Biomedical Chemistry: Research and Methods, 2018, 1(3), e00065
The 40th Anniversary of the Institute of Physiologically Active Compounds of the Russian Academy of Sciences

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

O.A. Raevsky*, D.E. Polianczyk, O.E. Raevskaja

Institute of Physiologically Active Compounds of the Russian Academy of Sciences, 1 Severny proezd, Moscow region, Chernogolovka, 142432 Russia;*e-mail: raevsky@ipac.ac.ru

Key words: QSAR; CNS; blood-brain barrier; binary classification; descriptors

DOI: 10.18097/BMCRM00065

The whole version of this paper is available in Russian.

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%.

CLOSE
Table 1. Statistic parameters of binary BBB+/BBB- classification of method of logistic regression.

ACKNOWLEDGEMENTS

The work was performed within the framework of the State Task for 2018 (topic number 0090-2017-0020).

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