PuSH - Publication Server of Helmholtz Zentrum München

Cassotti, M.* ; Ballabio, D.* ; Consonni, V.* ; Mauri, A.* ; Tetko, I.V. ; Todeschini, R.*

Prediction of acute aquatic toxicity toward Daphnia magna by using the GA-kNN method.

ATLA-Altern. Lab. Anim. 42, 31-41 (2014)
Publ. Version/Full Text Volltext PMC
Free by publisher
In this study, a QSAR model was developed from a data set consisting of 546 organic molecules, to predict acute aquatic toxicity toward Daphnia magna. A modified k-Nearest Neighbour (kNN) strategy was used as the regression method, which provided prediction only for those molecules with an average distance from the k nearest neighbours lower than a selected threshold. The final model showed good performance (R(2) and Q(2) cv equal to 0.78, Q(2) ext equal to 0.72). It comprised eight molecular descriptors that encoded information about lipophilicity, the formation of H-bonds, polar surface area, polarisability, nucleophilicity and electrophilicity.
Altmetric
Additional Metrics?
[➜Log in]
Edit extra informations Login
Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords Aquatic Toxicity ; Daphnia Magna ; Genetic Algorithms ; Knn ; Qsar; Quantitative Structure; Qsar Models; Organic-compounds; Classification; Environment; Chemicals; (benzo)triazoles; Pharmaceuticals; Prioritization; Antibiotics
ISSN (print) / ISBN 0261-1929
Journal ATLA - Alternatives to Laboratory Animals
Quellenangaben Volume: 42, Issue: 1, Pages: 31-41 Article Number: , Supplement: ,
Publisher Sage
Publishing Place North Sherwood St, Nottingham
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute of Structural Biology (STB)