Evidence map›Paper›PMID 39213289›Full record

ArticlePloS one2024

Identification of echinoderm metabolites as potential inhibitors targeting wild-type and mutant forms of Escherichia coli RNA polymerase (RpoB) for tuberculosis treatment.

Fatimah M Alsulais, Bayan A Alhaidhal, Ramzi A Mothana, Abdullah R Alanzi

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In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. 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

4 authors.

Fatimah M AlsulaisDepartment of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.ORCID 0009-0007-1391-6973
Bayan A AlhaidhalDepartment of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.ORCID 0009-0002-8340-4395
Ramzi A MothanaDepartment of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.
Abdullah R AlanziDepartment of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.ORCID 0009-0000-2565-6573

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tuberculosis (TB) remains a critical global health challenge, with the emergence of drug-resistant strains heightening concerns. The development of effective drugs targeting both wild-type (WT) and mutant Escherichia coli RNA polymerase β subunit (RpoB) is crucial for global TB control, aiming to alleviate TB incidence, mortality, and transmission. This study employs molecular docking and ADMET analyses to screen echinoderm metabolites for their potential inhibition of Escherichia coli RNA polymerase, focusing on wild-type and mutant RpoB variants associated with TB drug resistance. The evaluation of docking results using the glide gscore led to the selection of the top 10 compounds for each protein receptor. Notably, CMNPD2176 demonstrated the highest binding affinity against wild-type RpoB, CMNPD13873 against RpoB D516V mutant, CMNPD2177 against RpoB H526Y mutant, and CMNPD11620 against RpoB S531L mutant. ADMET screening confirmed the therapeutic potential of these selected compounds. Additionally, MM-GBSA binding free energy calculations and molecular dynamics simulations provided further support for the docking investigations. While the results suggest these compounds could be viable for tuberculosis treatment, it is crucial to note that further in-vitro research is essential for the transition from prospective inhibitors to clinical drugs.

Indexed as

Antitubercular AgentsDNA-Directed RNA PolymerasesEscherichia coliEscherichia coli ProteinsMolecular Docking SimulationAnimalsEnzyme InhibitorsHumansMolecular Dynamics SimulationMutationTuberculosisAntitubercular AgentsDNA-Directed RNA PolymerasesEnzyme InhibitorsEscherichia coli ProteinsrpoB protein, E coli

Identifiers

PMID39213289
PMCPMC11364244

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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.