Facial reconstruction

Search LJMU Research Online

Browse Repository | Browse E-Theses

Investigation of the Verhaar scheme for predicting acute aquatic toxicity: improving predictions obtained from Toxtree ver. 2.6

Ellison, CM and Madden, JC and Cronin, MTD and Enoch, SJ (2015) Investigation of the Verhaar scheme for predicting acute aquatic toxicity: improving predictions obtained from Toxtree ver. 2.6. Chemosphere, 139. pp. 146-154. ISSN 1879-1298

[img] Text
Ellison_et_al_Chemosphere_Accepted_version.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (439kB)

Abstract

Assessment of the potential of compounds to cause harm to the aquatic environment is an integral part 8 of the REACH legislation. To reduce the number of vertebrate and invertebrate animals required for 9 this analysis alternative approaches have been promoted. Category formation and read-across have 10 been applied widely to predict toxicity. A key approach to grouping for environmental toxicity is the 11 Verhaar scheme which uses rules to classify compounds into one of four mechanistic categories. 12 These categories provide a mechanistic basis for grouping and any further predictive modelling. A 13 computational implementation of the Verhaar scheme is available in Toxtree v2.6. The work 14 presented herein demonstrates how modifications to the implementation of Verhaar between version 15 1.5 and 2.6 of Toxtree have improved performance by reducing the number of incorrectly classified 16 compounds. However, for the datasets used in this analysis, version 2.6 classifies more compounds as 17 outside of the domain of the model. Further amendments to the classification rules have been 18 implemented here using a post-processing filter encoded as a KNIME workflow. This results in fewer 19 compounds being classified as outside of the model domain, further improving the predictivity of the 20 scheme. The utility of the modification described herein is demonstrated through building quality, 21 mechanism-specific Quantitative Structure Activity Relationship (QSAR) models for the compounds 22 within specific mechanistic categories.

Item Type: Article
Uncontrolled Keywords: MD Multidisciplinary
Subjects: R Medicine > RS Pharmacy and materia medica
Divisions: Pharmacy & Biomolecular Sciences
Publisher: Elsevier
Date Deposited: 04 Jun 2015 10:11
Last Modified: 16 Jun 2016 23:50
URI: http://researchonline.ljmu.ac.uk/id/eprint/1360

Actions (login required)

View Item View Item