A5065866115- Computational Drug Discovery Methods
- Pharmacogenetics and Drug Metabolism
- Metabolomics and Mass Spectrometry Studies
- Analytical Chemistry and Chromatography
- Synthesis and biological activity
- Bioinformatics and Genomic Networks
- Protein Structure and Dynamics
- X-ray Diffraction in Crystallography
- Crystallization and Solubility Studies
- Cholinesterase and Neurodegenerative Diseases
- Microbial Natural Products and Biosynthesis
- Receptor Mechanisms and Signaling
- Machine Learning in Materials Science
- HIV Research and Treatment
- HIV/AIDS drug development and treatment
- Medicinal Plants and Bioactive Compounds
- vaccines and immunoinformatics approaches
- Pharmacological Effects of Natural Compounds
- Drug Transport and Resistance Mechanisms
- Inflammatory mediators and NSAID effects
- Machine Learning in Bioinformatics
- RNA and protein synthesis mechanisms
- Synthesis of heterocyclic compounds
- Free Radicals and Antioxidants
- Pharmacovigilance and Adverse Drug Reactions
Institute of Biomedical Chemistry
2016-2025
Pirogov Russian National Research Medical University
2016-2025
Bioinformatics Institute
2011-2024
Ministry of Health of the Russian Federation
2022
Lomonosov Moscow State University
2022
Russian Academy of Sciences
2007-2018
Academy of Medical Sciences
2012-2015
Medico
2014
Central Drug Research Institute
2008
Aristotle University of Thessaloniki
2004-2007
The concept of the biological activity spectrum was introduced to describe properties biologically active substances. PASS (prediction spectra for substances) software product, which predicts more than 300 pharmacological effects and biochemical mechanisms on basis structural formula a substance, may be efficiently used find new targets (mechanisms) some ligands and, conversely, reveal targets. We have developed WWW interface software. A server on-line prediction substances has been constructed.
The method for QSAR modelling of rat acute toxicity based on the combination QNA (Quantitative Neighbourhoods Atoms) descriptors, PASS (Prediction Activity Spectra Substances) predictions and self-consistent regression (SCR) is presented. predicted biological activity profiles are used as independent input variables with SCR. models were developed using LD50 values compounds tested rats four types administration (oral, intravenous, intraperitoneal, subcutaneous). proposed was evaluated set...
In silico methods of phenotypic screening are necessary to reduce the time and cost experimental in vivo anticancer agents through dozens millions natural synthetic chemical compounds. We used previously developed PASS (Prediction Activity Spectra for Substances) algorithm create validate classification SAR models predicting cytotoxicity chemicals against different types human cell lines using ChEMBL data. A training set from 59,882 structures compounds was created based on data (IG50, IC50,...
In vitro cell-line cytotoxicity is widely used in the experimental studies of potential antineoplastic agents and evaluation safety drug discovery. silico estimation against hundreds tumor cell lines dozens normal considerably reduces time costs development assessment new pharmaceutical agent perspectives. 2018, we developed first freely available web application (CLC-Pred) for qualitative prediction 278 27 based on structural formulas 59,882 compounds. Here, present a version this...
The computer system PASS provides simultaneous prediction of several hundreds biological activity types for any drug-like compound. is based on the analysis structure-activity relationships training set including more than 30000 known biologically active compounds. In this paper we investigate influence accuracy predicting with by (a) reduction number structures in and (b) activities set. compounds from MDDR database are used to create heterogeneous evaluation sets. We demonstrate that...
The application of the program PASS (Prediction Activity Spectra for Substances) to about 250 000 compounds NCI Open Database and incorporation over 64 million predictions in Enhanced Browser are described. A total 565 different types activity included, encompassing general pharmacological effects, specific mechanisms action, known toxicities, others. Application this Web-based service prediction activities kinds "Angiogenesis inhibitor," "Antiviral (HIV)", a set that can be associated with...
New anti-inflammatory agents possessing dual cyclooxygenase/lipoxygenase (COX/LOX) inhibition were discovered by computer-aided prediction of biological activity for 573 virtually designed chemical compounds. Prediction was performed PASS, and results analyzed with PharmaExpert software. Nine 2-(thiazole-2-ylamino)-5-phenylidene-4-thiazolidinone derivatives differing the phenyl group substitution selected synthesis experimental testing as potential COX/LOX inhibitors. Eight tested compounds...
An essential characteristic of chemical compounds is their biological activity since its presence can become the basis for use substance therapeutic purposes, or, on contrary, limit possibilities practical application due to manifestation side action and toxic effects. Computer assessment spectra makes it possible determine most promising directions study pharmacological particular substances, filter out potentially dangerous molecules at early stages research. For more than 25 years, we...
Experimentally found gene expression profiles are used to solve different problems in pharmaceutical studies, such as drug repositioning, resistance, toxicity and drug-drug interactions. A special web service, DIGEP-Pred, for prediction of drug-induced changes based on structural formulae chemicals has been developed. Structure-activity relationships were determined by Prediction Activity Spectra Substances (PASS) software. Comparative Toxicogenomics Database with data the known was create...
OpenTox provides an interoperable, standards-based Framework for the support of predictive toxicology data management, algorithms, modelling, validation and reporting. It is relevant to satisfying chemical safety assessment requirements REACH legislation as it supports access experimental data, (Quantitative) Structure-Activity Relationship models, toxicological information through integrating platform that adheres regulatory OECD principles. Initial research defined essential components...
Abstract Summary: A new freely available web server site of metabolism predictor to predict the sites (SOM) based on structural formula chemicals has been developed. It is analyses ‘structure-SOM’ relationships using a Bayesian approach and labelled multilevel neighbourhoods atoms descriptors represent structures over 1000 metabolized xenobiotics. The allows predicting SOMs that are catalysed by 1A2, 2C9, 2C19, 2D6 3A4 isoforms cytochrome P450 enzymes UDP-glucuronosyltransferase family....
Application of structure-activity relationships (SARs) for the prediction adverse effects drugs (ADEs) has been reported in many published studies. Training sets creation SAR models are usually based on drug label information which allows generation data hundreds drugs. Since ADEs may not be related to consumption, one main problems such studies is quality drug-ADE pairs obtained from labels. The included three sections labels: "Boxed warning," "Warnings and Precautions," "Adverse...
Severe adverse drug reactions (ADRs) are the fourth leading cause of fatality in U.S. with more than 100 000 deaths per year. As up to 30% all ADRs believed be caused by drug–drug interactions (DDIs), typically mediated cytochrome P450s, possibilities predict DDIs from existing knowledge important. We collected data public sources on 1485, 2628, 4371, and 27 966 possible four P450 isoforms 1A2, 2C9, 2D6, 3A4 for 55, 73, 94, 237 drugs, respectively. For each these sets, we developed validated...
Estimation of interactions between drug-like compounds and drug targets is very important for discovery toxicity assessment. Using data extracted from the 19th version ChEMBL database (https://www.ebi.ac.uk/chembl) as a training set Bayesian-like method realized in PASS software (http://www.way2drug.com/PASSOnline), we developed computational tool prediction protein compounds. After training, Targets became able to predict with 2507 different organisms based on analysis structure–activity...
Abstract In the existing quantitative structure–activity relationship (QSAR) methods any molecule is represented as a single point in many-dimensional space of molecular descriptors. We propose new QSAR approach based on Quantitative Neighbourhoods Atoms (QNA) descriptors, which characterize each atom and depend whole structure. 'Star Track' methodology set points two-dimensional QNA With our method estimate target property chemical compound calculated average value function descriptors...
Toxicity of chemical compound is a complex phenomenon that may be caused by its interaction with different targets in the organism. Two distinct types toxicity can broadly specified: first one strong compound's single target (e.g. AChE inhibition); while second moderate many various targets. Computer program PASS predicts about 2500 kinds biological activities based on structural formula compounds. Prediction robust analysis structure-activity relationships for 60,000 biologically active...
The evaluation of possible interactions between chemical compounds and antitarget proteins is an important task the research development process. Here, we describe validation QSAR models for prediction end-points, created on basis multilevel quantitative neighborhoods atom descriptors self-consistent regression. Data 4000 interacting with 18 (13 receptors, 2 enzymes, 3 transporters) were used to model 32 sets end-points (IC(50), K(i), K(act)). Each set was randomly divided into training test...