Exploring the mechanism of action Xianlingubao Prescription in the treatment of osteoporosis by network pharmacology

In this study, the network pharmacology analysis method was used to explore the bioactive components and targets of Xianlinggubao (XLGB) and further elucidate its potential biological mechanisms of action in the treatment of osteoporosis (OP). The bioactive compounds and predictive targets of XLGB were collected from the traditional Chinese medicine systems pharmacology databases and analysis platform(TCMSP), the Encyclopeida of traditional Chinese medicine (ETCM), traditional Chinese medicine Databse@Taiwan, ChEMBL, STITCH, and SymMap database. The targets corresponding to OP were obtained by using Online Mendelian Inheritance in Man® (OMIM), GeneCards, the National Center for Biotechnology Information-Gene database. The XLGB-OP targets were obtained by intersecting with the targets of XLGB and OP. Protien-Protien interaciton (PPI) network was constructed using STRING online database and analyzed using Cytoscape 3.7.0 software to screen out hub genes. Gene ontology (GO) and KEGG enrichment analysis of the target in the PPI network was conducted using the ClusterProfiler package in R with adjusted p-value<0.05. A total of 65 XLGB bioactive compounds were screened corresponding to 776 XLGB targets and 2556 OP targets. The GO analysis and KEGG enrichment analyses suggested XLGB played a therapeutic roles in OP treatment via the interleukin-17 signaling pathway, hypoxia-inducible factor-1 signaling pathway, insulin resistance, Th-17 signaling pathway, etc. Five hub genes (AKT1, MAPK1, MAPK8, TP53, and STAT3) were screened using the degree algorithm, and molecular docking stimulation results showed that most bioactive compounds of XLGB had strong binding efficiency with hub genes. Overall, this study laid the foundation for further in vivo and in vitro experimental research and expanded the clinical applications of XLGB.     

Exploration of the mechanism of Zisheng Shenqi decoction against gout arthritis using network pharmacology

BackgroundIn this study, the network pharmacological methods were used to predict the target of effective components of compounds in Zisheng Shenqi Decoction (ZSD, or Nourishing Kidney Qi Decoction) in the treatment of gouty arthritis (GA).MethodThe main effective components and corresponding key targets of herbs in the ZSD were discerned through the Traditional Chinese Medicine Systems Pharmacology Database and Analysis (TCMSP), Bioinformatics Analysis Tool for Molecular mechanism of Traditional Chinese Medicine (BATMAN-TCM) database. UniProt database and Swiss Target Prediction (STP) database was used to rectify and unify the target names and supply the target information. The targets related to GA were obtained by using GeneCards database. After we discovered the potential common targets between ZSD and GA, the interaction network diagram of “ZSD-component-GA-target” was constructed by Cytoscape software (Version 3.7.1). Subsequently, the Protein-protein interaction (PPI) network of ZSD effective components-targets and GA-related targets was constructed by Search Tool for the Retrieval of Interacting Genes Database (STRING). Bioconductor package “org.Hs.eg.db” and “cluster profiler” package were installed in R software (Version 3.6.0) which used for Gene Ontology analysis and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis.Results146 components and 613 targets of 11 herbal medicines in the ZSD were got from TCMSP database and BATMAN-TCM database. 987 targets of GA were obtained from GeneCards database. After intersected and removed duplications, 132 common targets between ZSD and GA were screened out by Cytoscape software (Version 3.7.1). These common targets derived from 81 effective components of 146 components, such as quercetin, stigmasterol and kaempferol. They were closely related to anti-inflammatory, analgesic and anti oxidative stress and the principal targets comprised of Purinergic receptor P2X, ligand-gated ion channel 7 (P2x7R), Nod-like receptor protein 3 (NLRP3) and IL-1β. GO enrichment analysis and KEGG pathway enrichment analysis by R software (Version 3.6.0) showed that the key target genes had close relationship with oxidative stress, reactive oxygen species (ROS) metabolic process and leukocyte migration in aspects of biological process, cell components and molecular function. It also indicated that ZSD could decrease inflammatory reaction, alleviate ROS accumulation and attenuate pain by regulating P2 × 7R and NOD like receptor signaling pathway of inflammatory reaction.ConclusionA total of 81 effective components and 132 common target genes between ZSD and GA were screened by network pharmacology. The PPI network, GO enrichment analysis and KEGG pathway enrichment analysis suggested that ZSD can exerte anti-inflammatory and analgesic effects on the treatment of GA by reducing decreasing inflammatory reaction, alleviating ROS accumulation, and attenuating pain. The possible molecular mechanism of it mainly involved multiple components, multiple targets and multiple signaling pathways, which provided a comprehensive understanding for further study. In general, the network pharmacological method applied in this study provides an alternative strategy for the mechanism of ZSD in the treatment of GA.     

Network pharmacology analysis of Chaihu Lizhong Tang treating non-alcoholic fatty liver disease

BackgroundIn this study, the network pharmacological methods were used to predict the target of active components of Chaihu Lizhong Tang (CHLZT) in the treatment of non-alcoholic fatty liver disease (NAFLD).MethodThe active components of "CHLZT", their targets, and NAFLD related targets were screened by multiple databases, and the potential targets of "CHLZT" in the treatment of NAFLD were predicted. The active component-target network of "CHLZT" was constructed by Cytoscape software. The potential target of "CHLZT" for the treatment of NAFLD constructed protein-protein interaction (PPI) network in the Search Tool for the Retrieval of Interacting Genes Database (STRING). The hub genes of “CHLZT” in the treatment of NAFLD were screened by network topological parameters, and the results were verified by molecular docking. "ClusterProfiler" in R was used for Gene Ontology (GO) analysis and KEGG pathway enrichment analysis.ResultsOB ≥ 30 % and DL ≥ 0.18 were selected as the screening criteria of active components. A total of 83 active components and 456 targets were selected. Based on the evaluation of topological parameters of degree network, five hub genes for interaction with "CHLZT" therapy for NAFLD were screened, that is, AKT1, ALB, IL6, EGFR, and CASP3. The results of molecular docking showed that the active components in "CHLZT" had a good binding ability with the key targets. The enrichment analysis results showed that the treatment of NAFLD with "CHLZT" mainly involved in cofactor binding, protease binding, AGE-RAGE signaling pathway in diabetic complications, and IL-17 signaling pathway, which mediated the potential mechanism of "CHLZT" intervention in NAFLD.ConclusionThe molecular mechanism of "CHLZT" in the treatment of NAFLD indicated the synergistic features of multi-component, multi-target, and multi-pathway of traditional Chinese medicine, which provided an important scientific basis for further elucidating the mechanism of "CHLZT" in the treatment of NAFLD.     

Antitumor effect of guava leaves on lung cancer: A network pharmacology study

Guava is known for its hypoglycemic, antivirus, antibacterial, anti-inflammatory, antioxidant, and antitumor properties. In this study, triterpenoids, sesquiterpenes, and flavonoids were examined as potential targets of constituents of guava leaves. Our study was aimed to reveal the antitumor mechanism and construct the network pharmacology network of guava leaf constituents and lung cancer. The potential targets of guava leaf constituents were searched in target databases, while the disease genes were searched in the GeneCards database. The common targets of drugs and diseases were screened out. A network map was constructed by the Cytoscape software, and the GO and KEGG pathways were analyzed. The existing cases were studied by SystemsDock molecular docking and cBioPortal tumor database study. Among the 66 chemical constituents of guava leaves, 153 of their targets were the lung cancer genes involved in many signaling pathways, such as the PI3K-Akt signaling pathway, in small cell lung cancer and non-small cell lung cancer. There was a binding activity between ligand compounds and receptor proteins. Guava leaves inhibited tumor through a gene regulatory network, and may play an important role in gene-targeting therapy. Through network pharmacology, we found that guava leaves had potential targets that interacted with various tumors, regulating the signaling pathways of cancers. This study preliminarily verified the pharmacological basis and the mechanism of the antitumor effect of guava leaves, providing a foundation for further research.     

Down regulation of lactotransferrin enhanced radio-sensitivity of nasopharyngeal carcinoma

IntroductionIt is reported that LTF had a radiation resistance effect, and its expression in nasopharyngeal carcinoma (NPC) was significantly down-regulated. However, the mechanism of down-regulated LTF affecting the sensitivity of radiotherapy has remained elusive.MethodsWe re-analyzed the microarray data GSE36972 and GSE48503 to find differentially expressed genes (DEGs) in NPC cell line 5−8 F transfected with LTF or vector control, and the DEGs between radio-resistant and radio-sensitive NPC cell lines. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment and protein-protein interaction network (PPI) analysis of DEGs were performed to obtain the node genes. The target genes of miR-214 were also predicted to complement the mechanism associated with radiotherapy resistance because it could directly target LTF.ResultsThis study identified 1190 and 1279 DEGs, respectively. GO and KEGG analysis showed that apoptotic process and proliferation, PI3K-Akt signaling pathway were significantly enriched pathways. Four nodes (DUSP1, PPARGC1A, FOS and SMARCA1) associated with LTF were screened. And 42 target genes of miR-214 were cross-linked to radiotherapy sensitivity.ConclusionsThe present study demonstrates the possible molecular mechanism that the down-regulated LTF enhances the radiosensitivity of NPC cells through interaction with DUSP1, PPARGC1A, FOS and SMARCA1, and miR-214 as its superior negative regulator may play a role in regulating the radiotherapy effect.     

Network Pharmacology-Based Study to Uncover Potential Pharmacological Mechanisms of Korean Thistle (Cirsium japonicum var. maackii (Maxim.) Matsum.) Flower against Cancer

Cirsium japonicum var. maackii (Maxim.) Matsum. or Korean thistle flower is a herbal plant used to treat tumors in Korean folk remedies, but its essential bioactives and pharmacological mechanisms against cancer have remained unexplored. This study identified the main compounds(s) and mechanism(s) of the C. maackii flower against cancer via network pharmacology. The bioactives from the C. maackii flower were revealed by gas chromatography-mass spectrum (GC-MS), and SwissADME evaluated their physicochemical properties. Next, target(s) associated with the obtained bioactives or cancer-related targets were retrieved by public databases, and the Venn diagram selected the overlapping targets. The networks between overlapping targets and bioactives were visualized, constructed, and analyzed by RPackage. Finally, we implemented a molecular docking test (MDT) to explore key target(s) and compound(s) on AutoDockVina and LigPlot+. GC-MS detected a total of 34 bioactives and all were accepted by Lipinski’s rules and therefore classified as drug-like compounds (DLCs). A total of 597 bioactive-related targets and 4245 cancer-related targets were identified from public databases. The final 51 overlapping targets were selected between the bioactive targets network and cancer-related targets. With Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, a total of 20 signaling pathways were manifested, and a hub signaling pathway (PI3K-Akt signaling pathway), a key target (Akt1), and a key compound (Urs-12-en-24-oic acid, 3-oxo, methyl ester) were selected among the 20 signaling pathways via MDT. Overall, Urs-12-en-24-oic acid, 3-oxo, methyl ester from the C. maackii flower has potent anti-cancer efficacy by inactivating Akt1 on the PI3K-Akt signaling pathway.     

Molecular docking study on platelet-activating factor antagonistic activity of bioactive compounds isolated from Guttiferae and Ardisia species

A handful of bioactive compounds from plants have been reported to possess platelet-activating factor (PAF) antagonist activity. However, their mode of action is not well understood. Selected bioactive compounds that exhibit PAF antagonist activity and synthetic PAF antagonists were subjected to docking simulations using the MOE 2007.09 software package. The docking study of PAF antagonists was carried out on the PAF receptor (PAFR) protein which involves in various pathological responses mediated by PAF. The docking results revealed that amentoflavone (3) showed good interactions with the PAFR model where the flavone and phenolic moieties were mostly involved in these interactions. Knowledge on PAF antagonists' interactions with the PAFR model is a useful screening tool of potential PAF antagonists prior to performing PAF inhibitory assay.     

Uncovering the pharmacological mechanism of motherwort (Leonurus japonicus Houtt.) for treating menstrual disorders: A systems pharmacology approach

Leonurus japonicus (motherwort) is a traditional Chinese medicine that is widely used to treat menstrual disorders (MDs). However, the pharmacological mechanisms that underlie its clinical application remain unclear. In this study, a network pharmacology-based approach was used that integrated drug-likeness evaluation, oral bioavailability prediction, target exploration, network construction, bioinformatic annotation and molecular docking to investigate the mechanisms that underlie motherwort treatment for MDs. In total, 29 bioactive compounds were collected from 51 compounds in motherwort, which shared 17 common MDs-related targets. Network analysis indicated that motherwort played a therapeutic role in MDs treatment through multiple components that acted on multiple targets. Pathway enrichment analysis showed that the putative targets of motherwort were primarily involved in various pathways associated with the endocrine system, cancers, vascular system, and anti-inflammation process. Notably, five targets (i.e., AKT1, PTGS2, ESR1, AR and PPARG) were screened as hub genes based on a degree algorithm. Moreover, most of the bioactive components in motherwort had good binding ability with these genes, implying that motherwort could regulate their biological function. Collectively, this study elucidated the molecular mechanisms that underlay the efficiency of motherwort against MDs and demonstrated the potential of network pharmacology as an approach to uncover the action mechanism of herbal medicines.     

A novel method for investigating the mechanism of the anti-rheumatoid arthritis activity of Angelicae pubescentis radix by integrating UHPLC–QTOF/MS and network pharmacology

The study aimed to establish a strategy to elucidate the in vivo constituents of Angelicae Pubescentis Radix (APR, also known as Duhuo) and reveal the probable mechanisms underlying its anti-rheumatoid arthritis activity. First recorded by Shennong Bencao Jing, APR is mainly used to treat Bi syndrome. Eleven absorbed components of APR were successfully identified using the rheumatoid arthritis (RA) rat model and the UHPLC–QTOF/MS technique. Two active ingredients (osthole and columbianadin) and five corresponding targets (PTGS1, PTGS2, RXRA, CCNA2 and ACHE) were found to construct a compound–protein interaction network in RA. In addition, a non-alcoholic fatty liver disease pathway, which was related to anti-RA activity, was eventually identified by KEGG analysis. Subsequently, molecular docking was performed by establishing a mixed matrix network, including the absorbed component, corresponding target and signaling pathway with two key compounds (osthole and columbianadin) and two important targets (PTGS2 and PTGS1). The result of molecular docking is in agreement with the network pharmacology.     

Defining the Role of Isoeugenol from Ocimum tenuiflorum against Diabetes Mellitus-Linked Alzheimer’s Disease through Network Pharmacology and Computational Methods

The present study involves the integrated network pharmacology and phytoinformatics-based investigation of phytocompounds from Ocimum tenuiflorum against diabetes mellitus-linked Alzheimer’s disease. It aims to investigate the mechanism of the Ocimum tenuiflorum phytocompounds in the amelioration of diabetes mellitus-linked Alzheimer’s disease through network pharmacology, druglikeness and pharmacokinetics, molecular docking simulations, GO analysis, molecular dynamics simulations, and binding free energy analyses. A total of 14 predicted genes of the 26 orally bioactive compounds were identified. Among these 14 genes, GAPDH and AKT1 were the most significant. The network analysis revealed the AGE-RAGE signaling pathway to be a prominent pathway linked to GAPDH with 50.53% probability. Upon the molecular docking simulation with GAPDH, isoeugenol was found to possess the most significant binding affinity (−6.0 kcal/mol). The molecular dynamics simulation and binding free energy calculation results also predicted that isoeugenol forms a stable protein–ligand complex with GAPDH, where the phytocompound is predicted to chiefly use van der Waal’s binding energy (−159.277 kj/mol). On the basis of these results, it can be concluded that isoeugenol from Ocimum tenuiflorum could be taken for further in vitro and in vivo analysis, targeting GAPDH inhibition for the amelioration of diabetes mellitus-linked Alzheimer’s disease.     

基于网络药理学及分子对接技术研究向海雁鹅血的抗肺癌活性成分

对向海雁鹅血抗肺癌的活性成分、潜在作用靶点及信号通路进行研究,并应用分子对接技术探索其抗肺癌可能的作用机制。利用高效液相色谱-质谱联用技术（HPLC-MS/MS）分析向海雁鹅血活性物质的成分;采用网络药理学筛选靶点,分析信号通路,构建向海雁鹅血活性物质“成分-靶点-通路”网络;利用细胞增殖检测（CCK-8）细胞活力测定法检测向海雁鹅血提取物对4种人癌细胞活力影响;运用分子对接核心靶点与向海雁鹅血活性成分;实时定量聚合酶链反应检测（qPCR）检测向海雁鹅血提取物对人肺癌A549细胞p-AKT1的mRNA表达的影响。结果分析出Pro、H-Asn-Asp-Asp-Met-OH、Thr-Thr-Asn-Tyr-Thr-Asp、和Ala-Trp-Met-Asp-Phe-Val 4种向海雁鹅血活性成分;获得相关靶点258个,其中核心靶点46个;GO基因富集分析涉及AKT1、IL1BS、SRC等关键靶点;KEGG信号通路富集涉及癌症信号通路等;向海雁鹅血提取物对4种人癌细胞的细胞活力均有抑制,其中对人肺癌A549细胞的抑制效果最明显;向海雁鹅血活性成分的核心靶点与肺癌靶点相映射结果显示是通过AKT1、IL1BS、SRC等关键靶点起到抑制A549的作用;分子对接结果显示：H-Asn-Asp-Asp-Met-OH与ATK1的结合能最高;qPCR检测结果显示,向海雁鹅血提取物能够显著减低A549细胞p-AKT1的mRNA的含量水平。向海雁鹅血活性物质通过多靶点、多通路的形式诱导人肺癌A549细胞凋亡,为向海雁鹅血抗肺癌的活性物质研究与开发提供了新的思路和方向。     

Gene Interaction Network Analysis Reveals IFI44L as a Drug Target in Rheumatoid Arthritis and Periodontitis

Simple SummaryIn spite of substantial investigation, the biological link between periodontitis and rheumatoid arthritis remains unexplained. This study intended to correlate periodontitis and rheumatoid arthritis gene expression patterns to find shared targets for both the disease. We identified the differentially expressed genes (DEGs) in periodontitis and rheumatoid arthritis. The network was built by integrating DEGs and ranking the genes using GeneMANIA. FINDSITEcomb2.0 was used to find a possible inhibitor for the top-ranked gene. Further, the binding effectiveness and protein-ligand complex stability were then determined by molecular docking and molecular dynamics. The network analysis showed IFI44L as a highly ranking gene implicated in most immunological pathways. A virtual screening of 6507 compounds revealed vemurafenib as the best candidate for the IFI44L target. Molecular docking and molecular dynamics modelling revealed the stability of the IFI44L-vemurafenib complex, which suggest IFI44L is potential target and vemurafenib could be the better candidate to treat both diseases.AbstractObjective: Despite extensive research on periodontitis and rheumatoid arthritis, the underlying molecular connectivity between these condition remains largely unknown. This research aimed to integrate periodontitis and rheumatoid arthritis gene expression profiles to identify interconnecting genes and focus to develop a common lead molecule against these inflammatory conditions. Materials and Methods: Differentially expressed genes (DEGs) of periodontitis and rheumatoid arthritis were identified from the datasets retrieved from the Gene Expression Omnibus database. The network was constructed by merging DEGs, and the interconnecting genes were identified and ranked using GeneMANIA. For the selected top ranked gene, the potential inhibitor was searched using FINDSITE^comb2.0. Subsequently, the molecular docking and molecular dynamics were performed to determine the binding efficiency and protein-ligand complex stability, respectively. Results: From the network analysis, IFN-induced protein 44-like (IFI44L) was identified as a top ranked gene involved in most of the immunological pathway. With further virtual screening of 6507 molecules, vemurafenib was identified to be the best fit against the IFI44L target. The binding energy and stability of IFI44L with vemurafenib were investigated using molecular docking and molecular dynamics simulation. Docking results show binding energy of −7.7 Kcal/mol, and the simulation results show stability till 100 ns. Conclusions: The identified IFI44L may represent a common drug target for periodontitis and rheumatoid arthritis. Vemurafenib could be a potent anti-inflammatory drug for both diseases.     

A network-based pharmacology study of active compounds and targets of Fritillaria thunbergii against influenza

Seasonal and pandemic influenza infections are serious threats to public health and the global economy. Since antigenic drift reduces the effectiveness of conventional therapies against the virus, herbal medicine has been proposed as an alternative. Fritillaria thunbergii (FT) have been traditionally used to treat airway inflammatory diseases such as coughs, bronchitis, pneumonia, and fever-based illnesses. Herein, we used a network pharmacology-based strategy to predict potential compounds from Fritillaria thunbergii (FT), target genes, and cellular pathways to better combat influenza and influenza-associated diseases. We identified five compounds, and 47 target genes using a compound-target network (C-T). Two compounds (beta-sitosterol and pelargonidin) and nine target genes (BCL2, CASP3, HSP90AA1, ICAM1, JUN, NOS2, PPARG, PTGS1, PTGS2) were identified using a compound-influenza disease target network (C-D). Protein-protein interaction (PPI) network was constructed and we identified eight proteins from nine target genes formed a network. The compound-disease-pathway network (C-D-P) revealed three classes of pathways linked to influenza: cancer, viral diseases, and inflammation. Taken together, our systems biology data from C-T, C-D, PPI and C-D-P networks predicted potent compounds from FT and new therapeutic targets and pathways involved in influenza.     

Synthesis,biological evaluation,and molecular docking study of pyridine clubbed 1,3,4-oxadiazoles as potential antituberculars

A series of pyridine clubbed 1,3,4-oxadiazole derivatives were efficiently synthesized, characterized by standard spectral techniques and evaluated for their in vitro antitubercular activity against Mycobacterium tuberculosis (MTB) H₃₇Ra and Mycobacterium bovis BCG in active and dormant state using an established methods. Compounds 5a, 5m, and 5t were identified as the most active compounds against MTB. Molecular docking was performed against MTB enoyl-ACP (CoA) reductase (FabI/ENR/InhA) enzyme to predict the binding modes and affinity. The theoretical predictions from molecular docking could establish a link between the observed biological activity and the binding affinity shedding light into specific bonded and non-bonded interactions influencing the activity. The active compounds were studied for cytotoxicity against three cell lines and were found to be non-cytotoxic. Specificity of these compounds was checked by screening them for their antibacterial activity against four bacterial strains.     

Chemical Diversity and Potential Target Network of Woody Peony Flower Essential Oil from Eleven Representative Cultivars (Paeonia × suffruticosa Andr.)

Woody peony (Paeonia × suffruticosa Andr.) has many cultivars with genetic variances. The flower essential oil is valued in cosmetics and fragrances. This study was to investigate the chemical diversity of essential oils of eleven representative cultivars and their potential target network. Hydro-distillation afforded yields of 0.11–0.25%. Essential oils were analyzed by GC-MS and GC-FID which identified 105 compounds. Three clusters emerged from multivariate analysis, representative of phloroglucinol trimethyl ether (‘Caihui’), citronellol (‘Jingyu’, ‘Zhaofen’ and ‘Baiyuan Zhenghui’) and mixed (the rest of the cultivars) chemotypes. ‘Zhaofen’ and ‘Jingyu’ also exhibited low levels of other rose-related compounds. The main components were subjected to a target network approach. Drug-likeness screening gave 20 compounds with predictive blood–brain barrier permeation. Compound target network identified six key compounds, namely nerol, citronellol, geraniol, geranic acid, cis-3-hexen-1-ol and 1-hexanol. Top enriched terms in GO, KEGG and DisGeNET were mostly related to the central nervous system (CNS). Protein—protein interactions revealed a core network of 14 targets, 11 of which were CNS-related (targets for antidepressants, analgesics, antipsychotics, anti-Alzheimer’s and anti-Parkinson’s agents). This work provides useful information on the production of woody peony essential oils with specific chemotypes and reveals their potential importance in aromatherapy for alternative treatment of CNS disorders.     

Extraction and preparation of 5-lipoxygenase and acetylcholinesterase inhibitors from Astragalus membranaceus stems and leaves

In this study, an efficient method that employs 5-lipoxygenase and acetylcholinesterase as biological target molecules in receptor–ligand affinity ultrafiltration–liquid chromatography was developed for the screening of enzyme inhibitors derived from the Astragalus membranaceus stems and leaves. The effects of the extraction time, number of extraction cycles, ethanol concentration, and liquid–solid ratio on the total yield of the target compounds were investigated using response surface methodology, and the bioactive components were isolated using a combination of semi-preparative high-performance liquid chromatography and high-speed countercurrent chromatography via a two-phase solvent system consisting of n-hexane–ethyl acetate–methanol–water (1:6:2:6, v/v/v/v). Subsequently, 10 naturally-occurring bioactive components in the Astragalus membranaceus stems and leaves, including wogonin, ononin, isoquercitrin, calycosin-7-glucoside, 3-hydroxy-9,10-dimethoxyptercarpan, hyperoside, 7,2′-dihydroxy-3′,4′-dimethoxyisoflavan, baicalein, calycosin, and soyasaponin, were screened using affinity ultrafiltration to determine their potential effects against Alzheimer's disease. Consequently, all target compounds had purities higher than 95.0%, and the potential anti-Alzheimer's disease effect of the obtained bioactive compounds was verified using molecular docking analysis. Based on the results, the back-to-back screening of complex enzyme inhibitors and separation of the target bioactive compounds using complex chromatography could provide a new approach to the discovery and preparation of natural active ingredients.