Abstract
Using fragmental descriptors and artificial neural networks, a predictive model of the relationship between the structure of organic compounds and their blood-brain barrier permeability was constructed and the structural factors affecting the readiness of this penetration were analyzed. This model (N = 529, Q 2 = 0.82, RMSE cv = 0.32) surpasses the previously published models in terms of the prediction accuracy and the applicability domain and can be used for the optimization of the pharmacokinetic parameters during drug development.
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Original Russian Text © A.S. Dyabina, E.V. Radchenko, V.A. Palyulin, N.S. Zefirov, 2016, published in Doklady Akademii Nauk, 2016, Vol. 470, No. 6, pp. 720–723.
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Dyabina, A.S., Radchenko, E.V., Palyulin, V.A. et al. Prediction of blood-brain barrier permeability of organic compounds. Dokl Biochem Biophys 470, 371–374 (2016). https://doi.org/10.1134/S1607672916050173
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DOI: https://doi.org/10.1134/S1607672916050173