基于自验证集成模型设计的环境友好型印迹聚合物装饰传感器的计算机辅助设计用于盐酸氯他弗林剂型和人血浆定量。

IF 1.7 4区 农林科学 Q3 CHEMISTRY, ANALYTICAL
Aziza E Mostafa, Maya S Eissa, Ahmed Elsonbaty, Khaled Attala, Randa A Abdel Salam, Ghada M Hadad, Mohamed A Abdelshakour
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引用次数: 4

摘要

背景:计算设计的分子印迹聚合物(MIP)结合到电化学传感器中,对设计的传感器性能有许多优点。创新的自我验证集成建模(SVEM)方法是一种基于智能机器学习(ML)的技术,可以使用更小的数据集设计更准确的预测模型。目的:利用新型SVEM实验设计方法,优化四种环保PVC膜的组成,通过计算设计磁性分子印迹聚合物增强,定量测定盐酸曲维林(DVN)的联合剂型和人血浆。此外,混合计算模拟的应用,如分子动力学和量子力学计算(MD/QM),为MIP粒子的定制设计提供了节省时间和环保的服务。方法:本文首次将机器学习的预测能力与计算模拟相结合,采用四种不同的实验设计,即中心复合、svm - lasso、svm - fwd和svm - pfwd,开发了四种基于pvc的传感器,这些传感器由计算设计的MIP颗粒装饰。开创性的AGREE方法进一步评估了分析方法的绿色程度,证明了它们的生态友好性。结果:该传感器对DVN在58.60 ~ 59.09 mV/ 10年范围内表现出良好的Nernstian反应,线性定量范围为1 × 10-7 ~ 1 × 10-2 M,检出限为9.55 × 10-8 ~ 7.08 × 10-8 M。此外,该传感器在其联合剂型和加标血浆中对靶标具有良好的生态友好性和选择性。结论:该传感器符合国际纯粹与应用化学联合会(IUPAC)推荐标准,对盐酸曲维林剂型和人血浆中盐酸曲维林的检测具有较高的灵敏度和选择性。这项工作首次提出了创新的SVEM设计和MD/QM模拟在优化和制造盐酸敏感和选择性mip装饰PVC传感器中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computer-Aided Design of Eco-Friendly Imprinted Polymer Decorated Sensors Augmented by Self-Validated Ensemble Modeling Designs for the Quantitation of Drotaverine Hydrochloride in Dosage Form and Human Plasma.

Background: Computationally designed molecular imprinted polymer (MIP) incorporation into electrochemical sensors has many advantages to the performance of the designed sensors. The innovative self-validated ensemble modeling (SVEM) approach is a smart machine learning-based (ML) technique that enables the design of more accurate predictive models using smaller data sets.

Objective: The novel SVEM experimental design methodology is exploited here exclusively to optimize the composition of four eco-friendly PVC membranes augmented by a computationally designed magnetic molecularly imprinted polymer to quantitatively determine drotaverine hydrochloride (DVN) in its combined dosage form and human plasma. Furthermore, the application of hybrid computational simulations such as molecular dynamics and quantum mechanical calculations (MD/QM) is a time-saving and eco-friendly provider for the tailored design of the MIP particles.

Method: Here, for the first time, the predictive power of ML is assembled with computational simulations to develop four PVC-based sensors decorated by computationally designed MIP particles using four different experimental designs known as central composite, SVEM-LASSO, SVEM-FWD, and SVEM-PFWD. The pioneering AGREE approach further assessed the greenness of the analytical methods, proving their eco-friendliness.

Results: The proposed sensors showed decent Nernstian responses toward DVN in the range of 58.60-59.09 mV/decade with a linear quantitative range of 1 × 10-7 - 1 × 10-2 M and limits of detection in the range of 9.55 × 10-8 to 7.08 × 10-8 M. Moreover, the proposed sensors showed ultimate eco-friendliness and selectivity for their target in its combined dosage form and spiked human plasma.

Conclusions: The proposed sensors were validated in accordance with International Union of Pure and Applied Chemistry (IUPAC) recommendations, proving their sensitivity and selectivity for drotaverine determination in dosage form and human plasma.

Highlights: This work presents the first ever application of both the innovative SVEM designs and MD/QM simulations in the optimization and fabrication of drotaverine-sensitive and selective MIP-decorated PVC sensors.

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来源期刊
Journal of AOAC International
Journal of AOAC International 医学-分析化学
CiteScore
3.10
自引率
12.50%
发文量
144
审稿时长
2.7 months
期刊介绍: The Journal of AOAC INTERNATIONAL publishes the latest in basic and applied research in analytical sciences related to foods, drugs, agriculture, the environment, and more. The Journal is the method researchers'' forum for exchanging information and keeping informed of new technology and techniques pertinent to regulatory agencies and regulated industries.
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