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Pharmaceutical Chemistry Journal

, Volume 52, Issue 12, pp 975–979 | Cite as

Computer Regression Models for P-Glycoprotein Transport of Drugs

  • V. Yu. GrigorevEmail author
  • S. L. Solodova
  • D. E. Polianczyk
  • J. C. Dearden
  • O. A. Raevsky
Article
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Regression models of the cellular substrate specificity of 177 drugs for P-glycoprotein were built using linear regression, random forest, and support vector methods. QSAR modeling used a full-trial search of all possible combinations of the seven most significant molecular descriptors with clear physicochemical interpretations. The statistics of the obtained models were satisfactory according to an internal cross-validation and external validation tests using 44 new compounds. H-bond descriptors were components of almost all most significant QSAR models. This confirmed that H-bonds played an important role in penetration of the compounds through the blood–brain barrier. The developed statistical models could be used to assess P-glycoprotein transport of investigational new drugs.

Keywords

QSAR H-bond P-glycoprotein HYBOT 

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • V. Yu. Grigorev
    • 1
    Email author
  • S. L. Solodova
    • 1
  • D. E. Polianczyk
    • 1
  • J. C. Dearden
    • 2
  • O. A. Raevsky
    • 1
  1. 1.Institute of Physiologically Active CompoundsRussian Academy of SciencesChernogolovkaRussia
  2. 2.School of Pharmacy and Biomolecular SciencesLiverpool John Moores UniversityLiverpoolUK

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