College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China.
MOE Key Laboratory of Resources and Environmental Systems Optimization, North China Electric Power University, Beijing 102206, China.
Int J Environ Res Public Health. 2019 Oct 28;16(21):4156. doi: 10.3390/ijerph16214156.
In this paper, two-dimensional quantitative structure-activity relationship (2D-QSAR) and principal component analysis (PCA) methods were employed to screen the main parameters affecting the genotoxicity of fluoroquinolones (FQs), and the rules affecting the genetic toxicity of FQs were investigated by combining 2D-QSAR and PCA with the sensitivity analysis method. First, four types of parameters were calculated, namely, the geometric parameters (7), electronic parameters (5), physical and chemical parameters (8), and spectral parameters (7), but the physical and chemical parameters heat of formation (HF) and critical volume (CV) were excluded after the establishment of the 2D-QSAR model. Then, after PCA, it was found that the first principal component represented the main driving factors affecting the molecular genetic toxicity of FQs. In addition, after comprehensive analysis of the factor loading of the first, second, and third principal components, seven parameters affecting the genotoxicity of the FQs were screened out, namely, total energy (TE), critical temperature (CT), and molecular weight (Mol Wt) (increased with increasing genotoxicity of the FQs) and steric parameter (MR), quadrupole moment Q (Q), quadrupole moment Q (Q), and boiling point (BP) (decreased with increasing genotoxicity of the FQs); the above key parameters were also verified by sensitivity analysis. The obtained rules could be used to determine the substitution sites and the substitution groups associated with higher genotoxicity in the process of FQ modification, and these rules agreed well with the hologram quantitative structure-activity relationship (HQSAR) model. Finally, it was also found through SPSS analysis that the parameters screened in this paper were significantly correlated with FQ derivatives' genetic toxicity.
本文采用二维定量构效关系（2D-QSAR）和主成分分析（PCA）方法，筛选影响氟喹诺酮类（FQs）遗传毒性的主要参数，并结合 2D-QSAR 和 PCA 与灵敏度分析方法，探讨影响 FQs 遗传毒性的规律。首先计算了四类参数，即几何参数（7 个）、电子参数（5 个）、物理化学参数（8 个）和光谱参数（7 个），但在建立 2D-QSAR 模型后排除了物理化学参数生成热（HF）和临界体积（CV）。然后，经过 PCA 发现，第一主成分代表了影响 FQs 分子遗传毒性的主要驱动因素。此外，综合分析第一、第二和第三主成分的因子载荷，筛选出影响 FQs 遗传毒性的七个参数，即总能量（TE）、临界温度（CT）和分子量（Mol Wt）（随 FQs 遗传毒性的增加而增加）和立体参数（MR）、四极矩 Q（Q）、四极矩 Q（Q）和沸点（BP）（随 FQs 遗传毒性的增加而降低）；通过灵敏度分析验证了上述关键参数。所得规律可用于确定 FQ 修饰过程中与较高遗传毒性相关的取代位点和取代基团，这些规律与全息定量构效关系（HQSAR）模型吻合较好。最后，通过 SPSS 分析还发现，本文筛选的参数与 FQ 衍生物的遗传毒性显著相关。
