Systems pharmacology-based investigation of Sanwei Ganjiang Prescription: related mechanisms in liver injury / 中国天然药物

Liver injury remains a significant global health problem and has a variety of causes, including oxidative stress (OS), inflammation, and apoptosis of liver cells. There is currently no curative therapy for this disorder. Sanwei Ganjiang Prescription (SWGJP), derived from traditional Chinese medicine (TCM), has shown its effectiveness in long-term liver damage therapy, although the underlying molecular mechanisms are still not fully understood. To explore the underlining mechanisms of action for SWGJP in liver injury from a holistic view, in the present study, a systems pharmacology approach was developed, which involved drug target identification and multilevel data integration analysis. Using a comprehensive systems approach, we identified 43 candidate compounds in SWGJP and 408 corresponding potential targets. We further deciphered the mechanisms of SWGJP in treating liver injury, including compound-target network analysis, target-function network analysis, and integrated pathways analysis. We deduced that SWGJP may protect hepatocytes through several functional modules involved in liver injury integrated-pathway, such as Nrf2-dependent anti-oxidative stress module. Notably, systems pharmacology provides an alternative way to investigate the complex action mode of TCM.

Network pharmacology-based analysis of Chinese herbal Naodesheng formula for application to Alzheimer's disease / 中国天然药物

Naodesheng (NDS) formula, which consists of Rhizoma Chuanxiong, Lobed Kudzuvine, Carthamus tinctorius, Radix Notoginseng, and Crataegus pinnatifida, is widely applied for the treatment of cardio/cerebrovascular ischemic diseases, ischemic stroke, and sequelae of cerebral hemorrhage, etc. At present, the studies on NDS formula for Alzheimer's disease (AD) only focus on single component of this prescription, and there is no report about the synergistic mechanism of the constituents in NDS formula for the potential treatment of dementia. Therefore, the present study aimed to predict the potential targets and uncover the mechanisms of NDS formula for the treatment of AD. Firstly, we collected the constituents in NDS formula and key targets toward AD. Then, drug-likeness, oral bioavailability, and blood-brain barrier permeability were evaluated to find drug-like and lead-like constituents for treatment of central nervous system diseases. By combining the advantages of machine learning, molecular docking, and pharmacophore mapping, we attempted to predict the targets of constituents and find potential multi-target compounds from NDS formula. Finally, we built constituent-target network, constituent-target-target network and target-biological pathway network to study the network pharmacology of the constituents in NDS formula. To the best of our knowledge, this represented the first to study the mechanism of NDS formula for potential efficacy for AD treatment by means of the virtual screening and network pharmacology methods.

Network pharmacology-based analysis of Chinese herbal Naodesheng formula for application to Alzheimer's disease / 中国天然药物

Naodesheng (NDS) formula, which consists of Rhizoma Chuanxiong, Lobed Kudzuvine, Carthamus tinctorius, Radix Notoginseng, and Crataegus pinnatifida, is widely applied for the treatment of cardio/cerebrovascular ischemic diseases, ischemic stroke, and sequelae of cerebral hemorrhage, etc. At present, the studies on NDS formula for Alzheimer's disease (AD) only focus on single component of this prescription, and there is no report about the synergistic mechanism of the constituents in NDS formula for the potential treatment of dementia. Therefore, the present study aimed to predict the potential targets and uncover the mechanisms of NDS formula for the treatment of AD. Firstly, we collected the constituents in NDS formula and key targets toward AD. Then, drug-likeness, oral bioavailability, and blood-brain barrier permeability were evaluated to find drug-like and lead-like constituents for treatment of central nervous system diseases. By combining the advantages of machine learning, molecular docking, and pharmacophore mapping, we attempted to predict the targets of constituents and find potential multi-target compounds from NDS formula. Finally, we built constituent-target network, constituent-target-target network and target-biological pathway network to study the network pharmacology of the constituents in NDS formula. To the best of our knowledge, this represented the first to study the mechanism of NDS formula for potential efficacy for AD treatment by means of the virtual screening and network pharmacology methods.

Systems pharmacology-based investigation of Sanwei Ganjiang Prescription: related mechanisms in liver injury / 中国天然药物

Liver injury remains a significant global health problem and has a variety of causes, including oxidative stress (OS), inflammation, and apoptosis of liver cells. There is currently no curative therapy for this disorder. Sanwei Ganjiang Prescription (SWGJP), derived from traditional Chinese medicine (TCM), has shown its effectiveness in long-term liver damage therapy, although the underlying molecular mechanisms are still not fully understood. To explore the underlining mechanisms of action for SWGJP in liver injury from a holistic view, in the present study, a systems pharmacology approach was developed, which involved drug target identification and multilevel data integration analysis. Using a comprehensive systems approach, we identified 43 candidate compounds in SWGJP and 408 corresponding potential targets. We further deciphered the mechanisms of SWGJP in treating liver injury, including compound-target network analysis, target-function network analysis, and integrated pathways analysis. We deduced that SWGJP may protect hepatocytes through several functional modules involved in liver injury integrated-pathway, such as Nrf2-dependent anti-oxidative stress module. Notably, systems pharmacology provides an alternative way to investigate the complex action mode of TCM.

Network pharmacology study of effective constituents of traditional Chinese medicine for Alzheimer's disease treatment / 药学学报

This study aims to investigate the network pharmacology of Chinese medicinal formulae for treatment of Alzheimer's disease. Machine learning algorithms were applied to construct classifiers in predicting the active molecules against 25 key targets toward Alzheimer's disease (AD). By extensive data profiling, we compiled 13 classical traditional Chinese medicine (TCM) formulas with clinical efficacy for AD. There were 7 Chinese herbs with a frequency of 5 or higher in our study. Based on the predicted results, we built constituent-target, and further construct target-target interaction network by STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) and target-disease network by DAVID (Database for Annotation, Visualization and Integrated Discovery) and gene disease database to study the synergistic mechanism of the herbal constituents in the Chinese traditional patent medicine. By prediction of blood-brain penetration and validation by TCMsp (traditional Chinese medicine systems pharmacology) and Drugbank, we found 7 typical multi-target constituents which have diverse structure. The mechanism uncovered by this study may offer a deep insight into the action mechanism of TCMs for AD. The predicted inhibitors for the AD-related targets may provide a good source of new lead constituents against AD.

Development of HTS model on SERT inhibitors combined biological screening model with HTVS / 药学学报

In order to improve the efficiency of drug screening on serotonin transporter (SERT) inhibitors, a high-throughput screening (HTS) model is established in RBL-2H3 cells. The RBL-2H3 cells are very similar to the serotonin genetic neuro, in modulation of post-receptor mechanisms and transduction pathway of SERT reactivated. Depending on a fluorescence substrate ASP+ used in detection method of inhibitor rates, it's convenient, quick, accurate and effective, not making the environmental biohazard compared with radioactive experiments. Furthermore, biological screening model combined with computer aided virtual screening technique describing high-throughput virtual screening (HTVS). Bayesian classification method and molecular fingerprint similarity were applied to virtual screening technique, for screening compounds in compound library. Some compounds have been found, and then validated further by biological screening model. Combination of HTS and HTVS improves the efficiency of screening SERT inhibitors.

Research advance in the drug target prediction based on chemoinformatics / 药学学报

The emerging of network pharmacology and polypharmacology forces the scientists to recognize and explore new mechanisms of existing drugs. The drug target prediction can play a key significance on the elucidation of the molecular mechanism of drugs and drug reposition. In this paper, we systematically review the existing approaches to the prediction of biological targets of small molecule based on chemoinformatics, including ligand-based prediction, receptor-based prediction and data mining-based prediction. We also depict the strength of these methods as well as their applications, and put forward their developing direction.