Bulletin of Experimental Biology and Medicine

, Volume 154, Issue 4, pp 521–524

Computer Evaluation of Drug Interactions with P-Glycoprotein

  • A. A. Lagunin
  • T. A. Gloriozova
  • A. V. Dmitriev
  • N. E. Volgina
  • V. V. Poroikov
METHODS

DOI: 10.1007/s10517-013-1992-9

Cite this article as:
Lagunin, A.A., Gloriozova, T.A., Dmitriev, A.V. et al. Bull Exp Biol Med (2013) 154: 521. doi:10.1007/s10517-013-1992-9

The (Q)SAR models for evaluating the structure–property relationships, fit for prediction of drug interactions with P-glycoprotein as inhibitors or substrates, were constructed using PASS and GUSAR software. The models were constructed and validated on the basis of information on the structure and characteristics of 256 and 94 compounds used as P-glycoprotein substrates and inhibitors, respectively. The initial samples were divided 80:20 into training and test samples. The best prediction accuracy for the test samples was 78% for P-glycoprotein substrate prediction (PASS) and 89% for inhibitor prediction (GUSAR).

Key Words

(Q)SAR P-glycoprotein PASS GUSAR 

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • A. A. Lagunin
    • 1
  • T. A. Gloriozova
    • 1
  • A. V. Dmitriev
    • 1
  • N. E. Volgina
    • 2
  • V. V. Poroikov
    • 1
  1. 1.V. N. Orekhovich Institute of Biomedical Chemistrythe Russian Academy of Medical SciencesMoscowRussia
  2. 2.N. I. Pirogov Russian Medical University, the Ministry of Health and Social Development of the Russian FederationMoscowRussia

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