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Generation of in-silico cytochrome P450 1A2, 2C9, 2C19, 2D6, and 3A4 inhibition QSAR models

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Abstract

In-silico models were generated to predict the extent of inhibition of cytochrome P450 isoenzymes using a set of relatively interpretable descriptors in conjunction with partial least squares (PLS) and regression trees (RT). The former was chosen due to the conservative nature of the resultant models built and the latter to more effectively account for any non-linearity between dependent and independent variables. All models are statistically significant and agree with the known SAR and they could be used as a guide to P450 liability through a classification based on the continuous pIC50 prediction given by the model. A compound is classified as having either a high or low P450 liability if the predicted pIC50 is at least one root mean square error (RMSE) from the high/low pIC50 cut-off of 5. If predicted within an RMSE of the cut-off we cannot be confident a compound will be experimentally low or high so an indeterminate classification is given. Hybrid models using bulk descriptors and fragmental descriptors do significantly better in modeling CYP450 inhibition, than bulk property QSAR descriptors alone.

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Authors and Affiliations

  1. Department of Physical & Metabolic Sciences, AstraZeneca R&D Charnwood, Bakewell Road, Loughborough, Leicestershire, LE11 5RH, UK

    M. Paul Gleeson, Andrew M. Davis, Kamaldeep K. Chohan & Stuart W. Paine

  2. Computational and Structural Chemistry, GlaxoSmithKline Medicines Research Centre, Gunnels Wood Road, Stevenage, Hertfordshire, SG1 2NY, UK

    M. Paul Gleeson

  3. Computational Toxicology, Safety Assessment, AstraZeneca R&D, Molndal, Sweden

    Scott Boyer, Claire L. Gavaghan & Catrin Hasselgren Arnby

  4. HTS Screening, AstraZeneca R&D Mölndal, 431 83, Molndal, Sweden

    Cecilia Kankkonen

  5. Discovery DMPK & BAC, AstraZeneca R&D Mölndal, Molndal, Sweden

    Nan Albertson

Authors
  1. M. Paul Gleeson
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  2. Andrew M. Davis
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  3. Kamaldeep K. Chohan
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  4. Stuart W. Paine
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  5. Scott Boyer
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  6. Claire L. Gavaghan
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  7. Catrin Hasselgren Arnby
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  8. Cecilia Kankkonen
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  9. Nan Albertson
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Correspondence to M. Paul Gleeson.

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Gleeson, M.P., Davis, A.M., Chohan, K.K. et al. Generation of in-silico cytochrome P450 1A2, 2C9, 2C19, 2D6, and 3A4 inhibition QSAR models. J Comput Aided Mol Des 21, 559–573 (2007). https://doi.org/10.1007/s10822-007-9139-6

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  • DOI: https://doi.org/10.1007/s10822-007-9139-6

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