Background: Colistin is a last-resort treatment option for many MDR Gram-negative bacteria. The covalent addition of L-aminoarabinose to the lipid A moiety of LPS is the main colistin resistance mechanism in the human pathogen Pseudomonas aeruginosa. Objectives: Identification (by in silico screening of a chemical library) of potential inhibitors of ArnT, which catalyses the last committed step of lipid A aminoarabinosylation, and their validation in vitro as colistin adjuvants. Methods: The available ArnT crystal structure was used for a docking-based virtual screening of an in-house library of natural products. The resulting putative ArnT inhibitors were tested in growth inhibition assays using a reference colistin-resistant P. aeruginosa strain. The most promising compound was further characterized for its range of activity, specificity and cytotoxicity. Additionally, the effect of the compound on lipid A aminoarabinosylation was verified by MS analyses of lipid A. Results: A putative ArnT inhibitor (BBN149) was discovered by molecular docking and demonstrated to specifically potentiate colistin activity in colistin-resistant P. aeruginosa isolates, without relevant effect on colistinsusceptible strains. BBN149 also showed adjuvant activity against colistin-resistant Klebsiella pneumoniae and low toxicity to bronchial epithelial cells. Lipid A aminoarabinosylation was reduced in BBN149-treated cells, although only partially. Conclusions: This study demonstrates that in silico screening targeting ArnT can successfully identify inhibitors of colistin resistance and provides a promising lead compound for the development of colistin adjuvants for the treatment of MDR bacterial infections.

Ghirga, F., Stefanelli, R., Cavinato, L., Lo Sciuto, A., Corradi, S., Quaglio, D., et al. (2020). A novel colistin adjuvant identified by virtual screening for ArnT inhibitors. JOURNAL OF ANTIMICROBIAL CHEMOTHERAPY, 75(9), 2564-2572 [10.1093/jac/dkaa200].

A novel colistin adjuvant identified by virtual screening for ArnT inhibitors

Lo Sciuto A.;Imperi F.
2020

Abstract

Background: Colistin is a last-resort treatment option for many MDR Gram-negative bacteria. The covalent addition of L-aminoarabinose to the lipid A moiety of LPS is the main colistin resistance mechanism in the human pathogen Pseudomonas aeruginosa. Objectives: Identification (by in silico screening of a chemical library) of potential inhibitors of ArnT, which catalyses the last committed step of lipid A aminoarabinosylation, and their validation in vitro as colistin adjuvants. Methods: The available ArnT crystal structure was used for a docking-based virtual screening of an in-house library of natural products. The resulting putative ArnT inhibitors were tested in growth inhibition assays using a reference colistin-resistant P. aeruginosa strain. The most promising compound was further characterized for its range of activity, specificity and cytotoxicity. Additionally, the effect of the compound on lipid A aminoarabinosylation was verified by MS analyses of lipid A. Results: A putative ArnT inhibitor (BBN149) was discovered by molecular docking and demonstrated to specifically potentiate colistin activity in colistin-resistant P. aeruginosa isolates, without relevant effect on colistinsusceptible strains. BBN149 also showed adjuvant activity against colistin-resistant Klebsiella pneumoniae and low toxicity to bronchial epithelial cells. Lipid A aminoarabinosylation was reduced in BBN149-treated cells, although only partially. Conclusions: This study demonstrates that in silico screening targeting ArnT can successfully identify inhibitors of colistin resistance and provides a promising lead compound for the development of colistin adjuvants for the treatment of MDR bacterial infections.
Ghirga, F., Stefanelli, R., Cavinato, L., Lo Sciuto, A., Corradi, S., Quaglio, D., et al. (2020). A novel colistin adjuvant identified by virtual screening for ArnT inhibitors. JOURNAL OF ANTIMICROBIAL CHEMOTHERAPY, 75(9), 2564-2572 [10.1093/jac/dkaa200].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/375144
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