Repurposing FDA-approved drugs for combating tigecycline resistance in Acinetobacter baumannii: in silico screening against BaeR protein.

Autor: Alagesan K; Structural Biology and Bio-Computing Lab, Department of Bioinformatics, Alagappa University, Karaikudi, 630004, Tamil Nadu, India., Nagarajan H; Structural Biology and Bio-Computing Lab, Department of Bioinformatics, Alagappa University, Karaikudi, 630004, Tamil Nadu, India., Jeyakanthan J; Structural Biology and Bio-Computing Lab, Department of Bioinformatics, Alagappa University, Karaikudi, 630004, Tamil Nadu, India. jjbioinformatics@gmail.com.
Jazyk: angličtina
Zdroj: Molecular diversity [Mol Divers] 2024 Sep 26. Date of Electronic Publication: 2024 Sep 26.
DOI: 10.1007/s11030-024-10988-5
Abstrakt: Acinetobacter baumannii is becoming a gravely threatening nosocomial infection with a higher mortality rate. The present study targets the BaeR protein that mediates resistance to tigecycline antibiotics. The BaeR protein, along with the aid of BaeS, senses the incoming antibiotics and stimulates the expression of resistance proteins. These resistance proteins efflux the antibiotics and protect the cells from its effect. The main goal of the current study is to determine potential inhibitors from already existing FDA-approved drugs that could mitigate the BaeR protein. A range of in silico approaches, including molecular dynamics, virtual screening, SIFT analysis, ADMET, DFT, MM/GBSA, MMPBSA and per residue interaction analysis, were performed to identify inhibitors against this protein. The screening of FDA-approved compounds against the BaeR protein yielded 620 compounds. These compounds were clustered by SIFT to distinguish related compounds, it resulted in 20 different clusters. The top five clusters that can accommodate the binding site with better interaction and score by fulfilling all criteria were selected. The DFT analysis showed a smaller energy gap among all the compounds, indicating the ability of the compound to form firm interactions. All the compounds showed less binding free energy in both MM/GBSA and MM/PBSA analyses. The compounds were observed to be stable throughout the simulation. The per-residue interaction analysis confirmed that interactions with binding site residues were stable throughout the simulation. As a result of the study, four compounds, namely ZINC000003801919, DB01203, DB11217 and ZINC0000000056652, were identified as efficient candidates to deal with antimicrobial resistance in A. baumannii.
(© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)
Databáze: MEDLINE
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