AdeIJK Pump-Specific Inhibitors Effective against Multidrug Resistant Acinetobacter baumannii.

Multidrug-resistant Acinetobacter baumannii is a serious threat pathogen rapidly spreading in clinics and causing a range of complicated human infections. The major contributor to A. baumannii antibiotic resistance is the overproduction of AdeIJK and AdeABC multidrug efflux pumps of the resistance-nodulation-division (RND) superfamily of proteins. The dominant role of efflux in antibiotic resistance and the relatively high permeability of the A. baumannii outer membrane to amphiphilic compounds make this pathogen a promising target for the discovery of clinically relevant efflux pump inhibitors. In this study, we identified 4,6-diaminoquoniline analogs with inhibitory activities against A. baumannii AdeIJK efflux pump and followed up on these compounds with a focused synthetic program to improve the target specificity and to reduce cytotoxicity. We identified several candidates that potentiate antibacterial activities of antibiotics erythromycin, tetracycline, and novobiocin not only in the laboratory antibiotic susceptible strain A. baumannii ATCC17978 but also in multidrug-resistant clinical isolates AB5075 and AYE. The best analogs potentiated the activities of antibiotics in low micromolar concentrations, did not have antibacterial activities on their own, inhibited AdeIJK-mediated efflux of its fluorescent substrate ethidium ion, and had low cytotoxicity in A549 human lung epithelial cells.

Combined in silico approach and whole genome sequencing: Acinetobacter baumannii ST218 isolate harboring ADC-73 ß-lactamase which has a similar C-loop with ADC-56 and ADC-68 ß-lactamase.

PURPOSE: Multidrug-resistant Acinetobacter baumannii is a noteworthy nosocomial-pathogen and these pathogen-borne infections are difficult to treat. It is significant to make strain typing with WGS and to add new genome data to the literature. Therefore, in our study, we aimed to strain typing of the A. baumannii (A24) isolated from Turkey and reveal informations about ADC-73 ß-lactamase. METHODS: VITEK 2 system was used for the determination of antibiotic susceptibility. WGS was done on the Illumina NovaSeq 6000 platform. WGS results were analyzed with VFDB, ResFinder, PubMLST, IS Finder. Web-based bioinformatics software, homology modelling, molecular docking and dynamics simulations were used to determine all structural information about ADC-73 ß-lactamase. RESULTS: A24 was found to be multidrug-resistant. Various virulence factors were found in A24. The sequence type of the isolate was determined as ST218. Genes encoding ß-lactamase and aminoglycoside modifying enzymes, and IS elements were present in the genome of A24. Besides, secondary and 3D structures of ADC-73 were analyzed. Following, cefepime and imipenem were docked to ADC-56, ADC-68, and ADC-73 and interactions and stability of substrates were simulated. The binding-energies of imipenem to ADC-68 and ADC-73 were calculated -9.44 and -5.98 kcal/mol, respectively. Likewise, binding-energies of cefepime to ADC-56 and ADC-73 were calculated as -19.84 and -36.54 kcal/mol. CONCLUSION: A. baumannii ST218 isolate containing ADC-73 was reported for the first time in Turkey by WGS, and the effect of G225S mutation in this ß-lactamase on conformational change and possible interactions with cefepime and impinem were investigated in silico.

Three new inhibitors of class A ß-lactamases evaluated by molecular docking and dynamics simulations methods: relebactam, enmetazobactam, and QPX7728.

Antibiotic-resistant Acinetobacter baumannii, Pseudomonas aeruginosa, Mycobacterium tuberculosis, Staphylococcus aureus, and Enterobacterales infections are serious global health problems, and class A ß-lactamases are one mechanism that leads to antibiotic resistance. QPX7728, relebactam, and enmetazobactam are new ß-lactamase inhibitors to combat ß-lactam resistance. in silico approach was used in the current study to find which of the three inhibitors would be more effective for all class A ß-lactamases and to reveal molecular insights into the differences between their binding energies. The mutations in conserved residues of the active sites of ß-lactamases were defined using BLDB and Clustal Omega. FastME and MMseq2 were used for cluster and phylogeny analysis. 3D protein structure models for ß-lactamases were built using SWISS-MODEL. ERRAT and Galaxy Web Server were used to verify 42 ß-lactamase protein structures. QPX7728, relebactam, and enmetazobactam were docked to ß-lactamases by using AutoDock 4.2. The TEM76-relebactam, CTX-M-81-relebactam, TEM-76-enmetazobactam, and CTX-M-200-enmetazobactam complexes were simulated by molecular dynamics method for 500 ns. Based on molecular docking results, relebactam and QPX7728 were more favorable inhibitors for serine A ß-lactamases. A 2D representation of the interactions between ligands and ß-lactamases showed that S235, hydrogen bonded with TEM-76, might play a role in inhibitor design. A 500-ns MD analysis of complexes indicated that distance from S70, stability in the enzyme active cavity, and high atomic displacement would account for a significant difference in inhibitor binding affinity.