TarNet: An Evidence-Based Database for Natural Medicine Research

PlantMedOman: an online database for Oman's medicinal plants

The Sultanate of Oman has a rich biodiversity, particularly in medicinal plants, and plays a crucial role in traditional healthcare practices. However, the wealth of knowledge about these plants is scattered across various literature, making it challenging for researchers, practitioners, and the public to access comprehensive information. Therefore, the availability of a centralized, user-friendly online database to catalog Oman's medicinal plants is of great importance. PlantMedOman presented here, which currently holds 186 records helps to enhance academic research, support drug discovery studies, promote the conservation of medicinal plants, and foster greater awareness of Oman's ethnomedicinal heritage.

Evaluation of the key active ingredients of 'Radix Astragali and Rehmanniae Radix Mixture' and related signaling pathways involved in ameliorating diabetic foot ulcers from the perspective of TCM-related theories

BACKGROUND AND OBJECTIVE

Traditional Chinese Medicine is more inclined to holistic thinking than most modern pharmacological research. The multiple components and targets of traditional Chinese medicine have become a stumbling block in the study of drug action mechanisms in the life sciences. The current study aimed to reveal the active ingredients of "Radix Astragali and Rehmanniae Radix Mixture (RA-RRM)" involved in ameliorating diabetic foot ulcers and to analyze the related signaling pathways.

METHOD

The Traditional Chinese Medicine Systems Pharmacology Data base and Analysis Platform (TCMSP) was used to screen the active ingredients in RA-RRM based on the evaluation of the molecular weight (MW), bioavailability (OB), and transport of these active ingredients across intestinal epithelial cells (Caco-2) and the blood-brain barrier (BBB). The PubChem database was used to illustrate the structural formula and SMILES of these active ingredients in RA-RRM. The Swiss Target Prediction Database, DrugBank, Genecards, and CTD were used to predict the targets that were correlated with RA-RRM-based treatment of diabetic foot ulcers. Cytoscape 3.7.0 software was used to construct the protein/gene interaction network diagram, compound target interaction network diagram, and target pathway network diagram for these active ingredients in the amelioration of diabetic foot ulcers in RA-RRM. Topological parameter calculations of target information using Cytoscape 3.7.0 software yielded drug-disease targets were used to reveal the relationship between key active ingredients in RA-RMM and targets of interest for the treatment of diabetic foot. The disease targets of drug action were imported into the David database (GO and KEGG analysis) to analyze the enriched pathways and biological processes.

RESULTS

The following results were obtained using the abovementioned screening and analysis. Fourteen key active ingredients in RA-RRM and 309 targets were found; among them, 85 targets were found to be related to diabetic foot ulcers using TCMSP. Twenty-three biological processes, 7 cell components and 14 molecular functions were found to ameliorate diabetic foot ulcers using GO analysis. In addition, 29 signaling pathways were found to be involved in RA-RRM-induced amelioration, including the NF-κB, TNF, TGF-β, VEGF, and HIF-1 signaling pathways, using KEGG analysis.

CONCLUSIONS

Based on current available evidence obtained from the abovementioned data/information databases and based on the perspective of TCM-related theories, the present study revealed the key active ingredients in RA-RRM and related signaling pathways in the treatment of diabetic foot ulcers, promoting further studies on and clinical applications of RA-RRM.

Literature based discovery of alternative TCM medicine for adverse reactions to depression drugs

Background

In recent years, Traditional Chinese Medicine (TCM) and alternative medicine have been widely used along with western drugs as a complementary form of treatment. In this study, we first use the scientific literature to identify western drugs with obvious side effects. Then, we find TCM alternatives for these western drugs to ameliorate their side effects.

Results

We used depression as a case study. To evaluate our method, we showed the relation between herb-ingredients-target-disease for representative alternative herbs of western drugs. Further, a protein-protein interaction network of western drugs and alternative herbs was produced, and we performed enrichment analysis of the targets of the active ingredients of the herbs and examined the enrichment of Gene Ontology terms for Biological Process, Cellular Component, and Molecular Function and KEGG Pathway levels, to show how these targets affect different levels of gene expression.

Conclusion

Our proposed method is able to select herbs that are highly relevant to the target indication (depression) and are able to treat the side effects caused by the target drug. The compounds from our selected alternative herbal medicines can therefore be complementary to the western drugs and ameliorate their side effects, which may help in the development of new drugs.

Bioinformatics-assisted, integrated omics studies on medicinal plants

The immense therapeutic and economic values of medicinal plants have attracted increasing attention from the worldwide researchers. It has been recognized that production of the authentic and high-quality herbal drugs became the prerequisite for maintaining the healthy development of the traditional medicine industry. To this end, intensive research efforts have been devoted to the basic studies, in order to pave a way for standardized authentication of the plant materials, and bioengineering of the metabolic pathways in the medicinal plants. In this paper, the recent advances of omics studies on the medicinal plants were summarized from several aspects, including phenomics and taxonomics, genomics, transcriptomics, proteomics and metabolomics. We proposed a multi-omics data-based workflow for medicinal plant research. It was emphasized that integration of the omics data was important for plant authentication and mechanistic studies on plant metabolism. Additionally, the computational tools for proper storage, efficient processing and high-throughput analyses of the omics data have been introduced into the workflow. According to the workflow, authentication of the medicinal plant materials should not only be performed at the phenomics level but also be implemented by genomic and metabolomic marker-based examination. On the other hand, functional genomics studies, transcriptional regulatory networks and protein-protein interactions will contribute greatly for deciphering the secondary metabolic pathways. Finally, we hope that our work could inspire further efforts on the bioinformatics-assisted, integrated omics studies on the medicinal plants.

Natural Product Target Network Reveals Potential for Cancer Combination Therapies

A body of research demonstrates examples of in vitro and in vivo synergy between natural products and anti-neoplastic drugs for some cancers. However, the underlying biological mechanisms are still elusive. To better understand biological entities targeted by natural products and therefore provide rational evidence for future novel combination therapies for cancer treatment, we assess the targetable space of natural products using public domain compound-target information. When considering pathways from the Reactome database targeted by natural products, we found an increase in coverage of 61% (725 pathways), relative to pathways covered by FDA approved cancer drugs collected in the Cancer Targetome, a resource for evidence-based drug-target interactions. Not only is the coverage of pathways targeted by compounds increased when we include natural products, but coverage of targets within those pathways is also increased. Furthermore, we examined the distribution of cancer driver genes across pathways to assess relevance of natural products to critical cancer therapeutic space. We found 24 pathways enriched for cancer drivers that had no available cancer drug interactions at a potentially clinically relevant binding affinity threshold of < 100nM that had at least one natural product interaction at that same binding threshold. Assessment of network context highlighted the fact that natural products show target family groupings both distinct from and in common with cancer drugs, strengthening the complementary potential for natural products in the cancer therapeutic space. In conclusion, our study provides a foundation for developing novel cancer treatment with the combination of drugs and natural products.