三维定量构效关系（3D-QSAR）是一种合理的药物设计方法，是目前使用最多的方法之一。本文根据前期合成的28个姜黄素类似物其结构与抑制酪氨酸酶活性关系，建立了统计学意义显著的3D-QSAR模型，交叉验证系数q2为0.609，模型相关系数R2为0.997，F统计量的值为77.070。对该模型的可靠性和预测能力进行了分析。应用该模型设计了6个结构对称的姜黄素类似物A1、A2、B1、B2、B3和B4，对6个化合物进行合成、分离提纯以及结构表征。其中，化合物A2和B3经SCI Finder检索为未见合成报道的新型化合物。以左旋多巴（L-DOPA）为底物，测试合成物对酪氨酸酶的抑制活性，其中化合物B1的活性最强，所有合成物的活性均比姜黄素好，并且实验值与预测值十分接近，说明3D-QSAR模型具有良好的外部预测能力。

As a rational drug design approach, the three-dimensional quantitative structure-activity relationship (3D-QSAR) is one of the methods that is currently used most often for drug design and development. Based on the relationship between the structure and tyrosinase inhibitory activity of 28 curcumin analogues, a 3D-QSAR model with statistical significance was established, with a cross-validation correlation coefficient q2 of 0.609, a correlation coefficient R2 of 0.997, and an F statistic of 77.070. The reliability and predictive ability of the model were analyzed. Six curcumin analogues (A1, A2, B1, B2, B3, and B4) with a symmetrical structure were designed based on the model. These compounds were then synthesized, separated, and purified, and their structures were characterized. Among them, compounds A2 and B3 were new compounds that have not previously been reported. Using levodopa (L-DOPA) as substrate, the tyrosinase inhibitory activities of the six compounds were measured. Among them, B1 exhibited the strongest activity, and the activities of all compounds were higher than that of curcumin. Additionally, the experimental values were very close to the predicted values, suggesting that the 3D-QSAR model has good external predictive capabilities.

广东省科技计划项目（2013B090600090）