Development and validation of a dried blood spots assay for metabolic profiling of ginsenosides using ultra-high performance liquid chromatography-mass spectrometry.

ETHNOPHARMACOLOGICAL RELEVANCE: Panax ginseng C.A. Meyer., a famous and valuable traditional Chinese medicine with thousand years of history for its healthcare and therapeutic effects. It is necessary and meaningful to study the pharmacokinetic behavior of ginsenosides in vivo as they are the most active components. Dried blood spots (DBS) are a mature and advanced blood collection method with meet the needs for the measurement of numerous analytes. AIM OF THE STUDY: This study aimed to explore the feasibility on DBS in the metabolic profile analysis of complex herbal products. MATERIALS AND METHODS: An ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS/MS) method was developed and validated for the determination of ginsenosides. The preparation of DBS samples was conducted by spiking the whole blood with analytes to obtain 20 µL of blood spots on Whatman 903 collection card. A punched dish of 10 mm in diameter was extracted with 70 % methanol aqueous solution, digoxin was used as an internal standard. Target compounds were separated on a Waters T3 column (2.1 × 100 mm, 1.8 µm) with acetonitrile and water (0.1 % formic acid) at a flow rate of 0.4 mL/min. RESULTS: The various ginsenosides showed good linearity in the range of 1-2000 ng/mL. The extraction recoveries and matrix effects of the target analytes were above 82.2%. The intra- and inter-batch accuracy and precision were within the limits of ≤15% for all tested concentrations. Moreover, the collected dried blood spot samples could be stably stored at room temperature for 14 days and 4 °C for 1 month without being affected. And it is delightful that the DBS-based analysis is compatible or even superior to the conventional protein precipitation in terms of sensitivity, linearity, and stability. In particular, the target analytes are stable in the DBS sampling under normal storing condition and the sensitivity for some trace metabolites of ginsenosides, such as 20(S)-Rg3, 20(R)-Rg3, F1, Rk1, Rg5, etc. increases 3-4 folds as evaluated by LLOQ. CONCLUSIONS: The established method was successfully applied to pharmacokinetic studies of ginseng extract in mice, this suggests a more feasible strategy for pharmacokinetic study of traditional and natural medicines both in animal tests and clinical trials.

Uncovering the secrets of agarwood aroma according to regions and grades using a comprehensive analytical strategy.

Agarwood holds significant importance as a valuable resource for aromatic purposes, however, key components responsible for aroma and the differences between regions and grades remain to be deeply elucidated. Thus, the odors of agarwood sourced from typical zones, as well as the renowned Kynam agarwood, were analyzed by HS-SPME Arrow GC-MS in SCAN and MRM modes. The integrated strategy proposed herein exploits the respective advantages of non-targeted and targeted analysis. In addition to a total of 55 volatile components identified from the NIST database, 114 odor components were matched according to the Smart Aroma Database, and a series of differential compounds was also unearthed and quantified.

Identification of Dihydrobenzofuran Neolignans as Novel PDE4 Inhibitors and Evaluation of Antiatopic Dermatitis Efficacy in DNCB-Induced Mice Model.

Atopic dermatitis is a chronic relapsing skin disease characterized by recurrent, pruritic, localized eczema, while PDE4 inhibitors have been reported to be effective as antiatopic dermatitis agents. 3',4-O-dimethylcedrusin (DCN) is a natural dihydrobenzofuran neolignan isolated from Magnolia biondii with moderate potency against PDE4 (IC50 = 3.26 ± 0.28 µM) and a binding mode similar to that of apremilast, an approved PDE4 inhibitor for the treatment of psoriasis. The structure-based optimization of DCN led to the identification of 7b-1 that showed high inhibitory potency on PDE4 (IC50 = 0.17 ± 0.02 µM), good anti-TNF-α activity (EC50 = 0.19 ± 0.10 µM), remarkable selectivity profile, and good skin permeability. The topical treatment of 7b-1 resulted in the significant benefits of pharmacological intervention in a DNCB-induced atopic dermatitis-like mice model, demonstrating its potential for the development of novel antiatopic dermatitis agents.

Epimedin B exhibits pigmentation by increasing tyrosinase family proteins expression, activity, and stability.

Epimedin B (EB) is one of the main flavonoid ingredients present in Epimedium brevicornum Maxim., a traditional herb widely used in China. Our previous study showed that EB was a stronger inducer of melanogenesis and an activator of tyrosinase (TYR). However, the role of EB in melanogenesis and the mechanism underlying the regulation remain unclear. Herein, as an extension to our previous investigation, we provide comprehensive evidence of EB-induced pigmentation in vivo and in vitro and elucidate the melanogenesis mechanism by assessing its effects on the TYR family of proteins (TYRs) in terms of expression, activity, and stability. The results showed that EB increased TYRs expression through microphthalmia-associated transcription factor-mediated p-Akt (referred to as protein kinase B (PKB))/glycogen synthase kinase 3ß (GSK3ß)/ß-catenin, p-p70 S6 kinase cascades, and protein 38 (p38)/mitogen-activated protein (MAP) kinase (MAPK) and extracellular regulated protein kinases (ERK)/MAPK pathways, after which EB increased the number of melanosomes and promoted their maturation for melanogenesis in melanoma cells and human primary melanocytes/skin tissues. Furthermore, EB exerted repigmentation by stimulating TYR activity in hydroquinone- and N-phenylthiourea-induced TYR inhibitive models, including melanoma cells, zebrafish, and mice. Finally, EB ameliorated monobenzone-induced depigmentation in vitro and in vivo through the enhancement of TYRs stability by inhibiting TYR misfolding, TYR-related protein 1 formation, and retention in the endoplasmic reticulum and then by downregulating the ubiquitination and proteolysis processes. These data conclude that EB can target TYRs and alter their expression, activity, and stability, thus stimulating their pigmentation function, which might provide a novel rational strategy for hypopigmentation treatment in the pharmaceutical and cosmetic industries.

Transfer learning enhanced graph neural network for aldehyde oxidase metabolism prediction and its experimental application.

Aldehyde oxidase (AOX) is a molybdoenzyme that is primarily expressed in the liver and is involved in the metabolism of drugs and other xenobiotics. AOX-mediated metabolism can result in unexpected outcomes, such as the production of toxic metabolites and high metabolic clearance, which can lead to the clinical failure of novel therapeutic agents. Computational models can assist medicinal chemists in rapidly evaluating the AOX metabolic risk of compounds during the early phases of drug discovery and provide valuable clues for manipulating AOX-mediated metabolism liability. In this study, we developed a novel graph neural network called AOMP for predicting AOX-mediated metabolism. AOMP integrated the tasks of metabolic substrate/non-substrate classification and metabolic site prediction, while utilizing transfer learning from 13C nuclear magnetic resonance data to enhance its performance on both tasks. AOMP significantly outperformed the benchmark methods in both cross-validation and external testing. Using AOMP, we systematically assessed the AOX-mediated metabolism of common fragments in kinase inhibitors and successfully identified four new scaffolds with AOX metabolism liability, which were validated through in vitro experiments. Furthermore, for the convenience of the community, we established the first online service for AOX metabolism prediction based on AOMP, which is freely available at https://aomp.alphama.com.cn.

Application of ensemble learning for predicting GABAA receptor agonists.

BACKGROUND: Over the past few decades, agonists binding to the benzodiazepine site of the GABAA receptor have been successfully developed as clinical drugs. Different modulators (agonist, antagonist, and reverse agonist) bound to benzodiazepine sites exhibit different or even opposite pharmacological effects, however, their structures are so similar that it is difficult to distinguish them based solely on molecular skeleton. This study aims to develop classification models for predicting the agonists. METHODS: 306 agonists or non-agonists were collected from literature. Six machine learning algorithms including RF, XGBoost, AdaBoost, GBoost, SVM, and ANN algorithms were employed for model development. Using six descriptors including 1D/2D Descriptors, ECFP4, 2D-Pharmacophore, MACCS, PubChem, and Estate fingerprint to characterize chemical structures. The model interpretability was explored by SHAP method. RESULTS: The best model demonstrated an AUC value of 0.905 and an MCC value of 0.808 for the test set. The PubMac-based model (PubMac-GB) achieved best AUC values of 0.935 for test set. The SHAP analysis results emphasized that MaccsFP62, ECFP_624, ECFP_724, and PubchemFP213 were the crucial molecular features. Applicability domain analysis was also performed to determine reliable prediction boundaries for the model. The PubMac-GB model was applied to virtual screening for potential GABAA agonists and the top 100 compounds were given. CONCLUSION: Overall, our ensemble learning-based model (PubMac-GB) achieved comparable performance and would be helpful in effectively identifying agonists of GABAA receptors.

Veronica linariifolia subsp. dilatata ameliorates LPS-induced acute lung injury by attenuating endothelial cell barrier dysfunction via EGFR/Akt/ZO-1 pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: The dried aerial parts of Veronica linariifolia subsp. dilatata (Nakai & Kitag.) D.Y.Hong named Shui Man Jing (SMJ) is a traditional Chinese medicine with a long history of clinical use in the treatment of chronic bronchitis and coughing up blood, however, its role on acute lung injury (ALI) has not been revealed yet. AIM OF THE STUDY: To assess the efficiency of SMJ on ALI and to investigate whether it inhibited endothelial barrier dysfunction by regulating the EGFR/Akt/ZO-1 pathway to alleviate ALI in vivo and in vitro based on the result of network pharmacology. MATERIALS AND METHODS: An in vivo model of ALI was established using inhalation of atomized lipopolysaccharide (LPS), and the effects of SMJ on ALI were evaluated through histopathological examination and inflammatory cytokines, lung histology and edema, vascular and alveolar barrier disruption. Network pharmacology was applied to predict the mechanism of SMJ in the treatment of ALI. The crucial targets were validated by RT-PCR, Western Blotting, molecular docking, immunohistochemistry and immunofluorescence methods in vivo and in virto. RESULTS: Administration of SMJ protected mice against LPS-induced ALI, including ameliorating the histological alterations in the lung tissues, and decreasing lung edema, protein content of bronchoalveolar lavage fluid, infiltration of inflammatory cell and secretion of cytokines. SMJ exerted protective effects in ALI by inhibiting endothelial barrier dysfunction in mice and bEnd.3 cell. SMJ relieved endothelial barrier dysfunction induced by LPS through upregulating the EGFR expression. SMJ also increased the phosphorylation of Akt, and ZO-1 expression both in vivo and in vitro. CONCLUSION: SMJ attenuates vascular endothelial barrier dysfunction for LPS-induced ALI via EGFR/Akt/ZO-1 pathway, and is a promising novel therapeutic candidate for ALI.

Ursolic acid derivative UAOS-Na treats experimental autoimmune encephalomyelitis by immunoregulation and protecting myelin.

Introduction: Multiple sclerosis (MS) is an inflammatory demyelinating disease of the central nervous system (CNS). Ursolic acid (UA) can be used in the MS treatment with anti-inflammatory and neuroprotective activities. However, UA is insoluble in water, which may affect its medication effectiveness. In our previous study, UAOS-Na, a water-soluble derivative of UA was obtained. In this study, we evaluated the pharmacological effects and explored its underlying mechanism of UAOS-Na on experimental autoimmune encephalomyelitis (EAE). Methods: Firstly, the pharmacodynamics of UAOS-Na was investigated in EAE and Cuprizone-induced mice. And then the possible mechanisms were investigated by TMT proteomics and verified by in vitro and in vivo experiments. Results: UAOS-Na (30 mg/kg/d) delayed the onset time of EAE from 11.78 days post immunization (dpi) to 14.33 dpi, reduced the incidence from 90.0% to 42.9%. UAOS-Na (60 mg/kg/d) reduced the serum levels of IFN-γ, IL-17A, TNF-α and IL-6, reduced the mononuclear cell infiltration of spinal cord, and inhibited the overexpression of key transcription factors T-bet and ROR-γt of EAE mouse spinal cord. In addition, UAOS-Na attenuated demyelination and astrogliosis in the CNS of EAE and cuprizone-induced mice. Mechanistically, proteomics showed that 96 differential expression proteins (DEPs) were enriched and 94 were upregulated in EAE mice compared with normal group. After UAOS-Na treatment, 16 DEPs were enriched and 15 were downregulated, and these DEPs were markedly enriched in antigen processing and presentation (APP) signaling pathway. Moreover, UAOS-Na downregulated the protein levels of Tapbp and H2-T23 in MHC-I antigen presentation pathway and reduced the proliferation of splenic CD8 T cells, thereby inhibiting the CNS infiltration of CD8 T cells. Conclusion: Our findings demonstrated that UAOS-Na has both myelin protective and anti-inflammatory effects. And it could reduce the inflammation of MS by downregulating the expression of Tapbp and H2-T23 in the MHC-I antigen presentation pathway.

Corrigendum: SbWRKY75- and SbWRKY41- mediated jasmonic acid signaling regulates baicalin biosynthesis.

[This corrects the article DOI: 10.3389/fpls.2023.1213662.].

Loops Mediate Agonist-Induced Activation of the Stimulator of Interferon Genes Protein.

The stimulator of interferon genes (STING) is an important therapeutic target for cancer diseases. The activated STING recruits downstream tank-binding kinase 1 (TBK1) to trigger several important immune responses. However, the molecular mechanism of how agonist molecules mediate the STING-TBK1 interactions remains elusive. Here, we performed molecular dynamics simulations to capture the conformational changes of STING and TBK1 upon agonist binding. Our simulations revealed that multiple helices (α5-α7) and especially three loops (loop 6, loop 8, and C-terminal tail) of STING participated in the allosteric mediation of the STING-TBK1 interactions. Consistent results were also observed in the simulations of the constitutive activating mutant of STING (R284S). We further identified α5 as a key region in this agonist-induced activation mechanism of STING. Free-energy perturbation calculations of multiple STING agonists demonstrated that an alkynyl group targeting α5 is a determinant for agonist activities. These results not only offer deeper insights into the agonist-induced allosteric mediation of STING-TKB1 interactions but also provide a guidance for future drug development of this important therapeutic target.

Naringenin improves muscle endurance via activation of the Sp1-ERRγ transcriptional axis.

Skeletal muscle function declines in the aging process or disease; however, until now, skeletal muscle has remained one of the organs most undertreated with medication. In this study, naringenin (NAR) was found to build muscle endurance in wild-type mice of different ages by increasing oxidative myofiber numbers and aerobic metabolism, and it ameliorates muscle dysfunction in mdx mice. The transcription factor Sp1 was identified as a direct target of NAR and was shown to mediate the function of NAR on muscle. Moreover, the binding site of NAR on Sp1 was further validated as GLN-110. NAR enhances the binding of Sp1 to the CCCTGCCCTC sequence of the Esrrg promoter by promoting Sp1 phosphorylation, thus upregulating Esrrg expression. The identification of the Sp1-ERRγ transcriptional axis is of great significance in basic muscle research, and this function of NAR has potential implications for the improvement of muscle function and the prevention of muscle atrophy.

LogD7.4 prediction enhanced by transferring knowledge from chromatographic retention time, microscopic pKa and logP.

Lipophilicity is a fundamental physical property that significantly affects various aspects of drug behavior, including solubility, permeability, metabolism, distribution, protein binding, and toxicity. Accurate prediction of lipophilicity, measured by the logD7.4 value (the distribution coefficient between n-octanol and buffer at physiological pH 7.4), is crucial for successful drug discovery and design. However, the limited availability of data for logD modeling poses a significant challenge to achieving satisfactory generalization capability. To address this challenge, we have developed a novel logD7.4 prediction model called RTlogD, which leverages knowledge from multiple sources. RTlogD combines pre-training on a chromatographic retention time (RT) dataset since the RT is influenced by lipophilicity. Additionally, microscopic pKa values are incorporated as atomic features, providing valuable insights into ionizable sites and ionization capacity. Furthermore, logP is integrated as an auxiliary task within a multitask learning framework. We conducted ablation studies and presented a detailed analysis, showcasing the effectiveness and interpretability of RT, pKa, and logP in the RTlogD model. Notably, our RTlogD model demonstrated superior performance compared to commonly used algorithms and prediction tools. These results underscore the potential of the RTlogD model to improve the accuracy and generalization of logD prediction in drug discovery and design. In summary, the RTlogD model addresses the challenge of limited data availability in logD modeling by leveraging knowledge from RT, microscopic pKa, and logP. Incorporating these factors enhances the predictive capabilities of our model, and it holds promise for real-world applications in drug discovery and design scenarios.

Design, synthesis and biological evaluation of chalcone derivatives as potent and orally active hCYP3A4 inhibitors.

Human cytochrome P450 3A4 (hCYP3A4), one of the most important drug-metabolizing enzymes, catalyze the metabolic clearance of ∼50% therapeutic drugs. CYP3A4 inhibitors have been used for improving the in vivo efficacy of hCYP3A4-substrate drugs. However, most of existing hCYP3A4 inhibitors may trigger serious adverse effects or undesirable effects on endogenous metabolism. This study aimed to discover potent and orally active hCYP3A4 inhibitors from chalcone derivatives and to test their anti-hCYP3A4 effects both in vitro and in vivo. Following three rounds of screening and structural optimization, the isoquinoline chalcones were found with excellently anti-hCYP3A4 effects. SAR studies showed that introducing an isoquinoline ring on the A-ring significantly enhanced anti-CYP3A4 effect, generating A10 (IC50 = 102.10 nM) as a promising lead compound. The 2nd round of SAR studies showed that introducing a substituent group at the para position of the carbonyl group on B-ring strongly improved the anti-CYP3A4 effect. As a result, C6 was identified as the most potent hCYP3A4 inhibitor (IC50 = 43.93 nM) in human liver microsomes (HLMs). C6 also displayed potent anti-hCYP3A4 effect in living cells (IC50 = 153.00 nM), which was superior to the positive inhibitor ketoconazole (IC50 = 251.00 nM). Mechanistic studies revealed that C6 could potently inhibit CYP3A4-catalyzed N-ethyl-1,8-naphthalimide (NEN) hydroxylation in a competitive manner (Ki = 30.00 nM). Moreover, C6 exhibited suitable metabolic stability in HLMs and showed good safety profiles in mice. In vivo tests demonstrated that C6 (100 mg/kg, orally administration) significantly increased the AUC(0-inf) of midazolam by 3.63-fold, and strongly prolonged its half-life by 1.66-fold compared with the vehicle group in mice. Collectively, our findings revealed the SARs of chalcone derivatives as hCYP3A4 inhibitors and offered several potent chalcone-type hCYP3A4 inhibitors, while C6 could serve as a good lead compound for developing novel, orally active CYP3A4 inhibitors with improved druglikeness properties.

OTTM: an automated classification tool for translational drug discovery from omics data.

Omics data from clinical samples are the predominant source of target discovery and drug development. Typically, hundreds or thousands of differentially expressed genes or proteins can be identified from omics data. This scale of possibilities is overwhelming for target discovery and validation using biochemical or cellular experiments. Most of these proteins and genes have no corresponding drugs or even active compounds. Moreover, a proportion of them may have been previously reported as being relevant to the disease of interest. To facilitate translational drug discovery from omics data, we have developed a new classification tool named Omics and Text driven Translational Medicine (OTTM). This tool can markedly narrow the range of proteins or genes that merit further validation via drug availability assessment and literature mining. For the 4489 candidate proteins identified in our previous proteomics study, OTTM recommended 40 FDA-approved or clinical trial drugs. Of these, 15 are available commercially and were tested on hepatocellular carcinoma Hep-G2 cells. Two drugs-tafenoquine succinate (an FDA-approved antimalarial drug targeting CYC1) and branaplam (a Phase 3 clinical drug targeting SMN1 for the treatment of spinal muscular atrophy)-showed potent inhibitory activity against Hep-G2 cell viability, suggesting that CYC1 and SMN1 may be potential therapeutic target proteins for hepatocellular carcinoma. In summary, OTTM is an efficient classification tool that can accelerate the discovery of effective drugs and targets using thousands of candidate proteins identified from omics data. The online and local versions of OTTM are available at http://otter-simm.com/ottm.html.

Structure-Activity Relationship Study of 1H-Pyrrole-3-carbonitrile Derivatives as STING Receptor Agonists.

The use of small agonists to target stimulators of interferon genes (STING) has been demonstrated to be a promising strategy for the treatment of various cancers and infectious diseases. Herein, we discovered a series of 1H-pyrrole-3-carbonitrile derivatives as potential STING agonists. On this basis, the structure-activity relationship of this scaffold was studied by introducing various substituents on the aniline ring system. Representative compounds 7F, 7P, and 7R all displayed comparable activities to the reported STING agonist SR-717 in binding various hSTING alleles and induced reporter signal in human THP1 cell lines. Model compound 7F induced phosphorylation of TBK1, IRF3, p65, and STAT3 in a STING-dependent fashion and stimulated the expression of target genes IFNB1, CXCL10, and IL6 in a time-dependent manner in human THP1 cells. Our findings afforded a series of novel STING agonists with promising potential.

Learning protein fitness landscapes with deep mutational scanning data from multiple sources.

One of the key points of machine learning-assisted directed evolution (MLDE) is the accurate learning of the fitness landscape, a conceptual mapping from sequence variants to the desired function. Here, we describe a multi-protein training scheme that leverages the existing deep mutational scanning data from diverse proteins to aid in understanding the fitness landscape of a new protein. Proof-of-concept trials are designed to validate this training scheme in three aspects: random and positional extrapolation for single-variant effects, zero-shot fitness predictions for new proteins, and extrapolation for higher-order variant effects from single-variant effects. Moreover, our study identified previously overlooked strong baselines, and their unexpectedly good performance brings our attention to the pitfalls of MLDE. Overall, these results may improve our understanding of the association between different protein fitness profiles and shed light on developing better machine learning-assisted approaches to the directed evolution of proteins. A record of this paper's transparent peer review process is included in the supplemental information.

Discovery of a Novel Bifunctional Steroid Analog, YXG-158, as an Androgen Receptor Degrader and CYP17A1 Inhibitor for the Treatment of Enzalutamide-Resistant Prostate Cancer.

The androgen/androgen receptor (AR) signaling pathway plays an important role in castration-resistant prostate cancer (CRPC). Bifunctional agents that simultaneously degrade AR and inhibit androgen synthesis are expected to block the androgen/AR signaling pathway more thoroughly, demonstrating the promising therapeutic potential for CRPC, even enzalutamide-resistant CRPC. Herein, a series of steroid analogs were designed, synthesized, and identified as selective AR degraders, among which YXG-158 (23-h) was the most potent antitumor compound with dual functions of AR degradation and CYP17A1 inhibition. In addition, 23-h abrogated the hERG inhibition and exhibited excellent PK profiles. In vivo, 23-h effectively inhibited the growth of hormone-sensitive organs in the Hershberger assay and exhibited robust antitumor efficacy both in enzalutamide-sensitive (LNCaP/AR) and enzalutamide-resistant (C4-2b-ENZ) xenograft models. Thus, 23-h was chosen as a preclinical candidate for the treatment of enzalutamide-resistant prostate cancer.

Triterpenoids from the roots of Sanguisorba officinalis and their Nrf2 stimulation activity.

Thirteen undescribed ursane-type triterpenoids, named as sangosides A-M (1-13), including two nor-ursanes, one split ring-ursane and ten ursanes, along with thirty-six known triterpenoids (14-49) were isolated and identified from the roots of Sanguisorba officinalis (Rosaceae). Their structures and absolute configurations were elucidated through spectroscopic data, single-crystal X-ray crystallography and electronic circular dichroism analysis. Their Nrf2 activation activity was evaluated in 293 T cells in vitro. Compounds 2, 5-7, 9-13, 19, 25, 26, 28-39, 41 and 46 showed significant Nrf2 agonistic effects compared with the control group at 25 µM, their cytotoxicity and dose-effect relationship were further studied in a dose-dependent manner. Their structure-activity relationships analysis suggested that the pentacyclic triterpenoids (10, 11, 30-34 and 41) contains two pairs of double bonds on the C & E rings and the ursane-type triterpenoids (25 and 26) with a carbonyl to C-2 and a hydroxyl group at C-3 all showed a considerably Nrf2 activation activity. These results suggested that S. officinalis was worthy of further investigation to find small molecule Nrf2 activators and facilitate their utilization as natural antioxidants.

SbWRKY75- and SbWRKY41-mediated jasmonic acid signaling regulates baicalin biosynthesis.

Introduction: Scutellaria baicalensis Georgi is a traditional Chinese medicinal plant with broad pharmacological activities whose main active ingredient is the flavonoid baicalin. Given its medicinal value and increasing market demand, it is essential to improve the plant's baicalin content. Flavonoid biosynthesis is regulated by several phytohormones, primarily jasmonic acid (JA). Methods: In this study, we conducted transcriptome deep sequencing analysis of S. baicalensis roots treated with methyl jasmonate for different durations (1, 3, or 7 hours). Leveraging weighted gene co-expression network analysis and transcriptome data, we identified candidate transcription factor genes involved in the regulation of baicalin biosynthesis. To validate the regulatory interactions, we performed functional assays such as yeast one-hybrid, electrophoretic mobility shift, and dual-luciferase assays. Results: Our findings demonstrated that SbWRKY75 directly regulates the expression of the flavonoid biosynthetic gene SbCLL-7, whereas SbWRKY41 directly regulates the expression of two other flavonoid biosynthetic genes, SbF6H and SbUGT, thus regulating baicalin biosynthesis. We also obtained transgenic S.baicalensis plants by somatic embryo induction and determined that overexpressing SbWRKY75 increased baicalin content by 14%, while RNAi reduced it by 22%. Notably, SbWRKY41 indirectly regulated baicalin biosynthesis by modulating the expression of SbMYC2.1, SbJAZ3 and SbWRKY75. Discussion: This study provides valuable insights into the molecular mechanisms underlying JA-mediated baicalin biosynthesis in S. baicalensis. Our results highlight the specific roles of transcription factors, namely SbWRKY75 and SbWRKY41, in the regulation of key biosynthetic genes. Understanding these regulatory mechanisms holds significant potential for developing targeted strategies to enhance baicalin content in S. baicalensis through genetic interventions.