Synthesis and Density Functional Theory(DFT) Calculation of Haptens for PAHs

Five PAHs haptens 3 a～3 e were synthesized from naphthalene, anthracene, chrysene, pyrene and acenaphthene via two steps including Friedel-Crafts acylation and WolffKishner-Huang reduction. The sixth hapten 4-(acenaphthylen-3-yl)butanoic acid(3 f) was prepared from hapten 3 e via three steps including esterification, bromination and elimination. Their structures were confirmed by melting point, ~1H NMR and ~(13)C NMR. Their optical properties and crystal structures were also investigated. The results of density functional theory(DFT) calculation provided the supports that the size, shape(geometry) and electronic properties at the corresponding parts of 3 a～3 f did not change significantly, compared to those of PAHs. The haptens 3 a～3 f were coupled with bovine serum albumin(BSA) to make antigens. The coupling ratios were 1:20～1:38. These results show that the haptens could be used to induce specific antibodies for PAHs.     

多环芳烃交叉反应率QSAR模型构建及半抗原设计

多环芳烃(PAHs)作为主要环境污染物和致癌物受到广泛关注。免疫分析技术应用于多环芳烃检测时,由于其潜在交叉反应物太多,很难通过实验来确定所有的交叉反应率(CR)。本研究采用定量构效关系(QSAR)中的比较分子力场分析法(CoMFA),对芘多克隆抗体的CR进行了预测。结果表明,化合物的CR与其三维结构相关,立体场贡献率95%,静电场贡献率5%,相关性结果与随机选取的测试化合物的实际CR进行了比较,证明模型具有良好的预测能力。该模型被用于预测其他17种多环芳烃的CR,同时运用分子模拟和量子化学计算,从空间结构、疏水性、原子电荷、前线分子轨道和静电势比较了引入连接臂的三种半抗原,最终确定1-芘丁酸为最佳半抗原。     

1,4-二氢吡啶衍生物的QSAR模型构建及制备

采用Hyperchem 8.0软件,通过分子动力学MM+和半经验AM1算法,优化并计算得到30种1,4-二氢吡啶衍生物的17种量子化学参数。运用Statistica 8.0软件中的主成分分析法,结合线性回归分析法,筛选出3个最佳参数与1,4-二氢吡啶衍生物的抗结核活性关联,构建定量构效关系(QSAR)模型。所建多元线性回归方程的相关系数R²为0.75,留一法交叉检验系数q²为0.72,活性实验值与预测值相关性较好。采用该模型设计并制备得到1种具有良好水溶性和潜在抗结核活性的N³,N⁵-二(对磺酸钾基)苯基-2,6-二甲基-3,5-二甲酰氨基-1,4-二氢吡啶(TM),用¹H NMR、IR、MS和元素分析表征结构,并考察了紫外和荧光性能。良好的稳定性和预测能力使该QSAR模型有望用于结核病候选药物的筛选。