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Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry (UPLC-HRMS)
Published on: May 20, 2013
Determination of selectivity differences for basic compounds in gradient reverse phase high performance liquid
Emilia Fornal1, Phil Borman, Christopher Luscombe
1GlaxoSmithKline, Strategic Technologies, Chemical Development, 5G146 Gunnels Wood Road, Stevenage SG1 2NY, United Kingdom. efornal@kul.lublin.pl
Principal component analysis (PCA) and partial least squares (PLS) effectively modeled the complex interactions in high pH liquid chromatography (HPLC) for basic compounds. These multivariate methods identified selectivity differences across various octadecyl columns.
Area of Science:
- Analytical Chemistry
- Chromatography
- Chemometrics
Background:
- Compound retention in chromatography is influenced by multiple physico-chemical properties.
- Multivariate analysis techniques like Principal Component Analysis (PCA) and Partial Least Squares (PLS) are valuable for exploring complex solute-phase interactions.
- Understanding these interactions is crucial for optimizing separation and selectivity in High-Performance Liquid Chromatography (HPLC).
Purpose of the Study:
- To investigate the chromatographic behavior of basic compounds using optimized gradient conditions.
- To explore and model the selectivity differences among various octadecyl (C18) HPLC columns under high pH separation conditions.
- To establish quantitative structure-retention relationships (QSRRs) using multivariate modeling.
Main Methods:
- Analysis of three pharmaceutical mixtures using linear gradient reverse-phase HPLC (RP-HPLC) at high pH.
- Utilized ammonia as a pH modifier and methanol/acetonitrile as organic modifiers.
- Employed multivariate PCA and PLS modeling to analyze retention data and molecular descriptors across three different C18 columns (Waters XTerra MS C18, Agilent Zorbax Extend C18, Thermo Hypersil-Keystone BetaBasic-18).
Main Results:
- PCA and PLS successfully visualized and modeled the complex relationships between basic compounds and chromatographic system variables.
- Significant selectivity differences were identified among the tested octadecyl columns under high pH conditions.
- The study related compound molecular descriptors to the observed selectivity, explaining the interactions with mobile and stationary phases.
Conclusions:
- Multivariate PCA and PLS are powerful tools for understanding and explaining selectivity variations in HPLC systems, particularly for basic compounds at high pH.
- The choice of octadecyl column significantly impacts the separation selectivity of basic analytes under high pH conditions.
- Relating molecular descriptors to chromatographic selectivity provides insights into the fundamental interactions governing retention.
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