Staff Publications

  • external user (warningwarning)
  • Log in as
  • language uk
Record number 505774
Title Prediction of protein retention times in hydrophobic interaction chromatography by robust statistical characterization of their atomic-level surface properties.
Author(s) Hanke, A.T.; Klijn, M.E.; Verhaert, P.D.; Wielen, L. van der; Ottens, M.; Eppink, M.H.M.; Sandt, E.J.A.X. van de
Source Biotechnology Progress 32 (2016)2. - ISSN 8756-7938 - p. 372 - 381.
Department(s) Bioprocess Engineering
Publication type Refereed Article in a scientific journal
Publication year 2016
Abstract The correlation between the dimensionless retention times (DRT) of proteins in hydrophobic interaction chromatography (HIC) and their surface properties were investigated. A ternary atomic-level hydrophobicity scale was used to calculate the distribution of local average hydrophobicity across the proteins surfaces. These distributions were characterized by robust descriptive statistics to reduce their sensitivity to small changes in the three-dimensional structure. The applicability of these statistics for the prediction of protein retention behaviour was looked into. A linear combination of robust statistics describing the central tendency, heterogeneity and frequency of highly hydrophobic clusters was found to have a good predictive capability (R2  = 0.78), when combined a factor to account for protein size differences. The achieved error of prediction was 35% lower than for a similar model based on a description of the protein surface on an amino acid level. This indicates that a robust and mathematically simple model based on an atomic description of the protein surface can be used for the prediction of the retention behaviour of conformationally stable globular proteins with a well determined 3D structure in HIC. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:372-381, 2016.
There are no comments yet. You can post the first one!
Post a comment
Please log in to use this service. Login as Wageningen University & Research user or guest user in upper right hand corner of this page.