Evidence map›Paper›PMID 28420179›Full record

ArticleMolecules (Basel, Switzerland)2017

Systematic Understanding of the Mechanism of Salvianolic Acid A via Computational Target Fishing.

Shao-Jun Chen, Ming-Chao Cui

Abstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Recent Advances in In Silico Target Fishing.Molecules (Basel, Switzerland) · 2021
    Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Systematic Elucidation of the Mechanism ofEvidence-based complementary and alternative medicine : eCAM · 2020
    Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Antitumor Mechanisms of Curcumae Rhizoma Based on Network Pharmacology.Evidence-based complementary and alternative medicine : eCAM · 2018
    Article
  14. Article
  15. Review
  16. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Shao-Jun ChenDepartment of Traditional Chinese Medicine, Zhejiang Pharmaceutical College, 888 Yinxian Avenue Eastern Section, Ningbo 315100, China. chenshaojun@hotmail.com.
Ming-Chao CuiDepartment of Traditional Chinese Medicine, Zhejiang Pharmaceutical College, 888 Yinxian Avenue Eastern Section, Ningbo 315100, China. cuimc@mail.zjpc.net.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Salvianolic acid A (SAA) is one of the most abundant water-soluble and potent anti-oxidative compounds isolated from Danshen, a traditional Chinese medicine. A systematic overview of its mechanism of action is yet to be performed. In the present study, the druggability of SAA was measured using the TCMSP server, and potential targets of SAA were identified by PharmMapper and DRAR-CPI. Intersecting targets were then assessed by GeneMANIA and GO pathway analysis, and drug-target-pathway networks were constructed to give a visual view. The results showed that SAA has good druggability, and 13 putative protein targets were identified. Network analysis showed that these targets were associated with cancer, metabolism and other physiological processes. In summary, SAA is predicted to target multiple proteins and pathways to form a network that exerts systematic pharmacological effects.

Indexed as

Models, BiologicalModels, MolecularCaffeic AcidsLactatesProtein BindingSalvia miltiorrhizaSignal TransductionStructure-Activity RelationshipCaffeic AcidsLactatessalvianolic acid ADanshendruggabilitynetwork pharmacologysalvianolic acid Atarget fishing

Identifiers

PMID28420179
PMCPMC6153743

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.