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取代吡唑类化合物对肿瘤抑制活性的QSAR研究与分子设计 被引量:1

QSAR study and molecular design of tumor suppressive activity of substituted pyrazole compounds
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摘要 采用量子化学中的密度泛函理论(DFT)方法,在B3LYP/6-31++G(d,p)基组水平上系统计算了TβR-I抑制剂吡唑类衍生物(AHSPs)的量子化学结构参数。用逐步线性回归方法(SR)对该类AHSPs化合物进行了定量构效关系研究,筛选出了影响化合物抑制活性的主要因素,得到了最优QSAR方程。研究结果表明,抑制剂分子的偶极矩μ、疏水系数logP、分子中吡啶环的7-N原子的Mulliken电荷是影响AHSPs类化合物的抑制活性的主要因素。偶极矩μ和疏水系数logP越小,吡啶环的7-N原子Mulliken净电荷越正,则化合物的抑制活性越强。所得模型对该类吡唑类化合物针对TβR-Ⅰ的抑制活性有较好的预测结果,据此设计出14个新型AHSPs分子,计算其量子力学参数,利用构效方程预测出新型AHSPs分子的性能,发现其中有3个分子可能有较好的理论抑制活性。 The quantified parameters of the substituted pyrazole inhibitors of the transforming growth factor-beta receptor kinase TpR- I were calculated at B3LYP/6-31++G(d,p)using density functional theory( DFT)method. The quantitative structure-activity relationship( QSAR) of these compounds was determined by stepwise linear regression method(SR). The main factors affecting the inhibitory activity of the compounds were screened out,and one good QSAR equation was obtained. The results show that the dipole moment ya,the hydrophobic coefficient logP,the 1-N,2-N on the pyrazole ring and the Mulliken charge of the 7-N atom of the pyri-dine ring are the major factors. Dipole moment and the hydrophobic coefficient logP,the more the Mulliken net charge of the 7-N atom of the pyridine ring and the 2-N atom of the pyrazole ring is positive,the more negative the Mulliken net charge of the 1-N atom , the stronger the activity. The results showed that the proposed model had good predictive effect on the inhibitory activity of the pyrazole compounds against TpR- I,and 14 new molecules were also designed. After calculation,three of these new molecules were found to have better performance.
作者 袁钰涵 范旖旎 任玉婷 陈双扣 YUAN Yu- han;FAN Yi- ni;REN Yu- ting;CHEN Shuang- kou(Life Science and Engineering College of Northwest University of Nationalities,Lanzhou 730124,China;College of Chemistry and Chem-engineering,Chongqing University of Science and Technology,Chongqing 401331 ,China)
出处 《化学研究与应用》 CSCD 北大核心 2017年第12期1833-1839,共7页 Chemical Research and Application
关键词 转化生长因子-β受体激酶TβR-Ⅰ 定量构效关系(QSAR) 量子化学计算 逐步多元线性回归(SR) 分子设计 transforming growth factor-beta receptor kinase quantitative structure-activity relationship( QSAR) quantum chemical calculation stepwise linear regression method(SR) molecular design
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