Suppr超能文献

各种基于二氧化硅的整体柱用于分析大生物分子的比较。

Comparison of various silica-based monoliths for the analysis of large biomolecules.

机构信息

School of Pharmaceutical Sciences, University of Geneva, University of Lausanne, Geneva, Switzerland.

出版信息

J Sep Sci. 2013 Jul;36(14):2231-43. doi: 10.1002/jssc.201300323.

Abstract

In the present study, three types of silica-based monoliths, i.e. the first and second generations of commercial silica monolithic columns and a wide-pore prototype monolith were compared for the analysis of large biomolecules. These molecules possess molecular weights between 1 and 66 kDa. The gradient kinetic performance of the first-generation monolith was lower than that of the second generation, for large biomolecules (>14 kDa) but very close with smaller ones (1.3-5.8 kDa). In contrast, the wide-pore prototype column was particularly attractive with proteins larger than 19 kDa (higher peak capacity). Among these three columns, the selectivity and retention remained quite similar but a possible larger number of accessible and charged residual silanols was noticed on the wide-pore prototype material, which led to unpredicted small changes in selectivity and slightly broader peaks than expected. The peak shapes attained with the addition of 0.1% formic acid in the mobile phase remained acceptable for MS coupling, particularly for biomolecules of less than 6 kDa. It was found that one of the major issues with all of these silica-based monoliths is the possible poor recovery of large biomolecules (principally with monoclonal antibody fragments of more than 25 kDa).

摘要

在本研究中,我们比较了三种基于硅胶的整体柱,即第一代和第二代商业硅胶整体柱以及一种大孔原型整体柱,用于分析大生物分子。这些分子的分子量在 1 到 66 kDa 之间。对于大生物分子(>14 kDa),第一代整体柱的梯度动力学性能低于第二代,但对于较小的分子(1.3-5.8 kDa)则非常接近。相比之下,大孔原型柱对于大于 19 kDa 的蛋白质特别有吸引力(更高的峰容量)。在这三种柱子中,选择性和保留性非常相似,但在大孔原型材料上注意到可能有更多的可及和带电的残留硅醇,这导致选择性的不可预测的小变化和比预期稍宽的峰。在流动相中添加 0.1%甲酸后获得的峰形对于 MS 偶联仍然可以接受,特别是对于小于 6 kDa 的生物分子。结果发现,所有这些基于硅胶的整体柱的一个主要问题是可能对大生物分子的回收率较差(主要是对于大于 25 kDa 的单克隆抗体片段)。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验