Background and Objectives: Type 2 diabetes mellitus (T2DM) is a global health concern affecting more than 400 million people worldwide. Diabetic neuropathy, nephropathy, retinopathy, and cardiovascular complications lead to debilitating effects to patients. To prevent these, the treatment goal is to lower the blood sugar levels and maintain at a normal range which is achieved through conventional treatments like insulin and oral hypoglycemic agents. However, the high cost of these medications implicates patient treatment outcomes. Hence, alternatives are sought for including the use of herbal medicines. Momordica charantia (MC) and Lagerstroemia speciosa (LS) are common herbal medicines used to manage T2DM. In the Philippines, these herbal preparations are validated for their glucose lowering effects and are commonly found in combination in food supplements. The study aims to screen the possible mechanisms of compounds present in these herbal medicines which can offer possible explanations for their synergistic effects and rationalization of their combination in preparations. Methods: Network pharmacology was employed to determine pivotal proteins that are targeted by MC and LS compounds. Molecular docking was then done to evaluate the favorability of the binding of these compounds toward their target proteins. Results: Our results showed that TNF, HSP90AA1, MAPK3, ALDH2, GCK, AKR1B1, TTR and RBP4 are the possible pivotal targets of MC and LS compounds in T2DM. Conclusion Terpenoids from MC and decanoic acid from LS are the compounds which showed favorable binding towards pivotal protein targets in T2DM. By binding towards the different key proteins in T2DM, they may exhibit their synergistic effects. However, the results of this study are bound to the limitations of computational methods and experimental validation are needed to verify our findings.
Molecular Docking Simulation ; Network Pharmacology ; Momordica charantia

To optimize the extraction process of Chuanxiong Rhizoma-Gastrodiae Rhizoma herb pair by network pharmacology combined with analytic hierarchy process(AHP)-entropy weight method and multi-index orthogonal test. The potential active components and targets of Chuanxiong Rhizoma-Gastrodiae Rhizoma were screened by network pharmacology and molecular docking, and the process evaluation indexes were determined with reference to the Chinese Pharmacopoeia(2020 edition). The core components of Chuanxiong Rhizoma-Gastrodiae Rhizoma were determined as gastrodin, parishin B, parishin C, parishin E, ferulic acid, and 3-butylphthalide. With the extraction volume of each indicator and yield of dry extract as comprehensive evaluation indicators, the extraction conditions were optimized by the AHP-entropy weight method and orthogonal test as the ethanol volume of 50%, the solid-liquid ratio of 1∶8(g·mL~(-1)), extraction for three times, and 1.5 h each time. Through network pharmacology and molecular docking, the process evaluation index was determined, and the optimized process was stable and reproducible for the extraction of Chuanxiong Rhizoma-Gastrodiae Rhizoma herb pair, which could provide reference for in-depth research.
Drugs, Chinese Herbal/pharmacology* ; Network Pharmacology ; Molecular Docking Simulation ; Rhizome

The resin ethanol extract of Gegen Qinlian Decoction(GGQLD) has been found to significantly alleviate the intestinal toxicity caused by Irinotecan, but further research is needed to establish its overall quality and clinical medication standards. This study aimed to establish an HPLC characteristic fingerprint of the resin ethanol extract of GGQLD, predicted the targets and signaling pathways of its pharmacological effects based on network pharmacology, identified core compounds with pharmacological relevance, and analyzed potential quality markers(Q-markers) of the resin eluate of GGQLD for relieving Irinotecan-induced toxicity. By considering the uniqueness, measurability, and traceability of Q-markers based on the "five principles" of Q-markers and combining them with network pharmacology techniques, the overall efficacy of the resin ethanol extract of GGQLD can be characterized. Preliminary predictions suggested that the four components of puerarin, berberine, baicalin, and baicalein might serve as potential Q-markers for the resin etha-nol extract of GGQLD. This study provides a basis and references for the quality control and clinical mechanism of the resin ethanol extract of GGQLD.
Irinotecan ; Network Pharmacology ; Drugs, Chinese Herbal/therapeutic use*

Qijiao Shengbai Capsules(QJ) can invigorate Qi and replenish the blood, which is commonly used clinically for adjuvant treatment of cancer and leukopenia due to chemoradiotherapy. However, the pharmacological mechanism of QJ is still unclear. This work aims to combine the high-performance liquid chromatography(HPLC) fingerprints and network pharmacology to clarify the effective components and mechanism of QJ. The HPLC fingerprints of 20 batches of QJ were established. The similarity evaluation among 20 batches of QJ was performed by using Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine(version 2012), resulting in a similarity greater than 0.97. Eleven common peaks were identified by reference standard, including ferulic acid, calycosin 7-O-glucoside, ononin, calycosin, epimedin A, epimedin B, epimedin C, icariin, formononetin, baohuoside I, and Z-ligustilide. The "component-target-pathway" network was constructed by network pharmacy, and 10 key components in QJ were identified, such as ferulic acid, calycosin 7-O-glucoside, ononin, and calycosin. The components were involved in the phosphoinositide 3 kinase-protein kinase B(PI3K-Akt), mitogen-activated protein kinase(MAPK), and other signaling pathways by regulating potential targets, including EGFR, RAF1, PIK3R1, and RELA, to auxiliarily treat tumors, cancers, and leukopenia. The molecular docking conducted on the AutoDock Vina platform confirmed the high binding activity of 10 key effective components with core targets, with the binding energy less than-5 kcal·mol~(-1). In this study, the effective components and mechanism of QJ have been preliminary revealed based on HPLC fingerprint and network pharmacology, which provided a basis for quality control of QJ and a refe-rence for further study on its mechanism.
Network Pharmacology ; Capsules ; Molecular Docking Simulation ; Phosphatidylinositol 3-Kinases ; Drugs, Chinese Herbal/pharmacology*

Traditional Chinese medicine(TCM) has unique advantages in the prevention and treatment of diseases owing to its holistic view and more than 2 000 years of experience in the clinical use of natural medicine. The "holistic" characteristic of TCM gives birth to a new generation of research paradigm featuring "network" and "system", which has been developing rapidly in the era of biomedical big data and artificial intelligence. Network pharmacology, a representative research field, provides new ideas and methods for the research of the interdiscipline of artificial intelligence and medicine, the analysis of massive biomedical data, and the transformation from data to knowledge. TCM plays an important role in proposing the core theory of "network target" and promoting the establishment and development of network pharmacology, and has taken the lead in formulating the first international standard of network pharmacology--Network Pharmacology Evaluation Method Guidance. In terms of theory, network target can systematically link drugs and diseases and quantitatively interpret the overall regulatory mechanism of drugs. In the aspect of method, network pharmacology is developing towards a research model that combines computational, experimental, and clinical approaches. This review introduces the resent important progress of TCM network pharmacology in predicting drug targets, understanding the biological basis of drugs and diseases, and searching for disease and syndrome biomarkers. Under the guidance of Network Pharmacology Evaluation Method Guidance, the development of network pharmacology is expected to become more and more standardized and healthy. Network target will help produce more high-quality research outcomes in TCM and effectively boost the modernization and internationalization of TCM.
Artificial Intelligence ; Drugs, Chinese Herbal/pharmacology* ; Medicine, Chinese Traditional ; Network Pharmacology ; Research Design

The present study explored the underlying mechanism of Astragali Radix-Curcumae Rhizoma-Paridis Rhizoma(AR-CR-PR) in the treatment of colorectal cancer(CRC) by network pharmacology and molecular docking and animal tests and verified the core targets based on the orthotopic transplantation model in nude mice. The active components of AR-CR-PR were retrieved from databases such as TCMSP. The targets of drugs and the disease were obtained from PubChem, SwissTargetPrediction, TTD, and DrugBank, and the intersection targets were imported into STRING for the analysis of the protein-protein interaction(PPI). Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) analyses were performed through DAVID. AutoDock Vina was used to perform molecular docking and binding ability prediction between the active components and the core targets. The effects of AR-CR-PR on tumor growth, metastasis, and phosphorylation of core target proteins in tumor tissues based on the orthotopic transplantation model in nude mice. As revealed by network pharmacology, AR-CR-PR contained nine core components, such as quercetin, curcumin, and β-ecdysone, and the key targets included protein kinase B(AKT1), mitogen-activated protein kinase 3(MAPK3), MAPK1, and epithelial growth factor receptor(EGFR), which was indicated that the anti-CRC effect of AR-CR-PR was presumedly achieved by regulating tumor cell proliferation, apoptosis, migration, and angiogenesis through PI3 K-AKT, MAPK and other signaling pathways. The results of molecular docking showed that the nine core components had strong binding abilities to AKT1 and MAPK3. The results in vivo showed that AR-CR-PR could reduce the volume of the orthotopic tumor, inhibit liver metastasis, and decrease the phosphorylation of AKT1 and MAPK3 in the CRC model. The mechanism of AR-CR-PR in the intervention of CRC may be related to the activation of PI3 K-AKT and MAPK signaling pathway. This study provides a scientific basis for the clinical application of AR-CR-PR in the treatment of CRC and ideas for modern research on AR-CR-PR.
Animals ; Drugs, Chinese Herbal/pharmacology* ; Mice ; Mice, Nude ; Molecular Docking Simulation ; Neoplasms ; Network Pharmacology ; Rhizome

This study analyzed the molecular mechanism of Huangjing Qianshi Decoction(HQD) in the treatment of prediabetes based on network pharmacology and molecular docking. The active components of HQD were identified and screened based on Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP, http://Lsp.nwu.edu.cn/tcmsp.php) and then the targets of the components and the genes related to prediabetes were retrieved, followed by identifying the common targets of the decoction and the disease. The medicinal component-target network was constructed by Cytoscape to screen key components. The protein-protein interaction(PPI) network was established by STRING and hub genes were identified by Cytoscape-CytoNCA, followed by Gene Ontology(GO) term enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG) of the hub genes with R-clusterProfi-ler. Thereby, the possible signaling pathways were predicted and the molecular mechanism was deduced. A total of 79 active components of HQD and 785 diabetes-related targets of the components were screened out. The hub genes mainly involved the GO terms of tricarboxylic acid cycle, peptide binding, amide binding, hydrolase activity, and kinase activity regulation, and the KEGG pathways of AGE-RAGE signaling pathway, TNF signaling pathway, AMPK signaling pathway, IL-17 signaling pathway, and insulin signaling pathway. Western blot result showed that HQD-containing serum significantly reduced the expression of AKT1, AGE, and RAGE proteins in insulin resistance model cells. HQD's treatment of prediabetes is characterized by multiple pathways, multiple targets, and multiple levels. The main mechanism is that the components zhonghualiaoine, baicalein, kaempferol, and luteolin act on AKT1 and inhibit the AGE-RAGE axis.
Drugs, Chinese Herbal/pharmacology* ; Humans ; Medicine, Chinese Traditional ; Molecular Docking Simulation ; Network Pharmacology ; Prediabetic State/genetics*

This study aimed to explore the anti-depressant components of Rehmanniae Radix and its action mechanism based on network pharmacology combined with molecular docking. The main components of Rehmanniae Radix were identified by ultra-high performance liquid chromatography-quadrupole/Orbitrap high resolution mass spectrometry(UPLC-Q-Orbitrap HRMS), and the related targets were predicted using SwissTargetPrediction. Following the collection of depression-related targets from GeneCards, OMIM and TTD, a protein-protein interaction(PPI) network was constructed using STRING. GO and KEGG pathway enrichment analysis was performed by Metascape. Cytoscape 3.7.2 was used to construct the networks of "components-targets-disease" and "components-targets-pathways", based on which the key targets and their corresponding components were obtained and then preliminarily verified by molecular docking. Rehmanniae Radix contained 85 components including iridoids, ionones, and phenylethanoid glycosides. The results of network analysis showed that the main anti-depressant components of Rehmanniae Radix were catalpol, melittoside, genameside C, gardoside, 6-O-p-coumaroyl ajugol, genipin-1-gentiobioside, jiocarotenoside A1, neo-rehmannioside, rehmannioside C, jionoside C, jionoside D, verbascoside, rehmannioside, cistanoside F, and leucosceptoside A, corresponding to the following 16 core anti-depression targets: AKT1, ALB, IL6, APP, MAPK1, CXCL8, VEGFA, TNF, HSP90 AA1, SIRT1, CNR1, CTNNB1, OPRM1, DRD2, ESR1, and SLC6 A4. As revealed by molecular docking, hydrogen bonding and hydrophobicity might be the main action forms. The key anti-depression targets of Rehmanniae Radix were concentrated in 24 signaling pathways, including neuroactive ligand-receptor interaction, neurodegenerative disease-multiple diseases pathway, phosphatidylinositol 3-kinase/protein kinase B pathway, serotonergic synapse, and Alzheimer's disease.
Drugs, Chinese Herbal/pharmacology* ; Humans ; Molecular Docking Simulation ; Network Pharmacology ; Neurodegenerative Diseases ; Plant Extracts ; Rehmannia

This study aims to establish a method for analyzing the chemical constituents in Cistanches Herba by high performance liquid chromatography(HPLC) and quadrupole-time-of-flight tandem mass spectrometry(HPLC-Q-TOF-MS/MS), and to reveal the pharmacological mechanism based on network pharmacology for mining the quality markers(Q-markers) of Cistanches Herba. The chemical constituents of Cistanche deserticola and C. tubulosa were analyzed via HPLC-Q-TOF-MS/MS. The potential targets and pathways of Cistanches Herba were predicted via SwissTargetPrediction and DAVID. The compound-target-pathway-pharmacological action-efficacy network was constructed via Cytoscape. A total of 47 chemical constituents were identified, involving 95 targets and 56 signaling pathways. We preliminarily elucidated the pharmacological mechanisms of echinacoside, acteoside, isoacteoside, cistanoside F, 2'-acetylacteoside, cistanoside A, campneoside Ⅱ, salidroside, tubuloside B, 6-deoxycatalpol, 8-epi-loganic acid, ajugol, bartsioside, geniposidic acid, and pinoresinol 4-O-β-D-glucopyranoside, and predicted them to be the Q-markers of Cistanches Herba. This study identified the chemical constituents of Cistanches Herba, explained the pharmacological mechanism of the traditional efficacy of Cistanches Herba based on network pharmacology, and introduced the core concept of Q-markers to improve the quality evaluation of Cistanches Herba.
Chromatography, High Pressure Liquid/methods* ; Cistanche ; Drugs, Chinese Herbal/pharmacology* ; Network Pharmacology ; Tandem Mass Spectrometry/methods*

Two terpenes, 3-keto-tirucalla-8,24-dien-21-oic acid(KTDA) and 2-methoxy-5-acetoxy-furanogermacr-1(10)-en-6-one(FSA), are isolated from Olibanum and Myrrha respectively, which are characterized by high yield and easy crystallization during the preparation. The present study explored the regulatory targets and anti-inflammatory mechanism of KTDA and FSA based on network pharmacology and cell viability assay. First, the drug-likeness of KTDA and FSA was predicted by Swiss ADME. The target prediction of active components was carried out by Swiss Target Prediction and Pharmmapper. TTD, Drug Bank, and Gene Cards were searched for inflammation-related target genes of KTDA and FSA. Protein-protein interaction(PPI) analysis was performed on the inflammatory targets of KTDA and FSA by STRING, and Cytoscape was used to conduct topological analysis of the interaction results and construct the PPI network. GO function and KEGG pathway enrichment analyses of inflammatory targets of KTDA and FSA were carried out by DAVID, and a " component-target-pathway" network was constructed. Finally, lipopolysaccharide(LPS)-induced RAW264. 7 cells were treated with KTDA and FSA at different concentrations, and nitric oxide(NO) concentration and protein and m RNA expression levels were detected. The results showed that both KTDA and FSA showed good drug-likeness. A total of 157 and 142 inflammation-related targets of KTDA and FSA were screened out. PPI network analysis showed that MAPK1, AKT1, MAPK8, PIK3 CA,PIK3 R1, EGFR, etc. might be the key proteins for the anti-inflammatory effect. PI3 K/AKT and MAPK signaling pathways were obtained by KEGG and GO-BP enrichment. Cell experiment results showed that KTDA and FSA could exert anti-inflammatory effects by inhibiting NO production, reducing the phosphorylation levels of JNK, p38, and AKT proteins, and down-regulating the m RNA expression of interleukin(IL)-1β and IL-6. Meanwhile, FSA could also inhibit ERK phosphorylation. The results indicated that KTDA and FSA had significant anti-inflammatory activity, which provided a scientific basis and important support for the further research,development, and utilization of Olibanum and Myrrha.
Animals ; Ants ; Drugs, Chinese Herbal/pharmacology* ; Frankincense ; Lipopolysaccharides ; Molecular Docking Simulation ; Network Pharmacology