Evidence map›Paper›PMID 30487406›Full record

ArticleMolecules (Basel, Switzerland)2018

Discovery of a Natural Syk Inhibitor from Chinese Medicine through a Docking-Based Virtual Screening and Biological Assay Study.

Xing Wang, Junfang Guo, Zhongqi Ning, Xia Wu

Open access · goldAbstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.4field-weighted citation impact, top 39% of its field
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

8 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Discovery of Nine Dipeptidyl Peptidase-4 Inhibitors fromMolecules (Basel, Switzerland) · 2024
    Article
  5. Review
  6. Article
  7. Article
  8. 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

4 authors at 1 institution in 1 country.

Xing WangSchool of Traditional Chinese Medicine, Capital Medical University, Fengtai District, Beijing 100069, China. kingstar1016@sina.com.
Junfang GuoSchool of Traditional Chinese Medicine, Capital Medical University, Fengtai District, Beijing 100069, China. fanggj1519@ccmu.edu.cn.
Zhongqi NingSchool of Traditional Chinese Medicine, Capital Medical University, Fengtai District, Beijing 100069, China. ningzhongqi@163.com.
Xia WuSchool of Traditional Chinese Medicine, Capital Medical University, Fengtai District, Beijing 100069, China. wuxia6710@163.com.ORCID 0000-0002-2056-8344
Capital Medical University · CN

Funding

National Natural Science Foundation of China 81603311
6 · The paper itself

Abstract

Spleen tyrosine kinase (Syk) is a critical target protein for treating immunoreceptor signalling-mediated allergies. In this study, a virtual screening of an in-house Chinese medicine database followed by biological assays was carried out to identify novel Syk inhibitors. A molecular docking method was employed to screen for compounds with potential Syk inhibitory activity. Then, an in vitro kinase inhibition assay was performed to verify the Syk inhibitory activity of the virtual screening hits. Subsequently, a β-hexosaminidase release assay was conducted to evaluate the anti-mast cell degranulation activity of the active compounds. Finally, tanshinone I was confirmed as a Syk inhibitor (IC

Indexed as

Databases, FactualMedicine, Chinese TraditionalMolecular Docking SimulationProtein Kinase InhibitorsSyk KinaseAnimalsCell DegranulationCell LineMast CellsRatsProtein Kinase InhibitorsSyk KinaseSyk protein, ratcell-based assaySyk inhibition assaySyk inhibitorstanshinone Ivirtual screening

Identifiers

PMID30487406
PMCPMC6320911
OpenAlexW2903471893

What OpenQuestion 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 OpenQuestion graph.