Provincial Public Laboratory of Analysis and Testing Technology, Guangdong Institute of Analysis, Guangzhou 510070, China.
College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, China.
Molecules. 2018 Jun 27;23(7):1554. doi: 10.3390/molecules23071554.
Magnetic porous molecularly imprinted polymers (MPMIPs) for rapid and efficient selective recognition of chlorogenic acid (CGA) were effectively prepared based on surface precipitation polymerization using CGA as template, 4-vinylpyridine (4-VP) as functional monomer, and mesoporous SiO₂ (mSiO₂) layer as sacrificial support. A computational simulation by evaluation of electronic binding energy is used to optimize the stoichiometric ratio between CGA and 4-VP (1:5), which reduced the duration of laboratory trials. The porous MIP shell and the rid of solid MIPs by magnet gave MPMIPs high binding capacity (42.22 mg/g) and fast kinetic binding (35 min). Adsorption behavior between CGA and MPMIPs followed Langmuir equation and pseudo-first-order reaction kinetics. Furthermore, the obtained MPMIPs as solid phase adsorbents coupled with high performance liquid chromatography (HPLC) were employed for selective extraction and determination of CGA (2.93 ± 0.11 mg/g) in Duzhong brick tea. The recoveries from 91.8% to 104.2%, and the limit of detection (LOD) at 0.8 μg/mL were obtained. The linear range (2.0⁻150.0 μg/mL) was wide with ² > 0.999. Overall, this study provided an efficient approach for fabrication of well-constructed MPMIPs for fast and selective recognition and determination of CGA from complex samples.
基于表面沉淀聚合,以绿原酸(CGA)为模板,4-乙烯基吡啶(4-VP)为功能单体,介孔二氧化硅(mSiO₂)层为牺牲支撑,制备了用于快速高效选择性识别绿原酸(CGA)的磁性多孔分子印迹聚合物(MPMIPs)。通过评估电子结合能的计算模拟,优化了 CGA 与 4-VP 的化学计量比(1:5),从而缩短了实验室试验的时间。多孔 MIP 壳和通过磁铁去除固体 MIPs 赋予 MPMIPs 高结合能力(42.22 mg/g)和快速动力学结合(35 min)。CGA 与 MPMIPs 之间的吸附行为符合 Langmuir 方程和拟一级反应动力学。此外,将所得 MPMIPs 作为固相吸附剂与高效液相色谱(HPLC)联用,用于选择性提取和测定砖茶中的 CGA(2.93 ± 0.11 mg/g)。回收率在 91.8%至 104.2%之间,检测限(LOD)为 0.8 μg/mL。线性范围(2.0⁻150.0 μg/mL)很宽,²>0.999。总体而言,该研究为从复杂样品中快速选择性识别和测定 CGA 提供了一种制备结构良好的 MPMIPs 的有效方法。