Saral Sarıyer, Ayşegül2025-10-072025-10-07202216102940https://hdl.handle.net/11494/5983Antibiotic-resistant Acinetobacter baumannii, Pseudomonas aeruginosa, Mycobacterium tuberculosis, Staphylococcus aureus, and Enterobacterales infections are serious global health problems, and class A β-lactamases are one mechanism that leads to antibiotic resistance. QPX7728, relebactam, and enmetazobactam are new β-lactamase inhibitors to combat β-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 β-lactamases and to reveal molecular insights into the differences between their binding energies. The mutations in conserved residues of the active sites of β-lactamases were defined using BLDB and Clustal Omega. FastME and MMseq2 were used for cluster and phylogeny analysis. 3D protein structure models for β-lactamases were built using SWISS-MODEL. ERRAT and Galaxy Web Server were used to verify 42 β-lactamase protein structures. QPX7728, relebactam, and enmetazobactam were docked to β-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 β-lactamases. A 2D representation of the interactions between ligands and β-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.eninfo:eu-repo/semantics/openAccessClass A β-lactamasesEnmetazobactamMolecular dockingMolecular dynamic simulationsQPX7728RelebactamArticle28410.1007/s00894-022-05073-32-s2.0-85125691787Q2WOS:000764014400001Q3