Antibody Recognition of Human Epidermal Growth Factor Receptor-2 (HER2) Juxtamembrane Domain Enhances Anti-Tumor Response of Chimeric Antigen Receptor (CAR)-T Cells.

Chimeric antigen receptor (CAR) T cell therapy shows promise in treating malignant tumors. However, the use of human epidermal growth factor receptor-2 (HER2) CAR-T cells carries the risk of severe toxicity, including cytokine release syndrome, due to their "on-target off-tumor" recognition of HER2. Enhancing the quality and functionality of HER2 CARs could greatly improve the therapeutic potential of CAR-T cells. In this study, we developed a novel anti-HER2 monoclonal antibody, Ab8, which targets domain III of HER2, distinct from the domain IV recognition of trastuzumab. Although two anti-HER2 mAbs induced similar levels of antibody-dependent cellular cytotoxicity, trastuzumab-based CAR-T cells exhibited potent antitumor activity against HER2-positive cancer cells. In conclusion, our findings provide scientific evidence that antibody recognition of the membrane-proximal domain promotes the anti-tumor response of HER2-specific CAR-T cells.

Computer-driven formulation development of Ginsenoside Rh2 ternary solid dispersion.

(20 S)-Ginsenoside Rh2 is a natural saponin derived from Panax ginseng Meyer (P. ginseng), which showed significantly potent anticancer properties. However, its low water solubility and bioavailability strongly restrict its pharmaceutical applications. The aim of current research is to develop a modified (20 S)-Ginsenoside Rh2 formulation with high solubility, dissolution rate and bioavailability by combined computational and experimental methodology. The "PharmSD" model was employed to predict the optimal polymer for (20 S)-Ginsenoside Rh2 solid dispersion formulations. The solubility of (20 S)-Ginsenoside Rh2 in various polymers was assessed, and the optimal ternary solid dispersion was evaluated across different dissolution mediums. Characterization techniques included the Powder X-ray diffraction (PXRD) and Fourier transform infrared spectroscopy (FTIR). Molecular dynamics simulations were employed to elucidate the formation mechanism of the solid dispersion and the interactions among active pharmaceutical ingredient (API) and excipient molecules. Cell and animal experiments were conducted to evaluate the in vivo performance of the modified formulation. The "PharmSD" solid dispersion model identified Gelucire 44/14 as the most effective polymer for enhancing the dissolution rate of Rh2. Subsequent experiment also confirmed that Gelucire 44/14 outperformed the other selected polymers. Moreover, the addition of the third component, sodium dodecyl sulfate (SDS), in the ternary solid dispersion formulation significantly amplified dissolution rates than the binary systems. Characterization experiments revealed that the API existed in an amorphous state and interacted via hydrogen bonding with SDS and Gelucire. Moreover, molecular modeling results provided additional evidence of hydrogen bonding interactions between the API and excipient molecules within the optimal ternary solid dispersion. Cell experiments demonstrated efflux ratio (EfR) of Rh2 ternary solid dispersion was lower than that of pure Rh2. In vivo experiments revealed that the modified formulation substantially improved the absorption of Rh2 in rats. Our research successfully developed an optimal ternary solid dispersion for Rh2 with high solubility, dissolution rate and bioavailability by integrated computational and experimental tools. The combination of Artificial Intelligence (AI) technology and molecular dynamics simulation is a wise way to support the future formulation development.

m6A epitranscriptomic modification of inflammation in cardiovascular disease.

Cardiovascular disease is currently the number one cause of death endangering human health. There is currently a large body of research showing that the development of cardiovascular disease and its complications is often accompanied by inflammatory processes. In recent years, epitranscriptional modifications have been shown to be involved in regulating the pathophysiological development of inflammation in cardiovascular diseases, with 6-methyladenine being one of the most common RNA transcriptional modifications. In this review, we link different cardiovascular diseases, including atherosclerosis, heart failure, myocardial infarction, and myocardial ischemia-reperfusion, with inflammation and describe the regulatory processes involved in RNA methylation. Advances in RNA methylation research have revealed the close relationship between the regulation of transcriptome modifications and inflammation in cardiovascular diseases and brought potential therapeutic targets for disease diagnosis and treatment. At the same time, we also discussed different cell aspects. In addition, in the article we also describe the different application aspects and clinical pathways of RNA methylation therapy. In summary, this article reviews the mechanism, regulation and disease treatment effects of m6A modification on inflammation and inflammatory cells in cardiovascular diseases in recent years. We will discuss issues facing the field and new opportunities that may be the focus of future research.

Unravelling chilling-stress resistance mechanisms in endangered Mangrove plant Lumnitzera littorea (Jack) Voigt.

Lumnitzera littorea (Jack) Voigt is one of the most endangered mangrove species in China. Previous studies have showed the impact of chilling stress on L. littorea and the repsonses at physiological and biochemical levels, but few attentions have been paid at molecular level. In this study, we conducted genome-wide investigation of transcriptional and post-transcriptional dynamics in L. littorea in response to chilling stress (8 °C day/5 °C night). In the seedlings of L. littorea, chilling sensing and signal transducing, photosystem II regeneration and peroxidase-mediated reactive oxygen species (ROS) scavenging were substantially enhanced to combat the adverse impact induced by chilling exposure. We further revealed that alternative polyadenylation (APA) events participated in chilling stress-responsive processes, including energy metabolism and steroid biosynthesis. Furthermore, APA-mediated miRNA regulations downregulated the expression of the genes involved in fatty acid biosynthesis and elongation, and protein phosphorylation, reflecting the important role of post-transcriptional regulation in modulating chilling tolerance in L. littorea. Our findings present a molecular view to the adaptive characteristics of L. littorea and shed light on the conservation genomic approaches of endangered mangrove species.

Epigenetic hallmarks in pulmonary fibrosis: New advances and perspectives.

Epigenetics indicates that certain phenotypes of an organism can undergo heritable changes in the absence of changes in the genetic DNA sequence. Many studies have shown that epigenetic patterns play an important role in the lung and lung diseases. Pulmonary fibrosis (PF) is also a type of lung disease. PF is an end-stage change of a large group of lung diseases, characterized by fibroblast proliferation and massive accumulation of extracellular matrix, accompanied by inflammatory injury and histological destruction, that is, structural abnormalities caused by abnormal repair of normal alveolar tissue. It causes loss of lung function in patients with multiple complex diseases, leading to respiratory failure and subsequent death. However, current treatment options for IPF are very limited and no drugs have been shown to significantly prolong the survival of patients. Therefore, based on a systematic understanding of the disease mechanisms of PF, this review integrates the role of epigenetics in the development and course of PF, describes preventive and potential therapeutic targets for PF, and provides a theoretical basis for further exploration of the mechanisms of PF.

Predicting liposome formulations by the integrated machine learning and molecular modeling approaches.

Liposome is one of the most widely used carriers for drug delivery because of the great biocompatibility and biodegradability. Due to the complex formulation components and preparation process, formulation screening mostly relies on trial-and-error process with low efficiency. Here liposome formulation prediction models have been built by machine learning (ML) approaches. The important parameters of liposomes, including size, polydispersity index (PDI), zeta potential and encapsulation, are predicted individually by optimal ML algorithm, while the formulation features are also ranked to provide important guidance for formulation design. The analysis of key parameter reveals that drug molecules with logS [-3, -6], molecular complexity [500, 1000] and XLogP3 (≥2) are priority for preparing liposome with higher encapsulation. In addition, naproxen (NAP) and palmatine HCl (PAL) represented the insoluble and water-soluble molecules are prepared as liposome formulations to validate prediction ability. The consistency between predicted and experimental value verifies the satisfied accuracy of ML models. As the drug properties are critical for liposome particles, the molecular interactions and dynamics of NAP and PAL liposome are further investigated by coarse-grained molecular dynamics simulations. The modeling structure reveals that NAP molecules could distribute into lipid layer, while most PAL molecules aggregate in the inner aqueous phase of liposome. The completely different physical state of NAP and PAL confirms the importance of drug properties for liposome formulations. In summary, the general prediction models are built to predict liposome formulations, and the impacts of key factors are analyzed by combing ML with molecular modeling. The availability and rationality of these intelligent prediction systems have been proved in this study, which could be applied for liposome formulation development in the future.

Scutellarein alleviates chronic obstructive pulmonary disease through inhibition of ferroptosis by chelating iron and interacting with arachidonate 15-lipoxygenase.

Ferroptosis, an iron-dependent cell death characterized by lethal lipid peroxidation, is involved in chronic obstructive pulmonary disease (COPD) pathogenesis. Therefore, ferroptosis inhibition represents an attractive strategy for COPD therapy. Herein, we identified natural flavonoid scutellarein as a potent ferroptosis inhibitor for the first time, and characterized its underlying mechanisms for inhibition of ferroptosis and COPD. In vitro, the anti-ferroptotic activity of scutellarein was investigated through CCK8, real-time quantitative polymerase chain reaction (RT-qPCR), Western blotting, flow cytometry, and transmission electron microscope (TEM). In vivo, COPD was induced by lipopolysaccharide (LPS)/cigarette smoke (CS) and assessed by changes in histopathological, inflammatory, and ferroptotic markers. The mechanisms were investigated by RNA-sequencing (RNA-seq), electrospray ionization mass spectra (ESI-MS), local surface plasmon resonance (LSPR), drug affinity responsive target stability (DARTS), cellular thermal shift assay (CETSA), and molecular dynamics. Our results showed that scutellarein significantly inhibited Ras-selective lethal small molecule (RSL)-3-induced ferroptosis and mitochondria injury in BEAS-2B cells, and ameliorated LPS/CS-induced COPD in mice. Furthermore, scutellarein also repressed RSL-3- or LPS/CS-induced lipid peroxidation, GPX4 down-regulation, and overactivation of Nrf2/HO-1 and JNK/p38 pathways. Mechanistically, scutellarein inhibited RSL-3- or LPS/CS-induced Fe2+ elevation through directly chelating Fe2+ . Moreover, scutellarein bound to the lipid peroxidizing enzyme arachidonate 15-lipoxygenase (ALOX15), which resulted in an unstable state of the catalysis-related Fe2+ chelating cluster. Additionally, ALOX15 overexpression partially abolished scutellarein-mediated anti-ferroptotic activity. Our findings revealed that scutellarein alleviated COPD by inhibiting ferroptosis via directly chelating Fe2+ and interacting with ALOX15, and also highlighted scutellarein as a candidate for the treatment of COPD and other ferroptosis-related diseases.

How can machine learning and multiscale modeling benefit ocular drug development?

The eyes possess sophisticated physiological structures, diverse disease targets, limited drug delivery space, distinctive barriers, and complicated biomechanical processes, requiring a more in-depth understanding of the interactions between drug delivery systems and biological systems for ocular formulation development. However, the tiny size of the eyes makes sampling difficult and invasive studies costly and ethically constrained. Developing ocular formulations following conventional trial-and-error formulation and manufacturing process screening procedures is inefficient. Along with the popularity of computational pharmaceutics, non-invasive in silico modeling & simulation offer new opportunities for the paradigm shift of ocular formulation development. The current work first systematically reviews the theoretical underpinnings, advanced applications, and unique advantages of data-driven machine learning and multiscale simulation approaches represented by molecular simulation, mathematical modeling, and pharmacokinetic (PK)/pharmacodynamic (PD) modeling for ocular drug development. Following this, a new computer-driven framework for rational pharmaceutical formulation design is proposed, inspired by the potential of in silico explorations in understanding drug delivery details and facilitating drug formulation design. Lastly, to promote the paradigm shift, integrated in silico methodologies were highlighted, and discussions on data challenges, model practicality, personalized modeling, regulatory science, interdisciplinary collaboration, and talent training were conducted in detail with a view to achieving more efficient objective-oriented pharmaceutical formulation design.

Comparative Study of Temperature Impact in Spin-Torque Switched Perpendicular and Easy-Cone MTJs.

The writing performance of the easy-cone magnetic tunnel junction (MTJ) and perpendicularly magnetized MTJ (pMTJ) under various temperatures was investigated based on the macrospin model. When the temperature is changed from 273 K to 373 K, the switching current density of the pMTJ changes by 56%, whereas this value is only 8% in the easy-cone MTJ. Similarly, the temperature-induced variation of the switching delay is more significant in the pMTJ. This indicates that the easy-cone MTJ has a more stable writing performance under temperature variations, resulting in a wider operating temperature range. In addition, these two types of MTJs exhibit opposite temperature dependence in the current overdrive and write error rate. In the easy cone MTJ, these two performance metrics will reduce as temperature is increased. The results shown in this work demonstrate that the easy-cone MTJ is more suitable to work at high temperatures compared with the pMTJ. Our work provides a guidance for the design of STT-MRAM that is required to operate at high temperatures.

Synthesis of Carrier-Free Paclitaxel-Curcumin Nanoparticles: The Role of Curcuminoids.

The systemic administration of paclitaxel (PTX)-based combinatorial therapies is significantly restricted due to the multidrug resistance. Curcumin (CUR) not only inhibits cancer-cell proliferation but also reverses the PTX resistance. However, achieving codelivery of these two drugs is a challenge due to their poor water solubility. Herein, we synthesized carrier-free PTX NPs by a facile nanoprecipitation method with the help of CUR and other curcuminoids present in turmeric extract. The prepared NPs demonstrated spherical morphologies with high conformational stability. Experimental studies showed that the presence of both bisdemethoxycurcumin and demethoxycurcumin is essential for the successful formation of spherical and monodisperse NPs. Computational studies revealed that the presence of the more sterically available curcuminoids BMC and DMC makes the self-assembly procedure more adaptable with a higher number of potential conformations that could give rise to more monodisperse PTX-CUR NPs. Compared with PTX alone, PTX-CUR NPs have shown comparable therapeutic efficiency in vitro and demonstrated a higher cellular internalization, highlighting their potential for in vivo applications. The successful formation of PTX-CUR NPs and the understanding of how multiple drugs behave at the molecular level also provide guidance for developing formulations for the synthesis of high-quality and effective carrier-free nanosystems for biomedical applications.

A Voltage-Modulated Nanostrip Spin-Wave Filter and Spin Logic Device Thereof.

A nanostrip magnonic-crystal waveguide with spatially periodic width modulation can serve as a gigahertz-range spin-wave filter. Compared with the regular constant-width nanostrip, the periodic width modulation creates forbidden bands (band gaps) at the Brillouin zone boundaries due to the spin-wave reflection by the periodic potential owing to the long-range dipolar interactions. Previous works have shown that there is a critical challenge in tuning the band structures of the magnonic-crystal waveguide once it is fabricated. In this work, using micromagnetic simulations, we show that voltage-controlled magnetic anisotropy can effectively tune the band structures of a ferromagnetic-dielectric heterostructural magnonic-crystal waveguide. A uniformly applied voltage of 0.1 V/nm can lead to a significant frequency shift of ~9 GHz. A spin-wave transistor prototype employing such a kind of spin-wave filter is proposed to realize various logical operations. Our results could be significant for future magnonic computing applications.

De novo design of a transcription factor for a progesterone biosensor.

Identifying, isolating, and obtaining naturally occurring transcription factors (TFs) is crucial for developing transcription-dependent biosensors. However, identifying and optimizing TFs for given molecules requires extensive time and effort. Accordingly, here, we report a strategy for the de novo design of a nonnatural TF, DLA, on the basis of a subtle conformational change of the ligand-binding domain (LBD) after the binding of a target molecule with its receptor. For the de novo design of DLA, we applied molecular dynamics to simulate different conformational states of DLA in order to understand the complete activity of DLA, which involves shortening of the distance between the DNA-binding domain (DBD) and the activation domain (AD) after progesterone binds to its LBD within DLA. The simulated results suggested that prokaryotic LexA, a truncated LBD from the progesterone receptor, and prokaryotic B42 together constitute DLA with a TF function. As a proof of concept, DLA was used as a transcription activator controlling the transcription of green fluorescent protein to construct an S. cerevisiae biosensor for progesterone detection. The progesterone-specific biosensor was successfully constructed with a sensitivity index EC50 of 27 µg/L, working range (0.16-60 µg/L), and time-to-detection (2.5 h). Ultimately, a low-cost, user-friendly kit was developed for the rapid detection of progesterone in the clinic. Theoretically, this work can also be used to develop a variety of other biosensors by employing the same strategy.

Chlorogenic acid, a natural product as potential inhibitor of COVID-19: virtual screening experiment based on network pharmacology and molecular docking.

Chlorogenic acid (CGA) is a potential inhibitor of Coronavirus Disease 2019 (COVID-19). ACE2 and its co-expressed proteins are SARS-CoV-2 receptors, which have been linked to SARS-CoV-2 infection and considered as the key target of SARS-CoV-2 in entering target cells. Here, network pharmacology was used to investigate the mechanism by which CGA affected COVID-19. A total of 70 potential targets related to the treatment of COVID-19 were obtained, among which NFE2L2, PPARG, ESR1, ACE, IL6, and HMOX1 might be the main potential targets. Finally, CGA and potential target proteins were scored by molecular docking, and the prediction results of network pharmacology were preliminarily verified. Moreover, CGA had potential anti-SARS-CoV-2 activity via integrating three common receptors in clinical practice compared with clinical trial drugs registered for the treatment of COVID-19, as shown by molecular docking. The mechanism of CGA against COVID-19 was initially investigated using network pharmacology, followed by molecular docking.

Exploring two types of prenylated bitter compounds from hop plant (Humulus lupulus L.) against α-glucosidase in vitro and in silico.

Hops are abundant in natural bioactive compounds. In this work, nine prenylated bitter compounds from hop were evaluated for their inhibitory activity against α-glucosidase. As a result, four flavonoids and one phloroglucinol (lupulone, LP) outperformed acarbose in inhibiting α-glucosidase. Isoxanthohumol (IX) and LP with two types of structures were selected for inhibition mechanism studies by spectroscopic methods and molecular dynamics simulation (MD). Results showed that IX acted as noncompetitive inhibitor and bound to α-glucosidase in allosteric sites via hydrogen bonds, hydrophobic, van der Waals (vdW), and electrostatic force, whereas LP was uncompetitive inhibitor and bound to catalytic sites via hydrophobic and vdW interactions. Notably, the conformation around binding site of α-glucosidase formed stable α-helix and tightened after binding IX and LP, respectively, which helped to elucidate noncompetitive and uncompetitive inhibitory mechanisms. This work demonstrated that two types of prenylated bitter compounds are discrepant in their mechanisms of interaction with α-glucosidase.

Anti-Apoptotic Role of Sanhuang Xiexin Decoction and Anisodamine in Endotoxemia.

Endotoxemia is characterized by initial uncontrollable inflammation, terminal immune paralysis, significant cell apoptosis and tissue injury, which can aggravate or induce multiple diseases and become one of the complications of many diseases. Therefore, anti-inflammatory and anti-apoptotic therapy is a valuable strategy for the treatment of endotoxemia-induced tissue injury. Traditional Chinese medicine exhibits great advantages in the treatment of endotoxemia. In this review, we have analyzed and summarized the active ingredients and their metabolites of Sanhuang Xiexin Decoction, a famous formula in endotoxemia therapy. We then have summarized the mechanisms of Sanhuang Xiexin Decoction against endotoxemia and its mediated tissue injury. Furthermore, silico strategy was used to evaluate the anti-apoptotic mechanism of anisodamine, a well-known natural product that widely used to improve survival in patients with septic shock. Finally, we also have summarized other anti-apoptotic natural products as well as their therapeutic effects on endotoxemia and its mediated tissue injury.

The Underlying Molecular Mechanisms Involved in Traditional Chinese Medicine Smilax china L. for the Treatment of Pelvic Inflammatory Disease.

Smilax china L. (SCL) is extensively used in the treatment of pelvic inflammatory disease (PID). This study aimed to clarify the potential active ingredients of SCL and mechanisms on PID. SCL was widely distributed in Japan, South Korea, and China, which was traditionally considered heat-clearing, detoxicating, and dampness-eliminating medicine. Systems pharmacology revealed that 32 compounds in SCL may interact with 19 targets for immunoenhancement, antiapoptosis, anti-inflammation, and antioxidant activity of the PID model. Molecular docking revealed that isorhamnetin, moracin M, rutin, and oxyresveratrol may have higher binding potential with prostaglandin-endoperoxide synthase 2 (PTGS2), mitogen-activated protein kinase 1 (MAPK1), siderocalin (LCN2), tumor necrosis factor (TNF), and matrix metalloprotein-9 (MMP9), respectively. Molecular dynamics simulation showed that the binding modes of moracin M-MAPK1, rutin-TNF, and oxyresveratrol-MMP9 complexes were more stable, evidenced by relatively smaller fluctuations in root mean square deviation values. Conclusively, SCL may treat PID by inhibiting inflammatory factors, antitissue fibrosis, and microbial growth.

Gallic acid: Pharmacological activities and molecular mechanisms involved in inflammation-related diseases.

Gallic acid (GA), also known as 3,4,5-trihydroxybenzoic acid, is a natural secondary metabolite and widely isolated from various fruits, plants and nuts. In recent years, GA has received increasing attention for its powerful anti-inflammatory properties. The purpose of this review is to clearly illuminate the pharmacological activities and related molecular mechanisms of GA in inflammatory diseases. After consulting a large number of literatures, we made a comprehensive exposition on the chemical characteristics, plant origins, pharmacokinetics and toxicity of GA, especially its pharmacological activities and mechanisms of action. Although the plant source of GA is very rich, its lower extraction rate limits the application of GA in development. It is worth mentioning that GA can not only be separated from many plants, but also be produced in large quantities through biological and chemical synthesis. According to pharmacokinetic studies, the absorption and elimination of GA after oral administration are fast, while the structural optimization or dosage form adjustment of GA is beneficial to increase its bioavailability. Promisingly, toxicity studies have shown that GA scarcely has obvious toxicity or side effects in a variety of animal experiments and clinical trials. The results show that the anti-inflammatory mechanisms of GA mainly involved MAPK and NF-κB signaling pathways. It thus weakens the inflammatory response by reducing the release of inflammatory cytokines, chemokines, adhesion molecule and cell infiltration. Due to its excellent pharmacological activities, GA is expected to be a potential candidate for the treatment of various inflammation-related diseases. This paper will provide theoretical basis for the clinical application of GA and guide the future research and medicinal development of GA.

Virtual Screening Technique Used to Estimate the Mechanism of Adhatoda vasica Nees for the Treatment of Rheumatoid Arthritis Based on Network Pharmacology and Molecular Docking.

Adhatoda vasica Nees (AVN) is commonly used to treat joint diseases such as rheumatoid arthritis (RA) in ethnic minority areas of China, especially in Tibetan and Dai areas, and its molecular mechanisms on RA still remain unclear. Network pharmacology, a novel strategy, utilizes bioinformatics to predict and evaluate drug targets and interactions in disease. Here, network pharmacology was used to investigate the mechanism by which AVN acts in RA. The chemical compositions and functional targets of AVN were retrieved using the systematic pharmacological analysis platform PharmMapper. The targets of RA were queried through the DrugBank database. The protein-protein interaction network (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of key targets were constructed in the STRING database, and the network visualization analysis was performed in Cytoscape. Maestro 11.1, a type of professional software, was used for verifying prediction and analysis based on network pharmacology. By comparing the predicted target information with the targets of RA-related drugs, 25 potential targets may be related to the treatment of RA, among which MAPK1, TNF, DHODH, IL2, PTGS2, and JAK2 may be the main potential targets for the treatment of RA. Finally, the chemical components and potential target proteins were scored by molecular docking, and compared with the ligands of the protein, the prediction results of network pharmacology were preliminarily verified. The active ingredients and mechanism of AVN against RA were firstly investigated using network pharmacology. Additionally, this research provided a solid foundation for further experimental studies.

1H NMR-Based Metabolomics Coupled With Molecular Docking Reveal the Anti-Diabetic Effects and Potential Active Components of Berberis vernae on Type 2 Diabetic Rats.

The dried stem bark of Berberis vernae C.K.Schneid., known as "Xiao-bo-pi" in Chinese, is a representative anti-diabetic herb in traditional Tibetan medical system. However, its anti-diabetic mechanisms and active components remain unclear. In this study, 1H NMR-based metabolomics, biochemistry assay, molecular docking, and network analysis were integrated to evaluate the anti-diabetic effects of B. vernae extract on type 2 diabetic rats, and to explore its active components and underlying mechanisms. Diabetes was induced by high-fat diet and streptozotocin. After 30 days of treatment, B. vernae extract significantly decreased the serum levels of fasting blood glucose, insulin, insulin resistance index, glycated serum protein, TNF-α, IL-1ß, and IL-6, whereas significantly increased the serum levels of insulin sensitivity index in type 2 diabetic rats. A total of 28 endogenous metabolites were identified by 1H NMR-based metabolomics, of which 9 metabolites that were changed by diabetes were significantly reversed by B. vernae extract. The constructed compound-protein-metabolite-disease (CPMD) interaction network revealed the correlation between chemical constituents, target proteins, differential metabolites, and type 2 diabetes. Ferulic acid 4-O-ß-D-glucopyranoside, bufotenidine, jatrorrhizine, and berberine showed good hit rates for both the 30 disease-related proteins and 14 differential metabolites-related proteins, indicating that these four compounds might be the active ingredients of B. vernae against type 2 diabetes. Moreover, pathway analysis revealed that the anti-diabetic mechanisms of B. vernae might be related to its regulation of several metabolic pathways (e.g., butanoate metabolism) and disease-related signal pathways (e.g., adipocytokine signaling pathway). In summary, B. vernae exerts a significant anti-diabetic effect and has potential as a drug candidate for the treatment of type 2 diabetes.

Active Ingredients and Anti-Arthritic Mechanisms of Ba-Wei-Long-Zuan Granule Revealed by 1 H-NMR-Based Metabolomics Combined with Network Pharmacology Analysis.

Ba-Wei-Long-Zuan granule (BWLZ) is a traditional herbal preparation. It has been widely used for the treatment of rheumatoid arthritis (RA). However, its active ingredients and mechanisms of action are still unclear. The present study aims to reveal the active compounds and anti-arthritic mechanisms of BWLZ against collagen-induced arthritis (CIA) by using 1 H-NMR-based metabolomics, molecular docking and network pharmacology methods. After 30 days of administration, BWLZ could effectively improve the metabolic disorders in CIA rats. The anti-arthritic effect of BWLZ was related to its restoration of 16 disturbed serum metabolites. Molecular docking and network analysis showed that 20 compounds present in BWLZ could act on multiple targets. Among them, coclaurine and hesperidin showed the highest hit rates for target proteins related to both metabolic regulation and RA, indicating that these two compounds might be potential active ingredients of BWLZ. Moreover, pathway enrichment analysis suggested that the anti-arthritic mechanisms of BWLZ might be attributed to its network regulation of several biological processes, such as steroid hormone biosynthesis, mTOR signaling pathway, alanine, aspartate and glutamate metabolism, and synthesis and degradation of ketone bodies. These results provide further evidence for the anti-arthritic properties of BWLZ and are beneficial for its quality control and clinical application. The potential targets and biological processes found in this study may provide valuable information for further studying the molecular mechanisms of BWLZ against RA. In addition, our work provides new insights for revealing the active ingredients and regulatory mechanisms of complex herbal preparations.