[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.

[Linear and nonlinear QSAR models of acute intravenous toxicity to mice for organic chemicals].

QSAR analysis of acute intravenous toxicity to mice for 68 monofunctional chemicals is presented. There compounds represents seven classes of organic chemicals: hydrocarbons (6 chemicals), alcohols (13), amides (22), amines (12), ethers (5), ketones (7), nitriles (3). Preliminary consideration of data for these chemicals showed that it is necessary to consider not only linear toxicity--descriptors relationships, but also nonlinear models. The linear and nonlinear QSAR models were considered for each from indicated classes of organic chemicals. Analogical models were constructed for whole subset of monofunctional chemicals. The statistical parameters and robustness of nonlinear models are essential better then statistics of linear models. Replacing a lipophilicity descriptor with molecular polarizability and H-bond ability in nonlinear models permits also to improve statistical characteristics. Clearly, if relationships between the intravenous toxicity of compounds bearing only a single functional group and lipophilicity are nonlinear, then similar relationships must be considered with compounds containing more than one functional group. To check up this idea whole set of small clusters containing structure relative compounds with few functional groups was examined from position of linear and nonlinear relationships between toxicity and lipophilicity. It was estimated in most causes advantages of nonlinear models.