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Updated: Jan 21, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
Published on: January 26, 2024
Application of reversed-phase thin layer chromatography and QSRR modelling for prediction of protein binding of
Krzesimir Ciura1, Piotr Kawczak2, Katarzyna Ewa Greber1
1Medical University of Gdańsk, Faculty of Pharmacy, Department of Physical Chemistry, Al. Gen. J. Hallera 107, 80-416, Gdańsk, Poland.
Abstract:
Chromatographic properties of sixteen β-blockers were studied using planar chromatography. The aim of presented study was to investigate influence of different organic solvents (acetonitrile, methanol, dioxin and tetrahydrofurane) on β-blockers' retention on C18 bonded silica gel stationary phase. Group of sixteen, diverse in terms of structure, beta blockers was used as a model set. The main goal of this study was to compare chromatographically estimated lipophilicity parameters with values obtained with the use of computational methods. Furthermore, in order to understand molecular mechanisms of retention better, quantitative structure-retention relationships (QSRR) analysis was performed. The next step was focused on application of chromatographically obtained lipophilicity parameters for prediction of protein binding (PB), based on quantitative retention-activity relationships (QRAR) approach. The obtained results showed that reversed-phase thin layer chromatography (RP-TLC), especially with tetrafydrofurane used as an organic modifier of mobile phase, is a useful tool for lipophilicity estimation, as well as for prediction of β-blockers' biological properties. The QRAR model included C0 parameters for tetrahydrofuran-water as a mobile phase, as well as maximal projection area, and can be easily applied for prediction of systematically synthesized β-blockers structures' PB.
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