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

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.

Generation of an Ovomucoid-Immune scFv Library for the Development of Novel Immunoassays in Hen’s Egg Detection

“…However, the SR-G1/ovomucoid model was selected regarding the RMSD, where a score below 2 Å is considered to have high accuracy [49]. Therefore, although the selected model had a slightly worse HADDOCK score than other estimations, the significantly better RMSD was considered an important parameter in the docking analysis to avoid bias [50]. Based on the modeled complex, the PRODIGY tool was used to predict binding energy and identify the total number of interactions between the two molecules (charged-charged, charged-polar, charged-apolar, polar-polar, polar-apolar, and apolarapolar interactions) as summarized in Table S3.…”

ATP‐independent assembly machinery of bacterial outer membranes: BAM complex structure and function set the stage for next‐generation therapeutics

“…It also shows synergistic activity with rifampicin. VUF15259 (Selvam et al, 2023) (e), compound 2 (Rath et al, 2023) (f), and compound 14 (Rath et al, 2023) (g) were discovered through high throughput screening assays. They decrease OMP levels and increase OM permeability, presumably by targeting BamA.…”

“…High throughput screening (HTS) assays have exploited the activity of BAM complex as an OMP insertase, and OM perturbation and triggering of stress response by BAM complex inhibitors, to identify new compounds (Rath et al, 2023; Steenhuis et al, 2019). For example, VUF15259 (Figure 6e) was identified as an inhibitor of autotransporter secretion by monitoring the σ E stress response (Selvam et al, 2023). It also inhibits BAM activity, with BAM‐compromised strains showing significantly repressed levels of BamA and the fully assembled complex, and all the major OMPs.…”

Recent Advances in Aptamer-Based Biosensors for Bacterial Detection

“…The in silico method has been successfully conducted to select aptamers for bacterial surface proteins [81][82][83]. Another example is a recently employed computational screening method used to select antimicrobial aptamers against the pathogen Pseudomonas aeruginosa [84]. The in silico strategy is a powerful and complementary tool to SELEX for the development of new aptamers against pathogenic bacteria.…”