1. Department of Computer-Aided Molecular Design, Institute of Physiologically Active Compounds
of Russian Academy of Sciences 2. Molecular Drug Research Group, Medical Faculty; Heinrich-Heine-Universitat Dusseldorf
Ability of drugs to cross blood-brain barrier (BBB) (BBB+ for BBB-penetrating and BBB- for non-penetrating compounds) is one of the most important properties of chemicals acting on the central nervous system (CNS). This work presents the results of modelling of the relationship between chemicals structure and BBB-crossing ability. The data set included 1513 compounds BBB+/- (1276 BBB+ and 237 BBB-). Computer modelling of structure-activity relationship was realized by two directions: using the "read-across" method and linear discriminant analysis (LDA) based on physico-chemical descriptors. It was found that a sum of donor-acceptor factors is the principal parameter, which define BBB penetration.
Raevsky O.A., Solodova S.L., Raevskaya O.E., Liplavskiy Y.V., Mannhold R.M. (2012) Computer classification models on the relationship between chemical structures of compounds and drugs with their blood brain barrier penetration. Biomeditsinskaya Khimiya, 58(3), 246-256.
Raevsky O.A. et al. Computer classification models on the relationship between chemical structures of compounds and drugs with their blood brain barrier penetration // Biomeditsinskaya Khimiya. - 2012. - V. 58. -N 3. - P. 246-256.
Raevsky O.A. et al., "Computer classification models on the relationship between chemical structures of compounds and drugs with their blood brain barrier penetration." Biomeditsinskaya Khimiya 58.3 (2012): 246-256.
Raevsky, O. A., Solodova, S. L., Raevskaya, O. E., Liplavskiy, Y. V., Mannhold, R. M. (2012). Computer classification models on the relationship between chemical structures of compounds and drugs with their blood brain barrier penetration. Biomeditsinskaya Khimiya, 58(3), 246-256.
Lipinski C.A., Lombardo F., Dominy B.W., Feeney P.J. (1997) Adv. Drug Delivery Rev., 23, 3-25. Scholar google search
van de Waterbeemd H., Camenisch G., Folkers G., Chretien J.R., Raevsky O.A. (1998) J. Drug Targeting, 6, 151-165. CrossRef Scholar google search
Adenot M., Lahana R.J. (2004) Chem. Inf. Comput. Sci., 44, 239-248. Scholar google search
Zhao Y.H., Abraham M.H., Ibrahim A., Fish P.V., Cole S., Lewis M.L., de Groot M.J., Reynolds D.P. (2007) J. Chem. Inf. Model., 47, 170-175. Scholar google search
Raevsky O.A. (2004) Minireview in Medicinal Chemistry, 4, 1041-1052. Scholar google search
Raevsky O.A. (2008) In: Molecular Drug Properties. Measurement and Prediction (Mannhold R., ed.). Wiley-VCH Verlag GmbH & Co.KGaA, Weinheim, pp. 127-154. Scholar google search
Ertl P. (2008) Polar surface area In: Molecular Drug Properties. Measurement and Prediction (Mannhold R., ed.) Wiley-VCH Verlag GmbH & Co.KGaA, Weinheim, pp. 127-154. Scholar google search
Raevsky O.A., Skvortsov V.S. (2005) SAR & QSAR in Environmental Research, 15, 287-300. Scholar google search
Hansch C., Leo A., Hoekman D. (1995) Exploring QSAR: Hydrophobic, Electronic, and Steric Constants. American Chemical Society, Washington, DC. Scholar google search
Raevskii OA, Grigoriev V., SV Trepalin (26.02.1999) The program HYBOT, Rospatent number 990090 Scholar google search
SYBYL: SYBYL 8.0, Tripos International, 1699 South Hanley Rd., St. Louis, Missouri, 63144, USA. Scholar google search
Raevskii OA, Skvortsov VS (27.09.2004) The program 3D HYBOT, Rospatent number 2004612207. Scholar google search
Organization for Economic Cooperation and Development. Guidance on Grouping of Chemicals, OECD, Paris (2007). Scholar google search
European Chemical Agency, Guidance on Information Requirements and Chemical Safety Assessment, Chapter R6, QSAR and grouping of chemicals, ECHA, Helsinki (2008). Scholar google search
Dimitrov S., Mekenyan O. (2010) An Introduction to Read-Across for the Prediction of the Effects of Chemicals, in `In Silico Toxicology. Principles and Applications`. (Cronin M.T.D., Madden J.C., eds.), RSC, Cambridge, pp. 372-384. Scholar google search
Diderich R. (2010) Tools for Category Formation and Read-Across: Overview of the OECD (Q)SAR Application Toolbox, ibid., pp. 385-407. Scholar google search
Jeliazkova N., Jaworska J., Worth A.P. (2010) Open Source Tools for Read-Across and Category Formation, ibid, pp. 408-445. Scholar google search
Raevsky O.A., Grigor`ev V.Yu., Modina E.A., Worth A. (2010) SAR and QSAR in Environmental Research, 21, 265-275. Scholar google search
Raevskii OA, Gerasimenko, VA, Trepalin SV (26.02.1999) The program MOLDIVS, Rospatent number 990093. Scholar google search
Gerasimenko V.A., Trepalin S.V., Raevsky O.A. (2000) MOLDIVS - A New Program for Molecular Similarity and Diversity Calculations, in `Molecular Modelling and Prediction of Bioactivity`, (Gundertofe K., Jorgensen F., eds.), Kluwer Academic/Plenum Publ., pp. 423-424. Scholar google search
PharmaAlgorithms. ADME Boxes, Version 3.0; PharmaAlgorithms, Inc.: 591 Indian Road, Toronto, ON M6P 2C4, Canada. Scholar google search
Lipinski C.A. Drugs structure and properties, past and present. Can we design drugs with beautiful properties? http://www.iainm.demon.co.uk/spring99/lipins_n.pdf . Scholar google search
