Evidence map›Paper›PMID 37164985›Full record

ArticleScientific reports2023

Selecting antibacterial aptamers against the BamA protein in Pseudomonas aeruginosa by incorporating genetic algorithm to optimise computational screening method.

Rupany Selvam, Ian Han Yan Lim, Jovita Catherine Lewis, Chern Hong Lim, Michelle Khai Khun Yap, Hock Siew Tan

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
5.5field-weighted citation impact, top 4% 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

13 citing papers in PubMed, 22 citations in OpenAlex.

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  12. Aptamer-based technology for detecting Bacillus subtilis in soil.Applied microbiology and biotechnology · 2023
    Article
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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 1 institution in 1 country.

Rupany SelvamSchool of Science, Monash University Malaysia, Bandar Sunway, Selangor, Malaysia.
Ian Han Yan LimSchool of Science, Monash University Malaysia, Bandar Sunway, Selangor, Malaysia.
Jovita Catherine LewisSchool of Science, Monash University Malaysia, Bandar Sunway, Selangor, Malaysia.
Chern Hong LimSchool of Information Technology, Monash University Malaysia, Bandar Sunway, Selangor, Malaysia.
Michelle Khai Khun YapSchool of Science, Monash University Malaysia, Bandar Sunway, Selangor, Malaysia.
Hock Siew TanSchool of Science, Monash University Malaysia, Bandar Sunway, Selangor, Malaysia. tan.hocksiew@monash.edu.
Monash University Malaysia · MY

Funding

UCSF Core Center for Patient-centric Mechanistic Phenotyping in Chronic Low Back PainU19AR076737 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LOTZ, JEFFREY C. · 2019 to 2023
$34.1M
NIAMS NIH HHS U19 AR076737
6 · The paper itself

Abstract

Antibiotic resistance is one of the biggest threats to global health resulting in an increasing number of people suffering from severe illnesses or dying due to infections that were once easily curable with antibiotics. Pseudomonas aeruginosa is a major pathogen that has rapidly developed antibiotic resistance and WHO has categorised this pathogen under the critical list. DNA aptamers can act as a potential candidate for novel antimicrobial agents. In this study, we demonstrated that an existing aptamer is able to affect the growth of P. aeruginosa. A computational screen for aptamers that could bind to a well-conserved and essential outer membrane protein, BamA in Gram-negative bacteria was conducted. Molecular docking of about 100 functional DNA aptamers with BamA protein was performed via both local and global docking approaches. Additionally, genetic algorithm analysis was carried out to rank the aptamers based on their binding affinity. The top hits of aptamers with good binding to BamA protein were synthesised to investigate their in vitro antibacterial activity. Among all aptamers, Apt31, which is known to bind to an antitumor, Daunomycin, exhibited the highest HADDOCK score and resulted in a significant (p < 0.05) reduction in P. aeruginosa growth. Apt31 also induced membrane disruption that resulted in DNA leakage. Hence, computational screening may result in the identification of aptamers that bind to the desired active site with high affinity.

Indexed as

Aptamers, NucleotidePseudomonas aeruginosaAnti-Bacterial AgentsHumansMolecular Docking SimulationAnti-Bacterial AgentsAptamers, Nucleotide

Identifiers

PMID37164985
PMCPMC10170454
OpenAlexW4376133112

What OpenQuestion holds

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LicenceCC BY
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.