Biomedical subjects

A Dmitriev

Publications and source records attributed to A Dmitriev.

22 records · Page 2Linked to original sources

PubMedDate not supplied

Predicting biotransformation potential from molecular structure.

The program PASS-BioTransfo is presented, which is capable of predicting many classes of biotransformation for chemical compounds. A particular class of biotransformation is defined by the chemical transformation type and may additionally include the name of the enzyme involved in a transformation. An evaluation of the approach is presented, using biotransformations taken from the databases Metabolite (MDL) and Metabolism (Accelrys), respectively. When trained with biotransformations from Metabolite, PASS-BioTransfo predicts 1927 classes of biotransformation; the average accuracy estimated in LOO cross-validation is about 88%. After training with the biotransformations from the Metabolism database, 178 classes of biotransformation are predicted with an average accuracy of about 85%. The results of cross-prediction with several training and evaluation sets are presented and discussed.

Animals↗

PubMedDate not supplied

A new statistical approach to predicting aromatic hydroxylation sites. Comparison with model-based approaches.

A new approach is described that is able to predict the most probable metabolic sites on the basis of a statistical analysis of various metabolic transformations reported in the literature. The approach is applied to the prediction of aromatic hydroxylation sites for diverse sets of substrates. Training is performed using the aromatic hydroxylation reactions from the Metabolism database (Accelrys). Validation is carried out on heterogeneous sets of aromatic compounds reported in the Metabolite database (MDL). The average accuracy of prediction of experimentally observed hydroxylation sites estimated for 1552 substrates from Metabolite is 84.5%. The proposed approach is compared with two electronic models for P450 mediated aromatic hydroxylation: the oxenoid model using the atomic oxygen and the model using the methoxy radical as a model for the heme active oxygen species. For benzene derivatives, the proposed method is inferior to the oxenoid model and as accurate as the methoxy-radical model. For hetero- and polycyclic compounds, the oxenoid model is not applicable, and the statistical method is the most accurate. Broad applicability and high speed of calculations provide the basis for using the proposed statistical approach for high-throughput metabolism prediction in the early stages of drug discovery.

Journal Article↗

PubMedDate not supplied

[Factors and genetics of pathogenicity of group B Streptococci].

In this review data on the pathogenicity factors of streptococci and their genetic control are presented. Attention is paid mainly to protein antigens alpha and beta, C5a peptidase, CAMP factor, R, Rib and X proteins. The problems of making the genetic and physical charts of the genome of group B streptococci, the genetic regulation of the synthesis of pathogenicity factors and the specific features of the damaging action of the infective agent are discussed.

Animals↗

PubMedDate not supplied

Systemic acquired resistance in sunflower (Helianthus annuus L.).

Systemic acquired resistance (SAR) to infection by Botrytis cinerea in the leaves of sunflower (Helianthus annuus L.) plants was induced following cotyledon inoculation with B. cinerea or treatment with abiotic inducers. Salicylic acid (SA), benzo-(1,2,3)-thiadiazole-7-carbothioic S-methyl ester (BTH), 2,6-dichloroisonicotinic acid (INA) or EDTA protected sunflower plants against Botrytis infection, that was revealed by a reduction in the number and area of the necrotic lesions in upper leaves after challenge inoculation with the pathogen. SA and BTH were more potent inducers than INA, EDTA or pre-inoculation with the fungus. In addition to resistance to B. cinerea, the upper leaves have also developed resistance to maceration by a mixture of cell wall-degrading enzymes. Calcium nitrate inhibited both the protective effect and the resistance of leaf discs to cell-wall degrading enzymes. All the tested chemicals increased the synthesis and excretion of sunflower phytoalexins--coumarins scopoletin and ayapin and induced the PR-proteins chitinase and 1,3-beta-glucanase, being the inducer effect of each activator correlated with the level of protection against B. cinerea (BTH > SA > INA > EDTA). Thus, SAR induction is mediated by general increase of plant defence responses. This is the first report on SAR in sunflower.

Anti-Infective Agents↗