Evidence map›Paper›PMID 39327354›Full record

ArticleMolecular diversity2025

Repurposing FDA-approved drugs for combating tigecycline resistance in Acinetobacter baumannii: in silico screening against BaeR protein.

Karthika Alagesan, Hemavathy Nagarajan, Jeyaraman Jeyakanthan

Abstract read
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In one paragraph

Article in Molecular diversity, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Revisiting the Fight AgainstAntibiotics (Basel, Switzerland) · 2026
    Review
  3. Threat and Control ofFoods (Basel, Switzerland) · 2025
    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

3 authors.

Karthika AlagesanStructural Biology and Bio-Computing Lab, Department of Bioinformatics, Alagappa University, Karaikudi, 630004, Tamil Nadu, India.
Hemavathy NagarajanStructural Biology and Bio-Computing Lab, Department of Bioinformatics, Alagappa University, Karaikudi, 630004, Tamil Nadu, India.
Jeyaraman JeyakanthanStructural Biology and Bio-Computing Lab, Department of Bioinformatics, Alagappa University, Karaikudi, 630004, Tamil Nadu, India. jjbioinformatics@gmail.com.

Funding

DBT-NNP BT/PR40156/BTIS/137/54/2023Department of Biotechnology-Bioinformatics Centre (BIC) BT/PR40154/BTIS/137/34/2021DST-Fund for Improvement of S&T Infrastructure in Universities & Higher Educational Institutions (FIST) SR/FST/LSI-667/2016) (C)DST INDO-TAIWAN GITA/DST/TWN/P-86/2019DST-Promotion of University Research and Scientific Excellence (PURSE phase II) SR/PURSE Phase 2/38 (G), 2017MHRD-RUSA 2.0 F.24e51/2014-U, Policy (TNMulti-Gen)TANSCHE RGP/2019-20/ALU/HECP-0049 dated:27/04/2021
6 · The paper itself

Abstract

Acinetobacter baumannii is becoming a gravely threatening nosocomial infection with a higher mortality rate. The present study targets the BaeR protein that mediates resistance to tigecycline antibiotics. The BaeR protein, along with the aid of BaeS, senses the incoming antibiotics and stimulates the expression of resistance proteins. These resistance proteins efflux the antibiotics and protect the cells from its effect. The main goal of the current study is to determine potential inhibitors from already existing FDA-approved drugs that could mitigate the BaeR protein. A range of in silico approaches, including molecular dynamics, virtual screening, SIFT analysis, ADMET, DFT, MM/GBSA, MMPBSA and per residue interaction analysis, were performed to identify inhibitors against this protein. The screening of FDA-approved compounds against the BaeR protein yielded 620 compounds. These compounds were clustered by SIFT to distinguish related compounds, it resulted in 20 different clusters. The top five clusters that can accommodate the binding site with better interaction and score by fulfilling all criteria were selected. The DFT analysis showed a smaller energy gap among all the compounds, indicating the ability of the compound to form firm interactions. All the compounds showed less binding free energy in both MM/GBSA and MM/PBSA analyses. The compounds were observed to be stable throughout the simulation. The per-residue interaction analysis confirmed that interactions with binding site residues were stable throughout the simulation. As a result of the study, four compounds, namely ZINC000003801919, DB01203, DB11217 and ZINC0000000056652, were identified as efficient candidates to deal with antimicrobial resistance in A. baumannii.

Indexed as

Acinetobacter baumanniiAnti-Bacterial AgentsBacterial ProteinsDrug RepositioningDrug Resistance, BacterialTigecyclineComputer SimulationMinocyclineMolecular Docking SimulationMolecular Dynamics SimulationUnited States Food and Drug AdministrationAnti-Bacterial AgentsBacterial ProteinsMinocyclineTigecyclineAcinetobacter baumanniiAntimicrobial resistanceBaeRMolecular dynamicsSIFT

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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.