Evidence map›Paper›PMID 24401837›Full record

ReviewEMBO molecular medicine2014

Tuberculosis drug discovery in the post-post-genomic era.

Benoit Lechartier, Jan Rybniker, Alimuddin Zumla, Stewart T Cole

Abstract readReview
In one paragraph

Review in EMBO molecular medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 81 papers.

0numbers the graph read from it
0cells of the map it votes in
81citing 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

81 citing papers in PubMed.

  1. Article
  2. Article
  3. TowardMicroorganisms · 2024
    Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Target Identification in Anti-Tuberculosis Drug Discovery.International journal of molecular sciences · 2023
    Review
  12. Review
  13. Mutations inAntimicrobial agents and chemotherapy · 2022
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. Article

21 more citing papers are in PubMed but not listed here.

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.

Benoit LechartierEcole Polytechnique Fédérale de Lausanne Global Health Institute, Lausanne, Switzerland.
Jan Rybniker
Alimuddin Zumla
Stewart T Cole

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The expectation that genomics would result in new therapeutic interventions for infectious diseases remains unfulfilled. In the post-genomic era, the decade immediately following the availability of the genome sequence of Mycobacterium tuberculosis, tuberculosis (TB) drug discovery relied heavily on the target-based approach but this proved unsuccessful leading to a return to whole cell screening. Genomics underpinned screening by providing knowledge and many enabling technologies, most importantly whole genome resequencing to find resistance mutations and targets, and this resulted in a selection of leads and new TB drug candidates that are reviewed here. Unexpectedly, many new targets were found to be 'promiscuous' as they were inhibited by a variety of different compounds. In the post-post-genomics era, more advanced technologies have been implemented and these include high-content screening, screening for inhibitors of latency, the use of conditional knock-down mutants for validated targets and siRNA screens. In addition, immunomodulation and pharmacological manipulation of host functions are being explored in an attempt to widen our therapeutic options.

Indexed as

Drug DiscoveryGenomicsAnimalsAntitubercular AgentsGlobal HealthHost-Pathogen InteractionsHumansTuberculosisAntitubercular Agents

Identifiers

PMID24401837
PMCPMC3927952

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.