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Network pharmacology-based analysis of Chinese herbal Naodesheng formula for application to Alzheimer's disease
Pang XC, Kang, Fang JS, Zhao Y, Xu LJ, Lian WW, Liu AL, DU GH.. Chinese journal of natural medicines, 2018-01-01
Topic: Amyloid, tau and blood-test diagnosis
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.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Pang, X. C., Kang, Fang, J. S., Zhao, Y., Xu, L. J., Lian, W. W., et al. (2018). Network pharmacology-based analysis of Chinese herbal Naodesheng formula for application to Alzheimer's disease. Chinese journal of natural medicines. https://doi.org/10.1016/s1875-5364(18)30029-3
Vancouver
Pang XC, Kang, Fang JS, Zhao Y, Xu LJ, Lian WW, et al. Network pharmacology-based analysis of Chinese herbal Naodesheng formula for application to Alzheimer's disease. Chinese journal of natural medicines. 2018. doi:10.1016/s1875-5364(18)30029-3. PMID: 29425590.
BibTeX
@article{pang2018-29425590,
author = {Pang, X. C. and Kang and Fang, J. S. and Zhao, Y. and Xu, L. J. and Lian, W. W. and Liu, A. L. and DU, G. H.},
title = {{Network pharmacology-based analysis of Chinese herbal Naodesheng formula for application to Alzheimer's disease}},
journal = {Chinese journal of natural medicines},
year = {2018},
doi = {10.1016/s1875-5364(18)30029-3},
pmid = {29425590},
url = {https://doi.org/10.1016/s1875-5364(18)30029-3}
}
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record names 8 authors; APA and Vancouver show the first six, BibTeX and the downloads carry all of them. Check the citation against the original before you use it.
Key findings
- 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.
Why it matters
This network pharmacology analysis predicted potential targets and mechanisms of the Chinese herbal Naodesheng formula for Alzheimer's disease using machine learning, molecular docking and pharmacophore mapping. It is a computational prediction study and does not show that the formula treats, cures or prevents Alzheimer's disease in people.
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Study details
- Evidence strengthLow
How this study scored 37/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomized / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Chinese journal of natural medicines) |
| Journal's citation record | 0 / 4 | Chinese Journal of Natural Medicines: journal h-index 60 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 2 / 5 | 2018 — within 10 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomized / blinded | 0 / 2 | No randomization or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 4 / 7 | Cited 66 times (OpenAlex, 2026-10-10) |
| Citations per year | 2 / 5 | 6.6 citations a year over 10 year(s) since 2018 |
| Impact for its field and year | 3 / 6 | Cited 6.4× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 1 / 4 | Cited 13 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 3 / 4 | Last-listed author Guanhua Du: h-index 83 (OpenAlex, whole career) |
| Institution's track record | 1 / 3 | Chinese Academy of Medical Sciences & Peking Union Medical College: institution h-index 950 (OpenAlex) |
| Multicenter collaboration | 1 / 3 | OpenAlex lists 2 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 29425590) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Total | 37 / 100 | — |
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