多变量曲线分辨率 - 交替最小正方形加上部分最小正方形基线校正,应用于中红外激光光谱,通过减少旋转模糊性来解决蛋白质变性
Shilpa Vijayakumar1, Andreas Schwaighofer1, Georg Ramer1
1Research Division of Environmental Analytics, Process Analytics and Sensors, Institute of Chemical Technologies and Analytics, TU Wien, Getreidemarkt 9, Vienna 1060, Austria.
概括
使用外腔量子级联激光器 (EC-QCL) 的先进的中红外光谱学可进行敏感蛋白质分析. 新的化学测量方法,多变量曲线分辨率交替最小平方 (MCR-ALS) 和部分最小平方回归 (PLSR),简化了蛋白质二次结构确定复杂矩阵分析.
科学领域:
- 频谱学是一种光谱学.
- 生物物理学的生物物理.
- 分析化学 分析化学
背景情况:
- 外腔量子级联激光器 (EC-QCL) 为中红外光谱 (中红外光谱) 提供高光谱功率密度.
- 中红外光谱中的传输路径长度增加提高了水溶液中的蛋白质测量灵敏度.
- 蛋白质聚合可以阻碍流细胞测量,需要强大的分析方法.
研究的目的:
- 为了证明多变量曲线分辨率交替最小平方 (MCR-ALS) 的应用,用于分析蛋白质去和重新化.
- 在MCR-ALS分析之前,提出基于部分最小平方回归 (PLSR) 的矩阵组件减去方法.
- 从复杂矩阵中提取蛋白质二次结构信息,即使没有参考光谱.
主要方法:
- 利用基于激光的中红外光谱学,扩展了路径长度,用于在线反应监测.
- 应用多变量曲线分辨率交替最小正方形 (MCR-ALS) 来分析来自蛋白质变质化实验的光谱数据.
- 在MCR-ALS分析之前执行矩阵组件减去的部分最小平方回归 (PLSR).
- 研究了在水中用表面活性剂 (SDS和C12E8) 对β-乳糖球蛋白 (β-LG) 的定位.
主要成果:
- MCR-ALS成功地提取了复杂混合物中成分的光谱特征和度概况.
- 结合PLSR-MCR-ALS方法有效地从背景矩阵组件中隔离了蛋白质贡献.
- 自动的PLSR校正之后的MCR-ALS产生了与手动基线校正和独立的MCR-ALS相比的结果.
- 证明了在不依赖参考光谱的情况下获得蛋白质二次结构信息的能力.
结论:
- 开发的化学测量方法简化了蛋白质结构研究中复杂矩阵的分析.
- 中红外光谱与MCR-ALS和PLSR相结合,适用于在线反应监测.
- 这种技术有可能用于生物制药制造中的下游质量控制和工艺自动化.
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