Prediction of blood-brain barrier permeability of organic compounds


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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, Q2 = 0.82, RMSEcv = 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.

作者简介

A. Dyabina

Department of Chemistry

Email: genie@qsar.chem.msu.ru
俄罗斯联邦, Moscow, 119991

E. Radchenko

Department of Chemistry; Institute of Physiologically Active Compounds

编辑信件的主要联系方式.
Email: genie@qsar.chem.msu.ru
俄罗斯联邦, Moscow, 119991; Severnyi proezd 1, Chernogolovka, Moscow oblast, 142432

V. Palyulin

Department of Chemistry; Institute of Physiologically Active Compounds

Email: genie@qsar.chem.msu.ru
俄罗斯联邦, Moscow, 119991; Severnyi proezd 1, Chernogolovka, Moscow oblast, 142432

N. Zefirov

Department of Chemistry; Institute of Physiologically Active Compounds

Email: genie@qsar.chem.msu.ru
俄罗斯联邦, Moscow, 119991; Severnyi proezd 1, Chernogolovka, Moscow oblast, 142432

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