Repositioning drug discovery for Alzheimer's disease based on global marketed drug data / 药学学报

Alzheimer's disease (AD) is a neurodegenerative disease that seriously threatens the life of the elderly and there is no effective therapy to treat or delay the onset of this disease. Due to the multifactorial etiology of this disease, the multi-target-directed ligand (MTDL) approach is an innovative and promising method in search for new drugs against AD. In order to find potential multi-target anti-AD drugs through reposition of current drugs, the database of global drugs on market were mined by an anti-AD multi-target prediction platform established in our laboratory. As a result, inositol nicotinate, cyproheptadine, curcumin, rosiglitazone, demecarium, oxybenzone, agomelatine, codeine, imipramine, dyclonine, melatonin, perospirone, and bufexamac were predicted to act on at least one anti-AD drug target yet act against AD through various mechanisms. The compound-target network was built using the Cytoscape. The prediction was validated by molecular docking between agomelatine and its multiple targets, including ADORA2A, ACHE, BACE1, PTGS2, MAOB, SIGMAR1 and ESR1. Agomelatine was shown to be able to act on all the targets above. In conclusion, the potential drugs for anti-AD therapy in the database for global drugs on market was partially uncovered using machine learning, network pharmacology, and molecular docking methods. This study provides important information for drug reposition in anti-AD therapy.

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 study of Xiaoxuming Decoction based on vasodilatory and vasoconstrictory related GPCR targets / 中国中药杂志

In this study, bioinformatics methods such as molecular docking and network pharmacology were adopted to establish Xiaoxuming Decoction (XXMD) "compound-vasodilatory and vasoconstrictory related G protein-coupled receptors (GPCR) targets" network, then the vascular function regulatory effective components and the potential targets of XXMD were analyzed. Based on the XXMD herb sources, the chemical structures of the compounds were retrieved from the national scientific data sharing platform for population and health pharmaceutical information center, TCMSP database and the latest research literatures. The chemical molecular library was established after class prediction and screening for medicinal and metabolic properties. Then, five kinds of vasodilatory and vasoconstrictory related GPCR crystal structure including 5-HT receptors (5-HT1AR, 5-HT1BR), AT1R, β2-AR, hUTR and ETB were retrieved from RCSB Protein Data Bank database or constructed by homology modeling of Discovery Studio 4.1 built-in modeling tools. After virtual screening by Libdock molecular docking, the highest rated 50 compounds of each target were collected and analyzed. The collected data were further used to construct and analyze the network by Cytoscape 3.4.0. The results showed that most of the chemical composition effects were associated with different vasodilatory and vasoconstrictory related GPCR targets, while a few effective components could be applied to multiple GPCR targets at the same time, therefore forming synergies and vasorelaxant effects of XXMD.

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 study of Chinese medicine Xiao-Xu-Ming decoction based on vasoconstrictor related GPCR targets / 中国药理学与毒理学杂志

OBJECTIVE Using bioinformatics methods, to establish Xiao-Xu-Ming decoction (XX-MD)"compound-vasoconstriction G Protein-Coupled Receptors(GPCR)targets"network,and analyze the vasoconstriction regulatory effective components and the potential targets of XXMD. METHODS Ac-cording to the XXMD herb sources,we retrieved the chemical structures from the national scientific da-ta sharing platform for population and health pharmaceutical information center,TCMSP database and the latest research literature.The chemical molecular library was established after class prediction and screening for medicinal and metabolic properties.Five kinds of vasoconstriction GPCR crystal structure including 5-HT receptors(5-HT1AR,5-HT1BR),AT1R,β2-AR,hUTR and ETB were retrieved from Bank Pro-tein Data Bank database or homology modeling using Discovery Studio 4.1 built-in modeling tools.After virtual screening by Libdock molecular docking,the highest rated 50 compounds of each target were col-lected and analyzed. The collected data were further used to construct and analyze the network. RE-SULTS 859 single compound structures information in XXMD were generalized following the screen-ing of obtained 2043 compounds.The complicated compound-vasoconstriction GPCR targets network of XXMD was then constructed and analyzed by molecular docking with the above five kinds of GPCR target receptors. Most of the chemical composition effects were associated with different vasoconstric-tion GPCR targets,while a few effective components can be applied to multiple GPCR targets at the same time,therefore forming synergies.CONCLUSION Vasorelaxant effects of XXMD may not only result from the collaborative interaction between a variety of active ingredients in Chinese medicine and multi-ple targets,but also from the interaction between some effective component and multiple targets.

Network mechanism on effective constituents from Polygala Tenuifolia for anti-Alzheimer Disease / 中国药理学与毒理学杂志

OBJECTIVE To clarify out the network pharmacology mechanism of Polygala tenuifolia against Alzheimer disease(AD).METHODS Firstly,we collected the chemical constituents from Polyg-ala tenuifolia and key targets toward AD.Machine learning algorithms were applied to construct classifi-ers for predicting the effective constituents. Secondly, docking models were utilized for further evalua-tion.Finally,we built constituent-target,target-target network and target-biology pathway network.RE-SULTS 104 chemical constituents Polygala tenuifolia from were collected.Through prediction of blood-brain penetration and validation,36 chemical constituents were selected among 100 chemical constitu-ents,their action targets mainly focused on AChE,COX-2,TNF-α,insulin-degrading enzyme and APP. Their main structure types include Polygala saponins, Polygala glycosides, Polygala shrubby ketones, polygala xanthones and sterols,which acted on AchE,APP,M-TAU,GSK3β and 5HT1A with high fre-quency.Gene-Ontology and KEGG enrichment analysis showed that the main pathways of these con-stituents involve in neurotransmitter release,synaptic conduction and synaptic plasticity,apoptosis reg-ulation,phosphorylation pathway,Ca2+signaling pathway,and so on.CONCLUSION This study uncov-ered a network mechanism of Polygala tenuifolia against Alzheimer disease,which may provide impor-tant information for the further study and new drug development.

Network pharmacology study of the effective constituents in the Compound Yizhihao against influenza disease / 药学学报

Compound Yizhihao, consists of Radix isatidis, Folium isatidis, Artemisia rupestris, has a significant therapeutic effect on the treatment of influenza and fever. However, the mechanism of its action is still unclear. In this investigation, we collected the key target molecule of influenza disease and the chemical constituents of Compound Yizhihao, and developed Naïve Bayesian classification models based on the input molecular fingerprints and molecule descriptors. The built models were further applied to construct classifiers for predicting the effective constituents. We used the professional network-building software to build the constituent-target network and target-pathway network, which revealed the network pharmacology of the effective constituents in Compound Yizhihao. It will contribute to the further research of mechanism of Compound Yizhihao.

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.

Review on the application of drug target database / 中国药学杂志

OBJECTIVE: To help researchers learn and utilize drug target database for new drug research, and to provide important information for the management and construction of Drug Target Database.