Modeling and insights into the structural basis of chemical acute aquatic toxicity
It has become a top global regulatory priority to prevent and control pollution from the release of synthetic chemicals, which continues to affect the aquatic communities. In the past decades, computational tools were largely used to significantly reduce the budget and time cost of chemical acute aq...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-09-01
|
| Series: | Ecotoxicology and Environmental Safety |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0147651322007801 |
| _version_ | 1828298949424840704 |
|---|---|
| author | Ruiqiu Zhang Huizhu Guo Yuqing Hua Xueyan Cui Yinping Shi Xiao Li |
| author_facet | Ruiqiu Zhang Huizhu Guo Yuqing Hua Xueyan Cui Yinping Shi Xiao Li |
| author_sort | Ruiqiu Zhang |
| collection | DOAJ |
| description | It has become a top global regulatory priority to prevent and control pollution from the release of synthetic chemicals, which continues to affect the aquatic communities. In the past decades, computational tools were largely used to significantly reduce the budget and time cost of chemical acute aquatic toxicity assessment. But the structural basis of toxic compounds was rarely analyzed. In the present study, we collected 1438, 485 and 961 chemicals with acute toxicity data records for three representative aquatic species, including Tetrahymena pyriformis, Daphnia magna, and Fathead minnow, respectively. A series of artificial intelligence models were developed using OCHEM tools. For each aquatic toxicity endpoint, a consensus model was developed based on the top performed individual models. The consensus models provided good performance on external validation sets with total accuracy values 96.88 %, 90.63 %, and 84.90 % for Tetrahymena pyriformis toxicity (TPT), Daphnia magna toxicity (DMT), and Fathead minnow toxicity (FMT), respectively. The models can be freely accessed via https://ochem.eu/article/146910. Moreover, the analysis of physical-chemical properties suggested that several key molecular properties of aquatic toxic compounds were significantly different with those of non-toxic compounds. Thus, these descriptors may be associated to chemical acute aquatic toxicity, and may be useful for the understand of chemical aquatic toxicity. Besides, in this study, the structural alerts for aquatic toxicity were detected using f-score and frequency ratio analysis of predefined substructures. A total of 112, 58 and 33 structural alerts were identified responsible for TPT, DMT, and FMT, respectively. These structural alerts could provide useful information for the mechanisms of chemical aquatic toxicity and visual alerts for environmental assessment. All the structural alerts were integrated in the web-server SApredictor (www.sapredictor.cn). |
| first_indexed | 2024-04-13T12:48:29Z |
| format | Article |
| id | doaj.art-5feccd3bfc9a4714b40aa5973a33dab8 |
| institution | Directory Open Access Journal |
| issn | 0147-6513 |
| language | English |
| last_indexed | 2024-04-13T12:48:29Z |
| publishDate | 2022-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecotoxicology and Environmental Safety |
| spelling | doaj.art-5feccd3bfc9a4714b40aa5973a33dab82022-12-22T02:46:18ZengElsevierEcotoxicology and Environmental Safety0147-65132022-09-01242113940Modeling and insights into the structural basis of chemical acute aquatic toxicityRuiqiu Zhang0Huizhu Guo1Yuqing Hua2Xueyan Cui3Yinping Shi4Xiao Li5Department of Clinical Pharmacy, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Engineering and Technology Research Center for Pediatric Drug Development, Shandong Medicine and Health Key Laboratory of Clinical Pharmacy, Jinan 250014, ChinaDepartment of Clinical Pharmacy, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Engineering and Technology Research Center for Pediatric Drug Development, Shandong Medicine and Health Key Laboratory of Clinical Pharmacy, Jinan 250014, ChinaDepartment of Clinical Pharmacy, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Engineering and Technology Research Center for Pediatric Drug Development, Shandong Medicine and Health Key Laboratory of Clinical Pharmacy, Jinan 250014, ChinaDepartment of Clinical Pharmacy, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Engineering and Technology Research Center for Pediatric Drug Development, Shandong Medicine and Health Key Laboratory of Clinical Pharmacy, Jinan 250014, ChinaDepartment of Clinical Pharmacy, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Engineering and Technology Research Center for Pediatric Drug Development, Shandong Medicine and Health Key Laboratory of Clinical Pharmacy, Jinan 250014, ChinaDepartment of Clinical Pharmacy, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Engineering and Technology Research Center for Pediatric Drug Development, Shandong Medicine and Health Key Laboratory of Clinical Pharmacy, Jinan 250014, China; Department of Clinical Pharmacy, Shandong Provincial Qianfoshan Hospital, Shandong University, Jinan 250014, China; Corresponding author at: Department of Clinical Pharmacy, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Engineering and Technology Research Center for Pediatric Drug Development, Shandong Medicine and Health Key Laboratory of Clinical Pharmacy, Jinan 250014, China.It has become a top global regulatory priority to prevent and control pollution from the release of synthetic chemicals, which continues to affect the aquatic communities. In the past decades, computational tools were largely used to significantly reduce the budget and time cost of chemical acute aquatic toxicity assessment. But the structural basis of toxic compounds was rarely analyzed. In the present study, we collected 1438, 485 and 961 chemicals with acute toxicity data records for three representative aquatic species, including Tetrahymena pyriformis, Daphnia magna, and Fathead minnow, respectively. A series of artificial intelligence models were developed using OCHEM tools. For each aquatic toxicity endpoint, a consensus model was developed based on the top performed individual models. The consensus models provided good performance on external validation sets with total accuracy values 96.88 %, 90.63 %, and 84.90 % for Tetrahymena pyriformis toxicity (TPT), Daphnia magna toxicity (DMT), and Fathead minnow toxicity (FMT), respectively. The models can be freely accessed via https://ochem.eu/article/146910. Moreover, the analysis of physical-chemical properties suggested that several key molecular properties of aquatic toxic compounds were significantly different with those of non-toxic compounds. Thus, these descriptors may be associated to chemical acute aquatic toxicity, and may be useful for the understand of chemical aquatic toxicity. Besides, in this study, the structural alerts for aquatic toxicity were detected using f-score and frequency ratio analysis of predefined substructures. A total of 112, 58 and 33 structural alerts were identified responsible for TPT, DMT, and FMT, respectively. These structural alerts could provide useful information for the mechanisms of chemical aquatic toxicity and visual alerts for environmental assessment. All the structural alerts were integrated in the web-server SApredictor (www.sapredictor.cn).http://www.sciencedirect.com/science/article/pii/S0147651322007801Acute aquatic toxicityComputational modelPhysical-chemical propertyStructural alertSApredictor |
| spellingShingle | Ruiqiu Zhang Huizhu Guo Yuqing Hua Xueyan Cui Yinping Shi Xiao Li Modeling and insights into the structural basis of chemical acute aquatic toxicity Ecotoxicology and Environmental Safety Acute aquatic toxicity Computational model Physical-chemical property Structural alert SApredictor |
| title | Modeling and insights into the structural basis of chemical acute aquatic toxicity |
| title_full | Modeling and insights into the structural basis of chemical acute aquatic toxicity |
| title_fullStr | Modeling and insights into the structural basis of chemical acute aquatic toxicity |
| title_full_unstemmed | Modeling and insights into the structural basis of chemical acute aquatic toxicity |
| title_short | Modeling and insights into the structural basis of chemical acute aquatic toxicity |
| title_sort | modeling and insights into the structural basis of chemical acute aquatic toxicity |
| topic | Acute aquatic toxicity Computational model Physical-chemical property Structural alert SApredictor |
| url | http://www.sciencedirect.com/science/article/pii/S0147651322007801 |
| work_keys_str_mv | AT ruiqiuzhang modelingandinsightsintothestructuralbasisofchemicalacuteaquatictoxicity AT huizhuguo modelingandinsightsintothestructuralbasisofchemicalacuteaquatictoxicity AT yuqinghua modelingandinsightsintothestructuralbasisofchemicalacuteaquatictoxicity AT xueyancui modelingandinsightsintothestructuralbasisofchemicalacuteaquatictoxicity AT yinpingshi modelingandinsightsintothestructuralbasisofchemicalacuteaquatictoxicity AT xiaoli modelingandinsightsintothestructuralbasisofchemicalacuteaquatictoxicity |