Evidence map›Paper›PMID 38818453›Full record

ArticlePeerJ2024

Core proteome mediated subtractive approach for the identification of potential therapeutic drug target against the honeybee pathogen

Sawsen Rebhi, Zarrin Basharat, Calvin R Wei, Salim Lebbal, Hanen Najjaa, Najla Sadfi-Zouaoui, Abdelmonaem Messaoudi

Abstract read
In one paragraph

Article in PeerJ, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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.

Sawsen Rebhi *Université de Tunis-El Manar, Laboratoire de Mycologie, Pathologies et Biomarqueurs, Département de Biologie, Tunis, Tunisia.
Zarrin Basharat *Independent researcher, Islamabad, Pakistan.
Calvin R WeiDepartment of Research and Development, Shing Huei Group, Taipei, Taiwan.
Salim LebbalUniversity of Khenchela, Department of Agricultural Sciences, Faculty of Nature and Life Sciences, Khenchela, Algeria.
Hanen NajjaaUniversity of Gabes, Laboratory of Pastoral Ecosystem and Valorization of Spontaneous Plants and Associated Microorganisms, Institute of Arid Lands of Medenine, Medenine, Tunisia.
Najla Sadfi-ZouaouiUniversité de Tunis-El Manar, Laboratoire de Mycologie, Pathologies et Biomarqueurs, Département de Biologie, Tunis, Tunisia.
Abdelmonaem MessaoudiUniversité de Tunis-El Manar, Laboratoire de Mycologie, Pathologies et Biomarqueurs, Département de Biologie, Tunis, Tunisia.

Funding

Ministry of Higher Education and Scientific Research of Tunisia
6 · The paper itself

Abstract

Background & Objectives: American foulbrood (AFB), caused by the highly virulent, spore-forming bacterium Methods: We investigated effective novel drug targets through a comprehensive Results: Proteome mining led to the identification of Ketoacyl-ACP synthase III as a highly promising therapeutic target, making it a prime candidate for inhibitor screening. The subsequent virtual screening and MD simulation analyses further affirmed the selection of ZINC95910054 as a potent inhibitor, with the lowest binding energy. This finding presents significant promise in the battle against Conclusions: Computer aided drug design provides a novel approach for managing American foulbrood in honey bee populations, potentially mitigating its detrimental effects on both bee colonies and the honey industry.

Indexed as

Paenibacillus larvaeProteomeAnimalsAnti-Bacterial AgentsBacterial ProteinsBeesMolecular Docking SimulationMolecular Dynamics SimulationAnti-Bacterial AgentsBacterial ProteinsProteomeAmerican FoulbroodComputational drug designKetoacyl-ACP synthase IIIPaenibacillus larvae

Identifiers

PMID38818453
PMCPMC11138523

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.