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相关概念视频

Optimizing Chromatographic Separations01:15

Optimizing Chromatographic Separations

351
Optimizing chromatographic separations is crucial for obtaining clean separations in a minimum amount of time. Optimization is required for several factors, including kinetic effects related to band broadening, plate height, capacity factor, and separation factor.
Band broadening refers to spreading solute bands as they travel through the column. This broadening can impact resolution. Plate height (H) represents the length required for one theoretical plate. A lower plate height corresponds to...
351
Principles Of Column Chromatography01:13

Principles Of Column Chromatography

6.8K
The chromatography technique was first invented in 1901 by Michael S. Tswett, a Russian botanist, to separate plant pigments using organic solvents. Further, in 1941, Archer John Porter Martin and R. L. M. Synge modified the technique by packing silica gel into a column. A mixture of amino acids was then separated on the packed column using chloroform and water mixture as the mobile phase. This was the first report on column chromatography. At present, column chromatography is a widely used...
6.8K
Types Of Column Chromatography01:29

Types Of Column Chromatography

11.0K
The stability and compatibility of column material with samples are crucial for efficient purification in chromatographic techniques. Various operating parameters such as pH, temperature, or solvent affect the packing of the column material, thereby determining the purification efficiency. The choice of column material also plays an essential role in deciding the operating parameters and can be modified based on the proteins that need to be purified.
Gel Filtration Chromatography
When the...
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Affinity Chromatography01:03

Affinity Chromatography

556
Affinity chromatography is a powerful technique extensively utilized for separating and purifying specific biomolecules from complex mixtures. It capitalizes on the highly selective binding between an analyte and its counterpart, such as antibody-antigen interactions. The counterpart is immobilized on the stationary phase, forming an affinity column. The stationary phase typically consists of solid support, such as agarose or porous glass beads, immobilizing the affinity ligand. The mobile...
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相关实验视频

Updated: Jun 11, 2025

Multimer-PAGE: A Method for Capturing and Resolving Protein Complexes in Biological Samples
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从蛋白质结构到使用多尺度建模的优化色谱捕获步骤.

Daphne Keulen1, Tim Neijenhuis1, Adamantia Lazopoulou1

  • 1Department of Biotechnology, Delft University of Technology, Delft, The Netherlands.

Biotechnology progress
|September 30, 2024
PubMed
概括

这项研究整合了定量结构-属性关系 (QSPR) 和机械建模 (MM) 以优化生物制药酸交换 (CEX) 染色学. 这种in silico方法显著减少了用于高效的工艺开发的实验力度.

关键词:
生物制药下游加工 生物制药下游加工染色体学 染色体学 染色体学机械模型模型机械模型过程优化优化过程优化定量结构 财产关系

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Last Updated: Jun 11, 2025

Multimer-PAGE: A Method for Capturing and Resolving Protein Complexes in Biological Samples
07:40

Multimer-PAGE: A Method for Capturing and Resolving Protein Complexes in Biological Samples

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科学领域:

  • 生物制药工艺开发 生物制药过程开发
  • 计算化学的计算化学
  • 染色体学 染色体学 是一种染色学.

背景情况:

  • 优化生物制药净化过程是具有挑战性的,因为有限的过程理解,需要广泛的实验.
  • 机械或数据驱动建模等in silico技术可以增强过程理解,从而实现更具成本效益和时间效率的优化.

研究的目的:

  • 开发和验证一个多尺度建模策略,整合定量结构-属性关系 (QSPR) 和机械模型 (MM) 以优化阴子交换 (CEX) 染色学.
  • 通过从蛋白质结构中预测色谱行为来减少生物制药工艺开发中的实验力度.

主要方法:

  • 开发了使用蛋白质结构特征的QSPR模型来预测物理化学行为和保留量.
  • 将QSPR衍生参数集成到机械模型 (MM) 中,以预测染色图.
  • 在各种pH条件下实验确定了六种蛋白质的保留概况,以训练和验证模型.
  • 使用集成建模方法优化了CEX捕获步骤.

主要成果:

  • QSPR模型准确地预测了培训蛋白的保留量和特征性电荷.
  • 对于看不见的蛋白质,该模型预测与梯度长相对应的0.2%内的保留峰值差异.
  • 综合QSPR-MM方法成功优化了CEX捕获步骤,产生与实验方法一致的结果.
  • 模型参数信心分析确定了可行的过程条件,其中一个符合实验优化结果.

结论:

  • 多尺度建模方法有效地减少了对生物制药过程优化的实验要求.
  • 整合QSPR和MM为预测和优化色谱净化步骤提供了强大的工具.
  • 这种策略可以识别初始过程条件,简化下游优化工作.