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

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...

Full description

Saved in:

Bibliographic Details
Published in:	Scientific reports Vol. 13; no. 1; p. 7582
Main Authors:	Selvam, Rupany, Lim, Ian Han Yan, Lewis, Jovita Catherine, Lim, Chern Hong, Yap, Michelle Khai Khun, Tan, Hock Siew
Format:	Journal Article
Language:	English
Published:	London Nature Publishing Group UK 10-05-2023 Nature Publishing Group Nature Portfolio
Subjects:	631/114 631/326 631/61 Affinity Algorithms Anti-Bacterial Agents - pharmacology Antibacterial activity Antibiotic resistance Antibiotics Antimicrobial agents Aptamers Aptamers, Nucleotide - chemistry Bacteria Computer applications Daunomycin Deoxyribonucleic acid DNA Drug resistance Genetic algorithms Genetic analysis Global health Gram-negative bacteria Humanities and Social Sciences Humans Membrane proteins Molecular Docking Simulation multidisciplinary Pathogens Proteins Pseudomonas aeruginosa Public health Science Science (multidisciplinary)
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Description
Summary:	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.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	2045-2322 2045-2322
DOI:	10.1038/s41598-023-34643-5