Pharmaceutical Research

, Volume 22, Issue 12, pp 1989–1996 | Cite as

Quantitative Structure–Activity Relationship and Quantitative Structure–Pharmacokinetics Relationship of 1,4-Dihydropyridines and Pyridines as Multidrug Resistance Modulators

  • Xiao-Fei Zhou
  • Qingxiang Shao
  • Robert A. Coburn
  • Marilyn E. Morris
Research Paper


The aim of this study was to develop quantitative structure–activity/pharmacokinetic relationships (QSAR/QSPKR) for a series of synthesized 1,4-dihydropyridines (DHPs) and pyridines as P-glycoprotein (P-gp) inhibitors.


Molecular descriptors of test compounds were generated by 3D molecular modeling using SYBYL and KowWin programs. Forward inclusion coupled with multiple linear regression (MLR) was used to derive a QSAR equation for Ca2+ channel binding. A multivariate statistical technique, partial least square (PLS) regression, was applied to derive a QSAR model for P-gp inhibition and QSPKR models. Cross-validation using the “leave-one-out” method was performed to evaluate the predictive performance of models.


For Ca2+ channel binding, the MLR equation indicated a good correlation between observed and predicted values (R2 = 0.90), and cross-validation confirmed the predictive ability of the model (Q2 = 0.67). For P-gp reversal, the model obtained by PLS could account for most of the variation in P-gp inhibition (R2 = 0.76) with fair predictive performance (Q2 = 0.62). Nine structurally related 1,4-DHP drugs were used for QSPKR analysis. The models could explain the majority of the variation in clearance (R2 = 0.90), and cross-validation confirmed the prediction ability (Q2 = 0.69).


QSAR/QSPKR models were developed, and the QSAR models were capable of identifying synthesized 1,4-DHPs and pyridines with potent P-gp inhibition and reduced Ca2+ channel binding. The QSPKR models provide insight into the contribution of electronic, steric, and lipophilic factors to the clearance of DHPs.

Key Words

dihydropyridines (DHPs) multidrug resistance (MDR) P-glycoprotein (P-gp) quantitative structure–activity relationship (QSAR) quantitative structure–pharmacokinetic relationship (QSPKR) 







Connolly surface area


core–core repulsion


Connolly surface volume




electronic energy


filled levels


heat of formation


energy of the highest occupied molecular orbital


ionization potentials


energy of the lowest unoccupied molecular orbital


multidrug resistance


multiple linear regression


molecular weight




partial least square


polar surface area


quantitative structure–activity relationship


quantitative structure–pharmacokinetic relationship


total energy of the molecule


apparent volume of distribution





The authors thank Dr. Linping Zhang for synthesis of the 1,4-dihydropyridines and pyridines. Supported in part by a grant from the Kapoor Charitable Foundation (SUNY).


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Copyright information

© Springer Science + Business Media, Inc. 2005

Authors and Affiliations

  • Xiao-Fei Zhou
    • 1
  • Qingxiang Shao
    • 2
  • Robert A. Coburn
    • 3
  • Marilyn E. Morris
    • 1
  1. 1.Department of Pharmaceutical SciencesUniversity at Buffalo, State University of New YorkAmherstUSA
  2. 2.Department of Clinical PharmacologyZhejiang Academy of Medical SciencesHangzhouChina
  3. 3.Department of ChemistryUniversity at Buffalo, State University of New YorkAmherstUSA

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