Three-Dimensional Quantitative Structure Activity Relationship Analyses of Substrates for CYP2B6

  1. Sean Ekins1,3,
  2. Gianpaolo Bravi2,1,2,
  3. Barbara J. Ring3,
  4. Todd A. Gillespie3,
  5. Jennifer S. Gillespie3,
  6. Mark Vandenbranden3,
  7. Steven A. Wrighton3 and
  8. James H. Wikel1
  1. 1Computational Chemistry and Molecular Structure Research, Lilly Research Laboratories (G.B., J.H.W.); 2Glaxo Wellcome Research and Development, Medicines Research Center, Stevenage, Hertfordshire, United Kingdom (G.B.); and 3Department of Drug Disposition, Eli Lilly and Co., Indianapolis, Indiana (S.E., B.J.R., T.A.G., J.S.G., M.VB., S.A.W.).

    Abstract

    To begin to build an understanding of the interactions of CYP2B6 with substrates, two different 3-dimensional quantitative structure activity relationship (3D-QSAR) models were constructed using 16 substrates of B-lymphoblastoid expressed CYP2B6. A pharmacophore model was built using the program Catalyst, which was compared with a partial least-squares (PLS) model using molecular surface-weighted holistic invariant molecular (MS-WHIM) descriptors. The Catalyst model yielded a 3-dimensional model of the common structural features of CYP2B6 substrates, whereas PLS MS-WHIM generated a model based on statistical analyses of molecular descriptors for size and shape of the substrate. The pharmacophore model obtained with Catalyst consisted of three hydrophobes and one hydrogen bond acceptor region. The cross-validated PLS MS-WHIM model gave a good q2 value of 0.607. Size, positive electrostatic potential, hydrogen bonding acceptor capacity, and hydrophobicity were found to be the most relevant descriptors for the model. These models were then used to predict the Km (apparent) values of a test set of structurally diverse substrates for CYP2B6 not included in the model building, specifically lidocaine, amitriptyline, bupropion, arteether, and verapamil. Overall, both 3D-QSAR methods yielded satisfactory Km (apparent) value predictions for the majority of the molecules in the test set. However, PLS MS-WHIM was unable to reliably predict theKm (apparent) value for verapamil, whereas Catalyst did not predict the Km (apparent)value for lidocaine. In both of these cases the residual of theKm (apparent) value was greater than one log unit. The strengths and limitations of both of these 3D-QSAR approaches are discussed.

    Footnotes

    • Send reprint requests to: Steven A. Wrighton, Ph.D., Department of Drug Disposition, Lilly Research Laboratories, Eli Lilly and Co., Lilly Corporate Center, Drop Code 0825, Indianapolis, IN 46203.

    • ↵1 Present address: Central Research Division, Pfizer Inc., Groton, CT 06340.

    • ↵2 Present address: Glaxo Wellcome Research and Development, Medicines Research Center, Gunnels Wood Road, Stevenage, Hertfordshire, SG1 2NY, United Kingdom.

    • Abbreviations:
      CYP
      cytochrome P-450
      3D-QSAR
      3-dimensional quantitative structure activity relationship
      LOO
      leave one out
      MS-WHIM
      molecular surface-weighted holistic invariant molecular
      PLS
      partial least squares
      5RGx100
      five random groups repeated up to 100 times
      3D
      3-dimensional
      MEGX
      monoethylglycinexylidide
      HPLC
      high-performance liquid chromatography, LC/MS, liquid chromatography/mass spectroscopy
      LC/MS/MS
      liquid chromatography/mass spectroscopy/mass spectroscopy
      • Received March 26, 1998.
      • Accepted August 26, 1998.
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    1. JPET January 1, 1999 vol. 288 no. 1 21-29
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