Development of an effective QSAR-based hazard threshold prediction model for the ecological risk assessment of aromatic hydrocarbon compounds.

The insufficient hazard thresholds of specific individual aromatic hydrocarbon compounds (AHCs) with diverse structures limit their ecological risk assessment. Thus, herein, quantitative structure-activity relationship (QSAR) models for estimating the hazard threshold of AHCs were developed based on...

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Published in:Environmental Science and Pollution Research
Main Authors: Lv, Xiudi, He, Mei, Wei, Jiajia, Li, Qiang, Nie, Fan, Shao, Zhiguo, Wang, Zhansheng, Tian, Lei
Format: Article in Journal/Newspaper
Language:English
Published: Springer 2024
Subjects:
Online Access:https://doi.org/10.1007/s11356-024-34016-z
https://pubmed.ncbi.nlm.nih.gov/38990260
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spelling ftpubmed:38990260 2024-09-15T18:28:58+00:00 Development of an effective QSAR-based hazard threshold prediction model for the ecological risk assessment of aromatic hydrocarbon compounds. Lv, Xiudi He, Mei Wei, Jiajia Li, Qiang Nie, Fan Shao, Zhiguo Wang, Zhansheng Tian, Lei 2024 Jul 11 https://doi.org/10.1007/s11356-024-34016-z https://pubmed.ncbi.nlm.nih.gov/38990260 eng eng Springer https://doi.org/10.1007/s11356-024-34016-z https://pubmed.ncbi.nlm.nih.gov/38990260 © 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. Environ Sci Pollut Res Int ISSN:1614-7499 Aromatic hydrocarbon Effective hazardous concentration Molecular descriptor Quantitative structure–activity relationship Species sensitivity distribution Journal Article 2024 ftpubmed https://doi.org/10.1007/s11356-024-34016-z 2024-07-11T16:03:00Z The insufficient hazard thresholds of specific individual aromatic hydrocarbon compounds (AHCs) with diverse structures limit their ecological risk assessment. Thus, herein, quantitative structure-activity relationship (QSAR) models for estimating the hazard threshold of AHCs were developed based on the hazardous concentration for 5% of species (HC5) determined using the optimal species sensitivity distribution models and on the molecular descriptors calculated via the PADEL software and ORCA software. Results revealed that the optimal QSAR model, which involved eight descriptors, namely, Zagreb, GATS2m, VR3_Dzs, AATSC2s, GATS2c, ATSC2i, ω, and Vm, displayed excellent performance, as reflected by an optimal goodness of fit (R2adj = 0.918), robustness (Q2LOO = 0.869), and external prediction ability (Q2F1 = 0.760, Q2F2 = 0.782, and Q2F3 = 0.774). The hazard thresholds estimated using the optimal QSAR model were approximately close to the published water quality criteria developed by different countries and regions. The quantitative structure-toxicity relationship demonstrated that the molecular descriptors associated with electrophilicity and topological and electrotopological properties were important factors that affected the risks of AHCs. A new and reliable approach to estimate the hazard threshold of ecological risk assessment for various aromatic hydrocarbon pollutants was provided in this study, which can be widely popularised to similar contaminants with diverse structures. Article in Journal/Newspaper Orca PubMed Central (PMC) Environmental Science and Pollution Research 31 34 47220 47236
institution Open Polar
collection PubMed Central (PMC)
op_collection_id ftpubmed
language English
topic Aromatic hydrocarbon
Effective hazardous concentration
Molecular descriptor
Quantitative structure–activity relationship
Species sensitivity distribution
spellingShingle Aromatic hydrocarbon
Effective hazardous concentration
Molecular descriptor
Quantitative structure–activity relationship
Species sensitivity distribution
Lv, Xiudi
He, Mei
Wei, Jiajia
Li, Qiang
Nie, Fan
Shao, Zhiguo
Wang, Zhansheng
Tian, Lei
Development of an effective QSAR-based hazard threshold prediction model for the ecological risk assessment of aromatic hydrocarbon compounds.
topic_facet Aromatic hydrocarbon
Effective hazardous concentration
Molecular descriptor
Quantitative structure–activity relationship
Species sensitivity distribution
description The insufficient hazard thresholds of specific individual aromatic hydrocarbon compounds (AHCs) with diverse structures limit their ecological risk assessment. Thus, herein, quantitative structure-activity relationship (QSAR) models for estimating the hazard threshold of AHCs were developed based on the hazardous concentration for 5% of species (HC5) determined using the optimal species sensitivity distribution models and on the molecular descriptors calculated via the PADEL software and ORCA software. Results revealed that the optimal QSAR model, which involved eight descriptors, namely, Zagreb, GATS2m, VR3_Dzs, AATSC2s, GATS2c, ATSC2i, ω, and Vm, displayed excellent performance, as reflected by an optimal goodness of fit (R2adj = 0.918), robustness (Q2LOO = 0.869), and external prediction ability (Q2F1 = 0.760, Q2F2 = 0.782, and Q2F3 = 0.774). The hazard thresholds estimated using the optimal QSAR model were approximately close to the published water quality criteria developed by different countries and regions. The quantitative structure-toxicity relationship demonstrated that the molecular descriptors associated with electrophilicity and topological and electrotopological properties were important factors that affected the risks of AHCs. A new and reliable approach to estimate the hazard threshold of ecological risk assessment for various aromatic hydrocarbon pollutants was provided in this study, which can be widely popularised to similar contaminants with diverse structures.
format Article in Journal/Newspaper
author Lv, Xiudi
He, Mei
Wei, Jiajia
Li, Qiang
Nie, Fan
Shao, Zhiguo
Wang, Zhansheng
Tian, Lei
author_facet Lv, Xiudi
He, Mei
Wei, Jiajia
Li, Qiang
Nie, Fan
Shao, Zhiguo
Wang, Zhansheng
Tian, Lei
author_sort Lv, Xiudi
title Development of an effective QSAR-based hazard threshold prediction model for the ecological risk assessment of aromatic hydrocarbon compounds.
title_short Development of an effective QSAR-based hazard threshold prediction model for the ecological risk assessment of aromatic hydrocarbon compounds.
title_full Development of an effective QSAR-based hazard threshold prediction model for the ecological risk assessment of aromatic hydrocarbon compounds.
title_fullStr Development of an effective QSAR-based hazard threshold prediction model for the ecological risk assessment of aromatic hydrocarbon compounds.
title_full_unstemmed Development of an effective QSAR-based hazard threshold prediction model for the ecological risk assessment of aromatic hydrocarbon compounds.
title_sort development of an effective qsar-based hazard threshold prediction model for the ecological risk assessment of aromatic hydrocarbon compounds.
publisher Springer
publishDate 2024
url https://doi.org/10.1007/s11356-024-34016-z
https://pubmed.ncbi.nlm.nih.gov/38990260
genre Orca
genre_facet Orca
op_source Environ Sci Pollut Res Int
ISSN:1614-7499
op_relation https://doi.org/10.1007/s11356-024-34016-z
https://pubmed.ncbi.nlm.nih.gov/38990260
op_rights © 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
op_doi https://doi.org/10.1007/s11356-024-34016-z
container_title Environmental Science and Pollution Research
container_volume 31
container_issue 34
container_start_page 47220
op_container_end_page 47236
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