Neuropsychopharmacology: The Fifth Generation of Progress

Chinese medicine (CM) is usually prescribed as CM formula to treat disease. The lack of effective research approach makes it difficult to elucidate the molecular mechanisms of CM formula owing to its complicated chemical compounds. Network pharmacology is increasingly applied in CM formula research in recent years, which is identified suitable for the study of CM formula. In this review, we summarized the methodology of network pharmacology, including network construction, network analysis and network verification. The aim of constructing a network is to achieve the interaction between the bioactive compounds and targets and the interaction between various targets, and then find out and validate the key nodes via network analysis and network verification. Besides, we reviewed the application in CM formula research, mainly including targets discovery, bioactive compounds screening, toxicity evaluation, mechanism research and quality control research. Finally, we proposed prospective in the future and limitations of network pharmacology, expecting to provide new strategy and thinking on study for CM formula.

Network Pharmacology in Research of Chinese Medicine Formula: Methodology, Application and Prospective.

The rising burden of cancer worldwide calls for an alternative treatment solution. Herbal medicine provides a very feasible alternative to western medicine against cancer. This article reviews the selected plant species with active phytochemicals, the animal models used for these studies, and their regulatory aspects. This study is based on a meticulous literature review conducted through the search of relevant keywords in databases, Web of Science, Scopus, PubMed, and Google Scholar. Twenty plants were selected based on defined selection criteria for their potent anticancer compounds. The detailed analysis of the research studies revealed that plants play an indispensable role in fighting different cancers such as breast, stomach, oral, colon, lung, hepatic, cervical, and blood cancer cell lines. The in vitro studies showed cancer cell inhibition through DNA damage and activation of apoptosis-inducing enzymes by the secondary metabolites in the plant extracts. Studies that reported in vivo activities of these plants showed remarkable results in the inhibition of cancer in animal models. Further studies should be performed on exploring more plants, their active compounds, and the mechanism of anticancer actions for use as standard herbal medicine.

Anticancer Plants: A Review of the Active Phytochemicals, Applications in Animal Models, and Regulatory Aspects

There is emerging evidence that the balance between estrogen receptor-α (ERα) and androgen receptor (AR) signaling is a critical determinant of growth in the normal and malignant breast. In this study, we assessed AR status in a cohort of 215 invasive ductal breast carcinomas. AR and ERα were coexpressed in the majority (80-90%) of breast tumor cells. Kaplan-Meier product limit analysis and multivariate Cox regression showed that AR is an independent prognostic factor in ERα-positive disease, with a low level of AR (less than median of 75% positive cells) conferring a 4.6-fold increased risk of cancer-related death (P = 0.002). Consistent with a role for AR in breast cancer outcome, AR potently inhibited ERα transactivation activity and 17β-estradiol–stimulated growth of breast cancer cells. Transfection of MDA-MB-231 breast cancer cells with either functionally impaired AR variants or the DNA-binding domain of the AR indicated that the latter is both necessary and sufficient for inhibition of ERα signaling. Consistent with molecular modeling, electrophoretic mobility shift assays showed binding of the AR to an estrogen-responsive element (ERE). Evidence for a functional interaction of the AR with an ERE in vivo was provided by chromatin immunoprecipitation data, revealing recruitment of the AR to the progesterone receptor promoter in T-47D breast cancer cells. We conclude that, by binding to a subset of EREs, the AR can prevent activation of target genes that mediate the stimulatory effects of 17β-estradiol on breast cancer cells.

Androgen receptor inhibits estrogen receptor-A activity and is prognostic in breast cancer

As a traditional medical intervention in Asia and a complementary and alternative medicine in western countries, traditional Chinese medicine (TCM) has attracted global attention in the life science field. TCM provides extensive natural resources for medicinal compounds, and these resources are generally regarded as effective and safe for use in drug discovery. However, owing to the complexity of compounds and their related multiple targets of TCM, it remains difficult to dissect the mechanisms of action of herbal medicines at a holistic level. To solve the issue, in the review, we proposed a novel approach of systems pharmacology to identify the bioactive compounds, predict their related targets, and illustrate the molecular mechanisms of action of TCM. With a predominant focus on the mechanisms of actions of TCM, we also highlighted the application of the systems pharmacology approach for the prediction of drug combination and dynamic analysis, the synergistic effects of TCMs, formula dissection, and theory analysis. In summary, the systems pharmacology method contributes to understand the complex interactions among biological systems, drugs, and complex diseases from a network perspective. Consequently, systems pharmacology provides a novel approach to promote drug discovery in a precise manner and a systems level, thus facilitating the modernization of TCM.

/pdf/systems-pharmacology-for-investigation-of-the-mechanisms-of-3rn80tupk0.pdf

Systems Pharmacology for Investigation of the Mechanisms of Action of Traditional Chinese Medicine in Drug Discovery.

As a chronic inflammatory and angiogenic disease with increased morbidity and mortality, rheumatoid arthritis (RA) is characterized by the proliferation of synovial tissue and the accumulation of excessive mononuclear infiltration, which always results in the joint deformity, disability, and eventually the destruction of the bone and cartilage. Traditional Chinese Medicine (TCM), with rich history of proper effectiveness in treating the inflammatory joint disease containing RA, has long combated such illness from, actually, an integrative and holistic point of view. However, its “multi-components” and “multi-targets” features make it very difficult to decipher the molecular mechanisms of RA from a systematic perspective if employing only routine methods. Presently, an innovative systems-pharmacology approach was introduced, which combined the ADME screening model, drug targeting, and network pharmacology, to explore the action mechanisms of botanic herbs for the treatment of RA. As a result, we uncovered ...

Systems Pharmacology Dissection of Multiscale Mechanisms of Action for Herbal Medicines in Treating Rheumatoid Arthritis.

Breast cancer is the most common carcinoma in women. Comprehensive therapy on breast cancer including surgical operation, chemotherapy, radiotherapy, endocrinotherapy, etc. could help, but still has serious side effect and resistance against anticancer drugs. Complementary and alternative medicine (CAM) may avoid these problems, in which traditional Chinese medicine (TCM) has been highlighted. In this section, to analyze the mechanism through which TCM act on breast cancer, we have built a virtual model consisting of the construction of database, oral bioavailability prediction, drug-likeness evaluation, target prediction, network construction. The 20 commonly employed herbs for the treatment of breast cancer were used as a database to carry out research. As a result, 150 ingredient compounds were screened out as active molecules for the herbs, with 33 target proteins predicted. Our analysis indicates that these herbs 1) takes a ‘Jun-Chen-Zuo-Shi” as rule of prescription, 2) which function mainly through perturbing three pathways involving the epidermal growth factor receptor, estrogen receptor, and inflammatory pathways, to 3) display the breast cancer-related anti-estrogen, anti-inflammatory, regulation of cell metabolism and proliferation activities. To sum it up, by providing a novel in silico strategy for investigation of the botanical drugs, this work may be of some help for understanding the action mechanisms of herbal medicines and for discovery of new drugs from plants.

/pdf/a-methodology-for-cancer-therapeutics-by-systems-31rx51in7i.pdf

A Methodology for Cancer Therapeutics by Systems Pharmacology-Based Analysis: A Case Study on Breast Cancer-Related Traditional Chinese Medicines

As a chronic disorder, insomnia affects approximately 10% of the population at some time during their lives, and its treatment is often challenging. Since the antagonists of the H1 receptor, a protein prevalent in human central nervous system, have been proven as effective therapeutic agents for treating insomnia, the H1 receptor is quite possibly a promising target for developing potent anti-insomnia drugs. For the purpose of understanding the structural actors affecting the antagonism potency, presently a theoretical research of molecular interactions between 129 molecules and the H1 receptor is performed through three-dimensional quantitative structure-activity relationship (3D-QSAR) techniques. The ligand-based comparative molecular similarity indices analysis (CoMSIA) model (Q2 = 0.525, R2ncv = 0.891, R2pred = 0.807) has good quality for predicting the bioactivities of new chemicals. The cross-validated result suggests that the developed models have excellent internal and external predictability and consistency. The obtained contour maps were appraised for affinity trends for the investigated compounds, which provides significantly useful information in the rational drug design of novel anti-insomnia agents. Molecular docking was also performed to investigate the mode of interaction between the ligand and the active site of the receptor. Furthermore, as a supplementary tool to study the docking conformation of the antagonists in the H1 receptor binding pocket, molecular dynamics simulation was also applied, providing insights into the changes in the structure. All of the models and the derived information would, we hope, be of help for developing novel potent histamine H1 receptor antagonists, as well as exploring the H1-antihistamines interaction mechanism.

/pdf/computational-analysis-of-structure-based-interactions-for-1bju3gt20c.pdf

Computational Analysis of Structure-Based Interactions for Novel H1-Antihistamines

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Papers

Systems Pharmacology Dissection of Multiscale Mechanisms of Action for Herbal Medicines in Treating Rheumatoid Arthritis.

A Methodology for Cancer Therapeutics by Systems Pharmacology-Based Analysis: A Case Study on Breast Cancer-Related Traditional Chinese Medicines

Computational Analysis of Structure-Based Interactions for Novel H1-Antihistamines