Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Predictive approaches to gradient retention based on analyte structural descriptors from calculation chemistry.

Tomasz Baczek1, Roman Kaliszan

  • 1Department of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, Gen. J. Hallera 107, 80-416 Gdańsk, Poland.

Journal of Chromatography. A
|March 5, 2003
PubMed
Summary

Quantitative structure retention relationships (QSRRs) predict reversed-phase HPLC retention. Models using molecular modeling descriptors and log P showed similar prediction errors, suggesting practical analytical value.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Diagnosis-Driven Targeted Therapy in Acute Myeloid Leukemia: Clinical Integration of Tyrosine Kinase, BCL-2, and CD33-Directed Strategies with Midostaurin, Venetoclax, and Gemtuzumab Ozogamicin.

Journal of clinical medicine·2026
Same author

The transition of MXene research: the map and the gap.

Nanoscale·2026
Same author

Precision Medicine in Non-Hodgkin Lymphoma: Advances in BTK Inhibition, CD30-Directed Antibody-Drug Conjugates, and HDAC-Mediated Epigenetic Therapy with Pirtobrutinib, Brentuximab Vedotin, and Belinostat.

Journal of clinical medicine·2026
Same author

Molecular Profiling and Targeted Therapeutic Strategies in Breast Cancer: Clinical Integration of HER2, CDK4/6, and PI3K Inhibition with Trastuzumab, Abemaciclib and Alpelisib.

Journal of clinical medicine·2026
Same author

Therapeutic Targeting of VEGFR-2, PD-L1, and EGFR-MET Pathways in Non-Small Cell Lung Cancer: Clinical Progress with Ramucirumab, Atezolizumab, and Amivantamab.

Journal of clinical medicine·2026
Same author

Molecular Targeting of EGFR, BRAF, and HER2 Signaling in Colorectal Cancer: Contemporary Advances with Panitumumab, Encorafenib, and Tucatinib.

Journal of clinical medicine·2026

Area of Science:

  • Analytical Chemistry
  • Computational Chemistry

Background:

  • Quantitative structure retention relationships (QSRRs) are crucial for predicting chromatographic retention.
  • Reversed-phase high-performance liquid chromatography (HPLC) gradient elution is widely used but complex to model.
  • Accurate prediction of retention times aids in method development and optimization.

Purpose of the Study:

  • To compare the predictive performance of QSRR models using molecular modeling descriptors versus log P for reversed-phase HPLC gradient retention.
  • To evaluate the reliability of gradient retention time predictions based on different quantitative structure-property relationship approaches.

Main Methods:

  • Employed QSRR by utilizing three molecular modeling descriptors: total dipole moment, electron excess charge, and water-accessible molecular surface area.

Related Experiment Videos

  • Calculated logarithm of n-octanol-water partition coefficient (log P) using three commercial software packages.
  • Compared predicted retention parameters for a diverse set of small molecules in reversed-phase HPLC gradient elution.

    • Main Results:

    • QSRR models based on molecular modeling descriptors and log P exhibited comparable prediction errors for gradient retention times.
    • Both approaches demonstrated similar reliability in predicting retention behavior across structurally varied analytes.
    • The study validates the use of molecular descriptors for retention prediction in complex chromatographic systems.

    Conclusions:

    • Molecular modeling descriptors offer a viable alternative to log P for QSRR in reversed-phase HPLC gradient elution.
    • QSRR, combined with linear solvent strength theory, holds potential for optimizing chromatographic separations.
    • These findings can streamline analytical method development and enhance predictive capabilities in chromatography.