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中文摘要：
采用MOPAC-AM1方法对13种3-取代硫基-5-（2-羟基苯基）4H-1，2，4-三唑类化合物分子进行几何优化和计算E HOMO、E LUMO、Q CI～Q CE、Q NI～Q N3、Q O及Q S等量子化学描述符（Lt）．通过最佳变量子集回归建立这些化合物对白色念珠菌、大肠杆菌、金黄色葡萄球菌等抑菌活性（LJ：IM，IE和IS）的QSAR模型．结果显示E LUMO和QS直接影响这些化合物的生物活性：硫原子上电荷量增大，其抑菌活性增强；E LUMO越高，IJ下降．对于白色念珠菌的IM模型的相关系数（R2）和逐一剔除法交叉验证系数（R2 CV）依次为0．913和0．806，相应IE模型为0．907和0．838，相应IS模型为0．881和0．771．通过R2 adj、F、R2 ev、VIF、AIC、FIT等检验，上述模型具有令人满意的稳健性和预测能力．结果显示抑菌机理的重要信息，可用于新活性标题化合物的理论设计．
英文摘要：
The MOPAC-AMlmethod was employed to optimize the molecular geometries of thirteen 3- substituted sulfur-5-（2-hydroxy-phenyl）-4H-1,2,4-triazole compounds. It was also used to calculate quantum chemical descriptors （L,） such as EHOMO, ELuMo, Q CI -- QCS, QNI - QN3, QO and Qs of the compounds. The antibacterial activities （I J： I M, IE and Is） of these compounds to Monilia albican, Escherichia coli and Staphylococcus aureus along with the above descriptors were used to establish the quantitative structure-activity relationships （QSAR） with leaps-and-bounds regression analysis. It shows that the ELUMO and Qs affect the bioactivities of these compounds directly. The insecticidal activities of the compounds increase with the increase of the Qs; however, the higher the ELUMO is, the lower the I J is. The correlation coefficients （R2） and leave-one-out （ LOO ） cross validation R2 CV were 0. 913 and 0. 806 for IMmodel, 0. 907 and 0. 838 for IE model, 0. 881 and 0. 771 for Is model, respectively. The QSAR models have both favorable estimation stability and good prediction capability by using R2 adj F, R2 cv, VIF, AIC, FIT tests. The results present important information for the antibacterial mechanism and will be useful for theoretical designing new active title compounds.
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