Performance of In Silico Models for Mutagenicity Prediction of Food Contact Materials. (20th March 2018)
- Record Type:
- Journal Article
- Title:
- Performance of In Silico Models for Mutagenicity Prediction of Food Contact Materials. (20th March 2018)
- Main Title:
- Performance of In Silico Models for Mutagenicity Prediction of Food Contact Materials
- Authors:
- Van Bossuyt, Melissa
Van Hoeck, Els
Raitano, Giuseppa
Vanhaecke, Tamara
Benfenati, Emilio
Mertens, Birgit
Rogiers, Vera - Abstract:
- Abstract: In silico methodologies, such as (quantitative) structure-activity relationships ([Q]SARs), are available to predict a wide variety of toxicological properties and biological activities for structurally diverse substances. To obtain insights in the scientific value of these predictions, the capacity of the prediction models to generate (sufficiently) reliable results for a particular type of compounds needs to be evaluated. In the current study, performance parameters to predict the endpoint "bacterial mutagenicity" were calculated for a battery of common (Q)SAR tools, namely Toxtree, Derek Nexus, VEGA Consensus, and Sarah Nexus. Printed paper and board food contact material (FCM) constituents were chosen as study substances because many of these lack experimental data, making them an interesting group for in silico screening. Accuracy, sensitivity, specificity, positive predictivity, negative predictivity, and Matthews correlation coefficient for the individual models and for the combination of VEGA Consensus and Sarah Nexus were determined and compared. Our results demonstrate that performance varies among the four models, but can be increased by applying a combination strategy. Furthermore, the importance of the applicability domain is illustrated. Limited performance to predict the mutagenic potential of substances that are new to the model (ie, not included in the training set) is reported. In this context, the generally poor sensitivity for these newAbstract: In silico methodologies, such as (quantitative) structure-activity relationships ([Q]SARs), are available to predict a wide variety of toxicological properties and biological activities for structurally diverse substances. To obtain insights in the scientific value of these predictions, the capacity of the prediction models to generate (sufficiently) reliable results for a particular type of compounds needs to be evaluated. In the current study, performance parameters to predict the endpoint "bacterial mutagenicity" were calculated for a battery of common (Q)SAR tools, namely Toxtree, Derek Nexus, VEGA Consensus, and Sarah Nexus. Printed paper and board food contact material (FCM) constituents were chosen as study substances because many of these lack experimental data, making them an interesting group for in silico screening. Accuracy, sensitivity, specificity, positive predictivity, negative predictivity, and Matthews correlation coefficient for the individual models and for the combination of VEGA Consensus and Sarah Nexus were determined and compared. Our results demonstrate that performance varies among the four models, but can be increased by applying a combination strategy. Furthermore, the importance of the applicability domain is illustrated. Limited performance to predict the mutagenic potential of substances that are new to the model (ie, not included in the training set) is reported. In this context, the generally poor sensitivity for these new substances is also addressed. … (more)
- Is Part Of:
- Toxicological sciences. Volume 163:Number 2(2018)
- Journal:
- Toxicological sciences
- Issue:
- Volume 163:Number 2(2018)
- Issue Display:
- Volume 163, Issue 2 (2018)
- Year:
- 2018
- Volume:
- 163
- Issue:
- 2
- Issue Sort Value:
- 2018-0163-0002-0000
- Page Start:
- 632
- Page End:
- 638
- Publication Date:
- 2018-03-20
- Subjects:
- in silico -- (Q)SAR -- mutagenicity -- food contact materials -- validation
Toxicology -- Periodicals
Toxicology -- Periodicals
Toxicology
Periodicals
615.9 - Journal URLs:
- http://www.sciencedirect.com/science/journal/10966080 ↗
http://toxsci.oxfordjournals.org/ ↗
http://ukcatalogue.oup.com/ ↗ - DOI:
- 10.1093/toxsci/kfy057 ↗
- Languages:
- English
- ISSNs:
- 1096-6080
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8873.031900
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24982.xml