Evidence map›Paper›PMID 25458615›Full record

ReviewTuberculosis (Edinburgh, Scotland)2014

Future target-based drug discovery for tuberculosis?

Bavesh Davandra Kana, Petros C Karakousis, Tanya Parish, Thomas Dick

Abstract readReview
In one paragraph

Review in Tuberculosis (Edinburgh, Scotland), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Review
  2. Dissecting rifampicin heteroresistance inJournal of medical microbiology · 2025
    Article
  3. Article
  4. Antimicrobial agents and chemotherapy · 2021
    Article
  5. Article
  6. Article
  7. Coronin-1 levels in patients with tuberculosis.The Indian journal of medical research · 2021
    Article
  8. Article
  9. Review
  10. Tuberculosis Drug Discovery: A Decade of Hit Assessment for Defined Targets.Frontiers in cellular and infection microbiology · 2021
    Review
  11. Targeting theFrontiers in microbiology · 2021
    Review
  12. Mycobacterial drug discovery.RSC medicinal chemistry · 2020
    Review
  13. Review
  14. Biosynthesis of Galactan inAntibiotics (Basel, Switzerland) · 2020
    Review
  15. Review
  16. Article
  17. Construction of an overexpression library forBiology methods & protocols · 2018
    Article
  18. Article
  19. Microbiology spectrum · 2017
    Review
  20. Review
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.

Bavesh Davandra Kana
Petros C Karakousis
Tanya Parish
Thomas Dick

Funding

Soweto Clinical Trials UnitUM1AI069453 · NIAID · WITS HEALTH CONSORTIUM (PTY), LTD · PI Glenda E Gray, Lerato Mohapi · 2012 to 2026
$40.9M
Soweto Clinical Trials UnitU01AI069453 · NIAID · WITS HEALTH CONSORTIUM (PTY), LTD · PI GRAY, GLENDA · 2007 to 2011
$25.5M
Chemical probes of vulnerable pathways in antibiotic-resistant pathogensR01AI099188 · NIAID · ACCESS TO ADVANCED HEALTH INSTITUTE · PI PARISH, TANYA · 2012 to 2016
$3.7M
A Multidisciplinary Approach to Understanding TB Latency and ReactivationR01HL106786 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI BADER, JOEL S., KARAKOUSIS, PETROS C · 2010 to 2013
$3.1M
Regulatory networks involved in Mycobacterium tuberculosis persistenceR01AI083125 · NIAID · JOHNS HOPKINS UNIVERSITY · PI KARAKOUSIS, PETROS C · 2009 to 2013
$2.7M
High throughput assays to detect inhibition of a key M. tuberculosis proteaseR01AI095652 · NIAID · ACCESS TO ADVANCED HEALTH INSTITUTE · PI PARISH, TANYA · 2013 to 2015
$1.1M
The Role of Cell Wall Lipids in Pathogenesis of Rifampin-Resistant TBR01AI106613 · NIAID · JOHNS HOPKINS UNIVERSITY · PI KARAKOUSIS, PETROS C · 2013 to 2015
$765k
Howard Hughes Medical Institute HHMI000NHLBI NIH HHS R01 HL106786NIAID NIH HHS R01 AI083125NIAID NIH HHS R01 AI095652NIAID NIH HHS R01AI095652NIAID NIH HHS R01 AI099188NIAID NIH HHS R01AI099188NIAID NIH HHS R01 AI106613NIAID NIH HHS U01 AI069453NIAID NIH HHS U01 AI069453-07NIAID NIH HHS UM1 AI069453
6 · The paper itself

Abstract

New drugs that retain potency against multidrug/extensively drug-resistant strains of Mycobacterium tuberculosis, with the additional benefit of a shortened treatment duration and ease of administration, are urgently needed by tuberculosis (TB) control programs. Efforts to develop this new generation of treatment interventions have been plagued with numerous problems, the most significant being our insufficient understanding of mycobacterial metabolism during disease. This, combined with limited chemical diversity and poor entry of small molecules into the cell, has limited the number of new bioactive agents that result from drug screening efforts. The biochemical, target-driven approach to drug development has been largely abandoned in the TB field, to be replaced by whole-cell or target-based whole-cell screening approaches. In this context, the properties of a good drug target are unclear, since these are directly determined by the ability to find compounds, using current screening algorithms, which are able to kill M. tuberculosis. In this review, we discuss issues related to the identification and validation of drug targets and highlight some key properties for promising targets. Some of these include essentiality for growth, vulnerability, druggability, reduced propensity to evolve drug resistance and target location to facilitate ready access to drugs during chemotherapy. We present these in the context of recent drugs that have emerged through various approaches with the aim of consolidating the knowledge gained from these experiences to inform future efforts.

Indexed as

Antitubercular AgentsDrug DiscoveryHumansMolecular Targeted TherapyMycobacterium tuberculosisTuberculosisAntitubercular Agents

Identifiers

PMID25458615
PMCPMC6072889

What OpenQuestion holds

Textmetadata
LicenceTDM
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.