Pharmaceutical Research

, Volume 23, Issue 3, pp 483–492

Development of a QSAR Model for Binding of Tripeptides and Tripeptidomimetics to the Human Intestinal Di-/Tripeptide Transporter hPEPT1

  • Rikke Andersen
  • Flemming Steen Jørgensen
  • Lars Olsen
  • Jon Våbenø
  • Karina Thorn
  • Carsten Uhd Nielsen
  • Bente Steffansen
Research Paper

DOI: 10.1007/s11095-006-9462-y

Cite this article as:
Andersen, R., Jørgensen, F.S., Olsen, L. et al. Pharm Res (2006) 23: 483. doi:10.1007/s11095-006-9462-y

Purpose

The aim of this study was to develop a three-dimensional quantitative structure–activity relationship (QSAR) model for binding of tripeptides and tripeptidomimetics to hPEPT1 based on a series of 25 diverse tripeptides.

Methods

VolSurf descriptors were generated and correlated with binding affinities by multivariate data analysis. The affinities for hPEPT1 of the tripeptides and tripeptidomimetics were determined experimentally by use of Caco-2 cell monolayers.

Results

The Ki-values of the 25 tripeptides and tripeptidomimetics ranged from 0.15 to 25 mM and the structural diversity of the compounds was described by VolSurf descriptors. A QSAR model that correlated the VolSurf descriptors of the tripeptides with their experimental binding affinity for hPEPT1 was established.

Conclusion

Structural information on tripeptide properties influencing the binding to hPEPT1 was extracted from the QSAR model. This information may contribute to the drug design process of tripeptides and tripeptidomimetics where hPEPT1 is targeted as an absorptive transporter for improvement of intestinal absorption. To our knowledge, this is the first time a correlation between VolSurf descriptors and binding affinities for hPEPT1 has been reported.

Key Words

hPEPT1 QSAR tripeptides tripeptidomimetics VolSurf 

Abbreviations

Ψ

N- methyl amide bond isostere Ψ [CONCH3]

3D-QSAR

three-dimensional quantitative structure– activity relationship

CoMSIA

comparative molecular similarity indices analysis

PCA

principal component analysis

PLS

partial least square of latent variables

Supplementary material

NY00009462_ESM.pdf (178 kb)
Supplementary material (182 KB)

Copyright information

© Springer Science + Business Media, Inc. 2006

Authors and Affiliations

  • Rikke Andersen
    • 1
  • Flemming Steen Jørgensen
    • 2
  • Lars Olsen
    • 2
  • Jon Våbenø
    • 1
    • 4
  • Karina Thorn
    • 3
  • Carsten Uhd Nielsen
    • 1
  • Bente Steffansen
    • 1
  1. 1.Molecular BiopharmaceuticsThe Danish University of Pharmaceutical SciencesCopenhagenDenmark
  2. 2.Biostructural ResearchThe Danish University of Pharmaceutical SciencesCopenhagenDenmark
  3. 3.Medicinal ChemistryThe Danish University of Pharmaceutical SciencesCopenhagenDenmark
  4. 4.Center for Computational BiologyWashington University School of MedicineSt. LouisUSA

Personalised recommendations