羟基自由基（·OH）反应常数对于表征有机污染物在大气环境中持久性具有重要意义．依据经济合作与发展组织（ OECD）关于QSAR模型构建与验证的导则，采用量子化学方法对覆盖了不同种类的722个化合物进行结构优化，遗传算法筛选最优结构描述符，运用多元线性回归构建化学品羟基自由基反应常数预测模型．拟合结果显示，多元线性回归模型决定系数R2和标准误差分别为0．819和0．508，基于leverage法评价模型的应用域，结果表明模型具有较强的稳健性、预测性和拟合能力．美国环保局EPI Suite中AOPWIN模块羟基自由基反应常数预测模型没有给出明确的应用域，利用所建模型与美国EPI Suite对化学物质进行比较，其中，有85个化学物质预测优于EPI Suite软件．通过定量结构?活性关系（ QSAR）预测技术可弥补羟基自由基反应常数测试数据的缺失，减少测试费用和评估数据的不确定性．
Reaction rate constants of hydroxyl radicals (kOH) are of vital importance for assessing the persistence of organic pollutants in the atmosphere. 722 chemicals were optimized by quantum chemistry method and screened by genetic algorithm for optimal descriptors. A quantitative structure?activity relationship ( QSAR ) model for hydroxyl radical reaction constant was developed by employing multiple linear regression ( MLR ) according to the QSAR model development and validation guideline issued by Organization for Economic Cooperation and Development ( OECD ) . The QSAR modeling results indicated that the R2 and SE of multiple linear regressions model were 0.819 and 0.508, The application domain was evaluated based on the leverage method. The results showed that the model had high goodness?of?fit, robustness and good predictive ability. The hydroxyl radical reaction constant prediction model in AOPWIN module of the EPI Suite software did not have a definite application domain and the prediction of 85 chemicals was better than EPI software Suite. Thus, the QSAR model can be employed to make up the missing data, redue the cost of testing and evaluated of data uncertainty.
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