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Alexander V. Dmitriev
Researcher at Institute of Business & Medical Careers
Publications - 34
Citations - 680
Alexander V. Dmitriev is an academic researcher from Institute of Business & Medical Careers. The author has contributed to research in topics: Quantitative structure–activity relationship & Metabolite. The author has an hindex of 11, co-authored 32 publications receiving 504 citations. Previous affiliations of Alexander V. Dmitriev include Russian National Research Medical University & Russian Academy.
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Chemo- and bioinformatics resources for in silico drug discovery from medicinal plants beyond their traditional use: a critical review
Alexey Lagunin,Rajesh Kumar Goel,Dinesh Y. Gawande,Priynka Pahwa,Tatyana A. Gloriozova,Alexander V. Dmitriev,Sergey Ivanov,A. V. Rudik,Varvara I. Konova,Pavel V. Pogodin,D. S. Druzhilovsky,Vladimir Poroikov +11 more
TL;DR: This review contains a practical example of the application of combined chemo- and bioinformatics methods to study pleiotropic therapeutic effects of 50 medicinal plants from Traditional Indian Medicine.
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SOMP: web server for in silico prediction of sites of metabolism for drug-like compounds
TL;DR: A new freely available web server site of metabolism predictor to predict the sites of metabolism (SOM) based on the structural formula of chemicals has been developed using a Bayesian approach and labelled multilevel neighbourhoods of atoms descriptors to represent the structures of over 1000 metabolized xenobiotics.
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QSAR Modeling and Prediction of Drug-Drug Interactions.
Alexey V. Zakharov,Ekaterina V. Varlamova,Ekaterina V. Varlamova,Alexey Lagunin,Alexander V. Dmitriev,Eugene N. Muratov,Denis Fourches,Victor E. Kuz’min,Vladimir Poroikov,Alexander Tropsha,Marc C. Nicklaus +10 more
TL;DR: This work generated virtually all possible binary combinations of marketed drugs and employed QSAR models to identify drug pairs predicted to be instances of DDI, and 4500 of these predicted DDIs that were not found in the training sets were confirmed by data from the DrugBank database.
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Computer-aided prediction of biological activity spectra for organic compounds: the possibilities and limitations
Vladimir Poroikov,Dmitrii Filimonov,Tatyana A. Gloriozova,Alexey Lagunin,Dmitry S. Druzhilovskiy,A. V. Rudik,Leonid A. Stolbov,Alexander V. Dmitriev,Olga Tarasova,Sergey Ivanov,Pavel V. Pogodin +10 more
TL;DR: The current version of the PASS program for prediction of biological activity spectra of organic compounds based on analysis of structure—activity relationships (SAR) for a training set containing information on more than 1000 000 biologically active organic compounds is described.
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Metabolism site prediction based on xenobiotic structural formulas and PASS prediction algorithm.
TL;DR: A new ligand-based method for the prediction of sites of metabolism (SOMs) for xenobiotics has been developed on the basis of the LMNA (labeled multilevel neighborhoods of atom) descriptors and the PASS (prediction of activity spectra for substances) algorithm and applied to predict the SOMs of the 1A2, 2C9,2C19, 2D6, and 3A4 isoforms of cytochrome P450.