摘要
目的 采用改良量化构效关系（QSAR）方法,预测N-亚硝基化学物（NOCs）的致癌性,并为化学物的健康风险评估提供依据.方法 采用经济合作与发展组织新研发的基于分类和交叉参照的QSAR分析软件,纳入74种NOCs为目标化学物,采用＂有机官能团分析工具＂和＂DNA结合分析工具＂分别对74种目标化学物进行分类和亚分类,形成初始化学物分类组和亚分类化学物分类组.以NOCs对大鼠致癌性为预测目标,交叉参照读取化学物分类组中类似物的致癌性实验结果,从而得到目标化学物的致癌性预测结果.结果 74种NOCs包括26种非环状N-亚硝胺、24种环状N-亚硝胺和24种N-亚硝酰胺类,基于化学物分类的交叉参照法,预测74种NOCs致癌性的灵敏度、特异度、一致率分别为75%（48/64）、70%（7/10）和74%（55/74）;非环状N-亚硝胺、环状N-亚硝胺以及N-亚硝酰胺类预测结果一致率分别为88%（23/26）、71%（17/24）和63%（15/24）.结论 基于分类和交叉参照的QSAR预测性良好,且操作简便快速,可用于高通量定性预测NOCs致癌性.
Objective New quantitative structure-activity relationship （QSAR） method was used to predict N-nitroso compounds （NOCs） carcinogenicity. This could provide evidences for health risk assessment of the chemicals. Methods Total 74 chemical substances of NOCs were included as target chemicals for this validation study by using QSAR Toolbox based on category approach and read-across. The included 74 NOCs were categorized and subcategorized respectively using＂Organic functional groups, Norbert Haider＂profiler and＂DNA binding by OASIS V.1.1＂profiler. Carcinogenicity of rat were used as target of prediction, the carcinogenicity results of analogues in chemical categories were cross-read to obtain the carcinogenic predictive results of the target chemicals. Results 74 NOCs included 26 nonclic N-nitrosamines, 24 cyclic N-nitrosamines and 24 N-nitrosamides The sensitivity, specificity and concordance of the category approach and read-across for predicting carcinogenicity of 74 NOCs were 75%（48/64）, 70%（7/10） and 74% （55/74） respectively. The concordance for noncyclic N-nitrosamines, cyclic N-nitrosamines and N-nitrosamides were 88% （23/26）, 71% （17/24） and 63% （15/24） respectively. Conclusion QSAR based on category approach and read-across is good for prediction of NOCs carcinogenicity, and can be used for high-throughput qualitative prediction of NOCs carcinogenicity.
出处
《中华预防医学杂志》
CAS
CSCD
北大核心
2017年第7期621-627,共7页
Chinese Journal of Preventive Medicine
基金
国家卫生公益性行业专项（201302004）
国家自然科学基金（81273035、81325017）
关键词
分类法
量化构效关系
亚硝基化学物
交叉参照
Classification
Quantitative structure-activity relationship
Nitroso compounds
Read-across
