ArticleMolecular biotechnology2026
Molecular and Computational Insights of Novel Mutations in Aminoglycoside-Modifying Genes of P. aeruginosa.
Article in Molecular biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- An Integrated Computational and Biophysical Approach for Investigating the Structure-Function Impact of blaOXA-58 Mutations in Acinetobacter baumannii.Molecular biotechnology · 2026Article
- Molecular and Computational Insights of Novel Mutations in Aminoglycoside-Modifying Genes of P. aeruginosa.Molecular biotechnology · 2026Article
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11 authors.
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Abstract
The production of aminoglycoside-modifying genes by P. aeruginosa is one of the key mechanisms by which resistance to aminoglycoside antibiotics is developed. The aim of the present work was to examine the prevalence of aac(6)-Ib, aac(6)-IIa, and aac(3)-IIa aminoglycoside-modifying genes in clinical samples. A total of 500 clinical samples were collected from Khyber Teaching Hospital (KTH), and showed a prevalence of 43.8% for P. aeruginosa. The biochemical identification of isolates was performed by Analytical Profile Index kit (API 20E) and on molecular level by PCR for the OprL gene. The antibiotic susceptibility pattern of the identified isolates was determined by the following guidelines of Clinical and Laboratory Standards Institute (CLSI), 2021. The results revealed that 121 out of 219 P. aeruginosa isolates were resistant to aminoglycosides. The frequencies of aac(6)-Ib, aac(3)-IIa and aac(6)-IIa were 95, 71.9, and 60.33%, respectively. Among the aminoglycoside-resistant isolates, 41.32% showed the presence of all the three genes. After sequencing of the PCR products, mutations were detected in aac(6)-Ib (Q110H), aac(3)-IIa (W5F, M51T, M58K, G63S) and aac(6)-IIa (T75P, G89S). The mutated sequence was translated into a protein sequence, followed by the prediction of its structure. After structure prediction, the binding ability of the wild and mutated proteins was analyzed through molecular docking. The docking analysis calculated different binding energy scores of -7.6, -7.1, -8.3, -7.1, and -7.1 kcal/mol for the aac(6)-Ib wild protein and antibiotics, including Gentamicin, Tobramycin, Amikacin, Kanamycin, and Streptomycin, respectively. In the case of mutated proteins and antibiotics, binding energies of -6.8, -6.1, -7.3, -6, and -5.6 kcal/mol were calculated. The dynamic stability of the docked complex was examined using molecular dynamics simulations, and the results indicate that the docked complexes maintain their stability throughout the simulation time frame.
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