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Nonalcoholic fatty liver disease (NAFLD) is a rising global public health concern due to its prevalence. Danning Tablets (DNt), a composite prescription of Chinese herbal medicine, shows significant curative effects on NAFLD in clinical application. This study aimed to decipher the bioactive substances and potential mechanisms of action of DNt in the treatment of NAFLD, applying an integrated network pharmacology approach. First, the bioactive compounds of DNt were screened based on their pharmacokinetic properties, and the corresponding drug targets were predicted. Then, the NAFLD-related targets were collected. The overlapping targets between the putative targets of DNt and NAFLD-related targets were identified as the potential therapeutic targets of DNt against NAFLD. Subsequently, the networks were constructed and analyzed, and the key bioactive compounds and targets were screened out depending on their importance in the networks. Functional enrichment analysis was carried out to elucidate the potential mechanisms of DNt acting on NAFLD. Finally, a molecular docking simulation was implemented to assess the potential binding affinity between the key targets and the bioactive compounds. As a result, 43 bioactive compounds of DNt and 69 putative targets were identified. Based on the network analysis, we found seven key bioactive compounds (quercetin, ß-sitosterol, luteolin, kaempferol, supraene, curcumenolactone C, and stigmasterol) of DNt might treat NAFLD via intervening IL6, MAPK8, VEGFA, CASP3, ALB, APP, MYC, PPARG, and RELA. The functional enrichment analysis revealed that DNt might affect NAFLD by modulating the signaling pathways involved in lipid metabolism, inflammation, oxidation, insulin resistance (IR), atherosclerosis, and apoptosis. Furthermore, most key bioactive compounds might bind firmly with the key targets. This study predicted the multicomponent, multitarget, and multipathway mechanisms of DNt in the treatment of NAFLD from a holistic perspective. DNt could be a promising agent for NAFLD, but further experimental verifications are still needed. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is now the second most deadly cancer globally. Chinese herbal medicine (CHM) plays an indispensable role in CRC treatment in China. However, the core herbs (the CHs) in the treatment of CRC and their underlying therapeutic mechanisms remain unclear. This study aims to uncovering the CHs and their mechanisms of action of CRC treatment, applying data mining and network pharmacology approach. First, CHM prescriptions treating CRC were collected from clinical studies from the Chinese National Knowledge Infrastructure (CNKI) and MEDLINE databases, and the CHs were identified through data mining. Then, the bioactive compounds and the corresponding putative targets of the CHs were obtained from three traditional Chinese medicine (TCM) databases. CRC related targets were acquired from three disease databases; the overlapping targets between the CHs and CRC were identified as the therapeutic targets. Subsequently, functional enrichment analysis was performed to elucidate the mechanisms of the CHs on CRC. Moreover, networks were constructed to screen the major bioactive compounds and therapeutic targets. Finally, prognostic values of the major target genes were evaluated by survival analysis, and molecular docking simulation was performed to assess the binding affinity of key targets and major bioactive compounds. It came out that 10 the CHs from 113 prescriptions and 190 bioactive compounds with 118 therapeutic targets were identified. The therapeutic targets were mainly enriched in the biological progress of transcription, apoptosis, and response to cytokine. Various cancer-associated signaling pathways, including microRNAs, TNF, apoptosis, PI3K-Akt, and p53, were involved. Furthermore, 15 major bioactive compounds and five key target genes (VEGFA, CASP3, MYC, CYP1Y1, and NFKB1) with prognostic significance were identified. Additionally, most major bioactive compounds might bind firmly to the key target proteins. This study provided an overview of the anti-CRC mechanisms of the CHs, which might refer to the regulation of apoptosis, transcription, and inflammation. [ABSTRACT FROM AUTHOR]

Objective. Chinese herbs play a positive role in the management of hepatocellular carcinoma (HCC) in China. However, it is not clear which of Chinese herbs are critical for the treatment of HCC. Besides, mechanisms of CCHs in the treatment of HCC remain unclear. Hence, our goal is to identify the core Chinese herbs (CCHs) for treating HCC and explore their antitumor mechanism. Methods. Firstly, clinical traditional Chinese medicine (TCM) prescriptions for HCC were collected from Chinese National Knowledge Infrastructure (CNKI) database, and then, data mining software was used to identify CCHs. After that, bioactive compounds and corresponding target genes of CCHs were obtained using three TCM databases, and target genes of HCC were acquired from MalaCards and OMIM. Subsequently, common target genes of CCHs and HCC were screened. Moreover, biological functions and pathways were analyzed, and Cytoscape plugin cytoHubba was used to identify hub genes. Finally, prognostic values of hub genes were verified by survival analysis, and the molecular docking approach was utilized to validate the interactions between targets and bioactive compounds of CCHs. Results. Eight CCHs were determined from 630 prescriptions, and 100 bioactive compounds (e.g., quercetin and luteolin) and 126 common target genes were screened. Furthermore, common target genes of CCHs and HCC were mainly enriched in cancer-associated pathways, and six hub genes with statistical significance in survival analysis were selected as key target genes for molecular docking. Additionally, molecular docking showed that the bioactive compounds docked well with the protein receptors of key target genes. Conclusion. By combining data mining, network pharmacology, molecular docking, and survival analysis methods, we found that CCHs may play a therapeutic role in HCC through regulating the target genes and pathways related to cancer occurrence and development, angiogenesis, metastasis, and prognosis. [ABSTRACT FROM AUTHOR]

Objective. In this study, the data mining method was used to screen the core Chinese materia medicas (CCMMs) against primary liver cancer (PLC), and the potential mechanisms of CCMMs in treating PLC were analyzed based on network pharmacology. Methods. Traditional Chinese medicine (TCM) prescriptions for treating PLC were obtained from a famous TCM doctor in Shenzhen, China. According to the data mining technique, the TCM Inheritance Support System (TCMISS) was applied to excavate the CCMMs in the prescriptions. Then, bioactive ingredients and corresponding targets of CCMMs were collected using three different TCM online databases, and target genes of PLC were obtained from GeneCards and OMIM. Afterwards, common targets of CCMMs and PLC were screened. Furthermore, a network of CCMMs bioactive ingredients and common target gene was constructed by Cytoscape 3.7.1, and gene ontology (GO) and signaling pathways analyses were performed to explain the mechanism of CCMMs in treating PLC. Besides, protein-protein interaction (PPI) analysis was used to identify key target genes of CCMMs, and the prognostic value of key target genes was verified using survival analysis. Results. A total of 15 high-frequency Chinese materia medica combinations were found, and CCMMs (including Paeoniae Radix Alba, Radix Bupleuri, Macrocephalae Rhizoma, Coicis Semen, Poria, and Curcumae Radix) were identified by TCMISS. A total of 40 bioactive ingredients (e.g., quercetin, kaempferol, and naringenin) of CCMMs were obtained, and 202 common target genes of CCMMs and PLC were screened. GO analysis indicated that biological processes of CCMMs were mainly involved in response to drug, response to ethanol, etc. Pathway analysis demonstrated that CCMMs exerted its antitumor effects by acting on multiple signaling pathways, including PI3K-Akt, TNF, and MAPK pathways. Also, some key target genes of CCMMs were determined by PPI analysis, and four genes (MAPK3, VEGFA, EGF, and EGFR) were found to be correlated with survival in PLC patients. Conclusion. Based on data mining and network pharmacology methods, our results showed that the therapeutic effect of CCMMs on PLC may be realized by acting on multitargets and multipathways related to the occurrence and development of PLC. [ABSTRACT FROM AUTHOR]