QSAR modeling of mammal acute toxicity by oral exposure

  • O.A. Raevsky Institute of Physiologically Active Compounds of the Russian Academy of Sciences, 1 Severny proezd, Moscow region, Chernogolovka, 142432 Russia
  • V.Yu. Grigorev Institute of Physiologically Active Compounds of the Russian Academy of Sciences, 1 Severny proezd, Moscow region, Chernogolovka, 142432 Russia
  • A.V. Yarkov Institute of Physiologically Active Compounds of the Russian Academy of Sciences, 1 Severny proezd, Moscow region, Chernogolovka, 142432 Russia
  • O.V. Tinkov Institute of Physiologically Active Compounds of the Russian Academy of Sciences, 1 Severny proezd, Moscow region, Chernogolovka, 142432 Russia
Keywords: acute oral toxicity, QSAR, HYBOT

Abstract

7490 organic compounds exhibiting acute oral toxicity in mice were studied. Regression models with satisfactory statistical characteristics have been created using the original AMP (arithmetic mean property) approach. The best models using the training and test sets were characterized by the squared linear correlation coefficient and the standard deviation of 0.5 and 0.45 (in log(1/LD50) units).

References

  1. Devillers, J.,&Devillers, H. (2009) Prediction of acute mammalian toxicity from QSARs and interspecies correlations. SAR QSAR Environ. Res., 20(5-6), 467-500. DOI

  2. Lipnick, R.L. (1991) Outliers: Their origin and use in the classification of molecular mechanisms of toxicity. Sci. Total Environ., 109/110, 131–153. DOI

  3. Verhaar, H.J.M.,VanLeeuwen, C.J., &Hermens, J.L.M. (1992) Classifying environmental pollutants. Chemosphere, 25(4), 471–491. DOI

  4. Raevsky, O.A., Grigor'ev, V.Ju., Modina, E.A., & Worth, A.P. (2010) Prediction of acute toxicity to mice by the Arithmetic Mean Toxicity (AMT) modelling approach. SAR QSAR Environ. Res., 21(3-4), 265-275. DOI

  5. SYMYX Toxicity Database. Retrieved August 15, 2018, from http://accelrys.com/products/pdf/dg-pharmacology-package-ds.pdf

  6. Volsurf. Retrieved August 15, 2018, from http://www.moldiscovery.com/software/vsplus/

  7. Raevsky, O.A., Grigor’ev, V.Ju., Trepalin, S.V., HYBOT program package, Registration by Russian State Patent Agency No. 990090 of 26.02.99.

  8. DRAGON. Retrieved August 15, 2018, from http://www.talete.mi.it/products/dragon_projects.htm

  9. Lagunin, A., Zakharov, A., Filimonov, D., & Poroikov V. (2011) QSAR modelling of rat acute toxicity on the basis of PASS prediction. Mol. Inf., 30, 241-250. DOI

Published
2018-09-07
Section
Experimental Research