Selective Separation and Preconcentration of Caffeine from Natural and Pharmaceutical Products using New Polyurethane Foams

Abstract Two polyurethane foam-based sorbents (PUF) were synthesized by imprinting and grafting techniques and examined for selective separation and preconcentration of caffeine (CAF) in some pharmaceutical products and in black tea. Molecularly imprinted PUF was synthesized based on hydrogen-bonding interactions between CAF and alizarin yellow G (AYG) and subsequent polymerization into PUF. The static experiments indicated optimum sorption conditions at pH=6.5 and 5.5 for imprinted PUF (AY-IPUF) and grafted PUF (AY-GPUF), respectively. In the online experiments, the suitable preconcentration time was found to be 40 and 20s for (AY-IPUF) and (AY-GPUF), respectively, at a flow rate of 1.75 mL.min-1. Desorption of CAF has been affected by passing 500 μL of 0.05, 0.01 mol.L−1 HCl eluent onto (AY-IPUF) and (AY-GPUF), respectively. The online methods have provided satisfactory enrichment factors of 8.4 and 10.5 for (AY-IPUF) and (AY-GPUF), respectively. The time consumed for preconcentartion, elution and determination steps was 1.48 and 1.05 min, thus, the throughput was 42 and 57 h-1, for (AY-IPUF) and (AY-GPUF), respectively. The developed sorbents were studied for the determination of CAF in pharmaceutical samples which will be helpful to minimize caffeinism. Finally, in silico bioactivity, ADMET and drug-likeness predictive computational studies of caffeine were also carried out.

摘要 本研究通过印迹与接枝技术合成了两种聚氨酯泡沫基吸附剂（polyurethane foam, PUF），并将其用于部分药物制剂及红茶中咖啡因（caffeine, CAF）的选择性分离与预富集。基于CAF与茜素黄G（alizarin yellow G, AYG）之间的氢键相互作用，经后续聚合得到分子印迹PUF。静态实验结果表明，印迹型PUF（AY-IPUF）与接枝型PUF（AY-GPUF）的最佳吸附pH分别为6.5和5.5。在线实验中，当流速为1.75 mL·min⁻¹时，AY-IPUF与AY-GPUF的适宜预富集时间分别为40 s和20 s。分别采用500 μL浓度为0.05、0.01 mol·L⁻¹的盐酸洗脱剂流经AY-IPUF与AY-GPUF，即可实现CAF的解吸。在线方法对AY-IPUF与AY-GPUF的富集因子分别可达8.4和10.5，结果令人满意。预富集、洗脱与测定步骤的总耗时分别为1.48 min和1.05 min，因此AY-IPUF与AY-GPUF的样品处理通量分别为42 h⁻¹和57 h⁻¹。本研究对所开发的吸附剂用于药物样品中CAF的测定进行了考察，该方法有助于降低咖啡因中毒风险。最后，本研究还开展了咖啡因的计算机模拟生物活性、ADMET及类药性预测计算研究。