Hedysarum Multijugum Maxim–Curcumae Rhizoma (HMMCR), a well-known herb pair in traditional Chinese medicine (TCM), has been widely used for the treatment of various cancers. However, the active components of HMMCR and the underlying mechanism of HMMCR for non-small-cell lung carcinoma (NSCLC) remain unclear.via in vitro experiments.Active ingredients of HMMCR were detected by liquid chromatography electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS). On this basis, potential targets of HMMCR were obtained from SwissTargetPrediction database. NSCLC-related targets were collected from four public databases . The drug ingredients–disease targets network was visualized. The hub targets between HMMCR and NSCLC were further analyzed by protein–protein interaction (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Subsequently, the results predicted by network pharmacology were further validated in vitro experiments indicated that HMMCR inhibits the proliferation and migration of NSCLC cells via inactivation of the PI3K/Akt signaling pathway, consistent with the results predicted by network pharmacology.A total of 181 compounds were identified from the aqueous extract of HMMCR. Through network analysis, a compound–target network including 153 active ingredients of HMMCR and 756 HMMCR-NSCLC co-targets was conducted; 6 crucial compounds and 62 hub targets were further identified. The results of KEGG enrichment analysis showed that PI3K/Akt signaling pathway may be the critical pathway of HMMCR in the treatment of NSCLC. The in vitro experiments, this study shows that HMMCR has vital therapeutic effect on NSCLC through multi-compound, multi-target, and multi-pathway, which provides a rationale for using HMMCR for the treatment of NSCLC.Integrating LC-ESI-MS/MS, network pharmacology approach, and  Lung cancer (LC), one of the most frequently diagnosed cancers, remains the leading cause of cancer-related deaths . AccordiAstragalus membranaceus (Fisch.) Bge  and β-elemene (a terpenoid of CR) have been widely used as new drug for the treatment of tumors in China  preparations were widely used in cancer treatment and have unique advantages, especially in reducing the side effects of radiotherapy and chemotherapy, drug resistance, and prolonging the survival of cancer patients –10. Accoch.) Bge . Curcuma Valeton . Numerou pathway . Chengyo pathway . Kaempfe pathway . Curcumo pathway . Moreovein China , 18. Howin vitro experiments. The framework and detailed idea of this study are shown in Network pharmacology, a novel comprehensive analysis tool based on large databases, can help researchers reveal the therapeutic mechanisms of TCM compounds by predicting the potential relationships between drugs, targets, and diseases . The purTwo crude drugs of HMMCR were obtained from the Pharmacy Department of Dongfang Hospital, Beijing University of Chinese Medicine . Hedysarum Multijugum Maxim  were collected from the province of Neimenggu, China; Curcumae Rhizoma  were collected from the province of Guangxi, China. The quality of each crude drugs was strictly ensured according to Chinese Pharmacopoeia to guarantee quality control (http://www.swisstargetprediction.ch/), a public database for ligand-based target prediction of small biologically active molecule, was used to predict the potential targets of HMMCR. We transformed each compound identified by LC-ESI-MS/MS into canonical SMILES through the PubChem (https://pubchem.ncbi.nlm.nih.gov/). Subsequently, these SMILES were imported into SwissTargetPrediction to predict targets of compounds. Species were selected as “Homo sapiens” with probability >0 as the screening condition.Compounds of HMMCR were analyzed using liquid chromatography–mass spectrometry (LC-ESI-MS/MS) system . The identification of unknown compound was performed by Compound discover 3.1, with mzcloud and mzVault databases. SwissTargetPrediction (http://www.genecards.org/), Online Mendelian Inheritance in Man  databases, Therapeutic Target Database , and PharmGkb (https://www.pharmgkb.org/). The overlapped targets among putative targets of the chemical compounds of HMMCR and NSCLC-related targets were considered as the potential targets of HMMCR for non-small cell lung cancer, which was visualized with a Venn diagram. Cytoscape 3.9.0 (https://cytoscape.org/) was applied to establish HMMCR active compounds–NSCLC targets network.The keyword “non-small cell lung cancer” was utilized to collect disease-related targets from the following databases: the GeneCards database (https://string-db.org/), using the overlapping targets among targets of HMMCR active ingredients and NSCLC-related targets, with the species limited to “Homo sapiens” and minimum required interaction score selected as a highest confidence score (0.900). The topological property of each node in the PPI network was evaluated by calculating six parameters with a Cytoscape plugin CytoNCA: “betweenness centrality (BC)”, “closeness centrality (CC)”, “degree centrality (DC)”, “eigenvector centrality (EC)”, “network centrality (NC)”, and “local average connectivity (LAC)”. Subsequently, nodes above twofold median values were selected as key targets and the hub nodes of HMMCR on NSCLC were constructed.PPI network was constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins  <0.05 was considered statistically significant.Gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were conducted in R (version: 3.6.3) using the “ClusterProfiler” package, and The following reagents were used: Cell Counting Kit (CCK-8) assay solution and Cell Cycle Detection Kit ; Bicinchoninic Acid (BCA) Protein Assay Kit and bovine serum albumin (BSA), RIPA cell lysis buffer, and penicillin-streptomycin solution ; Fetal bovine serum ; SuperSignal Chemiluminescent HRP Substrate ; Trypsin-EDTA ; Dulbecco’s minimum essential medium ; antibodies against AKT1, p-AKT, PI3K, E-cadherin, N-cadherin, and β-actin .2.Human NSCLC cell lines NCI-A549 and NCI-H460 were kindly gifted by Professor Zongfang Zheng from Peking University Health Science Center. Cells were cultured in DMEM medium supplemented with 10% fetal bovine serum (FBS) and 100 U/ml of penicillin–streptomycin solution and maintained at 37°C in a humidified incubator with 5% CO3 cells/100μl/well) in 96-well plates were exposed to HMMCR at different concentrations  for 24, 48, and 72 h. Ten microliters of CCK-8 reagent was added to each well, and cells were incubated for 2 h at 37°C and 5% CO2. A microplate reader was used to measure the optical density (OD) at 450 nm of each well.Cell viability was explored using CCK-8 solution. Briefly, A549 cells and H460 cells  in six-well plate were cultured overnight before being exposed to different treatment conditions for 48 h and cultured in complete medium for additional 12 days. Colonies were fixed for 15 min at room temperature in methanol and stained for 15 min in crystal violet.5 cells/2 ml/well) were seeded in six-well plates. After cells were grown to 90% confluence, the cell was scraped lightly with the 200-μl tip of the spear to draw another straight line, perpendicular to the marking line on the back of each well at the center. Subsequently, cells were then rinsed with sterile phosphate-buffered saline (PBS) for three times and cultured with serum-free DMEM medium. The wound healing was observed and photographed at the time point of 0 and 24 h with different concentrations  of HMMCR. Image J Software was used to calculate the migrated distance.Wound healing assay was used to determine the migration of A549 and H460 cells. Briefly, a straight line was marked using a marker pen on the back of the well before cells (4×10g at 4°C for 20 min. Bicinchoninic acid (BCA) method was used to detect the protein concentration. Proteins (25 μg/sample) were separated by sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) and transferred to polyvinylidene fluoride (PVDF) membranes. After blocking in 5% BSA for 1 h at room temperature, the membranes were blotted with primary and secondary antibodies, respectively, then detected by the Enhanced Chemiluminescence Detection Kit. ChemiDoc MP Imaging System and the software Image Lab version were applied to acquire images of the Western blot. Image J Software was used to calculate the grayscale value.Total protein was extracted from A549 and H460 cells challenged with different concentrations  of HMMCR for 48 h. RIPA Cell Lysis Buffer was used to lyse cells on ice for 30 min, followed by centrifuged at 15,000 t-Test was used for differences between the two groups. Differences between multi-groups were assessed by one-way ANOVA. *p < 0.05, **p < 0.01, and ***p < 0.001 indicated statistically significant difference.All results shown in the current study are expressed as mean ± standard deviation (SD). SPSS 21.0 software was used for statistical analysis. HMMCR aquatic extract samples were analyzed by LC-ESI-MS/MS. A total of 181 compounds of HMMCR were detected , 101 cellular component (CC), and 171 molecular function (MF) terms were enriched Figure 6). Meanwhile, the result of colony formation assay demonstrated that HMMCR significantly reduced the colony formation of A549 and H460 cells . These above results indicated that HMMCR can significantly inhibit the proliferation of NSCLC cells in vitro.To explore the effect of HMMCR on NSCLC cell proliferation, viable cell numbers were continuously detected by CCK-8 for 72 h when A549 and H460 cells were challenged with different concentrations of HMMCR . Results showed that HMMCR dose- and time-dependently inhibited the viabilities of A549 and H460 cells -9,12,13-Trihydroxy-15-octadecenoic acid, isokaempferide, and naringenin. The results of hub targets network indicated that 62 hub targets  might be the most important targets of HMMCR for NSCLC. GO enrichment analysis confirmed the biological functions of the 62 hub targets of HMMCR against NSCLC. Furthermore, the results of KEGG pathway enrichment analysis showed that 172 related signaling pathways were obtained; PI3K/Akt signaling pathway may be the critical pathway of HMMCR in the treatment of NSCLC.in vitro experiments were performed to validate the results of network pharmacology. Our results indicated that HMMCR inhibited the viability and migration of NSCLC A549 and H460 cells. Meanwhile, we further detected the key protein expression of PI3K/Akt pathway. Increasing studies demonstrated that PI3K/Akt pathway was involved in the occurrence and development of various malignancies, including colorectal cancer, breast cancer, gastric cancer, and ovarian cancer  predicted by network pharmacology might also be involved in the anti-NSCLC effect of HMMCR, which needs further verification. Despite these limitations, our study provides powerful theoretical basis for using HMMCR in the treatment of NSCLC.Taken together, this is the first time that LC-ESI-MS/MS is used to detect the active compounds of HMMCR and integrate network pharmacology and in vitro experiments validation were utilized to explore the active ingredients of HMMCR and their mechanisms for non-small cell lung cancer. The results of our study demonstrated that HMMCR might inhibit the cell proliferation and reduce the migration of NSCLC cells, mainly via regulating PI3K/Akt signaling pathways. This study provides a rationale for using HMMCR in the treatment of NSCLC.In summary, LC-ESI-MS/MS, network pharmacology and The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Conception and design: SH, KH, and LG. Experimental operation: SH. Manuscript writing and data analysis: SH, MG, and SZ. Manuscript revision: MJ, KH, and LG. All authors contributed to the article and approved the submitted version.This study was supported by grants from National Natural Science Foundation of China (No. 82174458), the Fundamental Research Funds for the Central Universities , and New Innovation Project-Yiqilin Leading Talent Project.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


In this study, we investigated the potential material basis of Yupingfeng powder in the prevention and treatment of 2019 novel coronavirus pneumonia (NCP) by applying molecular docking and molecular dynamic simulation technology.  The active ingredients and predictive targets of Yupingfeng powder were sourced using the TCMSP, ETCM, and TCMIP traditional Chinese medicine databases. NCP-related targets were then acquired from the DisGeNET and GeneCards databases, and common disease-drug targets were imported into the STRING database, and Cytoscape software was used to generate a protein-protein interaction network following the use of a network topology algorithm to identify key target genes. Gene Ontology (GO) and KEGG pathway enrichment analysis was then performed using the target genes and GOEAST and DAVID online tools. The mechanism of Yupingfeng powder in the prevention and treatment of NCP was analyzed with reference to the relevant literature. AutoDock software was used for molecular docking, the preliminary analysis of binding status, and to identify the best conformation. Desmond software was used to perform molecular dynamic simulations for protein and compound complexes, perform free energy calculations and hydrogen bond analysis, and to further verify the binding mode.  Overall, 38 main active components and 218 predictive targets of Yupingfeng powder were identified and 298 disease targets related to NCP were retrieved from disease databases. Yupingfeng powder was found to act predominantly on the TNF, Toll-like receptor, HIF-1, NOD-like receptor, cytokine-receptor interaction, MAPK, T cell receptor, and VEGF signaling pathways. Molecular docking of the three selected key active components with the 3CL-like protease (3CL-Pro) of SARS-CoV-2 showed that they each had a strong binding force and good affinity.  Yupingfeng powder primarily acts on multiple active ingredients and potential targets through multiple action channels and signal pathways. Molecular docking and molecular dynamic simulation technology were used to effectively predict and analyze the potential mechanism by which this Chinese medicine can combat NCP. These results provide a reference for developing new modern Chinese medicine preparations against NCP in the future. HoweLU7 of thAstragalus root , Atractylodes macrocephala , and siler root . This powder can benefit qi, strengthen the surface of the body, and stop perspiration; it has become the classic ancient prescription for strengthening the foundation of life. Modern pharmacological studies have shown that this prescription can play a role in immune regulation and maintain an anti-inflammatory, bacteriostatic, and stable microecological environment. It also exerts antitumor potential, viaa variety of mechanisms, and has a significant effect on repeated upper-respiratory tract infection, influenza, refractory mycoplasma pneumonia, bronchial asthma, and other respiratory diseases [In the present study, we reviewed the prescriptions and performed statistical analysis of the prevention schemes of TCM that have demonstrated clinical curative effects in various provinces and cities in China and found that Yupingfeng powder is the basic prescription for clinical prevention in many TCM schemes. The powder consists of diseases , 8.Given its overall treatment characteristics in relation to multiple targets and the additional and numerous effects of this TCM compound, Yupingfeng powder appears to offer certain advantages and potential for addressing the current pandemic. However, there is a lack of comprehensive and systematic understanding of its active constituents and the molecular mechanisms of action, thus limiting the discovery, application, and promotion of this TCM compound and its preparation for treating NCP. Therefore, in the present study, we identified the key active components and targets of Yupingfeng powder using a combination of molecular docking and molecular dynamic simulation technology. Our aim is to systematically analyze the potential preventive mechanism of the prescription and to further explore potential relationships between the prescription and the disease. Next, we aimed to identify the best matching pattern of drug targets by complementing the spatial structure of active receptor sites. By adopting this approach, we hoped to provide a feasible strategy for basic research, clinical application, and new drug development towards the prevention and treatment of NCP by TCM in the future. Our findings may also advance the promotion of TCM towards globalization, internationalization, and modernization.Astragalus membranaceus, Atractylodes macrocephala, and Saposhnikovia divaricata) as keywords to retrieve all chemical composition information for each herb. Following the pharmacokinetic ADME  parameters recommended in relation to the TCMSP platform, the screening parameters of “oral bioavailability” and “drug likeness” were set at ≥30% and ≥0.18, respectively. Information relating to key active ingredients was collated and combined with herbal compound data obtained from the ETCM and TCMIP databases. A final data list for the compounds was obtained by eliminating any duplicated information. Next, we sourced the target protein information corresponding to the predicted compounds in the database, standardized the target protein name by reference to the UniProt platform, and finally summarized the target data for the compounds as the prediction targets of the main active ingredients of Yupingfeng powder.We used analysis platforms, along with TCMSP, ETCM, TCMIP, and other TCM databases and the names of three herbs  network was then constructed, and the data list, in the form of a tab-separated value (TSV) file, was saved for further analysis.We uploaded the intersecting targets to the STRING network platform and set the protein species to “The TSV data list was imported into Cytoscape, a bioinformatics image-processing software package, and a plug-in was used for the network topology analysis in an attempt to construct a direct or indirect compound or target protein network, thus revealing the effect of Yupingfeng powder for the prevention and treatment of NCP. We analyzed topological parameters such as “degree centrality,” “closeness centrality,” and “betweenness centrality” and selected nodes for which degree centrality was more than twofold higher than the median of the nodes. The selected nodes were then used as key active compounds and targets (hubs).p) and false discovery rate values. The annotated terms were then used to carry out cluster analysis, thus resulting in cluster scores: the higher the scores, the more important the biological processes regulated by the key genes.Gene Ontology (GO) functional enrichment analysis was carried out by using the GOEAST analysis tool; this allowed us to describe the biological process, cellular components, and molecular functions of the gene products. In the present study, we evaluated biological process, cellular components, and molecular function according to statistical probability , along with the length, width, and height (50 × 50 × 50). Finally, molecular docking was performed with AutoDock 4.2 software. The Lamarckian genetic algorithm was used for molecular docking calculations as follows: a population of 150, a maximum energy evaluation of 25 million, a maximum of 2000, a crossover rate of 0.8, and a mutation rate of 0.02. Independent docking was performed 100 times, and the final docking complex structure was evaluated based on the binding free energy. Molecular docking results were visualized by Pymol2.1 software. The action mode of the compound and the target protein was analyzed to identify the nature of the interaction between the compound and the protein residue, including hydrogen bond interaction, π-π interaction, and hydrophobic interaction. Then, by referring to the docking score of the compounds, we considered whether the compounds screened had similar activities to the positive compound.First, we downloaded mol2 files for kaempferol, quercetin, and wogonin from the PubChem database. After minimizing the energy of the downloaded compounds through Chem3D, the small molecule compounds were imported into MGLTools-1.5.6 software and processed to obtain pdbqt files. The 3CLpro  crystal structure was downloaded in PDB format from the Protein Data Bank (PDB). After deleting irrelevant small molecules using Pymol2.1 software, the protein molecules were imported into MGLTools-1.5.6 software to delete water molecules, add hydrogen atoms, set the atom type, and calculate the protein charge; data were then saved as pdbqt files. All processed compounds were used as small-molecule ligands, and the protein targets were used as receptors. The center position of the Grid Box was determined according to the site of interaction for the small molecule and the target (Molecular dynamic (MD) simulations of protein and compound complexes were performed using Desmond version 2020. Here, the molecular force field in the MD simulation was selected as OPLS3e, and the TIP3 water model was used to solvate the system. Charges of the system were neutralized by adding ions. Energy minimization for the entire system was achieved using the OPLS3e force field . The geometric structure of water molecules, the bond lengths, and bond angles of heavy atoms were constrained by the SHAKE algorithm. The continuous system was simulated by applying periodic boundary conditions, and long-range static electricity was maintained using the particle grid Ewald method. An NPT ensemble with a temperature of 300 k and a pressure of 1.0 bar was used to balance the system. The Berendsen coupling algorithm was used for the coupling of temperature and pressure parameters. During the subsequent preparation of the system, a 100 ns operation was performed with a time step of 1.2 fs and a track record was performed every 10 ps, which recorded a total of 1000 frames. The root-mean-square deviation (RMSD) of the main chain atoms was calculated, and graphical analysis was performed to investigate the nature of the protein-ligand interaction.Astragalus, 4 Atractylodes macrocephalae, and 18 fangfeng species. Of these, MOL000033 was found to be a common compound for Astragalus and Atractylodes macrocephala. Furthermore, 714 component-related target protein names were predicted. The names of the target proteins were standardized and corrected using the UniProt platform, and any duplicated information was removed. Following this process, 218 target proteins were identified. In addition, as different active compounds can act on the same target, and different targets may be associated with the same compound, the multicomponent, multitarget, and multilevel characteristics of the Chinese herbal medicines were fully confirmed, as detailed in The active parameter data, along with the absorption-, distribution-, metabolism-, and excretion-related parameter data pertaining to the herbs, were obtained by the interrogation of several TCM databases; duplicated material was deleted. Ultimately, 38 main active ingredients were identified, encompassing 17 By retrieving NCP-related target genes from the DisGeNET and GeneCards databases, merging disease target genes from each database, and deleting duplicate targets, 298 NCP-related target genes were obtained.The predicted targets of the herbal medicines and disease target data were imported using the OmicShare online tool to construct a Venn diagram and identify intersections. Through this process, 51 common targets were obtained, comprising related targets of Yupingfeng powder acting on disease. As illustrated in To better understand the mechanisms of Yupingfeng powder in relation to NCP, the 51 intersecting targets were imported into the STRING platform to generate a PPI network map and a TSV data list. There were 51 PPI targets in the network, and the 384 edges represent the PPI relationship. The mean node degree value of each node in the network was 15.1, and the mean local clustering coefficient was 0.641, as shown in The TSV list was imported into Cytoscape software, and network topology analysis was carried out. There were 49 nodes and 384 relationship edges in the network. Network topology analysis showed that the network density value was 0.055, the network concentration was 0.506, the network heterogeneity was 1.519, and the median value was 4.506. Then, we identified the key compounds and targets with nodes larger than 9.012. Note that the core node was used as the connection compounds or targets; thus, core nodes play an important role in the whole network. In our analysis, three key compounds and six key targets were identified, showing that Yupingfeng powder has great potential as a key compound or target and could play an important role in the prevention and control of NCP. Of these, the key compounds were MOL000098 (quercetin), MOL000173 (wogonin), and MOL000422 (kaempferol), which can interact with 62, 151, and 45 target proteins, respectively. The key targets were PTGS2, DPP4, PTGS1, NOS2, PPARG, and NOS3; these could interact with 32, 20, 17, 15, 12, and 10 compounds, respectively. These results indicate that there is synergism between the effective components of Yupingfeng powder and that the key targets also play a certain therapeutic role in the development of NCP, as detailed in p < 0.01 as the significant enrichment screening standard, 82 functional enrichments were identified. Moreover, the first 20 major GO functional enrichment analysis results involved 15 significant enrichments to biological processes, encompassing inflammatory response, cellular response to lipopolysaccharide, extrinsic apoptotic signaling pathways in the absence of a ligand, positive regulation of transcription from the RNA polymerase II promoter, response to drugs, negative regulation of the apoptosis process, immune response, the lipopolysaccharide-mediated signaling pathway, positive regulation of angiogenesis, positive regulation of transcription, DNA-templated, positive regulation of nitric oxide biosynthesis, positive regulation of gene expression, angiogenesis, and cellular response to organic cyclic compounds. Significant enrichment was observed in relation to cell composition, mainly involving extracellular levels. There was also enrichment pertaining to several molecular functions, mainly involving identical protein binding, cytokine activity, enzyme binding, and protein binding. The results of GO enrichment analysis are depicted in The 51 intersecting targets were mapped to the GOEAST platform for enrichment analysis of the related biological processes, cellular components, and molecular functions. Using p < 0.01, the top 20 major enrichment signal pathways were encapsulated in a bubble chart. We found that 12 signaling pathways were involved in related diseases, while the other eight signal pathways involved TNF, Toll-like receptor, HIF-1, NOD-like receptor, cytokine–receptor interaction, MAPK, T cell receptor, and VEGF signaling pathways. All signaling pathways overlapped with the key target enrichments related to Yupingfeng powder. These results suggest that the effective components of Yupingfeng powder may act on multiple signaling pathways to treat NCP, a finding that suggests an important direction for future research on Yupingfeng powder in the prevention and treatment of NCP , six key targets , and eight important signal pathways  involved in the action of Yupingfeng powder on NCP. We also identified that some signaling pathways were enriched and overlapped with the key targets related to Yupingfeng powder. Molecular dynamic simulations showed that kaempferol, quercetin, and wogonin could form stable complexes with the 3CLpro protein. This study not only clarified the efficacy of the mechanistic action of Yupingfeng powder; it also revealed the therapeutic effects of prescription drugs on NCP through multichannel and multiple approaches aimed towards intervention and regulation. It is hoped that this study will stimulate additional research concerning new targets and new pathways within the herbal medicine field, as well as further exploration of the mechanistic actions of various herbal medicines in respect of the observed synergistic effect, thereby providing innovation and facilitating the development of TCM. In the present work, the molecular mechanisms of a natural herbal medicine were investigated, and its complex mechanism was revealed at the molecular level, thus providing a theoretical basis for specific research and the development of natural and antiviral Chinese herbal medicines for clinical application. Furthermore, our findings confirm that the clinical application of TCM is recommended as the main entry point for prevention, to benefit from the proven advantages of both Chinese herbal medicine and Western medicine, and as a strategy for multidisciplinary combination therapy towards the prevention and control of NCP.


R,S-MXL hydrochloride. The aim of the current study was the development of a new, fast, and efficient method for the chiral separation of MXL enantiomers using capillary electrophoresis (CE) and cyclodextrins (CDs) as chiral selectors (CSs). After an initial CS screening, using several neutral and charged CDs, at four pH levels, heptakis-2,3,6-tri-O-methyl-β-CD (TM-β-CD), a neutral derivatized CD, was chosen as the optimum CS for the enantioseparation. For method optimization, an initial screening fractional factorial design was applied to identify the most significant parameters, followed by a face-centered central composite design to establish the optimal separation conditions. The best results were obtained by applying the following optimized electrophoretic conditions: 60 mM phosphate buffer, pH 5.0, 50 mM TM-β-CD, temperature 20 °C, applied voltage 30 kV, hydrodynamic injection 50 mbar/s. MXL enantiomers were baseline separated with a resolution of 1.52 during a migration time of under 5 min; S-MXL was the first migrating enantiomer. The method’s analytical performance was verified in terms of precision, linearity, accuracy, and robustness (applying a Plackett–Burman design). The developed method was applied for the determination of MXL enantiomers in pharmaceuticals. A computer modeling of the MXL-CD complexes was applied to characterize host–guest chiral recognition.Mexiletine (MXL) is a class IB antiarrhythmic agent, acting as a non-selective voltage-gated sodium channel blocker, used in therapy as a racemic mixture  Mexiletine (MXL) [1-propan-2-amine], is an antiarrhythmic agent belonging to class IB antiarrhythmics that acts at the sodium channel level. It reduces ventricular cardiac automaticity by shortening the potential of action and refractory period .R-MXL and S-MXL. It is used in therapy as the racemic mixture R,S-MXL, which is usually used as a hydrochloride salt [Structurally MXL is a primary amine, the 2,6-dimethylphenyl ether of 2-aminopropan-1-ol, and has in its structure a chiral center that generates the existence of two enantiomers, ide salt . The cheR-(-)-MXL shows higher antiarrhythmic activity than S-(+)-MXL, in terms of sodium channel blocking, membrane stabilization, and a reduction in cardiac excitability [R-MXL binding to human serum proteins is significantly higher than that of the binding of S-MXL [R-MXL is higher than that of S-MXL; while the AUC (area under the plasma concentration versus time curve) of S-MXL is significantly higher than that of R-MXL [S-MXL, while the aliphatic hydroxylation predominates for R-MXL [p-hydroxy-MXL and their corresponding alcohols, hydroxymethyl-MXL-alcohol, and p-hydroxy-MXL-alcohol. CYP2D6 mediated aromatic and aliphatic hydroxylation is enantioselective; in vivo studies have suggested that a noncytochrome P450 enzyme also plays a role in the stereoselective disposition of MXL [tability ,6. Moreoof S-MXL . The renof R-MXL . MXL undor R-MXL . MXL undn of MXL . Based oCapillary electrophoresis (CE) is a powerful and effective technique for the enantioresolution of pharmaceuticals and is being considered today as an alternative and complementary method to the more widely used high-performance liquid chromatographic (HPLC) methods. The advantages of using CE for the chiral separation of pharmaceuticals are related to the high separation efficiency, short analysis time, and relatively low operational costs, taking into consideration the reduced consumption of chemicals ). Moreover, in CE, usually a direct chiral separation is used simply by adding the CS to the background electrolyte (BGE) ,12.Several CSs are available in CE (cyclodextrins (CDs), macrocyclic antibiotics, proteins, crown ethers, etc.); however, the most efficient and frequently used by far are the CD derivatives. Today there are a large number of CD derivatives available as CSs in CE, including native and derivatized as well as neutral and ionized ones. The advantages of using CDs as CSs are related to the high complexation capacity towards many pharmaceuticals, relatively good solubility in aqueous BGE, low UV absorption, and commercial availability ,14.CD derivatives have established themselves as CSs in CE because of their ability to interact stereoselectively with many chiral analytes via intermolecular interactions, which generate complexes with different mobilities than the uncomplexed analyte. CD-based enantiorecognition methods are difficult to characterize because guest molecules may interact with CD macrocycles by inclusion in the CD hydrophobic cavity, but CD–guest interactions may also involve the exterior surface of the CD. Several variables can influence CD conformation and recognition ability, including CD structure, as well analyte structure, and separation medium characteristics . IntensiTraditionally, for analytical method development, the “one-factor-at-a-time” (OFAT) strategy was used, in which one analytical parameter is varied while the others are maintained at a constant; however, this technique has some limitations. The use of design of experiments (DoE) in analytical method development involves multifactorial experiments that lead to optimized solutions by performing the minimum required experiments. DoE is also used to establish factor-response relationships which further helps in identifying the most significant parameters by saving time, effort, and operational costs ,18.Based on an extensive literature review, we found only one article describing a chiral separation method by CE of MXL enantiomers using CDs as the CS, published in 1998 by Kang and Ou. In this study, MXL enantiomers were baseline separated using heptakis-2,3,6-tri-O-methyl-β-CD (TM-β-CD) as CSs and a 40 mM tris–phosphoric acid BGE at pH 2.5. Baseline separation was achieved with a resolution of 2.2 and a migration time of over 12 min; however, the method was developed using the OFAT approach, and no validation studies were made [p-hydroxy-MXL) using a phosphate BGE at pH 7.0 and 2% S-β-CD as the CS. MXL and its metabolites are protonated at pH 7.0, where the analysis was conducted; therefore, the electrostatic interaction with the negatively charged CD may explain the enantioresolution [Bonato et al. used MXL together with other basic drugs as model substances  to verify the enantioselective capacity of sulfated-β-CD (S-β-CD), alone or in dual CS systems. The method was applied for the enantioseparation of MXL and its main metabolites  in combination with a partial filling technique. Separation was performed at pH 7.4, at which MXL is positively charged and migrates towards the cathode, whereas both HSA and PSA migrated towards the anode, contrary to the electroosmotic flow (EOF). After evaluation of the chiral interactions, HSA showed higher selectivity for MXL over PSA . Xu et aS,S)-O,O’-di-p-toluoyl tartaric acid anhydride [S)-naproxen [S)-(-)-(N)-trifluoroacetyl-prolyl chloride, (1S)-(-)-camphanic chloride [l-alanine amide) [R)-(-)-3,5-dinitrobenzoylphenylglycine) [Several direct and indirect HPLC methods were published for the chiral separation of MXL enantiomers. For MXL enantioseparation through an indirect approach, several chiral derivatizing reagents have been used: Sanger reagent  , -Onhydride , (S)-napnaproxen ,25, cyannaproxen , (S)-(-)chloride , and Mare amide) ,28. MXL glycine) , Chiralpglycine) ,31, and glycine) ,33.Taking the data published in the literature into consideration, our aim was to develop a new, fast, and efficient method for the chiral separation of MXL enantiomers by CE using CDs as chiral selectors and applying DoE strategies for method optimization.MXL is a primary amine with a pKa value of 9.14 and, consequently, is positively charged in an acidic medium . To evalThe migration times decreased while increasing the pH of the BGE solution; however, at pH values over 7.0, MXL migrates close to or even together with EOF due to low ionization of the analyte in basic BGE.The initial CD screening was performed in a 50 mM phosphate BGE at four pH levels  by adding 10 mM neutral CDs -β-CD-DM-β-CD, heptakis-β-CD-TM-β-CD) and 5 mM ionized CDs , respectively, in the BGE. In the case of charged CDs, lower concentrations were used than in the case of neutral ones to avoid an elevated current in the capillary.Chiral interactions were observed between MXL and two neutral CD derivatives: heptakis 2,3,6-tri methoxy-β-CD (TM-β-CD), heptakis 2,6-di methoxy-β-CD (DM-β-CD) at pH levels 2.5 and 5.0. The initial chiral resolutions were higher for TM-β-CD, as in the case of DM-β-CD only a small peak splitting was observed. Moreover, the chiral resolutions were higher at pH 5.0 in comparison with pH 2.5 for both CDs. Based on the resolution, peak amplitude, and peak shapes, TM-β-CD was chosen as the optimal CS for further method development at pH 5.0.The preliminary results confirm the supposition of Kang and Ou , as methTM-β-CD is a neutral derivatized CD without own electrophoretic mobility; consequently, the electrophoretic mobility of the MXL-TM-β-CD complex will be influenced by the ionization of MXL.k design into a 2k − p design, where k is the total number of factors introduced in the design, while p is the size of the fraction [Screening designs are used as the first step in the optimization of an analytical method because they allow the analysis of many factors with a relatively small number of experiments. A fractional factorial design was applied, by fractionating a full factorial 2fraction ,18.6 − 3 = 23 = 8 experiments with four center point replicates that generated a matrix with 12 experiments. Replicated center point experiments can be used to estimate the experimental error and to assess the curvature of the model. All parameters were varied from the mean value on a specific range with a lower and a superior value, and the monitored responses were the chiral resolution (R) and migration times of the second migrating enantiomer (t). An overview of the experiments and the results obtained in the factorial screening design is presented in In our study, six experimental parameters were taken into consideration: BGE concentration, BGE pH, CD concentration, temperature, voltage, and injection pressure. We performed a fractional design with 2In the initial stage of DoE, screening designs are frequently used to identify the significant input factors and exclude the less significant ones. Therefore, an initial regression model is constructed, and then the significance of the model coefficients is determined. This can be performed by using graphical and/or statistical methods.As a graphical tool, Pareto charts were used to identify the most significant parameters on the chiral discrimination of the MXL enantiomers; CD concentration, BGE concentration, and injection pressure had a significant influence on chiral resolution, while voltage, BGE concentration, and CD concentration had a pronounced effect on migration times.The analysis of variance (ANOVA), performed as a statistical evaluation of the regression model, delivered the same results as those obtained by the graphical approach. The insignificant factors were removed one by one to improve the model, and the following regression equations were obtained:In accordance with the results obtained in the fractional factorial screening step, BGE concentration, CD concentration, and voltage were chosen as factors that significantly interfere with MXL enantioseparation and were further taken into consideration in the optimization design. The three other factors were kept constant: BGE pH—5.0, temperature—20 °C, injection pressure—50 mbar/s.A face-centered central composite design (FCCD) with three variables was used for method optimization based on the results of the screening design. The same experimental responses were monitored as in the screening design: chiral resolution (R) and migration time of the second migrating enantiomer (t). The FCCD matrix consisted of 15 experiments with five center points. Experiments were performed in random order to avoid systematic errors. An overview of the experiments and results obtained in the FCCD is presented in An initial quadratic regression model, including linear, interaction, and second order terms, was applied, and the ANOVA was performed to identify the statistically significant model terms. The factors considered insignificant were removed one by one. In the case of chiral resolution, as initially predicted through the factorial screening design, voltage did not represent a significant factor and was completely removed from the equation.The following recalculated regression equations were obtained, after insignificant parameter reduction:2R, 2adjR, and 2predR) were followed as performance indicators. According to the values 2R 0.9381 and 2adjR 0.9132 for R and 2R 0.9986 and 2adjR 0.9960 for t, respectively, both models fit the experimental results. Moreover, 2predR was in reasonable agreement with 2adjR .During regression model adjustment, the values of three types of determination coefficients  is statistically significant  in favor of R-MXL-CD complexes. The average binding constant (Kb) is higher in the case of the complex formed with R-MXL than with S-MXL (1.58 ± 0.57 mM and 1.48 ± 0.54 mM).Calculation with 1:1 MXL-CD stoichiometry provided an appropriate free binding energy (ΔG) to conclude the formation of inclusion complexes between the host and guest molecules in all 2 × 100 configurations analyzed, with an average ΔG value of −3.92 ± 0.201 kcal/mol for the R-MXL-CD complex.Regarding the conformation of the most stable complexes, the propan-2-ammonium moiety of MXL is oriented to the narrower end of the TM-β-CD cone. A hydrogen bond is formed between the oxygen in the glucopyranose unit of the TM-β-CD as a hydrogen bond acceptor and one of the hydrogens in the ammonium moiety of MXL with a length of 2.109 Å and an angle of 143.89° in the case of the In the case of the S-MXL-CD complex, a hydrogen bond is identified by the used software, linking the oxygen at the 6-O-methyl part of the TM-β-CD and the ammonium moiety of MXL with a length of 1.842 Å and an angle of 130.05° .S-MXL, and the second migration enantiomer as R-MXL, respectively. Taking the complexity of the chiral separation mechanism in CE into consideration, in addition to the stability of the enantiomer–CD complexes, other parameters could also influence the migration order as differences in the electrophoretic mobility of the complexes. The migration order established by molecular docking was in accordance with the experimental results.Other types of energies, such as van der Waals force, electrostatic, and desolvation potentials, hold the guest and host molecules together. Based on the data obtained from the docking study, the first migrating enantiomer could be identified as The analytical performance of the CE method developed for MXL enantioseparation has been verified in terms of precision and reproducibility (intra-day and inter-day), linearity, accuracy, and robustness.Intra-day precision was determined by injecting a sample of 0.15 mg/mL racemic mixture of MXL six times on the same day, while inter-day precision was determined by injecting a sample of the same concentration six times on three consecutive days. Relative standard deviations (RSDs) were calculated for the migration times, peak area, and peak height for both enantiomers.n = 3) at nine different concentrations over a specific concentration range (0.015–0.3 mg/mL). Correlation factors of 0.9998 for both enantiomers demonstrate the good linearity of the method.Calibration curves were obtained by measuring standard solutions (The limit of detection (LOD) and limit of quantification (LOQ) were estimated as follows: the standard deviation of the regression equation reported to the regression equation’s slope multiplied by 3.3 for the LOD and by 10 for the LOQ.Recovery experiments utilizing the common standard addition technique were carried out to evaluate the method’s accuracy. An appropriate amount of MXL capsule powder was weighed and spiked with a quantity of MXL standard; each sample was examined in triplicate. The good recovery values demonstrate good method accuracy.The data obtained for precision, linearity, and accuracy testing is presented in To verify the method robustness, a Plackett–Burman design was applied. Plackett–Burman designs are unique forms of two-level fractional factorial designs that permit the investigation of up to N-1 input variables using N experiments ,18. The The optimized method was applied for the determination of MXL enantiomers from a pharmaceutical product; capsules with a concentration of 100 mg MXL were used for the determination. The concentrations of the two enantiomers were determined using the optimized CE method and agreed with the composition of a racemic mixture with a 1:1 enantiomer ratio .A rapid, simple, and cost-effective method was developed for the chiral separation MXL enantiomers by CE using CDs as the CS. Based on a complex CD screening, TM-β-CD, a derivatized neutral CD, was chosen as the optimal CS, and was added in a phosphate BGE at pH 5.0 for the enantioseparation.An initial screening fractional factorial design was applied to identify the significant parameters that interfere with the enantioseparation. The significance ranking of analytical parameters was performed using Pareto charts as well as the ANOVA; BGE concentration, CD concentration, and voltage were chosen as significant factors to be introduced in the optimization design. For the method optimization, an FCCD was applied, and three levels were varied for each studied parameter. Baseline chiral separation of the MXL enantiomers was achieved with a chiral resolution of 1.52 and a migration time of under 5 min.The analytical performance of the method was evaluated in terms of precision, reproducibility, linearity, accuracy, and robustness by applying a Plackett–Burman DoE. The applicability of the method was verified by determining the ratio of the two enantiomers from a pharmaceutical product (capsules).The chiral discrimination mechanism was elucidated by applying molecular modeling calculations; the migration order of the enantiomers was in accordance with the one obtained experimentally.Compared with the previously published method of Kang and Ou , our metR-MXL hydrochloride  was used in the analysis. The following analytical grade reagents were used: phosphoric acid 85%, disodium hydrogen phosphate , monosodium hydrogen phosphate , sodium hydroxide , and methanol . Deionized water was prepared by using a Milli-Q apparatus .A pharmaceutical-grade racemic mixture of MXL hydrochloride  and pure enantiomer The following CDs were used as the CS in the screening process: neutral natural CDs—α-CD, β-CD, γ-CD ; neutral derivatized CDs—hydroxypropyl-β-CD (HP-β-CD) , methylated β-CD (M-β-CD) , heptakis-β-CD (DM-β-CD), and heptakis-β-CD (TM-β-CD) ; ionizable derivatized anionic CDs—carboxymethyl-β-CD (CM-β-CD), sulphated β-CD (S-β-CD) , and sulphobutylter-β-CD (SBE-β-CD) .To determine the concentration of enantiomers in pharmaceutical products, Mexitil 100 mg capsules  were used.The determinations were performed on an Agilent 1600 CE system  equipped with DAD (diode array) detector. For the separations, a silica capillary of 48 cm length (effective length 40 cm) and an internal diameter of 50 µm  was used. Chemstation 7.01 software  was used for electropherogram processing. The pH of the solutions was determined on a Terminal 740 pH meter .The method’s analytical performance was verified using Microsoft Excel 365 software , while the DoE optimization was carried out using Design Expert 7.0 software .R-MXL and S-MXL) and the host molecule (TM-β-CD) results in a different migration time. The 2D coordinates of MXL and TM-β-CD were imported from PubChem database, and the 3D structure was built and geometrically optimized at the protonation state, which correspond to pH = 5, used at the chiral separation under the optimized conditions , using the HyperChem 8.0 software  and saved in mol format. Using the OpenBabelGUI 3.1.1 interface, the mol files were converted into the pdb format. Molecular docking simulations with AutoDock 4.2.6  were performed using default parameters, considering flexible MXL and rigid TM-β-CD. Grid boxes, with dimensions of 50 × 50 × 50 Å and a grid spacing of 0.375 Å, were placed where MXL occupied the center of the box. The number of the Lamarckian genetic algorithm was set to 1000 runs [To estimate the migration order for the two enantiomers, a molecular docking study was performed, considering that the difference in binding energy between the guest molecules /(w1 + w2), where t1 and t2 represent the migration times, and w1 and w2 represent the peak widths of the two optical isomers.To evaluate the analyte–CS interactions, the separation factor and resolution were taken into consideration. The separation factor (α), was calculated from the ratio of the migration times of the two enantiomers, while the resolution was calculated based on the formula: R = 2 was dissolved in methanol, homogenized in the ultrasonic bath for 5 min, and diluted with methanol to the appropriate concentrations. Electrophoretic conditions were the same as those used in the chiral analysis of the standard.


We hypothesize that a cancer with an activated druggable cancer-specific pathway (DCSP) is more likely to respond to the relevant drug. Here we develop and validate a systematic method to search for such DCSPs, by (i) introducing a pathway activation score (PAS) that integrates cancer-specific driver mutations and gene expression profile and drug-specific gene targets, (ii) applying the method to identify DCSPs from pan-cancer datasets, and (iii) analyzing the correlation between PAS and the response to relevant drugs. In total, 4,794 DCSPs from 23 different cancers have been discovered in the Genomics of Drug Sensitivity in Cancer database and validated in The Cancer Genome Atlas database. Supporting the hypothesis, for the DCSPs in acute myeloid leukemia, cancers with higher PASs are shown to have stronger drug response, and this is validated in the BeatAML cohort. All DCSPs are publicly available at  Cancer is the second leading cause of deaths and was responsible for 9.6 million deaths worldwide in 2018. Approximately 1 in 6 deaths is due to cancer ) are significantly higher than those of the groups of different pathways or both drugs and pathways , indicating that quizartinib is more closely linked to the Martens–PML–RARA pathway compared to the other pathways. Compared to the group of the same pathway but different drugs, this DCSP also has significantly higher PASs (P < 1e-4). Similar results are also observed for the other DCSPs of AML. The details are provided in Fig. To investigate the hypothesis that cancers with activated druggable cancer-specific pathways are more likely to respond to the relevant drugs, we have introduced PAS and applied it to conduct a systematic search of druggable cancer-specific pathways in 23 cancers from the GDSC cohort. The DCSPs of these cancers are then validated in the TCGA cohort. In support of the hypothesis, we observe a significant correlation between higher PAS and stronger drug response among the DCSPs identified in AML and validate this in the BeatAML cohort. All results are provided in an interactive website available to users.PAS is defined to capture the druggability of a pathway for an individual cancer. In principle, this information can be used to build a model for predicting drug responses of tumors in precision medicine. Current models often apply black-box statistical and machine learning methods to multiple omics data to predict responses of a single drug (monotherapy) or combination of drugs (drug synergy) ,34. ThisThis study has been conducted using the rich resources; however, the data still have some weaknesses. First, information on drug target genes is often incomplete, and off-target genes are generally unknown. We collect the target gene list provided from the GDSC cohort and extend with the curated information from the DrugBank database . RecentlTo achieve the weights for PAS using the interaction between driver genes, pathway, and drug target genes, we utilize the network enrichment analysis (NEA) . BrieflydAF is the number of connected links between AGS and FGS, and AF are the mean and standard deviation of dAF, respectively, which are estimated on a randomized network under the null hypothesis. Thus, for each PAS, we collect 3 corresponding z scores expressing the overrepresentation of drug target genes on cancer driver genes (z1), driver genes on pathway genes (z2), and target genes on pathway genes (z3) based on the functional gene network. Finally, these 3 enrichment scores are then converted into normal probability scores , which are used as the weights for PAS.In the current application, NEA is applied for 3 pairs of gene sets, including driver genes, pathway genes, and drug target genes. For each pair, 1 gene set is selected for FGS and the remaining gene set is for the AGS. In particular, FGS is assigned for the set of drug target genes in  and  while for , the driver genes are used for FGS. Finally, NEA simplifies the assessment of the functional connectivity by defining an enrichment score asDi, a pathway Pj is considered as specific to a cancer Cz, that is, DCSP, if the pathway overactivates in that cancer while activation scores of this pathway in other cancers are not significantly different from each other , the standard method only ensures that a cancer is different from the rest, but the remaining cancers might be different from each other. Therefore, in this case, the specificity of the pathway for the remaining cancers is not guaranteed. To identify the DCSPs, we apply a 2-statistic approach originally developed in a recent study [t-test (T1) for comparing between that cancer and the rest and (ii) a χ2 statistic (T2) for jointly comparing the remaining cancers.Given a drug see Fig. . The issnt study  for the tstatistic for T1 and a small χ2 statistic for T2. To account for multiple testing, the FDRs [T1 are calculated, and we keep DCSPs with FDR <0.01. We further keep only DCSPs whose χ2 statistics are within the first quartile. Finally, we apply the following sample size conditions: (i) for each DCSP, the number of samples for each supporting cancer is larger than 5, and (ii) it is supported by at least 3 cancers.For an activated pathway that is cancer specific, we expect a large the FDRs  of T1 arPj mediates the response to drug Di in cancer Cz; statistically, this is the case if the pathway activity of DCSP correlates with the drug response. Fig. Di, Pj, Cz), we first apply the normal score transformation on both PAS and drug sensitivity (AUC) of the tumors in cancer Cz. Subsequently, we calculate the Pearson correlation between PAS and AUC as cor. Here, 2 versions of PAS for upstream and downstream activation are used to compute cor. The PAS of the upstream version is defined as PAS = PASu – PASd, while for the downstream version, PAS = PASd – PASu. As activation, only positive values are considered.Our hypothesis is supported if the pathway We use the GDSC cohort as the discovery set. Validation sets have been obtained from the following sources: (i) TCGA cohort, (ii) Therapeutically Applicable Research to Generate Effective Treatments (TARGET) cohort, and (iii) BeatAML cohort.The GDSC project  has beenThe drug data from the GDSC cohort (version 17.3) contain a total of 224,202 cell line–drug experiments from 251 drugs and 1,065 cell lines. We use only 125,894 monotherapy profiles of 684 cell lines from 23 cancers after removing the profiles with more than 1 replicate. The number of cell lines of a cancer ranges from 6 to 64; AML has 28 cell lines. The potential driver genes of the samples, including mutations and fusion genes, are collected from Depmap Portal . We keepTCGA  is led be − 2 in more than 50 and AUC are also collected. The data consist of 47,650 records from 528 patients with AML.BeatAML  is an onThe results of this study are available on the DCSP website .GigaScience respository, GigaDB [The implementations of the PAS generation and the shiny application are available on the DCSP website . All rel, GigaDB .Supplementary Table S1. List of 23 cancers of the GDSC cohort using in this study. Note that COAD and READ in the TCGA cohort are combined together to be consistent with the GDSC cohort.Supplementary Table S2. The DCSPs discovered from the GDSC cohort and the TCGA cohort across 23 cancers. The validated DCSPs are the DCSPs identified in the GDSC cohort and rediscovered in the TCGA cohort. The last column presents the proportion of validated DCSPs (PV) in the TCGA cohort.Supplementary Table S3. List of 28 DCSPs responding to anticancer drugs in the GDSC cohort and the BeatAML cohort.Supplementary Table S4. PAS of pathway Pj treated by drug Di in comparison with PASs of following 3 groups: (i) same pathway but different drugs  across 23 cancers and (B) AML.Supplementary Fig. S2. The proportion of identified DCSPs for individual diseases.Supplementary Fig. S3. PASs of Martens–PML–RARA druggable by quizartinib in the (A) GDSC cohort and (B) TCGA cohort. The orange box plots represent PAS of AML, and the green ones represent PASs of other cancers.Supplementary Fig. S4. The rediscovery rate (RDR) of DCSPs in terms of the association between PAS and drug sensitivity in AML. RDR is the proportion of the top DCSPs identified in the GDSC cohort that is significant in the BeatAML cohort. Here, PAS is defined as PASd − PASu, so a higher value of PAS indicates a higher activation of the downstream part than the upstream part. (A) RDR of DCSPs with negative correlations and (C) RDR of DCSPs with positive correlations. The horizontal dashed lines present the P value target lines (0.05 and 0.01). The RDRs follow the null target lines (0.05 and 0.01), that is, null results, indicating that there is no evidence of drug response when the pathway has higher activation downstream rather upstream of the drug targets.u/d: pathway activation score for up/downstream activity; RDR: rediscovery rate; TARGET: Therapeutically Applicable Research to Generate Effective Treatments; TCGA: The Cancer Genome Atlas; TPM: transcript per million.AGS: altered gene set; AML: acute myeloid leukemia; APL: acute promyelocytic leukemia; AUC: area under the curve; DCSP: druggable cancer-specific pathway; FDR: false discovery rate; FGS: functional gene set; GDSC: Genomics of Drug Sensitivity in Cancer; GSEA: gene-set enrichment analysis; NEA: network enrichment analysis; PAS: pathway activation score; PASThe authors declare no competing interests.This work was partially supported by funding from the KI Research Foundation, the Swedish Research Council (VR), and the Swedish Foundation for Strategic Research (SSF).TNV and YP initiated and oversaw the study. QTT, TNV, and YP contributed to method development and manuscript writing. QTT, TZ, and TNV performed the bioinformatics analysis and webpage development with input from YP.giac091_GIGA-D-22-00079_Original_SubmissionClick here for additional data file.giac091_GIGA-D-22-00079_Revision_1Click here for additional data file.giac091_GIGA-D-22-00079_Revision_2Click here for additional data file.giac091_GIGA-D-22-00079_Revision_3Click here for additional data file.giac091_Response_to_Reviewer_Comments_Original_SubmissionClick here for additional data file.giac091_Response_to_Reviewer_Comments_Revision_1Click here for additional data file.giac091_Response_to_Reviewer_Comments_Revision_2Click here for additional data file.giac091_Reviewer_1_Report_Original_SubmissionJing Tang -- 5/17/2022 ReviewedClick here for additional data file.giac091_Reviewer_1_Report_Revision_1Jing Tang -- 8/2/2022 ReviewedClick here for additional data file.giac091_Reviewer_2_Report_Original_SubmissionSebastian Vosberg -- 5/19/2022 ReviewedClick here for additional data file.giac091_Reviewer_2_Report_Revision_1Sebastian Vosberg -- 7/29/2022 ReviewedClick here for additional data file.giac091_Supplemental_FileClick here for additional data file.


Sulfoquinovose  is a sulfo-sugar with a ubiquitous distribution in the environment due to its production by plants and other photosynthetic organisms. Bacteria play an important role in degradation of SQ and recycling of its constituent sulfur and carbon. Since its discovery in 1963, SQ was noted to have a structural resemblance to glucose-6-phosphate and proposed to be degraded through a pathway analogous to glycolysis, termed sulfoglycolysis. Studies in recent years have uncovered an unexpectedly diverse array of sulfoglycolytic pathways in different bacteria, including one analogous to the Embden–Meyerhof–Parnas pathway (sulfo-EMP), one analogous to the Entner–Doudoroff pathway (sulfo-ED), and two involving sulfo-sugar cleavage by a transaldolase (sulfo-TAL) and transketolase (sulfo-TK), respectively, analogous to reactions in the pentose phosphate (PP) pathway. In addition, a non-sulfoglycolytic SQ degradation pathway was also reported, involving oxygenolytic C-S cleavage catalyzed by a homolog of alkanesulfonate monooxygenase (sulfo-ASMO). Here, we review the discovery of these new mechanisms of SQ degradation and lessons learnt in the study of new catabolic enzymes and pathways in bacteria. S. SE. colulfo-ED) A 20,21],21E. colulfo-ED) B, and a ulfo-ED) C 22]. I. IE. colulfo-ED)  22,23]..E. coli,Here we review the enzymes and pathways involved in SQ degradation in different bacteria. A recent comprehensive review by Snow et al. includes detailed descriptions of the structures and mechanisms of enzymes in the sulfo-EMP and sulfo-ASMO pathways, pre-sulfoglycolytic enzymes including sulfolipase and sulfoquinovosidase involved in release of SQ from SQDG, and an analysis of the energy balance and carbon flux of the different pathways . Here, wE. coli yih gene cluster . T. TE. col to DHPS , which iArthrobacter spp. and related Actinobacteria was recently reported, involving gene clusters encoding orthologs of YihS, YihV and YihT ..P. putidBacillus megaterium DSM 1804 ..+-dependE. coli phosphofructokinase isozyme PfkA), and then cleaved into DHAP and SLA by SF-1P aldolase SqiA . The sulfo-EMP2 pathway is present in Gram-positive Firmicutes bacteria. Similar to the sulfo-TAL pathway, the SLA is oxidized to SL in the aerobic Bacilli and reduced to DHPS in the anaerobes like Megamonas rupellensis , similar to the sulfo-TAL and sulfo-TK pathways. SF is then phosphorylated to SF-1P by the SF kinase SqiK  . I. I(R)-surylation B.2S [With the exception of the sulfo-SMO pathway, the other SQ degradation pathways do not involve cleavage of the inert sulfonate C-S bond and are accompanied by formation of a sulfonate by-product. The sulfo-EMP(2), sulfo-ED and sulfo-TAL pathways produce a C3 sulfonate by-product (DHPS or SL), while the sulfo-TK pathway produces a C2 sulfonate by-product (isethionate or sulfoacetate). Thus, the complete degradation of SQ through these pathways, including mineralization of the sulfonate sulfur, requires the involvement of other bacteria capable of sulfonate C-S cleavage. Enzymes and biochemical pathways for degradation of C2 and C3 sulfonates have been extensively studied, particularly in aerobic bacteria, as reviewed by Cook et al. ,40. Seve2S ,41,42.P. putida SQ1 , and the resultant (S)-SL is degraded by Paracoccus pantotrophus NKNCYSA (from anaerobic sludge) [Klebsiella oxytoca TauN1 (from soil) [S)-DHPS degraded by Cupriavidus pinatubonensis JMP134 (from volcanic mudflow deposits) [P. putida SQ1 was isolated from enrichment cultures with SQ as the sole carbon source, while the other three were previously studied for their ability to degrade various sulfonates. Crucially, neither P. pantotrophus nor C. pinatubonensis were able to metabolize SQ, but they were able to utilize the respective C3 sulfonates from spent media as substrates for growth, converting the sulfonate sulfur into a stoichiometric amount of sulfate [Insights into possible mechanisms of SQ sulfur mineralization by communities of environmental bacteria were provided by Denger et al. , who rep sludge) ,44. In tom soil) , and theeposits) . Of thes sulfate .P. pantotrophus and C. pinatubonensis, sulfonate C-S cleavage is ultimately catalyzed by (R)-sulfolactate sulfolyase SuyAB. In most sequenced Paracoccus species , the genome neighborhood of SuyAB contains close homologs of (S)-sulfolactate dehydrogenase SlcC and (R)-sulfolactate dehydrogenase ComC, which have been studied in Chromohalobacter salexigens, where they were proposed to catalyze racemization of (S)-SL prior to desulfonation by SuyAB [C. pinatubonensis JMP134, (S)-DHPS dehydrogenase HpsO and (R)-DHPS dehydrogenase HpsP catalyze racemization of (S)-DHPS, followed by oxidation by (R)-DHPS dehydrogenase HpsN to form (R)-SL (in two steps via SLA), and desulfonation by SuyAB [C as an electron acceptor [In both by SuyAB . In C. pby SuyAB . In bothacceptor .2S instead of sulfate, due to the involvement of SSRB. This process is of great relevance to sulfur metabolism and H2S production in the human gut. Burrichter et al. reported a defined bacterial co-culture system for the anaerobic degradation of SQ by E. coli K-12 and Desulfovibrio sp. strain DF1, isolated from enrichment cultures of anaerobic sewage sludge with DHPS as the sole carbon source and TEA [E. coli K-12 ferments SQ via the sulfo-EMP pathway, producing DHPS, and with the resultant GAP metabolized via mixed acid fermentation. In Desulfovibrio sp. DF1, DHPS is oxidized to SLA by NAD+-dependent DHPS dehydrogenase DhpA (a homolog of E. coli SLA reductase YihU), followed by oxidation to SL by NAD+-dependent SLA dehydrogenase SlaB (a homolog of SLA dehydrogenase present in other sulfoglycolysis pathways) and desulfonation by SuyAB. Sulfite released by SuyAB is reduced to H2S by dissimilatory sulfite reductase (Dsr). Homologs of SuyAB were found in many other SSRB in sequence databases, suggesting the widespread ability for C3 sulfonate degradation in these anaerobic bacteria [Bacterial degradation of SQ and other sulfonates in anoxic environments often terminates in the formation of H and TEA . In thisbacteria .Bilophila wadsworthia, a human intestinal pathogen associated with many disease conditions [Bilophila wadsworthia is unable to utilize sulfate as a TEA, but it is able to degrade a broad range of sulfonates, and to use the resultant sulfite as a TEA. In B. wadsworthia, degradation of SL is proposed to involve SuyAB [2-sensitive enzymes DHPS sulfolyase HpsG [B. wadsworthia with the abundant human gut bacterium E. rectale, in which E. rectale converts SQ to DHPS via the sulfo-TAL pathway, and B. wadsworthia converts DHPS to H2S via HpsG. Analysis of human fecal metatranscriptome datasets suggests the relevance of this pathway in human subjects across various health states.Of particular interest is the sulfite reducing bacterium nditions ,50. Bilove SuyAB , while dase HpsG  and isetase HpsG  , sulfo-ED, sulfo-TAL and sulfo-TK), with strong analogies to known glycolytic pathways. Among the naturally occurring sugars, SQ is unique in possessing an anionic and hydrolytically inert sulfonate group, which requires specialized enzymes for C-S cleavage. As a result, most organisms only metabolize a fraction of the SQ carbons and export the remaining carbons as a sulfonate by-product. By contrast, one non-sulfoglycolytic pathway has also been identified, involving oxygenolytic SQ desulfonation (sulfo-ASMO) to release sulfite as a by-product, enabling the complete utilization of SQ carbons .S)-DHPS and (S)-SL (products of sulfo-EMP(2), sulfo-ED and sulfo-TAL pathways) and isethionate (a product of the sulfo-TK pathway) are well studied. However, degradation of 3-sulfopropanol and 3-sulfopropionate (products of HpfG-dependent extended sulfoglycolysis pathways in anaerobes) and sulfoacetate (a product of the sulfo-TK pathway) require further investigation, particularly in anaerobic bacterial communities.Further degradation of sulfoglycolysis sulfonate by-products by other bacteria is required for mineralization and recycling of the sulfonate sulfur. Bacterial metabolism of (While the traditional approach to identification of new SQ degradation pathways has involved isolation and cultivation of SQ-degrading bacteria ,19,20,29


Malignant pleural mesothelioma (MPM) is a highly aggressive malignancy mainly triggered by exposure to asbestos and characterized by complex biology. A significant body of knowledge has been generated over the decades by the research community which has improved our understanding of the disease toward prevention, diagnostic opportunities and new treatments. Omics technologies are opening for additional levels of information and hypotheses. Given the growing complexity and technological spread of biological knowledge in MPM, there is an increasing need for an integrating tool that may allow scientists to access the information and analyze data in a simple and interactive way. We envisioned that a platform to capture this widespread and fast-growing body of knowledge in a machine-readable and simple visual format together with tools for automated large-scale data analysis could be an important support for the work of the general scientist in MPM and for the community to share, critically discuss, distribute and eventually advance scientific results. Toward this goal, with the support of experts in the field and informed by existing literature, we have developed the first version of a molecular pathway model of MPM in the biological pathway database WikiPathways. This provides a visual and interactive overview of interactions and connections between the most central genes, proteins and molecular pathways known to be involved or altered in MPM. Currently, 455 unique genes and 247 interactions are included, derived after stringent manual curation of an initial 39 literature references. The pathway model provides a directly employable research tool with links to common databases and repositories for the exploration and the analysis of omics data. The resource is publicly available in the WikiPathways database (Wikipathways : WP5087) and continues to be under development and curation by the community, enabling the scientists in MPM to actively participate in the prioritization of shared biological knowledge. Malignant pleural mesothelioma (MPM) is a rare and highly aggressive cancer that affects the mesothelial cells of the pleural cavity. The main cause of MPM is asbestos exposure , 2. In aBAP1, NF2, CDKN2A, TP53, LATS2 or SETD2 are a few examples of crucial genes affected in MPM which leads to well-demonstrated pathway dysregulation associated with cancer hallmarks like proliferation, angiogenesis, migration, resistance to apoptosis and others  data analysis, including molecular descriptors of genes, proteins and metabolites, additional molecular pathways and literature references. We zoom in on one of the highly relevant pathway sections (BAP1) to present an example of how such a resource may be used  . Common Interactions between genes, proteins, complexes and metabolites were illustrated using Molecular Interaction Maps (MIM) interactions  to descrTo extend detailed information and avoid duplicate content in the MPM pathway, common processes described elsewhere in the WikiPathways database were referred to by the relevant pathway nodes within this pathway (green rounded rectangles) and annotated with a WikiPathways identifier.Literature citations to papers were included in the whole pathway, specific sections, and particular interactions when appropriate. This was done using the ‘add literature reference’ option in PathVisio that created correct citations with the input of PubMed IDs.For visual clarification about cellular localization of genes, proteins and interactions, the graphics panel of PathVisio was used to draw the cellular membrane, nucleus, mitochondria and endoplasmic reticulum.www.wikipathways.org/instance/WP5087.Using the WikiPathways plugin in PathVisio, the pathway was uploaded to WikiPathways  and the Based on the 26 review papers and fifteen research papers found in the literature study, a molecular pathway of MPM was constructed Figure 1BAP1 (BRCA1 associated protein-1), NF2 (moesin-ezrin-radixin like (MERLIN) tumor suppressor), LATS2 (large tumor suppressor kinase 2), CDKN2A (cyclin dependent kinase inhibitor 2A), TP53 (tumor protein P53) and SETD2 (SET domain containing 2) to be among the most frequently mutated tumor suppressors in MPM together with frequently observed mutations of the TERT (telomerase reverse transcriptase) promoter region. These genes are important components of key tumorigenic processes in MPM such as the Hippo-merlin pathway, DNA damage response, cell survival, cell cycle, and epigenetic alterations. After having established the background biological pathway information about MPM, we therefore focused our attention toward more detailed information related to these genes, which we considered to be a useful starting point to begin building our first version of the MPM molecular pathway model.From our literature curation, we found the genes BAP1, a gene with both germline and somatic inactivating mutations in MPM. BAP1 has increasing relevance for MPM, being involved in susceptibility for the disease  and the OncoKB . Further, the WikiPathways team provides direct assistance to the users that can also directly request for changes in the pathway. The WikiPathway team provide also a preliminary curation of the changes introduced by the single user, before updates are published in the webpage.To support the users of the platform, a series of tutorials and user manuals has been created on how to perform pathway modelling and apply the elements and plug-ins of the platform (e.g. PathVisio). These users supports are accessible on the website of WikiPathways  can be found below: MMa, CE, FK, FC, and PN contributed to the conception of the work. MMa and FK developed the pathway model. FC, CE, PN, HM, MMe, DJ, FE, and AN have interpreted the work and provided substantial feedback to the model development. MMa, FK, and FC drafted the manuscript. All authors have read, revised, and approved the manuscript.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 681002 (EU-ToxRisk) and under the EJP RD COFUND-EJP No 825575. This work was funded by VHP4Safety – the Virtual Human Platform for safety assessment project NWA 1292.19.272. This project has received funding from Inserm, the Marlies Schwegler Foundation, and the Swedish fund for Research without Animals (N2020-0005). This work was supported by the US Environmental Protection Agency National Program in Chemistry Safety and Sustainability, Adverse Outcome Pathway, 4.3.2: Computational modeling approaches and case study validation to identify genetic-based susceptibility factors to environmental chemical exposures.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Metabolic syndrome-associated cardiovascular disease (MetS-CVD) is a cluster of metabolism-immunity highly integrated diseases. Emerging evidence hints that mitochondrial energy metabolism may be involved in MetS-CVD development. The physiopathological role of ATP5MG, a subunit of the F0 ATPase complex, has not been fully elucidated.In this study, we selected ATP5MG to identify the immunity-mediated pathway and mine drugs targeting this pathway for treating MetS-CVD. Using big data from public databases, we dissected co-expressed RNA (coRNA), competing endogenous RNA (ceRNA), and interacting RNA (interRNA) genes for ATP5MG.It was identified that ATP5MG may form ceRNA with COX5A through hsa-miR-142-5p and interplay with NDUFB8, SOD1, and MDH2 through RNA–RNA interaction under the immune pathway. We dug out 251 chemicals that may target this network and identified some of them as clinical drugs. We proposed five medicines for treating MetS-CVD. Interestingly, six drugs are being tested to treat COVID-19, which unexpectedly offers a new potential host-targeting antiviral strategy.Collectively, we revealed the potential significance of the ATP5MG-centered network for developing drugs to treat MetS-CVD, which offers insights into the epigenetic regulation for metabolism-immunity highly integrated diseases. Metabolic syndrome-associated cardiovascular disease (MetS-CVD) represents a cluster of metabolic deformities that contribute to increased oxidative stress and activated inflammatory pathways that cause cardiovascular remodeling and dysfunction . This coEmerging evidence proposes that energy metabolism may be involved in developing MetS-CVD besides substance metabolisms such as glucose and lipid dysregulation , 5. MoreMetS-CVD has a systemic effect, by intersecting ceRNA (competing endogenous RNA) genes and interRNA (interacting RNA) genes in the whole body with genes co-expressed in the heart, we looked for the ATP5MG-circled network for energy metabolic effects on the heart dysfunction using the inflammatory or immune pathway. We further identified chemicals perturbing this network to dig medicines for treating MetS-CVD. Our study may provide epigenetic insights into metabolism-immunity/inflammation highly integrated diseases for basic research and drug development.Free public resources, including tools and databases, were enlisted to obtain data and draw figures. To guarantee the objectivity of the result, all analyses throughout the study were employed according to the default settings of the database or tool, unless otherwise stated. When conducting analysis using default parameters, these excellent foolproof operating tools or databases displayed needed data instantly for free download. Figures were made using POWERPOINT or EXCEL unless otherwise specified.P-value, and false discovery rate (FDR) both ≤ 0.01; for interRNA, interact number ≥1, experiment number ≥1. GTEx data in the GEPIA2 database  PATHWAY, HIV INTERACTION (CATEGORY), and GAD DISEASE (CLASS) for coRNA, ceRNA, and interRNA datasets were achieved using well-known tool DAVID  database, a repository embodying the effects of environmental chemicals on human gene expression . All theZ-score was only 3.3 for “severe congenital neutropenia 2.” Considering that the number of disease associations was small and the highest score was low, it was concluded that the functional ATP5MG studies were presently weak, which supported the high originality of our project design.Identifying the involvement of the ATP5MG-mediated immune-inflammatory pathway in MetS-CVD is not easy. As MetS-CVD is a complex systemic disease and often related to several diseases such as diabetes, obesity, and heart disease, we enlisted the tool DISEASES to parse ATP5MG–disease associations mined from the literature. Only 33 types of disease associations were uncovered , and “seThe pathogenesis of complex diseases must involve complex molecular networks. Hence, to determine the functional annotations and molecular mechanisms underlying MetS-CVD, we used the coRNA, ceRNA, and interRNA genes of ATP5MG to conduct all the analyses. GO and KEGG were enlisted to annotate their functions. Intersections of coRNA and ceRNA genes and coRNA and interRNA genes were used to obtain molecules to form our target network . As a biDue to less verified functional information on ATP5MG, we first set out to prospect its functional notes in the heart. We extracted 200 coRNA genes in the human heart from GEPIA2 and dissected functional annotations of ATP5MG using the tool DAVID.Concerning GO-BP, we visualized the top 30 terms in 48 terms  and founAs observed in the above coRNA analysis, the ATP5MG functions are broad, including energy regulation, inflammation/infection, and substance metabolism, of which energy production is a high-frequency term.A total of 1,326 ceRNA genes extracted from ENCORI were parsed for functional comments in human tissues using DAVID. The top 30 terms for all the sets were visualized.We achieved 236 functional terms of GO-BP and found that ATP5MG may participate in the different biological processes, including “regulation of energy homeostasis,” “cellular response to glucose starvation,” “blood vessel development,” and “viral process” in the top 30 terms . For GO-It can be seen from the above ceRNA analysis that ATP5MG-related functions are extensive, including metabolism, cardiovascular event, energy regulation, and inflammation/infection.The coRNA and ceRNA gene sets of ATP5MG were recruited to dig intersection genes, and only four cross coding genes were obtained . PCC anaNext, we set out to mine intersection miRNAs. COX5A can bind 13 miRNAs, ATPAF1 35 miRNAs, H2AFV 51 miRNAs, and FDX1 26 miRNAs . All theUntil now, by dissecting expressional and functional comments on intersection coding genes and miRNAs, we reached the target ceRNA subnetwork formed by ATP5MG, hsa-miR-142-5p, and COX5A .We fetched 507 interRNA human genes for functional comments using DAVID, which was built on RNA-RNA interaction of ENCORI.Escherichia coli infection,” “leukocyte transendothelial migration,” “antigen processing and presentation,” “bacterial invasion of epithelial cells,” “herpes simplex infection,” “biosynthesis of antibiotics,” “hepatitis C,” “shigellosis,” “viral myocarditis,” “influenza A,” and “T-cell receptor signaling pathway” , which can be conscribed to win the WARS , showingIn this bioinformatics examination using public big data, it was revealed that ATP5MG might form ceRNA with COX5A through hsa-miR-142-5p and interplay with NDUFB8, SOD1, and MDH2 by the RNA–RNA interaction under inflammation-/immunity-related scenes. We decoded clinical trials of five medicines from 251 chemicals targeting this network, including zidovudine, cyclosporine, resveratrol, vitamin E, and acetaminophen, which may be recruited to treat CVD, metabolic diseases, and inflammation-/immunity-related diseases; reasonably, they may also treat MetS-CVD. Ecstatically, we got a windfall, that is, cyclosporine, vitamin E, acetaminophen, sodium selenite, hydrogen peroxide, and dihydroartemisinin may be employed to deal with COVID-19. Thus, our study may provide basic and clinical insights into epigenetic network regulation for metabolism-immunity highly integrated diseases.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/XL: conception, design, and manuscript writing. LL, XZ, and JC: provision of study materials. LL: collection and assembly of data. All authors: administrative support, data analysis and interpretation, and final approval of manuscript.This study was supported by the Outstanding Leaders Training Program of Pudong Health Bureau of Shanghai (PWRl2018-02), the Pudong New Area Science and Technology Commission of Shanghai (PKJ2019-Y21 and PKJ2020-Y38), and the Shanghai Municipal Health Commission (202140467).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Nonalcoholic steatohepatitis (NASH), a progression of nonalcoholic fatty liver disease (NAFLD), is a clinical syndrome characterized by liver steatosis, inflammation, and hepatocellular damage. Ganlu powder (GLP) is a classic traditional Chinese medicine prescription that has shown favorable treatment effects on NASH. However, the underlying therapeutic mechanisms are still poorly understood. This study is aimed at exploring the potential mechanism of GLP in the treatment of NASH via network pharmacology and molecular docking. PubMed and CNKI databases were used to identify the components of GLP. Swiss and STITCH databases were employed to obtain corresponding drug targets. NASH targets were adopted from the Therapeutic Target Database (TTD), DisGeNET, DrugBank, GeneCards, and MalaCards databases. Cytoscape software was utilized to construct “drug-ingredient-target-disease” networks and the protein-protein interaction (PPI) network of GLP in NASH. AKT1 was identified as the key target. The GO functional enrichment analysis revealed that GLP might treat NASH by modulating the inflammatory response and regulating phosphatidylinositol 3-kinase signaling. The KEGG analysis showed that GLP might treat NASH by regulating the tumor necrosis factor (TNF) signal pathway by affecting the role of AKT1. According to the network pharmacology results, a virtual docking of active compounds with AKT1 was carried out, and the results indicated that the 7 components, berberine, epiberberine, jatrorrhizine, coptisine, palmatine, evodiamine, and rutecarpine, can bind stably with AKT1 and have higher binding energy than AKT1 inhibitors. The overall study findings suggest that GLP may treat NASH by regulating AKT1. Nonalcoholic fatty liver disease (NAFLD) is one of the most common chronic liver diseases in the world . It is aSheng ji zong lu and composed of two herbs, namely Coptidis Rhizoma and Evodiae Fructus, which have been mainly used for the treatment of gastrointestinal diseases including diarrhea, dysentery, and other inflammatory diseases. Pharmacological studies showed that GLP can lower blood lipids, improve inflammation, and regulate cholesterol metabolism. Zhang et al. [Currently, there are no drugs approved for the treatment of NASH by the U.S. Food and Drug Administration (FDA). NASH is not unifactorial but a common multifactorial condition; thus, the effect of treatment for a single target is suboptimal . Traditig et al.  found thAs with many other TCMs, the underlying mechanisms of GLP in treating NASH remain poorly understood. The nature of TCM makes it difficult for traditional methods to fully understand how these herbs with multiple active ingredients exert their synergistic biological effects through multiple targets and pathways in human beings , 16. Nethttps://pubmed.ncbi.nlm.nih.gov/) and CNKI (https://www.cnki.net/), were utilized for bioactive compounds screening. The chemical structure of the components was drawn by ChemDraw 15.0. Swiss ADME was used to predict the drug-like properties and gastrointestinal absorption of the obtained ingredients of GLP, and the ingredients that did not meet the criteria were excluded. In order to comprehensively obtain the targets of bioactive components of GLP, the collected ingredients were imported into STITCH and Swiss Target Prediction for target prediction. During STITCH retrieval, the species was set to “homo sapiens”; during the Swiss Target Prediction retrieval, the SMILES number of the corresponding components was uploaded for target fishing. Finally, the targets downloaded from the two databases were merged and deduplicated, after which the targets of GLP were obtained.Two databases, PubMed . The intersection of GLP and NASH-related targets was derived. The “drug-component-target-disease” interaction was established through Cytoscape3.7.1. In the network, nodes represent the compounds of GLP and the targets of NASH, edges represent the relationship between each node, and the number of edges is defined as “degree.”The obtained targets of 7 compounds of GLP and NASH-related targets were merged together and delineated with the Venn diagram plotted by an online tool  is a widely used bioinformatic method for annotating genes, typically including biological processes (BP), molecular function (CC), and molecular functions (MF). KEGG is an important technique for analyses of functions between different genes. To better interpret the functions of those overlapped targets, GO and KEGG enrichment analyses were conducted using the Database for Annotation, Visualization, and Integrated Discovery (DAVID), and the top 20 terms with bble map .http://www.rcsb.org/). Meanwhile, we searched the inhibitors of core targets from DrugBank and PubMed. The protein structure was processed using PyMOL (version 1.7.2.1) to remove excess ligands, including removing water molecules and excess Mg2+, Cu2+, and SO42-. ChemDraw was then used to optimize small ligand molecules and save the files in a mol2 format. The standardized proteins and ligands were imported into AutoDockTools (version 1.5.6) and converted into a PDBQT format. Using the AutoDock Vina software (version 1.1.2), we ran a program for molecular docking using docking parameters; the complex conformation with the minimum binding energy and highest binding affinity for each molecule was selected for further analysis [Based on the results of network pharmacology, the three-dimensional (3D) structure of the core target was downloaded from the Protein Data Bank (PDB) database  including berberine, palmatine, jatrorrhizine, coptisine, epiberberine, evodiamine, and rutecarpine. The ADME properties of each component are shown in By searching PubMed and CNKI, we obtained the ingredients of the two herbs of GLP. After the screening of absorption, distribution, metabolism, and excretion (ADME) properties, we retained 7 main ingredients , and they are located in the active pocket of the inhibitor resveratrol, which fits well in the docking position . The drun forces . In addin forces .NASH is a metabolic stress liver injury strongly correlated with insulin resistance and genetic susceptibility, which can progress to liver cirrhosis and hepatocellular carcinoma. In addition, patients with NASH are at an increased risk of cardiovascular disease (CVD). The benefit of maintaining a healthy lifestyle is self-evident. The vast majority of patients, however, have difficulties in adhering to these healthy living habits, and the effect of behavioral changes on body weight and blood glucose management is often suboptimal. Due to the multiple and complex pathogenesis of NASH, there are no approved drugs for treatment. With the advancement of clinical medical research, the advantages of Chinese herbal medicine in the treatment of NASH have attracted substantial attention. As a historically old formula of TCM, the therapeutic effects of GLP on NASH attract our attention. In this study, 7 main active ingredients and 312 potential therapeutic targets of GLP, together with 879 NASH potential targets and 70 common targets, were screened using network analysis. As the complex network described, AKT1 is considered the core target of GLP in NASH treatment.AKT1 is a member of the AKT kinase family, which regulates glycolipid metabolism, proliferation, and cell survival through a series of downstream substrates. Usually, the activation of AKT requires two key phosphorylation processes. Phosphoinositide-dependent protein kinase 1 (PDK1) initially phosphorylates AKT on threonine 308 (T308), an active phosphorylation site of AKT, leading to the activation process; mTORC2 then phosphorylates AKT on serine 473 to fully activate AKT .In lipid metabolism, activated AKT induces the activation of mTOR, which subsequently recruits CRTC2 as a complex to promote SREBP-1 activity and adipogenesis. Yu et al.  found thκB mRNA expressions in liver tissues were significantly increased. Other clinical studies also found that the NF-κB activity was increased in NASH patients. AKT regulates NF-κB signal transduction through phosphorylation of IKKα, which leads to the degradation of IκB [κB from the cytoplasm into the nucleus to further regulate the expression of downstream target genes and finally mediate multiple pathological processes such as liver inflammation and apoptosis. The evidence indicates that GLP may reduce liver damage by regulating the release of downstream inflammatory factors through AKT1.According to the GO enrichment analysis result, the common targets of GLP and NASH were enriched to inflammatory response and regulation of phosphatidylinositol 3-kinase signaling, and AKT1 was also involved in these biological processes. Accumulating evidence has revealed that NASH is a metabolic inflammatory disease induced by lipid-oversupplied steatosis, and chronic inflammation is the main driver of NASH and one of the clinical features used to distinguish NASH from NAFLD , 32, 33.n of IκB . This prα) and tumor necrosis factor-beta (TNF-β). TNF-α, mainly secreted by activated macrophages, can promote the expression of proinflammatory factors and participate in systemic inflammation. Insulin resistance is involved in the development and progression of NASH. In NASH progression, TNF-α induces the activation of JNK, leading to the Ser site on the IRS protein in the phosphorylated insulin signaling pathway and consequently resulting in insulin resistance [KEGG enrichment results showed that the TNF signaling pathway was the most important signaling pathway, which involved the core target AKT1. TNF has two types: tumor necrosis factor-alpha  pathways [κB p65, ERK1/2, p38, and JNK [The protein-small molecular docking analysis showed that all 7 components of GLP were successfully docked to AKT1, located in the active pocket of resveratrol and fitting well in the active pocket. Meanwhile, the 7 components have better binding energy than the AKT1 inhibitor, resveratrol. The drug molecules and the protein receptors form multiple intermolecular forces, including hydrogen bonding, C-H bonding, pathways . Additiopathways . Epiberbpathways . Coptisipathways . Moreove and JNK . Nie et  and JNK  found thIn summary, this study tackles the molecular mechanism of GLP in the treatment of NASH based on bioinformatics and system pharmacology. Our findings indicate that multiple compounds in GLP may play a role in the treatment of NASH through the synergy of targets and signaling pathways. The active ingredients of GLP can act on the key gene target AKT1 and exert pharmacological effects through the TNF signaling pathway. Due to the limitations of biological calculation methods, future research with in vitro and in vivo experiments is needed to verify our findings.