Literature DB >> 18048048

Prediction of protein retention times in gradient hydrophobic interaction chromatographic systems.

Jie Chen1, Ting Yang, Steven M Cramer.   

Abstract

A two-step methodology has been developed for the prediction of protein retention time in linear-gradient HIC systems. Isocratic retention parameters were determined from ln(k')-salt concentration plots for a number of commercially available proteins with a range of properties. Quantitative structure property relationship (QSPR) models based on a support vector machine (SVM) approach were generated for predicting isocratic retention parameters for proteins not included in the model generation. The predicted parameters were then used to calculate protein gradient retention times and the results indicate that this approach is well suited for predicting experimental gradient retention data. The approach presented in this paper may have implications for HIC methods development at both the bench and process scales.

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Year:  2007        PMID: 18048048     DOI: 10.1016/j.chroma.2007.11.003

Source DB:  PubMed          Journal:  J Chromatogr A        ISSN: 0021-9673            Impact factor:   4.759


  3 in total

Review 1.  Recent applications of chemometrics in one- and two-dimensional chromatography.

Authors:  Tijmen S Bos; Wouter C Knol; Stef R A Molenaar; Leon E Niezen; Peter J Schoenmakers; Govert W Somsen; Bob W J Pirok
Journal:  J Sep Sci       Date:  2020-03-19       Impact factor: 3.645

2.  A new thermodynamic model describes the effects of ligand density and type, salt concentration and protein species in hydrophobic interaction chromatography.

Authors:  R W Deitcher; J E Rome; P A Gildea; J P O'Connell; E J Fernandez
Journal:  J Chromatogr A       Date:  2009-08-03       Impact factor: 4.759

3.  QSAR Implementation for HIC Retention Time Prediction of mAbs Using Fab Structure: A Comparison between Structural Representations.

Authors:  Micael Karlberg; João Victor de Souza; Lanyu Fan; Arathi Kizhedath; Agnieszka K Bronowska; Jarka Glassey
Journal:  Int J Mol Sci       Date:  2020-10-28       Impact factor: 5.923

  3 in total

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