[Classification models of structure - P-glycoprotein activity of drugs].

Thirty three classification models of substrate specificity of 177 drugs to P-glycoprotein have been created using of the linear discriminant analysis, random forest and support vector machine methods. QSAR modeling was carried out using 2 strategies. The first strategy consisted in search of all possible combinations from 1÷5 descriptors on the basis of 7 most significant molecular descriptors with clear physico-chemical interpretation. In the second case forward selection procedure up to 5 descriptors, starting from the best single descriptor was used. This strategy was applied to a set of 387 DRAGON descriptors. It was found that only one of 33 models has necessary statistical parameters. This model was designed by means of the linear discriminant analysis on the basis of a single descriptor of H-bond (ΣC(ad)). The model has good statistical characteristics as evidenced by results to both internal cross-validation, and external validation with application of 44 new chemicals. This confirms an important role of hydrogen bond in the processes connected with penetration of chemical compounds through a blood-brain barrier.

[Computer modeling of blood brain barrier permeability of physiologically active compounds].

At present work discusses the current level of computer modeling the relationship structure of organic compounds and drugs and their ability to penetrate the BBB. All descriptors that influence to this permeability within classification and regression QSAR models are generalized and analyzed. The crucial role of H-bond in processes both passive, and active transport across BBB is observed. It is concluded that further research should be focused on interpretation the spatial structure of a full-size P-glycoprotein molecule with high resolution and the creation of QSAR models describing the quantitative relationship between structure and active transport of substances across BBB.

[Computer classification models on the relationship between chemical structures of compounds and drugs with their blood brain barrier penetration].

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.