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Acute Toxicity-Supported Chronic Toxicity Prediction: A k-Nearest Neighbor Coupled Read-Across Strategy
Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences. (BBCL)ORCID iD: 0000-0003-4158-4148
Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences. (CCBG ; BMC)ORCID iD: 0000-0001-8696-3104
Linnaeus University, Faculty of Health and Life Sciences, Department of Chemistry and Biomedical Sciences. (BBCL ; BMC)ORCID iD: 0000-0002-0407-6542
2015 (English)In: International Journal of Molecular Sciences, ISSN 1422-0067, E-ISSN 1422-0067, Vol. 16, no 5, 11659-11677 p.Article in journal (Refereed) Published
Abstract [en]

k-nearest neighbor (k-NN) classification model was constructed for 118 RDT NEDO (Repeated Dose Toxicity New Energy and industrial technology Development Organization; currently known as the Hazard Evaluation Support System (HESS)) database chemicals, employing two acute toxicity (LD50)-based classes as a response and using a series of eight PaDEL software-derived fingerprints as predictor variables. A model developed using Estate type fingerprints correctly predicted the LD50 classes for 70 of 94 training set chemicals and 19 of 24 test set chemicals. An individual category was formed for each of the chemicals by extracting its corresponding k-analogs that were identified by k-NN classification. These categories were used to perform the read-across study for prediction of the chronic toxicity, i.e., Lowest Observed Effect Levels (LOEL). We have successfully predicted the LOELs of 54 of 70 training set chemicals (77%) and 14 of 19 test set chemicals (74%) to within an order of magnitude from their experimental LOEL values. Given the success thus far, we conclude that if the k-NN model predicts LD50classes correctly for a certain chemical, then the k-analogs of such a chemical can be successfully used for data gap filling for the LOEL. This model should support the in silico prediction of repeated dose toxicity.

Place, publisher, year, edition, pages
2015. Vol. 16, no 5, 11659-11677 p.
Keyword [en]
k-nearest neighbor;classification model; Estate fingerprint;LD50; LOEL; read-across; category formation
National Category
Analytical Chemistry
Research subject
Chemistry, Organic Chemistry
Identifiers
URN: urn:nbn:se:lnu:diva-45017DOI: 10.3390/ijms160511659ISI: 000356241400146PubMedID: 26006240Scopus ID: 2-s2.0-84930643618OAI: oai:DiVA.org:lnu-45017DiVA: diva2:825302
Funder
EU, FP7, Seventh Framework Programme, 238701
Available from: 2015-06-23 Created: 2015-06-23 Last updated: 2017-12-04Bibliographically approved

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Chavan, SwapnilFriedman, RanNicholls, Ian A.
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