Binary Classification of CNS and PNS Drugs
- Autores: Polianchik D.1, Grigor’ev V.1, Sandakov G.1, Yarkov A.1, Bachurin S.2, Raevskii O.1
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Afiliações:
- Department of Computer-Aided Molecular Design, Institute of Physiologically Active Substances, Russian Academy of Sciences
- Department of Biomedicinal Chemistry, Institute of Physiologically Active Substances, Russian Academy of Sciences
- Edição: Volume 50, Nº 12 (2017)
- Páginas: 800-804
- Seção: Article
- URL: https://journals.rcsi.science/0091-150X/article/view/244482
- DOI: https://doi.org/10.1007/s11094-017-1535-1
- ID: 244482
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Resumo
Stable classification predictive models of 626 drugs acting on the central (CNS) and peripheral (PNS) nervous systems were constructed based on linear discriminant analysis, logistic regression, random forest, and support vector machine methods with physicochemical descriptors characterizing the steric factors, electrostatic interactions, and H-bonding features. Internal cross-validations demonstrated that these models possessed satisfactory statistical properties.
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Sobre autores
D. Polianchik
Department of Computer-Aided Molecular Design, Institute of Physiologically Active Substances, Russian Academy of Sciences
Autor responsável pela correspondência
Email: danielpolian@yahoo.com
Rússia, Chernogolovka, Moscow Region, 142432
V. Grigor’ev
Department of Computer-Aided Molecular Design, Institute of Physiologically Active Substances, Russian Academy of Sciences
Email: danielpolian@yahoo.com
Rússia, Chernogolovka, Moscow Region, 142432
G. Sandakov
Department of Computer-Aided Molecular Design, Institute of Physiologically Active Substances, Russian Academy of Sciences
Email: danielpolian@yahoo.com
Rússia, Chernogolovka, Moscow Region, 142432
A. Yarkov
Department of Computer-Aided Molecular Design, Institute of Physiologically Active Substances, Russian Academy of Sciences
Email: danielpolian@yahoo.com
Rússia, Chernogolovka, Moscow Region, 142432
S. Bachurin
Department of Biomedicinal Chemistry, Institute of Physiologically Active Substances, Russian Academy of Sciences
Email: danielpolian@yahoo.com
Rússia, Chernogolovka, Moscow Region, 142432
O. Raevskii
Department of Computer-Aided Molecular Design, Institute of Physiologically Active Substances, Russian Academy of Sciences
Email: danielpolian@yahoo.com
Rússia, Chernogolovka, Moscow Region, 142432