Evidence map›Paper›PMID 28915268›Full record

ArticlePloS one2017

Large-scale cross-species chemogenomic platform proposes a new drug discovery strategy of veterinary drug from herbal medicines.

Chao Huang, Yang Yang, Xuetong Chen, Chao Wang, Yan Li, Chunli Zheng, Yonghua Wang

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 26% 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

2 citing papers in PubMed, 10 citations in OpenAlex.

  1. Review
  2. 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

7 authors at 5 institutions in 1 country.

Chao HuangBioinformatics Center, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China.
Yang YangSchool of Pharmacy, Shihezi University, Shihezi, China.
Xuetong ChenBioinformatics Center, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China.
Chao WangCollege of Economics & Management of Dalian Ocean University, Dalian, China.
Yan LiDepartment of Materials Science and Chemical Engineering, Dalian University of Technology, Dalian, Liaoning, China.
Chunli ZhengKey Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Life Sciences, Northwest University, Xi'an, China.
Yonghua WangBioinformatics Center, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China.ORCID http://orcid.org/0000-0002-3060-1072
Northwest A&F University · CNDalian Ocean University · CNDalian University of Technology · CNMinistry of Education of the People's Republic of China · CNShihezi University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Veterinary Herbal Medicine (VHM) is a comprehensive, current, and informative discipline on the utilization of herbs in veterinary practice. Driven by chemistry but progressively directed by pharmacology and the clinical sciences, drug research has contributed more to address the needs for innovative veterinary medicine for curing animal diseases. However, research into veterinary medicine of vegetal origin in the pharmaceutical industry has reduced, owing to questions such as the short of compatibility of traditional natural-product extract libraries with high-throughput screening. Here, we present a cross-species chemogenomic screening platform to dissect the genetic basis of multifactorial diseases and to determine the most suitable points of attack for future veterinary medicines, thereby increasing the number of treatment options. First, based on critically examined pharmacology and text mining, we build a cross-species drug-likeness evaluation approach to screen the lead compounds in veterinary medicines. Second, a specific cross-species target prediction model is developed to infer drug-target connections, with the purpose of understanding how drugs work on the specific targets. Third, we focus on exploring the multiple targets interference effects of veterinary medicines by heterogeneous network convergence and modularization analysis. Finally, we manually integrate a disease pathway to test whether the cross-species chemogenomic platform could uncover the active mechanism of veterinary medicine, which is exemplified by a specific network module. We believe the proposed cross-species chemogenomic platform allows for the systematization of current and traditional knowledge of veterinary medicine and, importantly, for the application of this emerging body of knowledge to the development of new drugs for animal diseases.

Indexed as

Drug DiscoveryHerbal MedicineVeterinary DrugsAnimal DiseasesAnimalsSpecies SpecificityVeterinary Drugs

Identifiers

PMID28915268
PMCPMC5600375
OpenAlexW2753960091

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.