Biomedical subjects

V Blinova

Publications and source records attributed to V Blinova.

3 recordsLinked to original sources

PubMed2004

Asphalt volcanism and chemosynthetic life in the Campeche Knolls, Gulf of Mexico.

In the Campeche Knolls, in the southern Gulf of Mexico, lava-like flows of solidified asphalt cover more than 1 square kilometer of the rim of a dissected salt dome at a depth of 3000 meters below sea level. Chemosynthetic tubeworms and bivalves colonize the sea floor near the asphalt, which chilled and contracted after discharge. The site also includes oil seeps, gas hydrate deposits, locally anoxic sediments, and slabs of authigenic carbonate. Asphalt volcanism creates a habitat for chemosynthetic life that may be widespread at great depth in the Gulf of Mexico.

Animals↗

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↗