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Investigation of potential descriptors of chemical compounds on prevention of nephrotoxicity via QSAR approach

Authors :
Hung-Jin Huang
Yu-Hsuan Lee
Chu-Lin Chou
Cai-Mei Zheng
Hui-Wen Chiu
Source :
Computational and Structural Biotechnology Journal, Vol 20, Iss , Pp 1876-1884 (2022)
Publication Year :
2022
Publisher :
Elsevier, 2022.

Abstract

Drug-induced nephrotoxicity remains a common problem after exposure to medications and diagnostic agents, which may be heightened in the kidney microenvironment and deteriorate kidney function. In this study, the toxic effects of fourteen marked drugs with the individual chemical structure were evaluated in kidney cells. The quantitative structure–activity relationship (QSAR) approach was employed to investigate the potential structural descriptors of each drug-related to their toxic effects. The most reasonable equation of the QSAR model displayed that the estimated regression coefficients such as the number of ring assemblies, three-membered rings, and six-membered rings were strongly related to toxic effects on renal cells. Meanwhile, the chemical properties of the tested compounds including carbon atoms, bridge bonds, H-bond donors, negative atoms, and rotatable bonds were favored properties and promote the toxic effects on renal cells. Particularly, more numbers of rotatable bonds were positively correlated with strong toxic effects that displayed on the most toxic compound. The useful information discovered from our regression QSAR models may help to identify potential hazardous moiety to avoid nephrotoxicity in renal preventive medicine.

Details

Language :
English
ISSN :
20010370
Volume :
20
Issue :
1876-1884
Database :
Directory of Open Access Journals
Journal :
Computational and Structural Biotechnology Journal
Publication Type :
Academic Journal
Accession number :
edsdoj.318166fcefe4933a8d88f278b0d609b
Document Type :
article
Full Text :
https://doi.org/10.1016/j.csbj.2022.04.013