Network understanding of herb medicine via rapid identification of ingredient-target interactions

Insights into the structure and drug design of benzimidazole derivatives targeting the epidermal growth factor receptor (EGFR)

Tyrosine kinase overexpression could result in an unfavourable consequence of cancer progression in the body. A number of kinase inhibitor drugs targeting various cancer-related protein kinases have been developed and proven successful in clinical therapy. Benzimidazole is one of the most studied scaffolds in the search for effective anticancer drugs. The association of various functional groups and the structural design of the compounds may influence the binding towards the receptor. Despite numerous publications on the design, synthesis and biological assays of benzimidazole derivatives, their inhibitory activities against epidermal growth factor receptor (EGFR), a receptor tyrosine kinase (RTK), have not been specifically analysed. This review covers recent research reports on the anticancer activity of benzimidazole derivatives focusing on EGFR expression cell lines, based on their structure-activity relationship study. We believe it would aid researchers to envision the challenges and explore benzimidazole's potentials as tyrosine kinase inhibitors.

Efficacy and safety of Brucea javanica oil emulsion injection as adjuvant therapy for cancer: An overview of systematic reviews and meta-analyses

BACKGROUND

In China, Brucea javanica oil emulsion injection (BJOEI) has been used as adjuvant therapy to treat cancer for many years. Many systematic reviews (SRs) or meta-analyses (MAs) were published to evaluate its efficacy and safety. Nevertheless, uneven quality made it difficult to reach a consensus and there has been no specific review to integrate the evidence of BJOEI for cancer at present. Therefore, a comprehensive evidence map is needed to guide clinicians.

PURPOSE

We, for the first time, conducted an overview to assess the SRs/MAs of BJOEI, and provided a comprehensive evidence map to guide clinicians. Besides, this study provided a promising direction for future research to promote the generation of advanced evidence.

STUDY DESIGN

An overview of SRs or MAs.

METHODS

The pre-defined search strategies were applied to 8 databases. Suitable SRs/MAs were included according to the inclusion and exclusion criteria. Methodological quality, reporting quality, and risk of bias were assessed. An evidence map was conducted to show the situation of clinical evidence.

RESULTS

27 SRs/MAs in 7 cancer types were included in this overview. The main problems of SRs/MAs were concentrated on the following aspects: without registration or protocol, lacking gray literature retrieval and a list of excluded studies, incomplete description in the literature retrieval strategy or the methods of merging results, the bias of each synthetic result, less exploration in heterogeneity or publication bias, deficiencies in assessing evidence quality and less description in conflict, funding or access to relevant information. Based on the rules of GRADE, the evidence quality of 154 items in 27 SRs/MAs was defined as moderate quality (103 items), low-quality (44 items), and very low-quality (7 items). Especially, risk of bias (154 items), imprecision (27 items), inconsistency (20 items), and publication bias (9 items) were the main downgrading factors.

CONCLUSION

BJOEI may be a promising adjuvant therapy for treating cancer, especially in the digestive system. However, high-quality SRs/MAs are expected to be carried out to improve the reliability of the above conclusion in the future.

A Mechanism of Action Study on Danggui Sini Decoction to Discover Its Therapeutic Effect on Gastric Cancer

Danggui Sini Decoction (DSD), a classic Chinese herb medicine (CHM) formula, has been used to treat various diseases in China for centuries. However, it remains challenging to reveal its mechanism of action through conventional pharmacological methods. Here, we first explored the mechanism of action of DSD with the assistance of network pharmacology and bioinformatic analysis tools, and found a potential therapeutic effect of DSD on cancer. Indeed, our in vivo experiment demonstrated that oral administration of DSD could significantly inhibit the growth of xenografted gastric cancer (GC) on mice. The subsequent enrichment analyses for 123 candidate core targets evacuated from the drug/disease-target protein-protein interaction network showed that DSD could affect the key biological processes involving the survival and growth of GC cells, such as apoptosis and cell cycle, and the disturbance of these biological processes is likely attributed to the simultaneous inhibition of multiple signaling pathways, including PI3K/Akt, MAPK, and p53 pathways. Notably, these in silico results were further validated by a series of cellular functional and molecular biological assays in vitro. Moreover, molecular docking analysis suggested an important role of MCM2 in delivering the pharmacological activity of DSD against GC. Together, these results indicate that our network pharmacology and bioinformatics-guided approach is feasible and useful in exploring not only the mechanism of action, but also the "new use" of the old CHM formula.

Evaluation of the combinatorial effect of Tinospora cordifolia and Zingiber officinale on human breast cancer cells

The present study was aimed to investigate the anticancer potential of the combination treatment of Tinospora cordifolia (TC) and Zingiber officinale (ZO) using network pharmacology approach. In silico analysis of the anticancer activity of TC + ZO was carried out using Cytoscape 3.2.0 software to elucidate the mechanism. The MTT assay confirms the combination of TC and ZO is more active (IC₅₀; 2 μg ml^-1) as compared to TC (509 μg ml^-1) and ZO (1 mg ml^-1) alone in MCF-7 cells. The TC + ZO combination treatment inhibits DNA synthesis, migration, and induces apoptosis in MCF-7 cells as compared to TC and ZO alone at a concentration of 1 µg ml^-1. TC + ZO combination treatment arrested cell cycle significantly at the G₀/G₁ phase. The proposed synergistic activity of the two herbs in the treatment of several cancers was correlated with an appropriate associated target/s, based on the pharmacological network. Interestingly, when both the plants used in combination, were found to regulate a total of 16 genes in 27 types of cancers. Further, ALOX5, MMP2, and MMP9 genes were identified as major targets which are responsible for the TC + ZO anticancer activity. According to merged and sub-networks of source-bioactive, bioactive-target, target-disease of TC, ZO alone and their combination; MMP9 was selected for validation purpose. The real-time PCR analysis confirmed that the TC + ZO combination treatment significantly down-regulated MMP9 mRNA expression by fivefold via up-regulation of its downstream target ER-α by 3.5-fold. In conclusion, the network analysis and in vitro validation confirmed the potent synergistic activity of TC + ZO combination treatment in breast cancer.

Advances in computational approaches in identifying synergistic drug combinations

Accumulated empirical clinical experience, supported by animal or cell line models, has initiated efforts of predicting synergistic combinatorial drugs with more-than-additive effect compared with the sum of the individual agents. Aiming to construct better computational models, this review started from the latest updated data resources of combinatorial drugs, then summarized the reported mechanism of the known synergistic combinations from aspects of drug molecular and pharmacological patterns, target network properties and compound functional annotation. Based on above, we focused on the main in silico strategies recently published, covering methods of molecular modeling, mathematical simulation, optimization of combinatorial targets and pattern-based statistical/learning model. Future thoughts are also discussed related to the role of natural compounds, drug combination with immunotherapy and management of adverse effects. Overall, with particular emphasis on mechanism of action of drug synergy, this review may serve as a rapid reference to design improved models for combinational drugs.

Brusatol, an NRF2 inhibitor for future cancer therapeutic

Background

Natural products from herbal medicines have long been investigated for their potentials as cancer therapeutics. Besides the development of several herbal medicine-derived anti-cancer agents, such as paclitaxel, vincristine and podophyllotoxin, many recent laboratory findings demonstrated that brusatol, a quassinoid from the seeds of Brucea sumatrana, exhibits potent tumor suppressing effect with improved disease outcome. Our recent finding further demonstrated that brusatol synergizes with the intrinsic metabolic burden in cancer cells.

Main body

Here, we summarized the recent investigations of brusatol as an experimental therapeutic for human malignancies, such as leukemia, lung cancer, pancreatic cancer and brain tumor. We also discussed the molecular target brusatol, with a focus on the Nuclear factor erythroid 2-related factor 2 (NRF2)-guided gene transcription, as well as glutathione de novo synthesis. Further, we discussed the challenges and future applications of brusatol for cancer therapy.

Conclusion

In conclusion, we believe increasing evidences have shown the value of brusatol as a novel strategy for cancer treatment, which may indicate future drug development and clinical translation.

Heterogeneous network propagation for herb target identification

BACKGROUND

Identifying targets of herbs is a primary step for investigating pharmacological mechanisms of herbal drugs in Traditional Chinese medicine (TCM). Experimental targets identification of herbs is a difficult and time-consuming work. Computational method for identifying herb targets is an efficient approach. However, how to make full use of heterogeneous network data about herbs and targets to improve the performance of herb targets prediction is still a dilemma.

METHODS

In our study, a random walk algorithm on the heterogeneous herb-target network (named heNetRW) has been proposed to identify protein targets of herbs. By building a heterogeneous herb-target network involving herbs, targets and their interactions and simulating random walk algorithm on the network, the candidate targets of the given herb can be predicted.

RESULTS

The experimental results on large-scale dataset showed that heNetRW had higher performance of targets prediction than PRINCE (improved F1-score by 0.08 and Hit@1 by 21.34% in one validation setting, and improved F1-score by 0.54 and Hit@1 by 69.08% in the other validation setting). Furthermore, we evaluated novel candidate targets of two herbs (rhizoma coptidis and turmeric), which showed our approach could generate potential targets that are valuable for further experimental investigations.

CONCLUSIONS

Compared with PRINCE algorithm, heNetRW algorithm can fuse more known information (such as, known herb-target associations and pathway-based similarities of protein pairs) to improve prediction performance. Experimental results also indicated heNetRW had higher performance than PRINCE. The prediction results not only can be used to guide the selection of candidate targets of herbs, but also help to reveal the molecule mechanisms of herbal drugs.

In Silico Insight into Potential Anti-Alzheimer's Disease Mechanisms of Icariin

Herbal compounds that have notable therapeutic effect upon Alzheimer's disease (AD) have frequently been found, despite the recent failure of late-stage clinical drugs. Icariin, which is isolated from Epimedium brevicornum, is widely reported to exhibit significant anti-AD effects in in vitro and in vivo studies. However, the molecular mechanism remains thus far unclear. In this work, the anti-AD mechanisms of icariin were investigated at a target network level assisted by an in silico target identification program (INVDOCK). The results suggested that the anti-AD effects of icariin may be contributed by: attenuation of hyperphosphorylation of tau protein, anti-inflammation and regulation of Ca²⁺ homeostasis. Our results may provide assistance in understanding the molecular mechanism and further developing icariin into promising anti-AD agents.

System analysis of LWDH related genes based on text mining in biological networks

Liuwei-dihuang (LWDH) is widely used in traditional Chinese medicine (TCM), but its molecular mechanism about gene interactions is unclear. LWDH genes were extracted from the existing literatures based on text mining technology. To simulate the complex molecular interactions that occur in the whole body, protein-protein interaction networks (PPINs) were constructed and the topological properties of LWDH genes were analyzed. LWDH genes have higher centrality properties and may play important roles in the complex biological network environment. It was also found that the distances within LWDH genes are smaller than expected, which means that the communication of LWDH genes during the biological process is rapid and effectual. At last, a comprehensive network of LWDH genes, including the related drugs and regulatory pathways at both the transcriptional and posttranscriptional levels, was constructed and analyzed. The biological network analysis strategy used in this study may be helpful for the understanding of molecular mechanism of TCM.