Evidence map›Paper›PMID 24971632›Full record

ArticlePloS one2014

Pros and cons of the tuberculosis drugome approach--an empirical analysis.

Feng-Chi Chen, Yu-Chieh Liao, Jie-Mao Huang, Chieh-Hua Lin, Yih-Yuan Chen, Horng-Yunn Dou, Chao Agnes Hsiung

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
0.9field-weighted citation impact, top 27% 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

12 citing papers in PubMed, 20 citations in OpenAlex.

  1. Deciphering tuberculosis: lysosome-centric insights into pathogenesis and therapies.Frontiers in cellular and infection microbiology · 2025
    Review
  2. Article
  3. Article
  4. Estradiol inhibits autophagy ofMolecular medicine reports · 2022
    Article
  5. Article
  6. Review
  7. Article
  8. Repurposing of Tamoxifen Against the Oral Bacteria.Turkish journal of pharmaceutical sciences · 2021
    Article
  9. Article
  10. Review
  11. Antiinfectives targeting enzymes and the proton motive force.Proceedings of the National Academy of Sciences of the United States of America · 2015
    Article
  12. 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 3 institutions in 1 country.

Feng-Chi ChenDivision of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli County, Taiwan; Department of Life Sciences, National Chiao-Tung University, Hsinchu, Taiwan; Department of Dentistry, China Medical University, Taichung, Taiwan.
Yu-Chieh LiaoDivision of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli County, Taiwan.
Jie-Mao HuangDivision of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli County, Taiwan.
Chieh-Hua LinDivision of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli County, Taiwan; Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, Taiwan.
Yih-Yuan ChenNational Institute of Infectious Diseases and Vaccinology, National Health Research Institutes, Zhunan, Miaoli County, Taiwan.
Horng-Yunn DouNational Institute of Infectious Diseases and Vaccinology, National Health Research Institutes, Zhunan, Miaoli County, Taiwan.
Chao Agnes HsiungDivision of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli County, Taiwan.
National Health Research Institutes · TWNational Tsing Hua University · TWNational Yang Ming Chiao Tung University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug-resistant Mycobacterium tuberculosis (MTB), the causative pathogen of tuberculosis (TB), has become a serious threat to global public health. Yet the development of novel drugs against MTB has been lagging. One potentially powerful approach to drug development is computation-aided repositioning of current drugs. However, the effectiveness of this approach has rarely been examined. Here we select the "TB drugome" approach--a protein structure-based method for drug repositioning for tuberculosis treatment--to (1) experimentally validate the efficacy of the identified drug candidates for inhibiting MTB growth, and (2) computationally examine how consistently drug candidates are prioritized, considering changes in input data. Twenty three drugs in the TB drugome were tested. Of them, only two drugs (tamoxifen and 4-hydroxytamoxifen) effectively suppressed MTB growth at relatively high concentrations. Both drugs significantly enhanced the inhibitory effects of three first-line anti-TB drugs (rifampin, isoniazid, and ethambutol). However, tamoxifen is not a top-listed drug in the TB drugome, and 4-hydroxytamoxifen is not approved for use in humans. Computational re-examination of the TB drugome indicated that the rankings were subject to technical and data-related biases. Thus, although our results support the effectiveness of the TB drugome approach for identifying drugs that can potentially be repositioned for stand-alone applications or for combination treatments for TB, the approach requires further refinements via incorporation of additional biological information. Our findings can also be extended to other structure-based drug repositioning methods.

Indexed as

Antitubercular AgentsBacterial ProteinsDrug CombinationsDrug Resistance, BacterialEthambutolHumansIsoniazidMicrobial Sensitivity TestsMycobacterium tuberculosisRifampinTamoxifenTuberculosisafimoxifeneAntitubercular AgentsBacterial ProteinsDrug CombinationsEthambutolIsoniazidRifampinTamoxifen

Identifiers

PMID24971632
PMCPMC4074101
OpenAlexW1970448606

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.