Network pharmacology, a promising approach to reveal the pharmacology mechanism of Chinese medicine formula.

Abstract Network pharmacology (NP) provides a new methodological perspective for understanding traditional medicine from a holistic perspective, giving rise to frontiers such as traditional Chinese medicine network pharmacology (TCM-NP). With the development of artificial intelligence (AI) technology, it is key for NP to develop network-based AI methods to reveal the treatment mechanism of complex diseases from massive omics data. In this review, focusing on the TCM-NP, we summarize involved AI methods into three categories: network relationship mining, network target positioning and network target navigating, and present the typical application of TCM-NP in uncovering biological basis and clinical value of Cold/Hot syndromes. Collectively, our review provides researchers with an innovative overview of the methodological progress of NP and its application in TCM from the AI perspective.

Network pharmacology: towards the artificial intelligence-based precision traditional Chinese medicine

Network pharmacology approaches for research of Traditional Chinese Medicines.

Genomic data have demonstrated considerable traction in accelerating contemporary studies in traditional medicine. However, the lack of a uniform format and dispersed storage limits the full potential of herb genomic data. In this study, we developed a Global Pharmacopoeia Genome Database (GPGD). The database contains 34,346 records for 903 herb species from eight global pharmacopoeias (Brazilian, Egyptian, European, Indian, Japanese, Korean, the Pharmacopoeia of the People's Republic of China, and U.S. Pharmacopoeia's Herbal Medicines Compendium). In particular, the GPGD contains 21,872 DNA barcodes from 867 species, 2,203 organelle genomes from 674 species, 55 whole genomes from 49 species, 534 genomic sequencing datasets from 366 species, and 9,682 transcriptome datasets from 350 species. Among the organelle genomes, 534 genomes from 366 species were newly generated in this study. Whole genomes, organelle genomes, genomic fragments, transcriptomes, and DNA barcodes were uniformly formatted and arranged by species. The GPGD is publicly accessible at http://www.gpgenome.com and serves as an essential resource for species identification, decomposition of biosynthetic pathways, and molecular-assisted breeding analysis. Thus, the database is an invaluable resource for future studies on herbal medicine safety, drug discovery, and the protection and rational use of herbal resources.

/pdf/global-pharmacopoeia-genome-database-is-an-integrated-and-hray6p6oo3.pdf

Global Pharmacopoeia Genome Database is an integrated and mineable genomic database for traditional medicines derived from eight international pharmacopoeias.

Rhizoma polygonati (Huangjing, RP) has been used for a long history with many chemical components in inducing anti-cancer, anti-aging, anti-diabetes, anti-fatigue, and more prevention of diseases or acts as nutrition sources in food. Here we investigated RP extract combination with kinase inhibitors in anti-cell growth and blockade in pathways targeting kinases. Experimental investigation and network pharmacology analysis were applied to test the potent kinase-mediated signaling. Herbzyme activity was determined by substrate with optical density measurement. Extract of processed RP inhibits cell growth in a much greater manner than alone when applied in combination with inhibitors of mTOR or EGFR. Moreover, processing methods of RP from Mount Tai (RP-Mount Tai) play essential roles in herbzyme activity of phosphatase suggesting the interface is also essential, in addition to the chemical component. The network pharmacology analysis showed the chemical component and target networks involving AKT and mTOR, which is consistent with experimental validation. Finally, EGFR inhibitor could be associated with nano-extract of RP-Mount Tai but not significantly affects the phosphatase herbzyme activity in vitro. Thus the processed extract of RP-Mount Tai may play a dual role in the inhibition of cell proliferation signaling by both chemical component and nanoscale herbzyme of phosphatase activity to inhibit kinases including mTOR/AKT in potent drug delivery of kinase inhibitors.

Network pharmacology and experimental investigation of Rhizoma polygonati extract targeted kinase with herbzyme activity for potent drug delivery.

Pharmacotranscriptomics has become a powerful approach for evaluating the therapeutic efficacy of drugs and discovering new drug targets. Recently, studies of traditional Chinese medicine (TCM) have increasingly turned to high-throughput transcriptomic screens for molecular effects of herbs/ingredients. And numerous studies have examined gene targets for herbs/ingredients, and link herbs/ingredients to various modern diseases. However, there is currently no systematic database organizing these data for TCM. Therefore, we built HERB, a high-throughput experiment- and reference-guided database of TCM, with its Chinese name as BenCaoZuJian. We re-analyzed 6164 gene expression profiles from 1037 high-throughput experiments evaluating TCM herbs/ingredients, and generated connections between TCM herbs/ingredients and 2837 modern drugs by mapping the comprehensive pharmacotranscriptomics dataset in HERB to CMap, the largest such dataset for modern drugs. Moreover, we manually curated 1241 gene targets and 494 modern diseases for 473 herbs/ingredients from 1966 references published recently, and cross-referenced this novel information to databases containing such data for drugs. Together with database mining and statistical inference, we linked 12 933 targets and 28 212 diseases to 7263 herbs and 49 258 ingredients and provided six pairwise relationships among them in HERB. In summary, HERB will intensively support the modernization of TCM and guide rational modern drug discovery efforts. And it is accessible through http://herb.ac.cn/.

HERB: a high-throughput experiment- and reference-guided database of traditional Chinese medicine.

Background: Molecular characteristics can be good indicators of tumor prognosis and have been introduced into the classification of gliomas. The prognosis of patients with newly classified lower-grade gliomas (LGGs, including grade 2 and grade 3 gliomas) is highly heterogeneous, and new molecular markers are urgently needed. Methods: Autophagy related genes (ATGs) were obtained from Human Autophagy Database (HADb). From the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA), gene expression profiles including ATG expression information and patient clinical data were downloaded. Cox regression analysis, receiver operating characteristic (ROC) analysis, Kaplan-Meier analysis, random survival forest algorithm (RSFVH) and stratification analysis were performed. Results: Through univariate Cox regression analysis, we found a total of 127 ATGs associated with the prognosis of LGG patients from TCGA dataset and a total of 131 survival-related ATGs from CGGA dataset. Using TCGA dataset as the training group (n = 524), we constructed a five-ATG signature (including BAG1, BID, MAP1LC3C, NRG3, PTK6), which could divide LGG patients into two risk groups with significantly different overall survival (Log Rank P < 0.001). Then we confirmed in the independent CGGA dataset that the five-ATG signature had the ability to predict prognosis (n = 431, Log Rank P < 0.001). We further discovered that the predictive ability of the five-ATG signature was better than the existing clinical indicators and IDH mutation status. In addition, the five-ATG signature could further classify patients after receiving radiotherapy or chemotherapy into groups with different prognosis. Conclusions: We identified a five-ATG signature that could be a reliable prognostic marker and might be therapeutic targets for autophagy therapy for LGG patients.

/pdf/prognostic-value-of-an-autophagy-related-five-gene-signature-4yakgguuoe.pdf

Prognostic Value of an Autophagy-Related Five-Gene Signature for Lower-Grade Glioma Patients.

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HERB: a high-throughput experiment- and reference-guided database of traditional Chinese medicine.

Prognostic Value of an Autophagy-Related Five-Gene Signature for Lower-Grade Glioma Patients.