Recent Advances in QSAR Studies

Volume 8 of the series Challenges and Advances in Computational Chemistry and Physics pp 223-259


QSAR in Chromatography: Quantitative Structure–Retention Relationships (QSRRs)

  • Roman KaliszanAffiliated withDepartment of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk
  • , Tomasz BączekAffiliated withDepartment of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk

* Final gross prices may vary according to local VAT.

Get Access


To predict a given physicochemical or biological property, the relationships can be identified between the chemical structure and the desired property. Ideally these relationships should be described in reliable quantitative terms. To obtain statistically significant relationships, one needs relatively large series of property parameters. Chromatography is a unique method which can provide a great amount of quantitatively precise, reproducible, and comparable retention data for large sets of structurally diversified compounds (analytes). On the other hand, chemometrics is recognized as a valuable tool for accomplishing a variety of tasks in a chromatography laboratory. Chemometrics facilitates the interpretation of large sets of complex chromatographic and structural data. Among various chemometric methods, multiple regression analysis is most often performed to process retention data and to extract chemical information on analytes. And the methodology of quantitative structure–(chromatographic) retention relationships (QSRRs) is mainly based on multiple regression analysis. QSRR can be a valuable source of knowledge on both the nature of analytes and of the macromolecules forming the stationary phases. Therefore, quantitative structure–retention relationships have been considered as a model approach to establish strategy and methods of property predictions.


QSRR Retention predictions Characterization of stationary phases