Binary classification of blood-brain barrier penetration by the logistic regression method

  • O.A. Raevsky Institute of Physiologically Active Compounds of the Russian Academy of Sciences, 1 Severny proezd, Moscow region, Chernogolovka, 142432 Russia
  • D.E. Polianczyk Institute of Physiologically Active Compounds of the Russian Academy of Sciences, 1 Severny proezd, Moscow region, Chernogolovka, 142432 Russia
  • O.E. Raevskaja Institute of Physiologically Active Compounds of the Russian Academy of Sciences, 1 Severny proezd, Moscow region, Chernogolovka, 142432 Russia
Keywords: QSAR, CNS, blood-brain barrier, binary classification, descriptors

Abstract

Stable classification predictive models of 83 drugs with different blood-brain barrier penetration capacity have been constructed by the logistic regression method using physicochemical descriptors characterizing steric, electrostatic interactions and hydrogen bond energy. The models are balanced, with the prediction level of 75-80%.

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Published
2018-09-10
Section
Experimental Research