Prediction of chemical warfare agents based on cholinergic array type meta-predictors
Abstract Molecular insights into chemical safety are very important for sustainable development as well as risk assessment. This study considers how to manage future upcoming harmful agents, especially potentially cholinergic chemical warfare agents (CWAs). For this purpose, the structures of known...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-10-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-21150-2 |
| _version_ | 1811194915442393088 |
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| author | Surendra Kumar Chandni Kumari Sangjin Ahn Hyoungrae Kim Mi-hyun Kim |
| author_facet | Surendra Kumar Chandni Kumari Sangjin Ahn Hyoungrae Kim Mi-hyun Kim |
| author_sort | Surendra Kumar |
| collection | DOAJ |
| description | Abstract Molecular insights into chemical safety are very important for sustainable development as well as risk assessment. This study considers how to manage future upcoming harmful agents, especially potentially cholinergic chemical warfare agents (CWAs). For this purpose, the structures of known cholinergic agents were encoded by molecular descriptors. And then each drug target interaction (DTI) was learned from the encoded structures and their cholinergic activities to build DTI classification models for five cholinergic targets with reliable statistical validation (ensemble-AUC: up to 0.790, MCC: up to 0.991, accuracy: up to 0.995). The collected classifiers were transformed into 2D or 3D array type meta-predictors for multi-task: (1) cholinergic prediction and (2) CWA detection. The detection ability of the array classifiers was verified under the imbalanced dataset between CWAs and none CWAs (area under the precision-recall curve: up to 0.997, MCC: up to 0.638, F1-score of none CWAs: up to 0.991, F1-score of CWAs: up to 0.585). |
| first_indexed | 2024-04-12T00:35:16Z |
| format | Article |
| id | doaj.art-743d32cda7eb45b5b94475b558980f90 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-12T00:35:16Z |
| publishDate | 2022-10-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-743d32cda7eb45b5b94475b558980f902022-12-22T03:55:11ZengNature PortfolioScientific Reports2045-23222022-10-0112111110.1038/s41598-022-21150-2Prediction of chemical warfare agents based on cholinergic array type meta-predictorsSurendra Kumar0Chandni Kumari1Sangjin Ahn2Hyoungrae Kim3Mi-hyun Kim4Department of Pharmacy, Gachon Institute of Pharmaceutical Science, College of Pharmacy, Gachon UniversityDepartment of Pharmacy, Gachon Institute of Pharmaceutical Science, College of Pharmacy, Gachon UniversityDepartment of Pharmacy, Gachon Institute of Pharmaceutical Science, College of Pharmacy, Gachon UniversityDepartment of Data Management, KEISDepartment of Pharmacy, Gachon Institute of Pharmaceutical Science, College of Pharmacy, Gachon UniversityAbstract Molecular insights into chemical safety are very important for sustainable development as well as risk assessment. This study considers how to manage future upcoming harmful agents, especially potentially cholinergic chemical warfare agents (CWAs). For this purpose, the structures of known cholinergic agents were encoded by molecular descriptors. And then each drug target interaction (DTI) was learned from the encoded structures and their cholinergic activities to build DTI classification models for five cholinergic targets with reliable statistical validation (ensemble-AUC: up to 0.790, MCC: up to 0.991, accuracy: up to 0.995). The collected classifiers were transformed into 2D or 3D array type meta-predictors for multi-task: (1) cholinergic prediction and (2) CWA detection. The detection ability of the array classifiers was verified under the imbalanced dataset between CWAs and none CWAs (area under the precision-recall curve: up to 0.997, MCC: up to 0.638, F1-score of none CWAs: up to 0.991, F1-score of CWAs: up to 0.585).https://doi.org/10.1038/s41598-022-21150-2 |
| spellingShingle | Surendra Kumar Chandni Kumari Sangjin Ahn Hyoungrae Kim Mi-hyun Kim Prediction of chemical warfare agents based on cholinergic array type meta-predictors Scientific Reports |
| title | Prediction of chemical warfare agents based on cholinergic array type meta-predictors |
| title_full | Prediction of chemical warfare agents based on cholinergic array type meta-predictors |
| title_fullStr | Prediction of chemical warfare agents based on cholinergic array type meta-predictors |
| title_full_unstemmed | Prediction of chemical warfare agents based on cholinergic array type meta-predictors |
| title_short | Prediction of chemical warfare agents based on cholinergic array type meta-predictors |
| title_sort | prediction of chemical warfare agents based on cholinergic array type meta predictors |
| url | https://doi.org/10.1038/s41598-022-21150-2 |
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