Quantitative analysis of PMLA nanoconjugate components after backbone cleavage.
Quantitative analysis of PMLA nanoconjugate components after backbone cleavage.
复制标题
DOI：
10.3390/ijms16048607
复制
发表时间：
2015-04-16
影响因子：
5.6
通讯作者：
Holler E
中科院分区：
文献类型：
--
作者：
Ding H;Patil R;Portilla-Arias J;Black KL;Ljubimova JY;Holler E
含有多个组分的多功能聚合物纳米缀合物在癌症治疗中显示出巨大的前景，但在大多数情况下，很难完全分析每个组分。基于聚苹果酸（PMLA）的纳米缀合物已被证明成功治疗脑癌和乳腺癌。它们由多个组分组成，包括靶向抗体、吗啉代反义寡核苷酸（AON）和内体逃逸部分。用传统的光谱法和HPLC法分析PMLA纳米复合物的成分是非常困难的。利用PMLA的聚酯性质，其可以被氢氧化铵切割，我们描述了一种通过选择性地切割PMLA骨架使用SEC-HPLC同时分析纳米缀合物内抗体和AON含量的方法。所选切割条件仅降解PMLA而不影响抗体的完整性和生物活性。虽然也可以使用二喹啉甲酸（BCA）方法测定抗体的量，但我们的选择性切割方法给出了更可靠的结果，并且更强大。该方法为聚合物纳米复合物和纳米颗粒的成分分析提供了新的方向。
Multifunctional polymer nanoconjugates containing multiple components show great promise in cancer therapy, but in most cases complete analysis of each component is difficult. Polymalic acid (PMLA) based nanoconjugates have demonstrated successful brain and breast cancer treatment. They consist of multiple components including targeting antibodies, Morpholino antisense oligonucleotides (AONs), and endosome escape moieties. The component analysis of PMLA nanoconjugates is extremely difficult using conventional spectrometry and HPLC method. Taking advantage of the nature of polyester of PMLA, which can be cleaved by ammonium hydroxide, we describe a method to analyze the content of antibody and AON within nanoconjugates simultaneously using SEC-HPLC by selectively cleaving the PMLA backbone. The selected cleavage conditions only degrade PMLA without affecting the integrity and biological activity of the antibody. Although the amount of antibody could also be determined using the bicinchoninic acid (BCA) method, our selective cleavage method gives more reliable results and is more powerful. Our approach provides a new direction for the component analysis of polymer nanoconjugates and nanoparticles.
登录
查看更多内容
DOI：
10.1016/j.jconrel.2013.06.001
发表时间：
2013-11-10
期刊：
Journal of controlled release : official journal of the Controlled Release Society
影响因子：
--
作者：
Ding H;Helguera G;Rodríguez JA;Markman J;Luria-Pérez R;Gangalum P;Portilla-Arias J;Inoue S;Daniels-Wells TR;Black K;Holler E;Penichet ML;Ljubimova JY
通讯作者：
Ljubimova JY
影响因子：
5.6
作者：
Patil R;Portilla-Arias J;Ding H;Konda B;Rekechenetskiy A;Inoue S;Black KL;Holler E;Ljubimova JY
通讯作者：
Ljubimova JY
影响因子：
9.5
作者：
Guo, Jintang;Hong, Hao;Chen, Guojun;Shi, Sixiang;Nayak, Tapas R.;Theuer, Charles P.;Barnhart, Todd E.;Cai, Weibo;Gong, Shaoqin
通讯作者：
Gong, Shaoqin
影响因子：
3.7
作者：
Patil, Rameshwar;Portilla-Arias, Jose;Ding, Hui;Inoue, Satoshi;Konda, Bindu;Hu, Jinwei;Wawrowsky, Kolja A.;Shin, Paul K.;Black, Keith L.;Holler, Eggehard;Ljubimova, Julia Y.
通讯作者：
Ljubimova, Julia Y.
影响因子：
14
作者：
Ding, Hui;Portilla-Arias, Jose;Patil, Rameshwar;Black, Keith L.;Ljubimova, Julia Y.;Holler, Eggehard
通讯作者：
Holler, Eggehard