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A rapid assessment model for liver toxicity of macrolides and an integrative evaluation for azithromycin impurities

ABSTRACT: A rapid assessment model for liver toxicity of macrolides and an integrative evaluation for azithromycin impurities

PROVIDER: PRJNA802658 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR17846327.fastq.gz	Fastqsanger.gz
	SRR17846328.fastq.gz	Fastqsanger.gz
	SRR17846329.fastq.gz	Fastqsanger.gz
	SRR17846330.fastq.gz	Fastqsanger.gz
	SRR17846331.fastq.gz	Fastqsanger.gz

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A rapid assessment model for liver toxicity of macrolides and an integrative evaluation for azithromycin impurities

Project description:we report an assessment of macrolides related liver toxicity by using ADMET prediction, molecular docking, structure-toxicity relationship and experimental verification via detecting the c-fos gene expression in liver cells.We employed the model to virtual screening of azithromycin impurities with high hepatotoxicity, and then experimental confirmed by liver toxicity in zebrafish, and c-fos gene expression.

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A Rapid Assessment Model for Liver Toxicity of Macrolides and an Integrative Evaluation for Azithromycin Impurities.

Project description:Impurities in pharmaceuticals of potentially hazardous materials may cause drug safety problems. Macrolide antibiotic preparations include active pharmaceutical ingredients (APIs) and different types of impurities with similar structures, and the amount of these impurities is usually very low and difficult to be separated for toxicity evaluation. Our previous study indicated that hepatotoxicity induced by macrolides was correlated with c-fos overexpression. Here, we report an assessment of macrolide-related liver toxicity by ADMET prediction, molecular docking, structure-toxicity relationship, and experimental verification via detection of the c-fos gene expression in liver cells. The results showed that a rapid assessment model for the prediction of hepatotoxicity of macrolide antibiotics could be established by calculation of the -CDOCKER interaction energy score with the FosB/JunD bZIP domain and then confirmed by the detection of the c-fos gene expression in L02 cells. Telithromycin, a positive compound of liver toxicity, was used to verify the correctness of the model through comparative analysis of liver toxicity in zebrafish and cytotoxicity in L02 cells exposed to telithromycin and azithromycin. The prediction interval (48.1∼53.1) for quantitative hepatotoxicity in the model was calculated from the docking scores of seven macrolide antibiotics commonly used in clinics. We performed the prediction interval to virtual screening of azithromycin impurities with high hepatotoxicity and then experimentally confirmed by liver toxicity in zebrafish and c-fos gene expression. Simultaneously, we found the hepatotoxicity of azithromycin impurities may be related to the charge of nitrogen (N) atoms on the side chain group at the C5 position via structure-toxicity relationship of azithromycin impurities with different structures. This study provides a theoretical basis for improvement of the quality of macrolide antibiotics.

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