化工学报 ›› 2015, Vol. 66 ›› Issue (6): 2303-2312.DOI: 10.11949/j.issn.0438-1157.20141557

• 材料化学工程与纳米技术 • 上一篇    下一篇

跨尺度方法研究聚合物载药胶束的定量构性关系

吴文胜1,2, 张灿阳1, 李秀喜1, 徐骁1, 钱宇1, 章莉娟1   

  1. 1. 华南理工大学化学与化工学院, 广东 广州 510641;
    2. 肇庆学院化学化工学院, 广东 肇庆 526061
  • 收稿日期:2014-10-15 修回日期:2015-01-22 出版日期:2015-06-05 发布日期:2015-03-25
  • 通讯作者: 章莉娟, 李秀喜
  • 基金资助:

    国家自然科学基金项目(91434125);广东省自然科学基金团队项目(S2011030001366);教育部博士点基金项目(20130172110009);广东省科技计划项目(2013B010404006)。

Cross-scale method for quantitative structure-property relationship of drug-loaded polymeric micelles

WU Wensheng1,2, ZHANG Canyang1, LI Xiuxi1, XU Xiao1, QIAN Yu1, ZHANG Lijuan1   

  1. 1. School of Chemistry and Chemical Engineering, South China University of Technology, Guangzhou 510641, Guangdong, China;
    2. School of Chemistry and Chemical Engineering, Zhaoqing College, Zhaoqing 526061, Guangdong, China
  • Received:2014-10-15 Revised:2015-01-22 Online:2015-06-05 Published:2015-03-25
  • Supported by:

    supported by the National Natural Science Foundation of China (91434125), the Team Project of the Natural Science Foundation of Guangdong Province (S2011030001366), the Doctoral Program of Higher Education of China (20130172110009) and the Science and Technology Foundation of Guangdong (2013B010404006).

摘要:

以两亲性聚合物自组装载药胶束为案例, 基于宏观到微观的跨尺度方法研究化学产品的定量构性关系(QSPR), 提出嵌段单元自相关方法计算表征两亲性聚合物结构的描述符, 结合遗传函数算法和多元线性回归建立了不同药物/聚合物配比下聚合物胶束载药量的QSPR预测模型, 经内部验证(R2>0.854, Qloo-cv2>0.651, RMSE<0.089)、Y-随机化检验和外部验证(Qext2>0.629), 以及应用域定义分析评估了模型的可靠性、稳定性和预测能力。通过对描述符的分析和载药机制解释, 很好地阐释了聚合物嵌段单元和聚合物拓扑结构对胶束载药量的影响。QSPR模型的建立将指导新聚合物及其载药胶束体系的设计, 并预测其载药能力, 这种跨尺度研究方法有望促进复杂结构化产品的设计和开发。

关键词: 产品工程, 聚合物, 遗传算法, 跨尺度方法, 聚合物胶束, 嵌段单元自相关描述符

Abstract:

Taking drug-loaded micelles self-assembled from the amphiphilic polymers as a case, the quantitative structure-property relationship (QSPR) of chemical products was studied on the basis of the cross-scale method from macroscopic to microscopic in this work. A block unit autocorrelation method to calculate the descriptors for characterization of amphiphilic polymer structure was proposed. A series of QSPR models to predict the drug-loading capacity of polymeric micelles at different drug/polymer ratios were established by combining genetic function approximation (GFA) algorithm and multiple linear regression (MLR). The reliability, stability and predictive ability of models were evaluated via internal validation (R2>0.854, Qloo-cv>0.651, RMSE<0.089), Y-randomization test, external validation (Qext2>0.629) as well as application domain definition analysis. The effect of blocks and topological structure of polymers on drug-loading capacity was well explained by descriptors and drug-loaded mechanism analysis. The QSPR models were hopefully used to provide a guide for new polymer design and drug-loading capacity prediction. Also this cross-scale method would be expected to promote the design and development of novel complex structured products.

Key words: production engineering, polymers, genetic algorithm, cross-scale method, polymeric micelles, block unit autocorrelation descriptor

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