TY - JOUR
T1 - Validation of the (Q)SAR combination approach for mutagenicity prediction of flavor chemicals
AU - Ono, Atsushi
AU - Takahashi, Mika
AU - Hirose, Akihiko
AU - Kamata, Eiichi
AU - Kawamura, Tomoko
AU - Yamazaki, Takeshi
AU - Sato, Kyoko
AU - Yamada, Masami
AU - Fukumoto, Takayuki
AU - Okamura, Hiroyuki
AU - Mirokuji, Yoshiharu
AU - Honma, Masamitsu
N1 - Funding Information:
This work was supported by Expenditure on Food Investigation and Health and Labour Sciences Research Grants (Research on Risk of Chemical Substances: H21-Chemistry-Ippan-002) from the Ministry of Health, Labour and Welfare of Japan. We would like to express our gratitude to Alex Cayley, senior scientist of the Knowledge Base Department, Lhasa Limited, UK.
PY - 2012/5
Y1 - 2012/5
N2 - Most exposure levels of flavor in food are considered to be extremely low. If at all, genotoxic properties should be taken into account in safety evaluations. We have recently established a (quantitative) structure-activity relationship, (Q)SAR, combination system, which is composed of three individual models of mutagenicity prediction for industrial chemicals. A decision on mutagenicity is defined as the combination of predictive results from the three models. To validate the utility of our (Q)SAR system for flavor evaluation, we assessed 367 flavor chemicals that had been evaluated mainly by JECFA and for which Ames test results were available. When two or more models gave a positive evaluation, the sensitivity was low (19.4%). In contrast, when one or more models gave a positive evaluation, the sensitivity increased to 47.2%. The contribution of this increased sensitivity was mainly due to the result of the prediction by Derek for Windows, which is a knowledge-based model. Structural analysis of false negatives indicated some common sub-structures. The approach of improving sub-structural alerts could effectively contribute to increasing the predictability of the mutagenicity of flavors, because many flavors possess categorically similar functional sub-structures or are composed of a series of derivatives.
AB - Most exposure levels of flavor in food are considered to be extremely low. If at all, genotoxic properties should be taken into account in safety evaluations. We have recently established a (quantitative) structure-activity relationship, (Q)SAR, combination system, which is composed of three individual models of mutagenicity prediction for industrial chemicals. A decision on mutagenicity is defined as the combination of predictive results from the three models. To validate the utility of our (Q)SAR system for flavor evaluation, we assessed 367 flavor chemicals that had been evaluated mainly by JECFA and for which Ames test results were available. When two or more models gave a positive evaluation, the sensitivity was low (19.4%). In contrast, when one or more models gave a positive evaluation, the sensitivity increased to 47.2%. The contribution of this increased sensitivity was mainly due to the result of the prediction by Derek for Windows, which is a knowledge-based model. Structural analysis of false negatives indicated some common sub-structures. The approach of improving sub-structural alerts could effectively contribute to increasing the predictability of the mutagenicity of flavors, because many flavors possess categorically similar functional sub-structures or are composed of a series of derivatives.
KW - (Quantitative) structure-activity relationship ((Q)SAR)
KW - Ames test
KW - Flavor
KW - Genotoxicity
KW - Mutagenicity
UR - http://www.scopus.com/inward/record.url?scp=84862795799&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84862795799&partnerID=8YFLogxK
U2 - 10.1016/j.fct.2012.02.009
DO - 10.1016/j.fct.2012.02.009
M3 - Article
C2 - 22369964
AN - SCOPUS:84862795799
SN - 0278-6915
VL - 50
SP - 1538
EP - 1546
JO - Food and Chemical Toxicology
JF - Food and Chemical Toxicology
IS - 5
ER -