drug–target pairs by establishing two experimentally validated datasets and propose a capsule network-based framework called CapBM-DTI to capture hierarchical relationships of drugs and targets, which adopts pre-trained bidirectional encoder representations from transformers (BERT) for contextual sequence feature extraction from target proteins through transfer learning and the message-passing neural network (MPNN) for the 2-D graph feature extraction of compounds to accurately and robustly identify drug–target interactions. We compared the performance of CapBM-DTI with state-of-the-art methods using four experimentally validated DTI datasets of different sizes, including human (Homo sapiens) and worm (Caenorhabditis elegans) species datasets, as well as three subsets (new compounds, new proteins, and new pairs). Our results demonstrate that the proposed model achieved robust performance and powerful generalization ability in all experiments. The case study on treating COVID-19 demonstrates the applicability of the model in virtual screening.

Background/Objectives: The rising global prevalence of metabolic diseases (e.g., obesity, type 2 diabetes mellitus) underscores the need for effective interventions. Omega-3 polyunsaturated fatty acids (PUFAs) exhibit therapeutic potential, yet their molecular mechanisms remain unclear. This systematic review synthesizes a decade (2014–2024) of omics research to elucidate Omega-3 PUFA mechanisms in metabolic diseases and identify future directions. Methods: A PRISMA-guided search of the Web of Science identified studies on Omega-3 PUFAs, metabolic diseases, and omics. After excluding reviews, non-English articles, and irrelevant studies, 72 articles were analyzed (16 multi-omics, 17 lipidomics, 10 transcriptomics/metabolomics/microbiomics each, and 6 proteomics). Results: Omics studies demonstrated that Omega-3 PUFAs, particularly EPA and DHA, improve metabolic health through interconnected mechanisms. They regulate epigenetic processes, including DNA methylation and miRNA expression, influencing genes linked to inflammation and insulin sensitivity. Omega-3 PUFAs reduce oxidative stress by mitigating protein carbonylation and enhancing antioxidant defenses. Gut microbiota modulation is evident through increased beneficial taxa (e.g., Bacteroidetes, Akkermansia) and reduced pro-inflammatory species, correlating with improved metabolic parameters. Mitochondrial function is enhanced via upregulated fatty acid oxidation and TCA cycle activity, while anti-inflammatory effects arise from NF-κB pathway suppression and macrophage polarization toward an M2 phenotype. Challenges include interindividual variability in responses and a limited understanding of dynamic metabolic interactions. Conclusions: Omega-3 PUFAs target multiple pathways to improve metabolic health. Future research should prioritize chemoproteomics for direct target identification, multi-omics integration, and personalized strategies combining Omega-3 with therapies like calorie restriction.