Evidence map›Paper›PMID 36717817›Full record

ArticleBMC medical genomics2023

Relationship between drug targets and drug-signature networks: a network-based genome-wide landscape.

Chae Won Lee, Sung Min Kim, Soonok Sa, Myunghee Hong, Sang-Min Nam, Hyun Wook Han

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.6field-weighted citation impact, top 9% 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

3 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

6 authors at 2 institutions in 1 country.

Chae Won Lee *Department of Biomedical Informatics, CHA University School of Medicine, CHA University, Seongnam, 13488, South Korea.
Sung Min Kim *Department of Biomedical Informatics, CHA University School of Medicine, CHA University, Seongnam, 13488, South Korea.
Soonok SaDepartment of Biomedical Informatics, CHA University School of Medicine, CHA University, Seongnam, 13488, South Korea.
Myunghee HongDepartment of Biomedical Informatics, CHA University School of Medicine, CHA University, Seongnam, 13488, South Korea.
Sang-Min NamDepartment of Ophthalmology, CHA Bundang Medical Center, CHA University, Seongnam, South Korea. forustous@cha.ac.kr.
Hyun Wook HanDepartment of Biomedical Informatics, CHA University School of Medicine, CHA University, Seongnam, 13488, South Korea. stepano7@gmail.com.
CHA University · KRCHA University Bundang Medical Center · KR

Funding

Hyun Wook Han NRF-2020R1F1A1068423
6 · The paper itself

Abstract

Drugs produce pharmaceutical and adverse effects that arise from the complex relationship between drug targets and signatures; by considering such relationships, we can begin to understand the cellular mechanisms of drugs. In this study, we selected 463 genes from the DSigDB database corresponding to targets and signatures for 382 FDA-approved drugs with both protein binding information for a drug-target score (KDTN, i.e., the degree to which the protein encoded by the gene binds to a number of drugs) and microarray signature information for a drug-sensitive score (KDSN, i.e., the degree to which gene expression is stimulated by the drug). Accordingly, we constructed two drug-gene bipartite network models, a drug-target network and drug-signature network, which were merged into a multidimensional model. Analysis revealed that the KDTN and KDSN were in mutually exclusive and reciprocal relationships in terms of their biological network structure and gene function. A symmetric balance between the KDTN and KDSN of genes facilitates the possibility of therapeutic drug effects in whole genome. These results provide new insights into the relationship between drugs and genes, specifically drug targets and drug signatures.

Indexed as

Drug Delivery SystemsGene Regulatory NetworksDatabases, FactualGenomeBioinformaticsDrug-gene networkNetwork analysis

Identifiers

PMID36717817
PMCPMC9885570
OpenAlexW4318478274

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.