Evidence map›Paper›PMID 35449379›Full record

ArticleScientific reports2022

Integrated computer-aided drug design and biophysical simulation approaches to determine natural anti-bacterial compounds for Acinetobacter baumannii.

Raed A H Almihyawi, Ziad Tareq Naman, Halah M H Al-Hasani, Ziyad Tariq Muhseen, Sitong Zhang, Guang Chen

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
3.3field-weighted citation impact, top 8% of its field
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

9 citing papers in PubMed, 19 citations in OpenAlex.

  1. Frontiers in cellular and infection microbiology · 2026
    Article
  2. Determination of Potential Inhibitors againstCurrent pharmaceutical design · 2026
    Review
  3. Article
  4. Article
  5. Article
  6. Novel Coumarins Derivatives for A. baumannii Lung Infection Developed by High-Throughput Screening and Reinforcement Learning.Journal of neuroimmune pharmacology : the official journal of the Society on NeuroImmune Pharmacology · 2024
    Article
  7. Article
  8. Identification of novel drug targets forFrontiers in bioinformatics · 2024
    Article
  9. 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

6 authors at 5 institutions in 2 countries.

Raed A H AlmihyawiCollege of Life Sciences, Jilin Agricultural University, Jilin, China.
Ziad Tareq NamanDepartment of Medical Laboratory Techniques, Al Mamoon University College, Baghdad, Iraq.
Halah M H Al-HasaniDepartment of Biotechnology, College of Science, University of Diyala, Baqubah, Iraq.
Ziyad Tariq MuhseenDepartment of Biomedical Engineering, College of Engineering and Applied Sciences, Nanjing University, Nanjing, 210093, China.
Sitong ZhangCollege of Life Sciences, Jilin Agricultural University, Jilin, China. 18943132269@163.com.
Guang ChenCollege of Life Sciences, Jilin Agricultural University, Jilin, China. Chg61@163.com.
Baghdad Medical City · IQJilin Agricultural University · CNMinistry of Education of the People's Republic of China · CNNanjing University · CNUniversity of Diyala · IQ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acinetobacter baumannii is a nosocomial bacterial pathogen and is responsible for a wide range of diseases including pneumonia, necrotizing fasciitis, meningitis, and sepsis. The enzyme 5-enolpyruvylshikimate-3-phosphate (EPSP) synthase (encoded by aroA gene) in ESKAPE pathogens catalyzes the sixth step of shikimate pathway. The shikimate pathway is an attractive drug targets pathway as it is present in bacteria but absent in humans. As EPSP is essential for the A. baumannii growth and needed during the infection process, therefore it was used as a drug target herein for high-throughput screening of a comprehensive marine natural products database (CMNPD). The objective was to identify natural molecules that fit best at the substrate binding pocket of the enzyme and interact with functionally critical residues. Comparative assessment of the docking scores allowed selection of three compounds namely CMNPD31561, CMNPD28986, and CMNPD28985 as best binding molecules. The molecules established a balanced network of hydrophobic and hydrophilic interactions, and the binding pose remained in equilibrium throughout the length of molecular simulation time. Radial distribution function (RDF) analysis projected key residues from enzyme active pocket which actively engaged the inhibitors. Further validation is performed through binding free energies estimation that affirms very low delta energy of <-22 kcal/mol in MM-GBSA method and <-12 kcal/mol in MM-PBSA method. Lastly, the most important active site residues were mutated and their ligand binding potential was re-investigated. The molecules also possess good druglike properties and better pharmacokinetics. Together, these findings suggest the potential biological potency of the leads and thus can be used by experimentalists in vivo and in vitro studies.

Indexed as

Acinetobacter baumanniiAnti-Bacterial AgentsComputer SimulationDrug DesignHumansLigandsMolecular Docking SimulationMolecular Dynamics SimulationAnti-Bacterial AgentsLigands

Identifiers

PMID35449379
PMCPMC9023527
OpenAlexW4224255460

What OpenQuestion holds

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LicenceCC BY
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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.