Laboratory of Structure-Function Based Drug Design

About Laboratory

The main directions of research and development laboratories:

– Structure-activity and structure-property relationship, prediction of biological
activity spectra, biotransformations and metabolism, toxicity of drug-like compounds
in biological systems.

– Structure and function of biological macromolecules, analysis of the molecular
mechanisms underlying the physiological and pathological processes in the organism.

– Evolution of regulatory signaling networks to search for promising pharmacological
targets and their combinations, and analysis of molecular mechanisms of
pharmacological and adverse effects in the organism.

– Methods and computer technologies for design & discovery of physiologically active
compounds with the desired properties: development and validation.

Teaching by Research:

– Permanent staff and Ph.D. students of Laboratory of Structure-Function Based Drug Design provide lectures and seminars in the framework of special courses “Introduction to Bioinformatics”, “Current Problems of Biomedical Chemistry” and “Bioinformatics and Computer-Aided Drug Discovery” for students from Medico-Biological Faculty, Russian State Medical University (MBF RSMU).
– Students from some Moscow’s universities (RSMU, MSU, MIPT, MEPhI) perform their practical and diploma works in the Laboratory. The best ones continue their post-graduate studies, to earn Ph.D. Degree in Bioinformatics or Biochemistry.

Diploma works and Ph.D. Theses prepared in the Laboratory in the past years

Phone: +7 (499) 246-09-20, +7 (499) 255-30-29

Web site: http://www.way2drug.com/

Staff



Students

  • Stolbov Leonid Alexeevich – Volunteer
  • Bikmayev Khaidar Kamalovich – Student
  • Sukhachev Vladislav Sergeevich – Student
  • Yazykova Ekaterina Igorevna – Student
  • Antipin Timur Vladislavoivich – Student

Projects

Current Projects:

  1. Analysis of the interactions between HIV and human organism considering prescribed HIV/AIDS therapy (RSCF grant No. 19-75-10097).
  2. Determination of the protein targets for small molecules based on the amino acid sequences and ligand structures (RFBR grant No. 19-015-00374)
  3. Analysis of the biological activity profiles of organic compounds taking into account their metabolism in the human body for the discovery and development of new drugs (RSCF grant No. 19-15-00396)
  4. Prediction of drug-drug interactions for a rational use of drugs (RSCF grant No. 17-75-20250).
  5. Exploration of Chemical-Biological Space via a Very Large Database of Synthesizable Compounds to Discover Novel Anti-HIV Agents (RFBR grant No. 17-54-30015-NIH_a)

The completed projects:

  1. Analysis of HIV resistance mechanisms to HIV reverse transcriptase and protease inhibitors using bio- and chemoinformatics approaches (RSCF grant No. 17-75-10187).
  2. Assessment of adverse effects of drug combinations on the cardiovascular and hepatobiliary systems using methods of bioinformatics (RSCF grant No. 17-75-10168).
  3. Network pharmacology for identification of phytomolecules from traditional Indian medicine for effective treatment of dementia (RFBR grant No. 16-54-45016)
  4. A Knowledge based approach to drug repurposing for socially important and rare diseases (RSCF grant No. 16-45-02012)
  5. Integral assessment of the molecular mechanisms of drug-induced hepatotoxicity using methods of bioinformatics (RFBR grant No. 16-34-01077)
  6. The role of single amino acid residues in the protein forming the functional specificity (RFBR grant No. 16-04-00491) P450 (RSCF grant No. 14-15-00449)
  7. Integrated estimation of xenobiotics toxicity taking into account their metabolism in a human by isoforms 3A4, 2C9, 2C19, 2D6, 1A2 of cytochrome
  8. Fighting with HIV-1 inhibitors resistance (RFBR grant № 16-34-60187)
  9. Computer-aided search for serine/threonine-protein kinase NEK6 inhibitors selective across the human kinome (RFBR grant No. 16-34-01243)
  10. Research of substrate specificity of cytochromes P450 taking part in synthesis of steroid hormones (RFBR grant No. 13-04-01668).
  11. Computer-aided design and biological testing of novel compounds towards prevention and cure of HIV/AIDS (RFBR grant No. 13-04-91455-NIH_a).
  12. The system for support of network for research of molecular structure – biological activities relationships using Internet (RFBR grant No. 12-07-00597-а).
  13. Сomputer design in the synthesis of new biologically active compounds (RFBR grant No. 13-04-9042513)
  14. Prediction of sites of metabolism using information about structural formulae of
    xenobiotics (RFBR grant No. 12-04-31670_mol_a).
  15. Development of the experimental-computational system for prediction of dynamics and revealing of key factors in pathogenesis of neoplastic disorders and their application for diagnostics and treatment (Ministry of Education and Science grant No. 14.512.11.0093).
  16. Development of computer program for prediction of effects caused by blockade of genes/proteins combinations in regulatory networks (Contract No. 1/2013, FSUE “RIPA”).
  17. Determination of posttranslational modifications in human proteins on the basis of
    local similarities of amino acid sequences (Ministry of Education and Science grant
    No. 8274).
  18. Computer-aided study of hidden potential in traditional Indian medicine and its pharmacological validation (RFBR grant No. 11-04-92713-IND_a).
  19. Virtual screening and biological testing of anti-HIV microbicides (RFBR/NIH grant No. 12-04-91445-NIH_А).
  20. Optimization of the methods for identification of gene clusters directing the biosynthesis of secondary metabolites in bacteria (IFTI grant No. RU.55229907.00160).
  21. Prediction of functional specificity of proteins on the basis of amino acid sequences and ligands’ structure (RFBR grant No. 09-04-01281-a).
  22. OpenTox – An Open Source Predictive Toxicology Framework (FP7 grant No. 200787)
  23. Building a Comprehensive Model of Mammalian Cell-Cycle Regulatory Network in Normal and Pathological States to Predict Potential Anticancer Agents for Key Target Molecules (in collaboration with DTIDT SB RAS, Novosibirsk; BioBase, Germany; Institute of Biomedical Technologies, Italy; INTAS grant № 03-55-5218).
  24. From Gene Regulatory Networks to Drug Prediction (Net2Drug) (in collaboration with several organizations from Germany, Russia, Finland, Sweden, Spain, Italy; grant ЕС FP6 № LSH-2005-1.2.5-4).
  25. In Silico Prediction of Biotransformation Enzymatic Profile and C-Hydroxylation Sites in the Human Organism for Drug-Like Compounds (supported by Korean Institute of Science and Technology – KIST; IFTI grant № DPG.55229907.00106).
  26. Method of Predicting Physicochemical Properties and Bioactivities for Chemical Compounds (in collaboration with the Shanghai Institute of Organic Chemistry (SIOC), RFBR grant 06-03-39015-GFEN_а).
  27. Computer-assisted discovery of new HIV-1 integrase inhibitors (in collaboration with National Cancer Institute, NIH, USA; grant ISTC/BTEP # 3197/111).
  28. In Silico Prediction of Metabolism Sites of Xenobiotics on Basis of Combination Quantum-Chemical and Statistical Algorithms (in collaboration with IGIC RAS, grant in the framework of RAS program “Biomolecular and Medical Chemistry”).
  29. License Agreement on Use of Computer Program PASS (Novo-Nordisk, Denmark).
  30. Agreement on Prediction of Biological Activity for the Customer’s Compounds (Teva, Israel).
  31. Studies of Possibilities of German-Russian Cooperation in the Fields of Bio- And Chemoinformatics (in collaboration with BioBase, Germany).
  32. In Silico Prediction of Drug-Like Compounds Biotransformation in the Human Organism (supported by Korean Institute of Science and Technology – KIST; IFTI grant № DPG.55229907.00190).
  33. Development and Updating of the Internet Resource for Prediction of Biological Activity Spectra for Chemical Compounds (RFBR grant № 05-07-90123).
  34. Determination of functional specificity of proteins in emerging pathogenic microorganisms on the basis of comparative analysis of amino acid sequences (RFBR grant № 04-04-49390а).
  35. Computer prediction ans selection of compounds prospective for creation of new drugs (in collaboration with UPI, RFBR grant № 05-03-08077 ofi-а).
  36. Computer-Aided Prediction of Drug-Drug Interactions (FASI grant № 02.442.11.7430).
  37. Development of Computer Programs for Estimation of Toxicity for Chemical Compounds (FASI grant № 02.434.11.1014).
  38. Structural Elements Responsible for Particular Functions in Enzyme Families (RFBR grant №01-04-48710).
  39. Hepatitis C: Creation of Specialized Portal on Molecular-Biological and Medico-Social Aspects of the Problem (RFHR grants № 04-06-12019 and № 02-06-12003b).
  40. Identification of Prospective Targets of Action for New Pharmaceuticals on the Basis of Gene Networks Reconstruction (in collaboration with ICG SB RAS, in the framework of FASI grant).
  41. Development of Web-Based System for Solution of Molecular Modelling Problems Using Distributed Computation Technologies (in collaboration with SRCC MSU, in the framework of FASI grant).
  42. Computer Search for Analogs of Biologically Active Compounds in Databases and Prediction of Their Biological Activity (agreement with Moscow Plant “DIOD”).
  43. Development of the Pilot Version of Computer Program BIOGENPHARM (agreement with BioSergen, Norway).
  44. Development of Computer Program MacroPASS (in collaboration with Norwegian University of Science and Technology, Norway Research Foundation grant №165190/V40 “Novel biologically active molecules through a combined application of bioinformatics and genetic engineering”).
  45. License Agreement on Use of Computer Programs PASS and PharmaExpert (Biosergen, Norway).
  46. Development of Computer Program BIOGENERATOR for Generation of Virtual Macrolides Libraries by in Silico Manipulations with Polyketide Structures (agreement with Sinvent AS, Norway).
  47. Delayed Neurotoxicity. Early Diagnostics and Computer-Aided Prediction (in collaboration with GOSNIIOCT, ISTC grant # 574).
  48. Computer-Assisted Combinatorial Design, Synthesis and Testing of New Cognition Enhancers, Anxiolytics and Anticonvulsants (in collaboration with several institutions from Greece, Belgium, France, Portugal, UK, Moldova, Russia; INTAS grant # 00-0711).
  49. License Agreement on Use of Computer Programs PASS (SanofiSynthelabo, France).
  50. Computer-Assisted Mechanism-of-Action Analysis of Large Databases Including 250,000 Chemical Compounds Registered by NCI (in collaboration with National Cancer Institute, NIH; CRDF grant # RC1-2064).

Main results

DEVELOPMENT OF BIO- AND CHEMOINFORMATICS METHODS AND THEIR APPLICATIONS

An original method of analysis of amino acid sequences based on local similarity has been developed, which has essential advantages in performance and flexibility in comparison with commonly used approaches based on the alignment of the primary structure of proteins. Computer programs for the analysis of amino acid sequences have been implemented that allow establishing the structure-function relationships and identifying functionally essential sites.

An innovative system of atom-centric molecular descriptors has been proposed, which allows characterizing intermolecular interactions and, on this basis, analyzing various structure-property relationships. These are MNA (Multilevel Neighborhoods of Atoms), QNA (Quantitative Neighborhoods of Atoms), LMNA (Labeled Multilevel Neighborhoods of Atoms), etc.

A novel method has been implemented for analyzing quantitative structure-activity relationships (QSAR) and predicting the activity of new substances; its advantages have been demonstrated in comparison with the number of other widely used QSAR methods.

A new fragment-based drug design method is proposed for the design of physiologically active substances with the required properties using molecular descriptors and algorithms developed in our laboratory. Using this approach, anti-inflammatory drugs with dual mechanisms of action (cyclooxygenase 1, 2 and lipoxygenase inhibitors) were designed, synthesized, and tested experimentally.

A novel method is proposed for in silico generating combinatorial libraries of macrolides with a simultaneous assessment of the properties of the generated molecules, to select the substances with desired properties, following the further design and preparation of the corresponding producer strains by genetic engineering methods.

A method for dichotomic modelling of processes in regulatory signaling networks has been developed to identify promising molecular targets, the inhibition of which leads to a blockage of the cell cycle or the switching of tumor cells into apoptosis. Its validation on the case study of breast cancer allowed identifying pharmacological targets and their combinations and, based on virtual screening of over 24 million chemical compounds from the ChemNavigator library, to reveal promising new inhibitors that exhibit synergism with the RITA substance, the well-known P53 protein reactivator suppressed in many types of tumors. The activity of the compounds found has been confirmed by in vivo in experiments on xenograft mice with transfected human tumors.

The possibilities of predicting resistance to antiretroviral drugs based on the analysis of amino acid and nucleotide sequences in order to optimize HIV/AIDS therapy have been investigated.

An approach is proposed to determine the mechanisms of adverse drugs effects at different levels of biological organization, based on the assessment of the profiles of the effects of drug substances on human proteins; analysis of drug-induced changes in gene expression with the search for genes whose expression change correlates with an adverse effect; examining the role of identified proteins and genes in known signaling pathways to establish those pathways for which exposure plays a key role in inducing a side effect. The developed approach was validated on the example of evaluating the mechanisms of side effects of drugs on the cardiovascular system and hepatobiliary system.

A method has been developed for the integrated in silico assessment of the toxicity of xenobiotics, taking into account their metabolism in the human body, allowing to evaluate the metabolic pathways of compounds in the human body and to evaluate their acute, specific (cardiotoxicity, hepatotoxicity, nephrotoxicity) and chronic (carcinogenicity, teratogenicity, mutagenicity, effect on reproductive system) toxicity.

Using our computer-aided drug design methods, new physiologically active compounds have been found with nootropic, anxiolytic, antidepressant, anticonvulsant, antidiabetic, antitumor, antimicrobial, antifungal, antiretroviral and several other types of biological activity.

A previously unknown nootropic effect is predicted in antihypertensive drugs – angiotensin-converting enzyme inhibitors (perindopril, quinapril, etc.), confirmed by the experiment and, subsequently, in the clinical trials.

Based on a computer-aided estimation, anti-inflammatory action of the antibacterial drug clarithromycin was predicted and confirmed by the experiment, due to which this drug can be used for the treatment of Inflammatory Bowel Disease.

Using our computational methods, new piperazine derivatives, TRPC6 (Transient Receptor Potential Canonical 6) channel agonists, have been discovered. They may be further developed as potential pharmacological substances for the treatment of Alzheimer’s disease.

An analysis of the hidden pharmacological potential of the phytocomponents from some preparations of traditional Indian Ayurveda medicine is carried out. New types of biological activity predicted for a number of natural substances have been experimentally confirmed.

A comparison of 283 million structures from the SAVI (Synthetically Accessible Virtual Inventory) library with 97 million structures of the PubChem database showed that only about 0.015% of SAVI is represented in PubChem, which demonstrates a significant novelty of this virtual library. Among them, 41 compounds with antiretroviral activity were identified, which highlights the opportunities for finding new anti-HIV compounds in the Big Data chemical space of the SAVI library.

Based on our computational methods, it was found that the metabolism of the original Russian drug phenazepam is carried out with the participation of CYP3A4; the in silico prediction is confirmed by in vitro and in vivo experiments.

It was predicted that the metabolism of the anticoagulant drug phenindione is carried out with the participation of cytochrome P450 1A2, rather than 2C9, as previously thought, which allowed us to explain the absence of cytochrome gene polymorphism CYP2C9 influence on the action of the drug in the clinic, rationalize the drug treatment of atrial fibrillation options and increase patient adherence therapy by reducing hemorrhagic complications.

DEVELOPMENT OF FREELY AVAILABLE WEB SERVICES

The first in the world freely accessible Internet resource PASS Online has been implemented, predicting over 4000 types of biological activity with an average accuracy of about 95%.

The Way2Drug informational-computational platform was created, where a number of other freely accessible web services are presented:

  • PASS Targets, prediction of interaction with molecular targets;
  • KinScreen, prediction of interaction of pharmacological substances with human kinome;
  • DIGEP-Pred, prediction of drug-induced gene expresion;
  • PASS CLC Pred, prediction of interaction with tumor and non-tumor cell lines;
  • AntiHIV-Pred, prediction of antiretroviral activity and effects associated with treatment of HIV-associated comorbidities;
  • AntiBac-Pred, prediction of antibacterial activity;
  • SOMP, prediction of metabolism sites for pharmacological agents;
  • SMP, prediction of substrate’s and metabolite’s specificity to the biotransformation enzymes;
  • RA, prediction of reacting atoms during the biotransformation;
  • MetaTox, prediction of toxicity taking into account the metabolism of drug;
  • Acute Rat Toxicity, prediction of acute rat toxicity for four administration routes;
  • Antitarget Prediction, prediction of interaction with the undesirable targets;
  • ROSC-Pred, prediction of organ-specific carcinogenicity;
  • ADVER-Pred, prediction of adverse drugs effects on cardiovascular and hepatobiliary systems;
  • DDI-Pred, prediction of drug-drug interactions.

Currently, our web services are used by over 23 thousand researchers, PhD and graduate students from 100 countries to select the most promising molecules for synthesis and determine the optimal assays to test their biological activity.

Publications


Articles
2020

  1. Stolbov L., Druzhilovskiy D., Rudik A., Filimonov D., Poroikov V., Nicklaus M. (2020). AntiHIV-Pred: Web-resource for in silico prediction of anti-HIV/AIDS activity. Bioinformatics. 36 (3), 978–979. DOI: 10.1093/bioinformatics/btz638.
  2. Mansouri K., Kleinstreuer N., Abdelaziz A.M., Alberga D., Alves V.M., Andersson P.L., Andrade C.H., Bai F., Balabin I., Ballabio D., Benfenati E., Bhhatarai B., Boyer S., Chen J., Consonni V., Farag S., Fourches D., García-Sosa A.T., Gramatica P., Grisoni F., Grulke C.M., Hong H., Horvath D., Hu X., Huang R., Jeliazkova N., Li J., Li X., Liu H., Manganelli S., Mangiatordi G.F., Maran U., Marcou G., Martin T., Muratov E., Nguyen D.-T., Nicolotti O., Nikolov N.G., Norinder U., Papa E., Petitjean M., Piir G., Pogodin P., Poroikov V., Qiao X., Richard A.M., Roncaglioni A., Ruiz P., Rupakheti C., Sakkiah S., Sangion A., Schramm K.-W., Selvaraj C., Shah I., Sild S., Sun L., Taboureau O., Tang Y., Tetko I.V., Todeschini R., Tong W., Trisciuzzi D., Tropsha A., Van Den Driessche G., Varnek A., Wang Z., Wedebye E.B., Williams A.J., Xie H., Zakharov A.V., Zheng Z., Judson R.S. (2020). CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity, Environmental Health Perspectives, 128 (2), 027002-1 – 027002-17. DOI: 10.1289/EHP5580.
  3. Stolbov L.A., Druzhilovskiy D.S., Filimonov D.A., Nicklaus M.C., Poroikov V.V. (2020), (Q)SAR models of HIV-1 proteins inhibition by drug-like compounds, Molecules, V. 25(1), P. 87, doi: 10.3390/molecules25010087.
  4. Savosina P., Karasev D., Veselovsky A., Miroshnichenko Yu., Sobolev B. (2020). Functional and structural features of proteins associated with alternative splicing, International Journal of Biological Macromolecules, V. 147, P. 513-520, doi:10.1016/j.ijbiomac.2019.09.241
  5. Karasev D., Sobolev B.,Lagunin A., Filimonov D., Poroikov V. (2020). Prediction of Protein-Ligand Interaction Based on the Positional Similarity Scores Derived from Amino Acid Sequences. International Journal of Molecular Sciences, v.21(1), p. 24. Doi: 10.3390/ijms 21010024.
  6. Masamrekh R.A., Kuzikov A.V., Haurychenka Y.I., Shcherbakov K.A., Veselovsky A.V., Filimonov D.A., Dmitriev A.V., Zavialova M.G., Gilep A.A., Shkel T.V., Strushkevich N.V., Usanov S.A., Archakov A.I., Shumyantsevaa V.V. (2020). In vitro interactions of abiraterone, erythromycin, and CYP3A4: implications for drug–drug interactions, Fundamental & Clinical Pharmacology, v. 34(1), p. 120-130, doi:10.1111/fcp.12497.
  7. Alexey A. Lagunin, Sergey M. Ivanov, Tatyana A. Gloriozova, Pavel V. Pogodin, Dmitry A. Filimonov, Sandeep Kumar & Rajesh K. Goel. (2020). Combined network pharmacology and virtual reverse pharmacology approaches for identification of potential targets to treat vascular dementia. SCIENTIFIC REPORTS, 10:257, doi:10.1038/s41598-019-57199-9.
  8. Olga Tarasova, Nadezhda Biziukova, Dmitry Kireev, Alexey Lagunin, Sergey Ivanov, Dmitry Filimonov, Vladimir Poroikov A Computational Approach for the Prediction of Treatment History and the Effectiveness or Failure of Antiretroviral Therapy, International Journal of Molecular Sciences, 2020, 21(), 748-0, doi:10.3390/ijms21030748.

2019

  1. Gomazkov O.A. (2019). Astrocytes as the elements of the regulation of higher brain functions. Neurokhimiya, 36 (4), 267–274. DOI: 10.1134/S1027813319030075
  2. Rudik A.V., Dmitriev A.V., Lagunin A.A., Ivanov S.M., Filimonov D.A, Poroikov V.V. (2019). Biochemistry (Moscow), Supplement Series B: Biomedical Chemistry, 13 (3), 228-236.
  3. Pogodin P.V., Lagunin A.A., Filimonov D.A., Nicklaus M.C., Poroikov V.V. (2019). Improving (Q)SAR predictions by examining bias in the selection of compounds for experimental testing. SAR and QSAR in Environmental Research, DOI: 10.1080/1062936X.2019.1665580
  4. Tarasova O.A., Biziukova N.Yu., Filimonov D.A., Poroikov V.V., Nicklaus M.C. (2019). Data mining approach for extraction of useful information about biologically active compounds from publications. Journal of Chemical Information and Modeling. DOI: 10.1021/acs.jcim.9b00164
  5. Rudik A.V., Dmitriev A.V., Lagunin A.A., Filimonov D.A., Poroikov V.V. (2019). PASS-based prediction of metabolites detection in biological systems. SAR and QSAR in Environmental Research, DOI: 10.1080/1062936X.2019.1665099.
  6. Stolbov L., Druzhilovskiy D., Rudik A., Filimonov D., Poroikov V., Nicklaus M. (2019). AntiHIV-Pred: Web-resource for in silico prediction of anti-HIV/AIDS activity. Bioinformatics. DOI: 10.1093/bioinformatics/btz638
  7. Dmitriev A.V., Filimonov D.A., Rudik A.V., Pogodin P.V., Karasev D.A., Lagunin A.A., Poroikov V.V. (2019) Drug-drug interaction prediction using PASS. SAR and QSAR in Environmental Research, 30 (9), 655–664. DOI: 10.1080/1062936X.2019.1653966.
  8. Lloyd K., Papoutsopoulou S., Smith E., Stegmaier P., Bergey F., Morris L., Kittner M., England H., Spiller D., White M.H.R., Duckworth C.A., Campbell B.J, Poroikov V., dos Santos V.M., Kel A., Müller W., Pritchard D.M., Probert C., Burkitt M., SysmedIBD Consortium. (2019). Identification of a novel therapeutic agent for Inflammatory Bowel Disease guided by systems medicine. bioRxiv. Posted January 07, 2019. DOI: https://doi.org/10.1101/513838
  9. Nadaraia N.S., Amiranashvili L.S., Merlani M., Kakhabrishvili M.L., Barbakadze N.N., Geronikaki A., Petrou A., Poroikov V., Ciric A., Glamoclija J., Sokovic M. (2019). Novel antimicrobial agents’ discovery among the steroid derivatives, Steroids, 144 (2019), 52-65. DOI:10.1016/j.steroids.2019.02.012
  10. Popugaeva E., Chernyuk D., Zhang H., Postnikova T.Y., Pats K., Fedorova E., Poroikov V., Zaitsev A.V., Bezprozvanny I. (2019). Derivatives of piperazines as potential therapeutic agents for Alzheimer’s disease. Molecular Pharmacology, 95 (4), 337-348. DOI: 10.1124/mol.118.114348
  11. Ivanov S., Lagunin A., Filimonov D., Poroikov V. (2019). Assessment of the cardiovascular adverse effects of drug-drug interactions through a combined analysis of spontaneous reports and predicted drug-target interactions. PLoS Comput. Biol., 15 (7), e1006851. doi: 10.1371/journal.pcbi.1006851.
  12. Rudik A., Bezhentsev V., Dmitriev A., Lagunin A., Filimonov D., Vladimir Poroikov (2019). Metatox – Web application for generation of metabolic pathways and toxicity estimation. Journal of Bioinformatics and Computational Biology, 17 (1), 1940001. DOI: 10.1142/S0219720019400018
  13. Kumar S., Ivanov S., Lagunin A., Goel R.K. (2019). Glycogen synthase kinase-3 inhibition as a potential pharmacological target for vascular dementia: In silico and in vivo evidence. Computers in Biology and Medicine, 108, 305–316. DOI: 10.1016/j.compbiomed.2019.03.002
  14. Kumar S., Ivanov S., Lagunin A., Goel R.K. (2019). Attenuation of hyperhomocysteinemia induced vascular dementia by sodium orthovanadate perhaps via PTP1B: Pertinent downstream outcomes. Behavioural Brain Research, 364, 29–40. DOI: 10.1016/j.bbr.2019.01.039
  15. Vera A.Vil, Alexander O.Terent’ev, Nick Savidov, Tatyana A. Gloriozova, Vladimir V. Poroikov, Tatyana A. Pounina, Valery M. Dembitsky. Hydroperoxy steroids and triterpenoids derived from plant and fungi: Origin, structures and biological activities. Journal of Steroid Biochemistry and Molecular Biology,190: 76-87. https://doi.org/10.1016/j.jsbmb.2019.03.020.
  16. Vera Vil, Tatyana A. Gloriozova, Vladimir V. Poroikov, Alexander O. Terent’ev, Nick Savidov, Valery M. Dembitsky. Naturally occurring of α,β-diepoxy-containing compounds: origin, structures, and biological activities. Applied Microbiology and Biotechnology, v.103, issue 8, p. 3249-3264. https://doi.org./10.1007/s00253-019-09711-4.
  17. Vera Vil, Alexander O.Terent’ev, Abed Al Aziz AL Quntar, Tatyana A. Gloriozova, Nick Savidov, Valery M. Dembitsky. (2019). Oxetane-containing metabolites: origin, structures and biological activities. Applied Microbiology and Biotechnology, v.103, Issue 6, p. 2449-2467. https://doi.org/10.1007/ s00253-018-09576-z.
  18. Vera A. Vil, Tatyana A. Gloriozova, Alexander O. Terent’ev, Nick Savidov, Valeru M. Dembitsky. (2019). Hydroperoxides derived from marine sources: origin and biological activities. Applied Microbiology and Biotechnology, volume103, issue 4, p. 1627-1642. https://doi.org/10.1007/s00253-018-9560-x.
  19. Vil V., Gloriozova T.A., Terent’ev A.O., Zhukova N.V., Dembitsky V.M. Highly oxygenated isoprenoid lipids derived from terrestrial and aquatic sources: Origin, structures and biological activities. Vietnam J. Chem., 2019, 57(1), 1-15. DOI: 10.1002/vjch.201960001
  20. Rudik A.V., Dmitriev A.V., Lagunin A.A., Ivanov S.M., Filimonov D.A., Poroikov V.V. (2019). Xenobiotic toxicity prediction combined with xenobiotic metabolism prediction in the human body. Biomeditsinskaya Khimiya, 65 (2), 14-122. DOI: 10.18097/ PBMC20196502114.
  21. Savosina P.I., Stolbov L.A., Druzhilovskiy D.S., Filimonov D.A., Nicklaus M.C., Poroikov V.V. (2019). Discovering new antiretroviral compounds in “Big data” chemical space of the SAVI library. Biomeditsinskaya Khimiya, 65 (2), 73-79. DOI: 10.18097/ PBMC20196502073.
  22. Lagunin A.A., Geronikaki A., Eleftheriou P., Pogodin P.V., Zakharov A.V. Rational Use of Heterogeneous Data in Quantitative Structure-Activity Relationship (QSAR) Modeling of Cyclooxygenase/Lipoxygenase Inhibitors. J. Chem. Inf. Model., 2019, 59 (2): 713-730. doi: 10.1021/acs.jcim.8b00617.
  23. Merlani M., Barbakadze V., Amiranashvili L., Gogilashvili L., Poroikov V., Petrou A., Geronikaki A., Ciric A., Glamoclija J., Sokovic M. New Caffeic Acid Derivatives as Antimicrobial Agents: Design, Synthesis, Evaluation and Docking. Curr Top Med Chem. 2019; 19(4): 292-304. doi: 10.2174/1568026619666190122152957.
  24. Dmitriev A.V., Lagunin A.A., Karasev D.A., Rudik A.V., Pogodin P.V., Filimonov D.A., Poroikov V.V. (2019). Prediction of Drug-Drug Interactions Related to Inhibition or Induction of Drug-Metabolizing Enzymes. Current Topics in Medicinal Chemistry, 19 (5) 319-336. DOI: 10.2174/1568026619666190123160406

2018

  1. Gaur A.S., Nagamani S., Tanneeru K., Druzhilovskiy D., Rudik A., Poroikov V., Sastry G.N. (2018). Molecular Property Diagnostic Suite for Diabetes Mellitus (MPDSDM): An Integrated Web Portal for Drug Discovery and Drug Repurposing. Journal of Biomedical Informatics, 85, 114-125. DOI: 10.1016/j.jbi.2018.08.003.
  2. Ivkin D.Yu., Luzhanin V.G., Karpov A.A., Minasyan S.M., Poleshchenko Ya.I., Mamedov A.E., Povydysh M.N., Poroikov V.V., Narkevich I.A. (2018). Embinin – promising cardiotonic medicine of natural origin. Development and Registration of Pharmaceuticals, No. 3, 58–62.
  3. Tarasova O., Poroikov V., Veselovsky A. (2018). Molecular docking studies of HIV-1 resistance to reverse transcriptase inhibitors: mini-review. Molecules, 23, 1233. DOI: 10.3390/molecules23051233.
  4. Vil V.A., Gloriozova T.A., Poroikov V.P., Terent’ev A.O., Savidov N., Dembitsky V.M. (2018). Peroxy steroids derived from plant and fungi and their biological activities. Applied Microbiology and Biotechnology. DOI: 10.1007/s00253-018-9211-2
  5. Zawacka-Pankau J., Grinkevich V.V., Burmakin M., Vema A., Ridderstrale K., Issaeva N., Andreotti V., Dickinson E.R., Hedstrom E., Spinnler C., Inga A., Larsson K.-G., Karlen A., Tarasova O., Poroikov V., Lavrenov S., Preobrazhenskaya M., Wilhelm M., Barran P.E., Okorokov A.L., Selivanova G. (2018). Novel allosteric mechanism of p53 activation by small molecules for targeted anticancer therapy. bioRxiv, 384248. DOI: https://doi.org/10.1101/384248
  6. Nakhod K.V., Rusanov A.L., Luzgina E.D., Druzhilovskiy D.S., Luzgina N.G., Lisitsa A.V. (2018). Quality control study of engineered skin tissue. Biomeditsinskaya Khimiya, 64 (1), 10-15. DOI:10.18097/PBMC2018
  7. Gloriozova T.A., Dembitsky V.M. (2018). The impact factor of the thiirane group in organic compounds on their predicted pharmacological activities: A brief review. International Journal of Chemical Studies, 6 (1), 832-839.
  8. Dembitsky V.M., Savidov N., Poroikov V.V., Gloriozova T.A., Imbs A.B. (2018). Naturally occurring aromatic steroids and their biological activities. Applied Microbiology and Biotechnology. 102(11), p. 4663-4674 DOI: 10.1007/s00253-018-8968-7
  9. Pogodin P.V., Lagunin A.A., Rudik A.V., Filimonov D.A., Druzhilovskiy D.S., Nicklaus M.C., Poroikov V.V. (2018). How to achieve better results using PASS-based virtual screening: case study for kinase inhibitors. Frontiers in Chemistry, 6, 133. DOI: 10.3389/fchem.2018.00133
  10. Dembitsky V.M., Gloriozova T.A., Imbs A.B, (2018). Ferrocene and Titanocene Steroid Conjugates: Structures and Biological Activities. Vietnam Journal of Chemistry, 2018, 56(2), 127-138. DOI: 10.1002/vjch.201800001
  11. Tarasova O, Poroikov V. (2018). HIV Resistance Prediction to Reverse Transcriptase Inhibitors: Focus on Open Data. (2018). Molecules. 19;23(4). pii: E956. doi: 10.3390/molecules23040956.
  12. Dmitry V. Ivashchenko, Anastasia V. Rudik, Andrey A. Poloznikov, Sergey V. Nikulin, Valery V. Smirnov, Alexander G. Tonevitsky, Eugeniy A. Bryun and Dmitriy A. Sychev. (2018). Which cytochrome P450 does metabolize phenazepam? Step by step in silico, in vitro and in vivo studies. Drug Metabolism and Personalized Therapy, 32 (2), 65–73. DOI: 10.1515/dmpt-2017-0036
  13. Filimonov D.A., Druzhilovskiy D.S., Lagunin A.A., Gloriozova T.A., Rudik A.V., Dmitriev A.V., Pogodin P.V., Poroikov V.V. (2018). Computer-aided prediction of biological activity spectra for chemical compounds: opportunities and limitations. Biomedical Chemistry: Research and Methods, 1 (1), e00004. DOI: 10.18097/bmcrm00004
  14. Gomazkov O.A. Astrocytes as Mediators of Integration Processes in the Brain. Biology Bulletin Reviews, 2019, Vol. 9, No. 2, pp. 157–165. DOI: 10.1134/S2079086419020051.
  15. Shumyantseva V.V., Bulko T.V., Sigolaeva L.V., Kuzikov A.V., Pogodin P.V., Archakov A.I., Molecular imprinting coupled with electrochemical analysis for plasma samples classification in acute myocardial infarction diagnostic, Biosensors & Bioelectronics, 2018, V.99, P.216-222
  16. Karasev D.А., Veselova D.A., Veselovsky A.V., Sobolev B.N., Zgoda V.G., Archakov A.I., Spatial features of proteins related to their phosphorylation and associated structural changes, Proteins: Structure, Function and Bioinformatics, 2018, V.86(1), P.13-20
  17. V. R. Khairullina, A. Ya. Gerchikov, A. A. Lagunin, F. S. Zarudii, Qsar modelling of thymidylate synthase inhibitors in a series of quinazoline derivatives, Pharmaceutical Chemistry Journal,2018, 51(10), 884-888
  18. Ivanov S.M., Lagunin A.A., Rudik A.V., Filimonov D.A., Poroikov V.V. (2018). ADVERPred – web service for prediction of adverse effects of drugs. Journal of Chemical Information and Modeling, 58 (1), 8-11. DOI: 10.1021/acs.jcim.7b00568
  19. Lagunin A., Rudik A., Filimonov D., Druzhilovsky D., Poroikov V. (2018). ROSC-Pred: web-service for rodent organ-specific carcinogenicity prediction. Bioinformatics, 34 (4), 710–712. DOI: 10.1093/bioinformatics/btx678
  20. Janardhan S, Konova V., Lagunin A., Rao B.V., Sastry G.N., Poroikov V. (2018). Recent Advances in the development of pharmaceutical agents for metabolic disorders: a computational perspective. Curr. Med. Chem. 25 (39), 5432-5463. DOI: 10.2174/0929867324666171002120647
  21. Bezhentsev V., Ivanov S., Kumar S., Goel R., Poroikov V. (2018). Identification of potential drug targets for treatment of refractory epilepsy using network pharmacology. Journal of Bioinformatics and Computational Biology, 16 (1), 1840002. DOI: 10.1142/S0219720018400024
  22. Lagunin A.A., Dubovskaja V.I., Rudik A.V., Pogodin P.V., Druzhilovskiy D.S., Gloriozova T.A., Filimonov D.A., Sastry G.N., Poroikov V.V. (2018). CLC-Pred: a freely available web-service for in silico prediction of human cell line cytotoxicity for drug-like compounds. PLOS One, 13 (1), e0191838. DOI: 10.1371/journal.pone.0191838
  23. Goel R.K., Gawande D.Y., Lagunin A.A., Poroikov V. (2018). Pharmacological repositioning of Achyranthes aspera as antidepressant using pharmacoinformatic tools PASS and PharmaExpert: A case study with wet lab validation. SAR and QSAR in Environmental Research, 29 (1), 69-81.

2017

  1. Khayrullina V.R., Gerchikov A.Y., Lagunin A.A., Zarudiy F.S. (2017).
    QSAR-modelling of thymidilate synthase inhibitors in the series of quinazoline derivatives. Pharmaceutical Chemistry Journal, 51 (10), 33-37 (Rus.).
  2. Dembitsky V.M., Gloriozova T.A., Poroikov V.V. (2017). Pharmacological Activities of Epithio Steroids Journal of Pharmaceutical Research International, 18 (4), 1-19. DOI: 0.9734/JPRI/2017/36199.
  3. Dembitsky V.M., Gloriozova T.A., Poroikov V.V. (2017). Biological Activities of Nitro Steroids. Journal of Pharmaceutical Research International, 18 (4), 1-19. DOI: 10.9734/JPRI/2017/36196.
  4. Dmitriev A., Rudik A., Filimonov D., Lagunin A., Pogodin P., Druzhilovsky D., Ivanov S., Tarasova O., Konova V., Bezhentsev V., Poroikov V. (2017). Integral estimation of xenobiotics’ toxicity with regard to their metabolism in human organism. Pure and Applied Chemistry, 89 (10), 1449-1458. DOI: https://doi.org/10.1515/pac-2016-1205.
  5. Gomazkov O.A., Lagunin A.A. (2017). Vascular dementia. Molecular targets of neuroprotective therapy. Biology Bulletin Reviews, 2015, 138 (3), 256-267.
  6. Stasevych M., Zvarych V., Lunin V., Deniz N.G., Gokmen Z., Akgun O., Ulukaya E., Poroikov V., Gloriozova T., Novikov V. (2017). Computer-aided prediction and experimental testing of the dithiocarbamate derivatives of 9,10-anthracenedione as anticancer agents. SAR & QSAR Environ. Res., 28(5), 355-366. DOI: 10.1080/1062936X.2017.1323796.
  7. Ivanov S., Semin M., Lagunin A., Filimonov D., Poroikov V. (2017). In silico identification of proteins associated with drug-induced liver injury based on the prediction of drug-target interactions. Mol. Inform., 36 (7), 1600142. DOI: 10.1002/minf.201600142
  8. Rudik A.V., Bezhentsev V.M., Dmitriev A.V., Druzhilovskiy D.S., Lagunin A.A., Filimonov D.A., Poroikov V.V. (2017). MetaTox: Web Application for Predicting Structure and Toxicity of Xenobiotics’ Metabolites. Journal of Chemical Information and Modeling, 57 (4), 638–642. DOI: 10.1021/acs.jcim.6b00662
  9. Tarasova O., Filimonov D., Poroikov V. (2017). PASS-based approach to predict HIV-1 reverse transcriptase resistance. J. Bioinform. Comput. Biol., 15 (2), 1650040-1 – 1650040-15. DOI: http://dx.doi.org/10.1142/S0219720016500402
  10. Bezhentsev V. M., Druzhilovskiy D. S., Ivanov S. M., Filimonov D. A., Sastry G. N., Poroikov V. V. (2017). Web resources for discovery and development of new medicines. Pharm.-Chem. J., 51 (2), 91-99. DOI: 10.1007/s11094-017-1563-x
  11. Gawande D.Y., Druzhilovsky D., Gupta R.C., Poroikov V., Goel R.K. (2017). Anticonvulsant activity and acute neurotoxic profile of Achyranthes aspera Linn. Journal of Ethnopharmacology, 202 (18) 97-102. DOI: 10.1016/j.jep.2017.03.018
  12. Dembitsky V.M., Gloriozova T.A., Poroikov V.V. (2017). Pharmacological and predicted activities of natural azo compounds. Nat. Prod. Bioprospect., 7, 151. DOI 10.1007/s13659-016-0117-3
  13. Gomazkov O.A., Correction of neurogenesis in the adult brain: Selection of Therapeutic Targets, Neurochemical Journal, 2017, 11(1), 1-9
  14. Vassiliev P.М., Kalitin K.Y., Spasov A.A., Grechko O.Y., Poroikov V.V., Filimonov D.А., Anisimova V.A. (2017). Prediction and study of anticonvulsant properties of some benzimidazole derivatives. Pharm. Chem. J., 50 (12), 3-8. (Rus).

2016

  1. Lagunin A.A., Druzhilovsky D.S., Rudik A.V., Filimonov D.A., Gawande D., Suresh K., Goel R., Poroikov V.V. (2016). Capacities of Computer Evaluation of Hidden Potential of Phytochemicals of Medicinal Plants of the Traditional Indian Ayurvedic Medicine, Biochemistry (Moscow) Supplement Series B: Biomedical Chemistry, 10(1), 43-54.
  2. Guasch L., Zakharov A.V., Tarasova O.A., Poroikov V.V., Liao C., Nicklaus M.C. (2016). Novel HIV-1 integrase inhibitor development by virtual screening based on QSAR models. Current Topics in Medicinal Chemistry, 2016, 16 (4), 441-448. DOI: 10.2174/1568026615666150813150433.
  3. Kel A.E., Stegmaier P., Valeev T., Koschmann J., Poroikov V., Kel-Margoulis O.V., Wingender E. Multi-omics “Upstream Analysis” of regulatory genomic regions helps identifying targets against methotrexate resistance of colon cancer. European Journal of Integrative Medicine, 2016. DOI: 10.1016/j.euprot.2016.09.002
  4. Tarasova O.A., Filimonov D.A., Poroikov V.V. Structure-activity relationships of HIV-1 reverse transcriptase inhibitors: how to increase the accuracy and predictability of models? HIV-infection and immunosuppression, 2016, 8 (3), 78-82 (Rus).
  5. Nikolin A.A., Kramarova E.P., Shipov A.G., Baukov Yu.I., Negrebetsky V.N., Arkhipov D.E., Korlyukov A.A., Lagunin A.A., Bylikin S.Yu., Bassindalee A.R., Taylore P.G. (2016) N,N-Bis-(dimethylfluorosilylmethyl)amides of N-organosulfonylproline and sarcosine: synthesis, structure, stereodynamic behaviour and in silico studies. RSC Adv., 2016, 6, 75315. DOI: 10.1039/c6ra14450k
  6. Sarapultsev A.P., Sarapultsev P.A., Sidorova L.P., Poroikov V.V., Chupakhin O.N. (2016). Substituted thiadiazines as potential anti-stress agents. Results of (Q)SAR prediction and experiments in vivo. The FASEB Journal, 30 (1), supplement 938.5.
  7. Gomazkov O.A. (2016). Neurogenesis as an Organizing Function of Adult Brain. Is There Enough Evidence? Biology Bulletin Reviews, 136 (3), 227-246.
  8. Bezhentsev V.M., Tarasova O.A., Dmitriev A.V., Rudik A.V., Lagunin A.A., Filimonov D.A., Poroikov V.V. Computer-aided prediction of xenobiotics metabolism in the human organism. Russ. Chem. Rev., 2016, 85 (8) 854-879. DOI: 10.1070/RCR4614
  9. Zakharov A.V., Varlamova E.V., Lagunin A.A., Dmitriev A.V., Muratov E.N., Fourches D., Kuz’min V.E., Poroikov V.V., Tropsha A., Nicklaus M.C. (2016). QSAR Modeling and Prediction of Drug-Drug Interactions. Molecular Pharmaceutics, 13 (2), 545-556. DOI 10.1021/acs.molpharmaceut.5b00762
  10. Levitsky D.O., Gloriozova T.A., Poroikov V.V., Dembitsky V.M. (2016). Naturally Occurring Isocyano/Isothiocyanato Compounds: Their Pharmacological and SAR Activities. Mathews Journal of Pharmaceutical Science, 1 (1), 003. http://www.mathewsopenaccess.com/PDF/pharmaceutical-science/M_J_Pharma_1_1_003.pdf
  11. Ivanov S.M., Lagunin A.A., Poroikov V.V. (2016). In silico assessment of adverse drug reactions and associated mechanisms. Drug Discovery Today, 21 (1), 58-71. DOI: 10.1016/j.drudis.2015.07.018.
  12. Druzhilovsky D.S., Rudik A.V., Filimonov D.A., Lagunin A.A., Gloriozova T.A., Poroikov V.V. (2016). Web-resources for prediction of biological activity of organic compounds. Russian Chemical Bulletin, No. 2, 384-393.
  13. Karasev D.A., Veselovsky A.V., Oparina N.Yu., Filimonov D.A., Sobolev B.N. (2016). Prediction of amino acid positions specific for functional groups in a protein family based on local sequence similarity. Journal of Molecular Recognition, 29 (4), 159-169. DOI: 10.1002/jmr.2515.
  14. Geronikaki A., Eleftheriou P., Poroikov V. (2016). Anti-HIV Agents: Current Status and Recent Trends. Topics in Medicinal Chemistry. 1-59. DOI: 10.1007/7355_2015_5001.

2015

  1. Gomazkov O.A. (2015). Epigenetic enzymes as therapeutic targets of brain diseases. Experimental and clinical pharmacology, 2015, 78 (11), 35-44 (Rus).
  2. Konova V., Lagunin A., Pogodin P., Kolotova E., Shtil A., Poroikov V. (2015). Virtual screening of chemical compounds active against breast cancer cell lines based on cell cycle modeling, prediction of cytotoxicity and interaction with targets. SAR and QSAR in Environmental Research, 26 (10), 595-604. DOI: 10.1080/1062936X.2015.1076516.
  3. Pogodin P.V., Lagunin A.A., Filimonov D.A., Poroikov V.V. (2015) PASS Targets: ligand-based multi-target computational system based on public data and naive Bayes approach. SAR and QSAR in Environmental Research, 26 (10), 783-793. DOI: 10.1080/1062936X.2015.1078407.
  4. Anusevicius K., Mickevicius V., Stasevych M., Zvarych V., Komarovska-Porokhnyavets O., Novikov V., Tarasova O., Gloriozova T., Poroikov V. (2015). Design, synthesis, in vitro antimicrobial activity evaluation and computational studies of new N-(4-iodophenyl)-β-alanine derivatives. Research on Chemical Intermediates. 41 (10), 7517-7540. DOI: 10.1007/s11164-014-1841-0
  5. Giniyatyllina G.V., Smirnova I.E., Kazakova O.B., Yavorskaya N.P., Golubeva I.S., Zhukova O.S., Pugacheva R.B., Apryshko G.N., Poroikov V.V. (2015). Synthesis and anticancer activity of aminopropoxytriterpenoids. Med. Chem. Res., 24 (9), 3423-3436. DOI: 10.1007/s00044-015-1392-y.
  6. Tarasova O.A., Urusova A.F., Filimonov D.A., Nicklaus M.C., Zakharov A.V., Poroikov V.V. (2015). QSAR Modeling Using Large-Scale Databases: Case Study for HIV-1 Reverse Transcriptase Inhibitors. Journal of Chemical Information and Modeling, 55 (7), 1388-1399, DOI: 10.1021/acs.jcim.5b00019
  7. Poroikov V. (2015). 20th EuroQSAR: Understanding Chemical-Biological Interactions. Molecular Informatics, 34 (6-7), 340. DOI: 10.1002/minf.201580631
  8. Ivanov S.M., Lagunin A.A., Pogodin P.V., Filimonov D.A., Poroikov V.V. (2015). Identification of drug targets related to the induction of ventricular tachyarrhythmia through systems chemical biology approach. Toxicological Sciences, 145 (2): 321-336. DOI: 10.1093/toxsci/kfv054
  9. Rudik A., Dmitriev A., Lagunin A., Filimonov D., Poroikov V. (2015). SOMP: web-service for in silico prediction of sites of metabolism for drug-like compounds. Bioinformatics, 31 (12), 2046-2048. DOI: 10.1093/bioinformatics/btv087.
  10. Goel R.K., Poroikov V., Gawande D., Lagunin A., Randhawa P., Mishra A. (2015). Revealing medicinal plants useful for comprehensive management of epilepsy and associated co-morbidities through in silico mining of their phytochemical diversity. Planta Medica, 81(6), 495-506. DOI: 10.1055/s-0035-1545884
  11. Lagunin A.A., Druzhilovsky D.S., Rudik A.V., Filimonov D.A., Gawande D., Suresh K., Goel R., Poroikov V.V. (2015). Computer evaluation of hidden potential of phytochemicals of medicinal plants of the traditional Indian Ayurvedic medicine. Biomedical Chemistry, 61 (2), 286-297.
  12. Dembitsky V.M., Gloriozova T.A., Poroikov V.V. (2015). Naturally occurring plant isoquinoline N-oxide alkaloids: Their pharmacological and SAR activities. Phytomedicine, 22 (1), 183-202. DOI: 10.1016/j.phymed.2014.11.002.
  13. Khayrullina V.R., Gerchikov A.Ya., Lagunin A.A.,, Zarudii F.S. (2015). Quantitative analysis of structure−activity relationships of tetrahydro-2-isoindole cyclooxygenase-2 Inhibitors. Biochemistry (Moscow), 80 (1), 74-86.
  14. Kolesanova E.F., Sobolev B.N., Moisa A.A., Egorova A.A., Archakov A.I. (2015). Way to the Hepatitis C peptide vaccine. Biomedical Chemistry, 61(2), 254-264.
  15. Gomazkov O.A. Signaling Molecules and Disturbances of Cognitive Function. Neurochemical Journal. 2015; 9(3):169–180.
  16. Gomazkov O.A. How Do Signaling Molecules Organize Higher Brain Function? Biology Bulletin Reviews. 2015; 5(4):281-295.
  17. Gomazkov OA. [Cortexin. Molecular mechanisms and targets of neuroprotective activity]. Zh Nevrol Psikhiatr Im S S Korsakova. 2015;115(8):99-104.

2014

  1. Zvarych V.I., Stasevych M.V., Stan’ko O.V., Komarovskaya-Porokhnyavets E.Z., Poroikov V.V., Rudik A.V., Lagunin A.A., M.V. Vovk, Novikov V.P. Computerized prediction, synthesis, and antimicrobial activity of new amino-acid derivatives of 2-chloro-n-(9,10-dioxo-9,10-dihydroanthracen-1-yl)acetamide. (2014). Pharmaceutical Chemistry Journal, 48 (9), 584-588.
  2. Gomazkov O.A. (2014). Transformation of neural stem cells and the reparative processes in the brain. Korsakov Journal of Neurology and Psychiatry, 114 (8), 4-12.
  3. Gomazkov O.A. (2014). How the signaling molecules organize the higher functions in the brain? Uspekhi sovremennoi biologii (Biology Bulletin Reviews), 30 (6), 333-355.
  4. Gomazkov O.A. (2014). Neurogenesis as an Adaptive Function of the Adult Brain. Biology Bulletin Reviews, 4 (2), 86–100.
  5. Tretyakova E.V., Smirnova I.E., Kazakova O.B., Tolstikov G.A., Yavorskaya N.P., Golubeva I.S., Pugacheva R.B., Apryshko G.N., Poroikov V.V. (2014). Synthesis and anticancer activity of quinopimaric and maleopimaric acids’ derivatives. Bioorganic and Medicinal Chemistry, 22 (22), 6481–6489.
  6. Zvarych V.I., Stasevych M.V., Stanko O.V., Komarovska-Porokhnyavets O.Z., Poroikov V.V., Rudik A.V., Lagunin A. A., Vovk I.V., Novikov V.P. Computer-aided prediction, synthesis and antimicrobial activity of new amino acid derivatives of 2-chloro-n-(9,10-dioxo-9,10-dihydroanthracen-1-yl)acetamide. Pharmaceutical-Chemistry Journal, 48 (9) 20-24.
  7. Lagunin A.A., Goel R.K., Gawande D.Y., Priynka P., Gloriozova T.A. Dmitriev A.V., Ivanov S.M., Rudik A.V., Konova V.I., Pogodin P.V., Druzhilovsky D.S., and Poroikov V.V. (2014). Chemo- and bioinformatics resources for in silico drug discovery from medicinal plants beyond their traditional use: a critical review. Natural Product Reports, 31 (11), 1585-1611.
  8. Fedorova E.V., Buryakina A.V., Zakharov A.V., Filimonov D.A., Lagunin A.A., Poroikov V.V. (2014). Design, synthesis and pharmacological evaluation of novel vanadium-containing complexes as antidiabetic agents.
    PLoS ONE, 9 (7): e100386.
  9. Fedyushkina I.V., Romero Reyes I.V., Lagunin A.A., Skvortsov V.S. (2014).
    Prediction of the Action of Ligands of Steroid Hormone Receptors.
    Biochemistry (Moscow) Supplement Series B: Biomedical Chemistry, 8 (1), 53–58.
  10. Ivanov S.M., Lagunin A.A., Pogodin P.V., Filimonov D.A., and Poroikov V.V.
    (2014). Identification of drug-induced myocardial infarction-related protein targets through the prediction of drug-target interactions and analysis of biological processes. Chemical Research in Toxicology. DOI:
    10.1021/tx500147d.
  11. Filimonov D.A., Lagunin A.A., Gloriozova T.A., Rudik A.V., Druzhilovskii D.S., Pogodin P.V., Poroikov V.V. (2014). Prediction of the biological activity spectra of organic compounds using the PASS online web resource.
    Chemistry of Heterocyclic Compounds, 50 (3), 444-457.
  12. Raevsky O.A., Solodova S.L., Lagunin A.A., Poroikov V.V. (2014). Computer modelling of blood-brain barrier permeability of physiologically active compounds. Biomedical Chemistry, 60 (2), 161-181 (Rus).
  13. Veselovsky A.V., Zharkova M.S., Poroikov V.V., Nicklaus M.C. (2014).
    Computer-aided design & discovery of protein-protein interaction inhibitors as agents for anti-HIV therapy. SAR and QSAR in Environmental Research, 25 (6), 457-471.
  14. Filimonov D.A., Lagunin A.A., Gloriozova T.A., Rudik A.V., Druzhilovsky D.S., Pogodin P.V., Poroikov V.V. (2014). Prediction of biological activity of organic compounds using web-resource PASS Online. Chemistry of Heterocyclic Compounds, No. 3, 483-499.
  15. Ivanov S.M., Lagunin A.A., Zakharov A.V., Filimonov D.A., Poroikov V.V. (2014). Computer search for molecular mechanisms of ulcerogenic action of non-steroidal anti-inflammatory drugs. Biomedical Chemistry, 60 (1), 7-17.
  16. Rudik A.V., Dmitriev A.V., Lagunin A.A., Filimonov D.A., Poroikov V.V. (2014). Metabolism sites prediction based on xenobiotics structural formulae and PASS prediction algorithm. Journal of Chemical Information and Modeling, 54 (2), 498–507.
  17. Singh D., Gawande D., Singh T., Poroikov V., Goel R.K. (2014). Revealing pharmacodynamics of medicinal plants using in silico approach: A case study with wet lab validation. Computers in Biology and Medicine, 47 (1), 1-6.
  18. Sobolev B.N., Veselovsky A.V., Poroikov V.V. (2014). Prediction of posttranslational modifications in proteins: trends and methods, Russ.
    Chem. Rev., 83 (2), 143–154.

2013

  1. Otdelenov V.A., Smirnov V.V., Dmitriev A.V., Poroikov V.V., Shumyantseva V.V., Krasnykh L.M., Sychev D.A., Kukes V.G. (2013). The influence of ethylmethylhydroxypyridne malate on CYP3A4 activity: complex approach to assessment of the new drug effect on biotransformation. Medicinal Drugs and Rational Pharmacotherapy, No. 2, 30-36.
  2. Danilov-Danil’ian V.I., Poroikov V.V., Chiganova M.A., Kozlov M.N., Filimonov D.A., Barenboim G.M. (2013). Estimation of biological hazard of organic xenobiotics in water supply sources. Water Supply and Sanitary Technique. No. 10, 17-25.
  3. Gomazkov O.A., Afanasiev V.V., Rumyantseva S.A., Stupin V.A., Silina E.V., Sokhova O.A. (2013). Current concepts on neurocytoprotective therapy. Neuroscience and Behavioral Physiology, 43 (3), 374-379.
  4. Gawande D.,Randhawa P., Lagunin A., Mishra A., Poroikov V., Goel R.K.
    (2013). In Silico Approach for Appropriate Selection of Medicinal Plant
    for Management of Epilepsy and Associated Depression and Memory Deficit.
    Indian Journal of Pharmacology, 45, Supplement 1, S98.
  5. Zvarych V., Stasevych М., Stanko О., Novikov V., Vovk М., Poroikov V., Solovyov O. (2013). Computer prediction and synthesis of new azoles based on N-benzoyl-N’-(9,10-dioxo-9,10-dihydroanthracen-1-yl)thioureas. Cheminė Technologija, Nr. 2 (64), 25-33.
  6. Pogodin P.V., Lagunin A.A., Ivanov S.M., Konova V.I., Filimonov D.A., Poroikov V.V. (2013). Computer prediction of low molecular organic compounds interaction with protein-targets. Bulletin of RSMU, No. 4, 69-74.
  7. Noskov D.S., Poroikov V.V., Shikh E.V., Yasnetsov V.V. (2013). Deanol Aceglumate (Nooklerin): clinical-pharmacological aspects and prospects for utilization in clinical practice. S.S. Korsakov Journal of Neurology and Psychiatry, 113 (11), 97-99.
  8. Lagunin A.A., Filimonov D.A., Gloriozova T.A., Tarasova O.A., Zakharov A.V., Guasch L., Nicklaus M.C., Poroikov V.V. (2013). Virtual screening for potential substances for the prophylaxis of HIV infection in libraries of commercially available organic compounds. Pharmaceutical Chemistry Journal, 47 (7), 343-360.
  9. Lagunin A.A., Filimonov D.A., Gloriozova T.A., Tarasova O.A., Zakharov A.V., Guasch-Pamies L., Nicklaus M.C., Poroikov V.V. (2013). Virtual screening for potential substances for the prophylaxis of HIV infection in libraries of commercially available organic compounds. Khimiko-Farmacevticheskiy Zhurnal, 47 (7), 3-21.
  10. Gomazkov O.A. (2013). Signaling Molecules as Regulators of Neurogenesis in the Adult Brain. Neurochemical Journal, 7 (4), 241-255.
  11. Gomazkov O.A. (2013). Signaling Molecules as Regulators of Neurogenesis in the Adult Brain. Neurochemistry, 30 (4), 1-16.
  12. Gomazkov O.A. (2013). Neurotrophic therapy and concept of “minipeptides”. Consilium Medicum, V.15/№2, Rational Pharmacotherapy, p.1-7.
  13. Raevsky O.A., Solodova S.L., Lagunin A.A., Poroikov V.V. (2013). Computer modeling of blood brain barrier permeability for physiologically active compounds. Biochemistry (Moscow) Supplement Series B: Biomedical Chemistry, 7 (2), 95–107.
  14. Gomazkov O.A. (2013). Neurogenesis as an adaptive function of brain. Uspekhi sovremennoi biologii (Biology Bulletin Reviews). 133 (4) 349-366.
  15. Lagunin A., Ivanov S., Rudik A., Filimonov D., Poroikov V. (2013). DIGEP-Pred: web-service for in-silico prediction of drug-induced expression profiles based on structural formula. Bioinformatics, 29 (16), 2062-2063.
  16. Romero Reyes I.V., Fedyushkina I.V., Skvortsov V.S., Filimonov D.A. (2013). Prediction of progesterone receptor inhibition by high-performance neural network algorithm. Internat. J. Math. Models and Methods Appl. Sci., 7(3) 303-310.
  17. Choudhary K.M., Mishra A., Poroikov V.V., Goel R.K. (2013). Ameliorative effect of Curcumin on seizure severity, depression like behavior, learning and memory deficit in post-pentylenetetrazole-kindled mice. Eur. J.
    Pharmacol., 704 (1-3), 33-40.
  18. Ivanov S.M., Lagunin A.A., Zakharov A.V., Filimonov D.A., Poroikov V.V. (2013). Computer search for molecular mechanisms of ulcerogenic action of non-steroidal anti-inflammatory drugs. Biochemistry (Moscow) Supplement Series B: Biomedical Chemistry, 7 (1), 40–45.
  19. Lagunin A.A., Gloriozova T.A., Dmitriev A.V., Volgina N.E., Poroikov V.V. (2013). Computer Evaluation of Drug Interactions with P-Glycoprotein. Bulletin of Experimental Biology and Medicine, 154 (4), 521-524.
  20. Zharkova M.S., Sobolev B.N., Oparina N.Yu., Veselovsky A.V., Archakov A.I. (2013) Prediction of amino acid residues participated in substrate recognition by cytochrome P450 subfamilies with broad substrate specificity. J. Mol. Recognit.; 26(2), 86-91.
  21. Korolev S.P., Kondrashina O.V., Druzhilovsky D.S., Starosotnikov A.M., Dutov M.D., Bastrakov M.A., Dalinger I.L., Filimonov D.A., Shevelev S.A., Poroikov V.V., Agapkina Yu.Yu., Gottokh M.B. (2013). Structural-functional analysis of 1,2,5-benzoxadiasoles and their n-oxides as HIV-1 integrase inhibitors. Acta Naturae, 5, No. 1 (16) 75-85.

2012

  1. Buchkevych I., Stasevych M., Chervetsova V., Musyanovych R., Novikov V., Poroikov V., Gloriozova T., Filimonov D., Zagoriy G., Ponomarenko M. (2012). Synthesis, computational and antimicrobial studies of new 1,4-naphthoquinone aminothiazole derivatives. Cheminė Technologija, Nr. 3 (61) 62-69.
  2. Zakharov A.V., Lagunin A.A., Filimonov D.A., Poroikov V.V. (2012). Quantitative prediction of antitarget interaction profiles for chemical compounds. Chemical Research in Toxicology, 25 (11) 2378-2385.
  3. Lagunin A.A., Gloriozova T.A., Dmitriev A.V., Volgina N.E., Poroikov V.V. (2012) Computational estimates of pharmacological substances interaction with P-glycoprotein. Bulletin of Experimental Biology and Medicine, 154(10), 520-524.
  4. Gomazkov O.A., Afanasiev V.V., Rumyantseva S.A., Stupin V.A., Silina E.V., Sokhova O.A. (2012). Modern concepts of neurocytoprotective therapy. S.S. Korsakov Journal of Neurology and Psychiatry, 111 (12), issue 2: Insult, 58-63.
  5. Gomazkov O.A. (2012). Neurotrophines: therapeutic potential and concept of “minipeptides”. Neurochemistry, therapeutical potential and concept of “minipeptides”. Neurochemistry, 29 (3), 1–11.
  6. Gomazkov O.A. (2012). Neurotrophines: therapeutic potential. Priroda, No. 5, 62-70.
  7. Gomazkov O.A. (2012). Neurotrophins: The Therapeutic Potential and Concept of Minipeptides. Neurochemical Journal, 6 (3), 163-172.
  8. Barenboim G., Chiganova M., Poroikov V. (2012). Water monitoring: Estimation of biological hazard of organic xenobiotics (methodological aspects). Water:
    Chemistry and Ecology, No. 1, p.3-12.
  9. Tcheremenskaia O., Benigni R., Nikolova I., Jeliazkova N., Escher S.E., Grimm H., Baier T., Poroikov V., Lagunin A., Rautenberg M., Hardy B.
    (2012). OpenTox Predictive Toxicology Framework: toxicological ontology and semantic media wiki-based OpenToxipedia. J. Biomed. Semantics, 3 (Suppl.1): S7.
  10. Vydrina N.D., Tretyakov A.Y., Sychev D.A., Poroikov V.V., Dmitriev A.V., Grishchenko S.P., Zakharchenko S.P., Shilenok V.N., Leukhin I.N., Dmitriev V.A., Kukes V.G. (2012). Computer prediction of interaction between phenindione and cytochromes P450 to improve anticoagulant treatment of atrial fibrillation patients. Quality Management in Healthcare and Social Development, 11 (1), 88-91.
  11. Kryzhanovskii S.A., Salimov R.M., Lagunin A.A., Filimonov D.A., Gloriozova T.A., Poroikov V.V. (2012). Nootropic action of some antihypertensive
    drugs: computer predicting and experimental testing. Pharmaceut. Chem. J.,
    45 (10), 605-611.
  12. Filz O.A., Lagunin A.A., Filimonov D.A., Poroikov V.V. (2012). In silico fragment-based drug design using PASS approach. SAR & QSAR Environ. Res.,
    23 (3-4), 279-296.
  13. Gomazkov O.A. (2012). Cellular and molecular principles of brain aging. Advances in Modern Biology, 132 (2), 141-154.
  14. Filz O.A., Poroikov V.V. (2012). Design of chemical compounds with desired properties using fragment libraries. Russian Chemical Reviews, 81 (2), 158–174.
  15. Eleftheriou P., Geronikaki A., Hadjipavlou-Litina D., Vicini P., Filz O., Filimonov D., Poroikov V., Chaudhaery S.S., Roy K.K., Saxena A. (2012).
    Fragment-based design, docking, synthesis, biological evaluation and structure–activity relationships of 2-benzo/benzisothiazolimino–5–aryliden–4-thiazolidinones as cycloxygenase/lipoxygenase inhibitors. Eur. J. Med. Chem., 47 (1), 111-124.

2011

  1. Kryzhanovsky S.A., Salimov R.M., Lagunin A.A., Filimonov D.A., Gloriozova T.A., Poroikov V.V. (2011). Nootropic action of some antihypertensive drugs: computational prediction and experimental testing. Pharm. Chem. J., 45 (10), 25-31.
  2. Otdelenov V.A., Dmitriev A.V., Sychev D.A., Poroikov V.V., Kukes V.G. (2011). Appointment of substrates of cytochrome P450 isozymes major cerebrovascular disease patients: implications for the assessment of inhibitory and inducing effects of new antioxidants. Bulletin of Ural Medical Academic Science, № 3 (37), 93-95.
  3. Kokurkina G.V., Dutov M.D., Shevelev S.A., Popkov S.V., Zakharov A.V., Poroikov V.V. (2011). Synthesis, antifungal activity and QSAR study of 2-arylhydroxynitroindoles. Eur. J. Med. Chem., 46 (9), 4374-4382.
  4. Lagunin A., Zakharov A., Filimonov D., Poroikov V. (2011). QSAR Modelling of Rat Acute Toxicity on the Basis of PASS Prediction. Molecular Informatics, 30 (2-3), 241–250.
  5. Prasad Y.R., Raja Sekhar K.K., Shankarananth V., Sireesha G., Swetha Harika K., Poroikov V. (2011). Synthesis and in silico biological activity evaluation of some 1,3,5-trisubstituted -2-pyrazolines. Journal of Pharmacy Research, 4 (2), 558-560.
  6. Goel R.K., Singh D., Lagunin A., Poroikov V. (2011). PASS-assisted exploration of new therapeutic potential of natural products. Med. Chem.
    Res., 20 (9), 1509-1514.

2010

  1. Hardy B., Douglas N., Helma C., Rautenberg M., Jeliazkova N., Jeliazkov V., Nikolova I., Benigni R., Tcheremenskaia O., Kramer S., Girschick T., Buchwald F., Wicker J., Karwath A., Gutlein M., Maunz A., Sarimveis H., Melagraki G., Afantitis A., Sopasakis P., Gallagher D., Poroikov V., Filimonov D., Zakharov A., Lagunin A., Gloriozova T., Novikov S., Skvortsova N., Druzhilovsky D., Chawla S., Ghosh I., Ray S., Patel H., Escher S. Collaborative development of predictive toxicology applications. Journal of Cheminformatics, 2010, 2: 7.
  2. Poroikov V. (2010). Computer-assisted prediction and design of multitargeted drugs. Med. Chem. Res., 19 (S1), s30.
  3. Druzhilovsky D.S., Filimonov D.A., Liao C., Peach M., Marc Nicklaus, Poroikov V.V. (2010). Computer-assisted search and optimization of new human immunodeficiency virus integrase inhibitors. Biochemistry (Moscow) Supplemental Series B. Biomedical Chemistry, 4 (1), 59-67.
  4. Sobolev B.N., Filimonov D.A., Lagunin A.A., Zakharov A.V., Koborova O.N, Kel A., Poroikov V.V. (2010). Prediction of protein-protein interactions using the scores of sequence local similarity: application to prediction of protein kinase substrates, BMC Bioinformatics, 11: 313.
  5. Veselovsky A.V., Sobolev B.N., Zharkova M.S., Archakov A.I. (2010). Computer-based substrate specificity predicton for cytochromes P450. Biomedical chemistry (Rus.), 56 (1), 90-100.
  6. Lagunin A., Filimonov D.A., Poroikov V.V. (2010). Multi-targeted natural products evaluation based on biological activity prediction with PASS. Cur. Phar. Des., 16 (15), 1703-1717.

2009

  1. Filimonov D.A., Zakharov A.V., Lagunin A.A., Poroikov V.V. (2009). QNA based “Star Track” QSAR approach. SAR and QSAR Environ. Res., 20 (7-8), 679-709.
  2. Koborova O.N., Filimonov D.A., Zakharov A.V., Lagunin A.A., Ivanov S.M., Kel A., Poroikov V.V. (2009). In silico method for identification of promising anticancer drug targets. SAR and QSAR Environ. Res., 20 (7-8), 755-766.
  3. Druzhilovsky D.S., Filimonov D.A., Liao C., Peach M., Nicklaus M., Poroikov V.V. (2009). Computer-assisted search of new HIV integrase inhibitors. Biomedical Chemistry, 55 (5), 544-557.
  4. Lagunin A., Zakharov A., Filimonov D., Poroikov V.(2009). In silico assessment of acute toxicity in rodents. Toxicololgy Letters, 189 (S1), S254.
  5. Lagunin A., Filimonov D., Zakharov A., Xie W., Huang Y., Zhu F., Shen T., Yao J., Poroikov V. (2009). Computer-Aided Prediction of Rodent Carcinogenicity by PASS and CISOC-PSCT. QSAR and Combinatorial Science, 28 (8) 806-810.
  6. Fleisher M., Belyakov S., Jansone D., Poroikov V., Leite L., Lukevics E. (2009). Investigation of the structure and prediction of the biological activity of 1,3-bis(3-cyano-6,6-dimethyl- 2-oxo-5,6-dihydro-2H-pyran-4-yl)- 2-(4-methoxyphenyl)propane. Chemistry of Heterocyclic Compounds, 5 (503), 680-685.
  7. Koborova O.N., Filimonov D.A., Zakharov A.V., Lagunin A.A., Kel A., Kolpakov F., Sharipov R., Kondrachin Y., Poroikov V.V. (2009). Modelling of regulatory networks in identification of promising drug targets for breast cancer therapy. The Herald of Vavilov Society for Genecitists and Breeding Scientists, 13 (1) 201-207.
  8. Poroikov V.V., Filimonov D.A., Gloriozova T.A., Lagunin A.A., Druzhilovsky D.S., Stepanchikova A.V. (2009). Computer-aided prediction of biological activity spectra for substances: virtual chemogenomics. The Herald of Vavilov Society for Genecitists and Breeding Scientists, 13 (1) 137-143.
  9. Alexandrov K., Sobolev B., Filimonov D., Poroikov V. (2009). Functional annotation of the amino acid sequences using local similarity. The Herald of Vavilov Society for Genecitists and Breeding Scientists, 13 (1) 114-121.
  10. Geronikaki A., Vicini P., Dabarakis N., Lagunin A., Poroikov V., Dearden J., Modarresi H., Hewitt M., Theophilidis G. (2009). Evaluation of the local anaesthetic activity of 3-aminobenzo[d]isothiazole derivatives using the rat sciatic nerve model. Eur. J. Med. Chem., 44 (2) 473-481.
  11. Britiv A.N., Gomazkov O.A. (2009). Biochemical, structural and clinical analysis of pleiotropic effects of statins. Cardiovascular Therapy and Prophylaxis, 8 (5), 92–102.
  12. Kuzmina T.I., Olenina L.V., Sanzhakov M.A., Farafonova T.E., Abramikhina T.V., Dubuisson Zh., Sobolev B.N., Kolesanova E.F. (2009). Antigenicity and epithopic mapping of the envelop protein E2 of Hepatitis C virus. Biomedical Chemistry, 55 (1), 32-40.
  13. Rufanova V., Pozdnеv V., Gomazkov O., Medvedev O., Medvedeva N. (2009). Endothelin-Converting Enzyme Inhibition in Rat Model of Acute Heart Failure: Heart Function and Neurohormonal Activation. Exp. Biol. Med., 234, 1201-1211.

2008

  1. Filimonov D.A., Poroikov V.V. (2008). Probabilistic approach in activity prediction. In: Chemoinformatics Approaches to Virtual Screening. Eds. Alexandre Varnek and Alexander Tropsha. Cambridge (UK): RSC Publishing, p.182-216.
  2. Apryshko G.N., Filimonov D.A., Poroikov V.V. (2008). Preexperimental screening of new antitumor substances by PASS approach based on the N.N. Blokhin RCRC RAMS database on antitumor substances. Journal of N. N. Blokhin Russian Cancer Research Center RAMS, 19 (4), 4-8.
  3. Apryshko G.N., Filimonov D.A., Poroikov V.V. (2008). Prediction of biological activity of chemical compounds from the N.N. Blokhin RCRC RAMS database on antitumor substances using PASS system. Journal of N. N. Blokhin Russian Cancer Research Center RAMS, 19 (3), 11-15.
  4. Gomazkov O.A., Lagunin A.A., Poroikov V.V. (2008). Computer-aided prediction of combined action of medicines used in therapy of arterial hypertension. Cardiovascular Therapy and Prophylaxis, 7 (5), 100-104.
  5. Koborova O.N., Filimonov D.A., Zakharov A.V., Lagunin A.A., Kel A., Kolpakov F., Kondrakhin Yu., Sharipov R., Poroikov V. (2008). Finding of anticancer targets using bioinformatics technologies. Rus. Biotherapeut. J., 7 (2), 54-56.
  6. Alexandrov K., Sobolev B., Filimonov D., Poroikov V. (2008). Recognition of protein function using the local similarity. J. Bioinform. Computat. Biol., 6 (4), 709-725.
  7. Fjodorova N., Novich M., Vrachko M., Smirnov V., Kharchevnikova N., Zholdakova Z., Novikov S., Skvortsova N., Filimonov D., Poroikov V., Benfenati E. (2008). Directions in QSAR Modeling for Regulatory Uses in OECD Member Countries, EU and in Russia. J. Env.. Sci. Health, Part C, 26, 201–236.
  8. Zakharov A., Lagunin A., Filimonov D., Poroikov V. (2008). Computer-Aided Prediction of potential antineoplastic agents. Chemistry Central Journal, 2 (Suppl.1), 18.
  9. Sergeiko A.P., Poroikov V.V., Hanus L.O., Dembitsky V.M. (2008). Cyclobutane-Containing Alkaloids: Origin, Synthesis, and Biological Activities. The Open Medicinal Chemistry Journal, 2008, 2, 26-37.
  10. Geronikaki A., Druzhilovsky D., Zakharov A., Poroikov V. (2008). Computer-aided predictions for medicinal chemistry via Internet. SAR and QSAR in Environ. Res., 19 (1 & 2), 27-38.
  11. Geronikaki A.A., Lagunin A.A., Hadjipavlou-Litina D.I., Elefteriou P.T., Filimonov D.A., Poroikov V.V., Alam I., Saxena A.K. (2008). Computer-aided discovery of anti-inflammatory thiazolidinones with dual cyclooxygenase/lipoxygenase inhibition. J. Med. Chem., 51 (6), 1601-1609.
  12. Filz O., Lagunin A., Filimonov D., Poroikov V. (2008). Computer-aided prediction of QT-prolongation. SAR and QSAR in Environ. Res., 19 (1 & 2), 81-90.

2007

  1. Sergeiko A.P., Stepanchikova A.V., Sobolev B.N., Zotchev S.B., Filimonov D.A., Lagunin A.A., Poroikov V.V. (2007). Computer-aided design of polyketides with the required properties. Biomedical Chemistry, 53 (5), 522-531.
  2. Devillers J., Dore J.C., Guyot M., Poroikov V., Gloriozova T., Lagunin A., Filimonov D. (2007). Prediction of biological activity profiles of cyanobacterial secondary metabolites. SAR and QSAR in Environ. Res., 18 (7-8), 629-643.
  3. D’yachkov P.N., Kharchevnikova N.V., Dmitriev A.V., Kuznetsov A.V., Poroikov V.V. (2007). Quantum chemical simulation of cytochrome p450 catalyzed aromatic oxidation: Metabolism, toxicity, and biodegradation of benzene derivatives. International Journal of Quantum Chemistry, 107 (13), 2454-2478.
  4. Zakharov A.V., Lagunin A.A., Filimonov D.A., Poroikov V.V. (2007). Quantitative Structure-Activity Relationships of Cyclin-Dependent Kinase I Inhibitors. Biochemistry (Moscow), Supplement, Series B, Biomedical Chemistry, 1 (1), 17-28.
  5. Dembitsky V.M., Gloriozova T.A., Poroikov V.V. (2007). Natural Peroxy Anticancer Agents. Mini-Reviews in Medicinal Chemistry, 7, 571-589.
  6. Kolpakov F., Poroikov V., Sharipov R., Kondrakhin Y., Zakharov A., Lagunin A., Milanesi L. and Kel A. (2007). Cyclonet – an integrated database on cell cycle regulation and carcinogenesis. Nucleic Acid Research, 35, Database Issue, D550-D556.
  7. Lagunin A.A., Zakharov A.V., Filimonov D.A., Poroikov V.V. (2007). New approach for QSAR modeling of the acute toxicity. SAR & QSAR in Environmental Research, 18 (3-4), 285-298.
  8. Poroikov V., Filimonov D., Lagunin A., Gloriozova T., Zakharov A. (2007). PASS: Identification of probable targets and mechanisms of toxicity. SAR & QSAR in Environmental Research., 18 (1-2, Part I), 101-110.
  9. BIOGENPHARM program package, © Zotchev A.B., Sobolev B.N., Stepanchikova A.V., Sergeiko A.P., Filimonov D.A., Lagunin A.A., Gloriozova T.A., Poroikov V.V. Russian State Patent Agency, N 2006614395 of 15.02.2007.
  10. BIOGENERATOR program package, © Zotchev A.B., Sobolev B.N., Stepanchikova A.V., Sergeiko A.P., Poroikov V.V. Russian State Patent Agency, N 2006614396 of 15.02.2007.

2006

  1. Dembitsky V.M., Levitsky D.O., Gloriozova T.A., Poroikov V.V. (2006). Acetylenic aquatic anticancer agents and related compounds. Natural Product Communications, 1 (89), 773-812.
  2. Zotchev S.B., Stepanchikova A.V., Sergeyko A.P., Sobolev B.N., Filimonov D.A., Poroikov V.V. (2006). Rational Design of Macrolides by Virtual Screening of Combinatorial Libraries Generated through in Silico Manipulation of Polyketide Synthases. J. Med. Chem., 49 (6), 2077-2087.
  3. Devillers J., Dore J.C., Marchand-Geneste N., Porcher J.M., Poroikov V. (2006). Modelling the endocrine disruption profile of xenobiotics. Lecture Series on Computer and Computational Sciences, 6, 1-3.
  4. Geronikaki A., Vasilevsky S., Hadjipablou-Litina D., Lagunin A., Poroikov V. (2006). Synthesis and antiinflammator activity of ethylylthiazoles. Chemistry of Heterocyclic Compoiunds, № 5, 769-774.
  5. Filimonov D.A., Poroikov V.V. (2006). Prediction of biological activity spectra for organic compounds. Russian Chemical Journal, 50 (2), 66-75.
  6. Zakharov A.V., Lagunin A.A., Filimonov D.A., Poroikov V.V. (2006). Quantitative analysis of structure-activity relationships for cycline-dependent kinase 1 inhibitors. Biomedical Chemistry (Rus.), 52 (1), 3-18.
  7. Fomenko A.E., Filimonov D.A., Sobolev B.N., Poroikov V.V. (2006). New approach to predict enzyme function without the alighnment. OMICS: A Journal of Integrative Biology, 10 (1), 56-65.
  8. Poroikov V.V., Filimonov D.A., Gloriozova T.A., Lagunin A.A. (2006). Computer prediction of biological activity spectra for nitrogen-containing organic compounds. In.: Nitrogen-Containing Heterocycles, Moscow: ICSPF, p.92-97.
  9. Ivanov A.S., Poroikov V.V., Archakov A.I. (2006). Bioinformatics education in the Institute of Biomedical Chemistry RAMS: course «Bioinformatics – the way from gene to drug» and special course «Bioinformatics and computer-aided drug design». In: Proceedings of the Fifth International Conference on Bioinformatics of Genome Regulation and Structure. Eds. N. Kolchanov, R. Hofestadt, Novosibirsk, July 16-22, 2006, v.3, p.262-265.
  10. GUSAR (General Unrestricted Structure-Activity Relationships) program package, © Zakharov A.V., Filimonov D.A., Lagunin A.A., Poroikov V.V., Russian State Patent Agency, N 2006613591 of 16.10.2006.
  11. PharmaExpert program package, © Lagunin A.A., Poroikov V.V., Filimonov D.A., Gloziozova T.A. Russian State Patent Agency, N 2006613590 of 16.10.2006.
  12. PreTox program package, © Filimonov D.A., Poroikov V.V., Gloziozova T.A., Lagunin A.A. Russian State Patent Agency, N 2006613276 of 15.09.2006.
  13. PASS program package, © Filimonov D.A., Poroikov V.V., Gloziozova T.A., Lagunin A.A. Russian State Patent Agency, N 2006613275 of 15.09.2006.

2005

  1. Varfolomeev S., Efremenko E., Beletskaya I., Bertini I., Blackburn G., Bogdanov A., Cunin R., Eichler J., Galaev I., Gladyshev V., O’Hagan D., Haertle T., Jarv J., Karyakin A., Kurochkin I., Mikolajczyk M., Poroikov V., Sakharov I., Spener F., Voyer N., Wild J. (2005). Postgenomic chemistry (IUPAC Technical Report). Pure and Applied Chemistry, 77 (9), 1641-1654.
  2. Filimonov D.A., Poroikov V.V. (2005). Why relevant chemical information cannot be exchanged without disclosing structures. J. Comput.-Aided Mol. Design, 19 (9-10), 705 – 713.
  3. Lagunin A.A., Dearden J., Filimonov D.A., Poroikov V.V. (2005). Computer-aided rodent carcinogenicity prediction. Mutation Research, 586 (2), 138-146.
  4. Akimov D.V., Filimonov D.A., Prikazchikova T.T., Gottikh M.B., Poroikov V.V. (2005). Computer-aided finding of new HIV-1 integrase inhibitors. Biomedical Chemistry (Rus.), 51 (3), 335-340.
  5. Dembitsky V.M., Gloriozova T.A., Poroikov V.V. (2005). Novel antitumor agents: marine sponge alkaloids, their synthetic analogues and derivatives. Mini-Reviews in Medicinal Chemistry, 5 (3), 319-336.
  6. Sobolev B.N., Olenina L.V., Kuraeva T.E., Kolesanova E.F., Poroikov V.V., Archakov A.I. (2005). Computer design of vaccines: approaches, software tools and informational resources. Current Computer-Aided Drug Design, 1 (2), 207-222.
  7. Poroikov V., Filimonov D. (2005). PASS: Prediction of Biological Activity Spectra for Substances. In: Predictive Toxicology. Ed. by Christoph Helma. N.Y.: Taylor & Francis, 459-478.
  8. Poroikov V.V. (2005). State system for registration and biological testing of chemical compounds: reminiscences about the future. In: Medical Biophysics. Biological Testing of Chemical Compounds. Moscow: Medicine, p.546-549.
  9. Filimonov D.A., Lagunin A.A., Poroikov V.V. (2005). Prediction of activity spectra for substances using new local integrative descriptors. QSAR and Molecular Modelling in Rational Design of Bioactive Molecules. Eds. Esin Aki Sener, Ismail Yalcin, Ankara (Turkey), CADD & D Society, p.98-99.
  10. Kovaleva V.L., Geronikaki A., Krylov I.A., Shilova E.V., Goncharenko L.V., Poroikov V.V. (2005). New potent bronhodilators bearing 2-aminothiazole roup discovered on the basis of computer-aided prediction. QSAR and Molecular Modelling in Rational Design of Bioactive Molecules. Eds. Esin Aki Sener, Ismail Yalcin, Ankara (Turkey), CADD & D Society, p.108-110.
  11. Dmitriev A., Rudik A., Borodina Yu., Filimonov D., Poroikov V., Blinova V., Kharchevnikova N. (2005). A new statistical approach to predicting aromatic hydroxilation sites. Comparison with model-based approaches. QSAR and Molecular Modelling in Rational Design of Bioactive Molecules. Eds. Esin Aki Sener, Ismail Yalcin, Ankara (Turkey), CADD & D Society, p.207-208.
  12. Lagunin A., Dearden J., Filimonov D., Poroikov V. (2005). A new in silico approach for the mutagenicity prediction. QSAR and Molecular Modelling in Rational Design of Bioactive Molecules. Eds. Esin Aki Sener, Ismail Yalcin, Ankara (Turkey), CADD & D Society, p.209-210.
  13. Zakharov A., Lagunin A., Filimonov D., Poroikov V. (2005). Computer prediction of human carcinogenicity for chemical compounds according to the IARC classification. QSAR and Molecular Modelling in Rational Design of Bioactive Molecules. Eds. Esin Aki Sener, Ismail Yalcin, Ankara (Turkey), CADD & D Society, p.211-212.
  14. Poroikov V., Lagunin A., Filimonov D. (2005). PharmaExpert: diseases, targets and ligands – three in one. QSAR and Molecular Modelling in Rational Design of Bioactive Molecules. Eds. Esin Aki Sener, Ismail Yalcin, Ankara (Turkey), CADD & D Society, p.514-515.

2004

  1. Geronikaki A., Babaev E., Dearden J., Dehaen W., Filimonov D., Galaeva I., Krajneva V., Lagunin A., Macaev F., Molodavkin G., Poroikov V., Saloutin V., Stepanchikova A., Voronina T. (2004). Design of new anxiolytics: from computer prediction to synthesis and biological evaluation. Bioorg. Med. Chem., 12 (24), 6559-6568.
  2. Borodina Yu., Rudik A., Filimonov D., Kharchevnikova N., Dmitriev A., Blinova V., Poroikov V. (2004). A new statistical approach to predicting aromatic hydroxylation sites. Comparison with model-based approaches. J. Chem. Inform. Comput. Sci., 44 (6), 1998-2009.
  3. Stepanchikova A.V., Sobolev B.N., Olenina K.V., Nikolaeva L.I., Kolesanova E.F., Poroikov V.V. (2004). Hepatitis C: molecular-biological and medical-social aspects of the problem. Popular resource in the Internet. Biomedical Chemistry, 50 (Supplement 1), 153-157.
  4. Kovalev P.V., Drozdov-Tikhomirov L.N., Poroikov V.V., Alexandrov A.A. (2004). Role of the electrostatic interactions in pre-orientation of subunits in the formation of protein-protein complexes. J. Biomol. Structure & Dynamics, 22 (1), 111-118.
  5. Geronikaki A., Dearden J., Filimonov D., Galaeva I., Garibova T., Gloriozova T., Krajneva V., Lagunin A., Macaev F., Molodavkin G., Poroikov V., Pogrebnoi S., Shepeli F., Voronina T., Tsitlakidou M., Vlad L. (2004). Design of new cognition enhancers: from computer prediction to synthesis and biological evaluation. J. Med. Chem., 47 (11), 2870-2876.
  6. Levchenko M.A., Poroikov V.V., Kanehisa M. (2004). G-proteins coupled peptide receptors and their endogenous ligands in the human genome. Biomedical Chemistry (Rus), 50 (2), 149-158.
  7. Poroikov V.V., Filimonov D.A., Borodina Yu.V., Gloriozova T.A., Sitnikov V.B., Sadovnikov S.V., Sosnov A.V. (2004). Analysis of quantitative structure – delayed neurotoxicity relationships by self-consistent regression on the basis of PASS. Chem. & Pharm. J. (Rus), 38 (4) 17-19.
  8. Filimonov D.A., Akimov D.V., Poroikov V.V. (2004). Method of self-consistent regression in analysis of quantitative structure-property relationships of chemical compounds. Chem. & Pharm. J. (Rus), 38 (1) 21-24.
  9. METAPREDICT (Prediction of Biotransformations) program package, © Poroikov V.V., Filimonov D.A., Borodina Yu.V., Rudik A.V. Registration by Russian State Patent Agency, N 2004610666 of 12.03.2004.

Books, Reviews, Ph.D. Theses, Preprints:

  1. Gomazkov O.A. The brain – a miracle without mysticism and magic. Moscow: IKAR, 2019. – 168 P.
  2. Poroikov V., Druzhilovskiy D. Drug Repositioning: New Opportunities for Older Drugs. In: In Silico Drug Design, 1st Edition. Repurposing Techniques and Methodologies. Chapter 1. Editors: Kunal Roy. Elsevier, Academic Press, 2019, p. 3-17.
  3. Gomazkov O.A. Astrocytes – the Stars That Control the Brain. IKAR, MOSCOW, 2018, 108 P.
  4. Gomazkov O.A. Why the brain needs new nerve cells? Moscow: IKAR, 2016. – 140 pp. ISBN 9-785-7974-0545-0.
  5. Zakharov A., Lagunin A. (2014). Computational toxicology in drug discovery: opportunities and limitations. In: Application of Computational Techniques in Pharmacy and Medicine. Leonid Gorb, Victor Kuz’min and Eugene Muratov Eds.. Springer, 2014, p. 325-367.
  6. Filimonov D.A., Lagunin A.A., Gloriozova T.A., Gawande D., Goel R., Poroikov V.V.. Libraries of natural and synthetic compounds as sources of novel drug-candidates. In: Chemistry of Heterocyclic Compounds. Modern Trends. Moscow: ICSPF, 2014, vol. 1, p. 464-471 (Rus).
  7. Lagunin A., Ivanov S., Pogodin P., Rudik A., Gloriozova T., Gawande D., Goel R., Poroikov V. (2013)/ In silico estimation of interactions between the phytoconstituents of medicinal plants and human regulatory pathways. In: Proceedings of the 9th International Symposium on Integrative Bioinformatics 2013, Gatersleben, Germany, 2013, p.p. 160-161.
  8. Gomazkov O.A. Neurogenesis as an adaptive function of brain. Moscow: IKAR Publishers, 2013. – 136 p.
  9. Gomazkov O.A. (2011). Aging of the brain and neurotrophic therapy. IKAR, Moscow, 180 p.
  10. Barenboim G.M., Chiganova M.A., Poroikov V.V. (2010). Evaluation of biological hazard of organic xenobiotics in the monitoring of water bodies (methodological problems and some solutions). In.: Managing the development of large-scale systems (MLSD’2010): Proceedings of the Fourth International Conference (4-6 October 2010, Moscow, Russia). Volume II. – M.: The V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences , 2010. (ISBN 978-5-91450-069-3), pp. 298-309.
  11. Gomazkov O.A. Pleiotropic effects of neurotrophines. The principles of therapeutic action of cerebrolysine. Moscow.: KDM Ltd., 2010. – 136 p.
  12. Poroikov V.V., Filimonov D.A., Lagunin A.A., Gloriozova T.A. Computer-aided prediction of biological activity of natural compounds and their derivatives. In: Modern aspects of chemistry of heterocycles. V.G. Kartsev, Ed. Moscow: ICSPF, 2010, p.142-148.
  13. Filimonov D.A., Poroikov V.V. (2008). Probabilistic approach in activity prediction. In: Chemoinformatics Approaches to Virtual Screening. Eds. Alexandre Varnek and Alexander Tropsha. Cambridge (UK): RSC Publishing, p.182-216.
  14. Gomazkov O.A. (2006). Neurotrophic regulation and stem cells of the brain. Monograph, Moscow, 332 p. (Rus.).
  15. Ivanov A.S., Poroikov V.V., Archakov A.I. (2006). Bioinformatics education in the Institute of Biomedical Chemistry RAMS: course «Bioinformatics – the way from gene to drug» and special course «Bioinformatics and computer-aided drug design». In: Proceedings of the Fifth International Conference on Bioinformatics of Genome Regulation and Structure. Eds. N. Kolchanov, R. Hofest?dt, Novosibirsk, July 16-22, 2006, v.3, p.262-265.
  16. Poroikov V.V., Filimonov D.A., Gloriozova T.A., Lagunin A.A. (2006). Computer prediction of biological activity spectra for nitrogen-containing organic compounds. In.: Nitrogen-Containing Heterocycles, Moscow: ICSPF, p.92-97. (Rus.).
  17. Poroikov V.V., Filimonov D.A., Gloriozova T.A., Lagunin A.A. (2006). Computer Prediction of Biological Activity Spectra for Nitrogen-Containing Organic Compounds. In: Nitrogen-Containing Heterocycles, M.: ICSPF, p.109-120.
  18. Poroikov V.V. (2005). State system for registration and biological testing of chemical compounds: reminiscences about the future. In: Medical Biophysics. Biological Testing of Chemical Compounds. Moscow: Medicine, p.546-549. (In Russian).
  19. Filimonov D.A., Lagunin A.A., Poroikov V.V. (2005). Prediction of activity spectra for substances using new local integrative descriptors. QSAR and Molecular Modelling in Rational Design of Bioactive Molecules. Eds. Esin Aki Sener, Ismail Yalcin, Ankara (Turkey), CADD & D Society, p.98-99.
  20. Kovaleva V.L., Geronikaki A., Krylov I.A., Shilova E.V., Goncharenko L.V., Poroikov V.V. (2005). New potent bronhodilators bearing 2-aminothiazole roup discovered on the basis of computer-aided prediction. QSAR and Molecular Modelling in Rational Design of Bioactive Molecules. Eds. Esin Aki Sener, Ismail Yalcin, Ankara (Turkey), CADD & D Society, p.108-110.
  21. Dmitriev A., Rudik A., Borodina Yu., Filimonov D., Poroikov V., Blinova V., Kharchevnikova N. (2005). A new statistical approach to predicting aromatic hydroxilation sites. Comparison with model-based approaches. QSAR and Molecular Modelling in Rational Design of Bioactive Molecules. Eds. Esin Aki Sener, Ismail Yalcin, Ankara (Turkey), CADD & D Society, p.207-208.
  22. Lagunin A., Dearden J., Filimonov D., Poroikov V. (2005). A new in silico approach for the mutagenicity prediction. QSAR and Molecular Modelling in Rational Design of Bioactive Molecules. Eds. Esin Aki Sener, Ismail Yalcin, Ankara (Turkey), CADD & D Society, p.209-210.
  23. Zakharov A., Lagunin A., Filimonov D., Poroikov V. (2005). Computer prediction of human carcinogenicity for chemical compounds according to the IARC classification. QSAR and Molecular Modelling in Rational Design of Bioactive Molecules. Eds. Esin Aki Sener, Ismail Yalcin, Ankara (Turkey), CADD & D Society, p.211-212.
  24. Poroikov V., Lagunin A., Filimonov D. (2005). Pharmaexpert: diseases, targets and ligands – three in one. QSAR and Molecular Modelling in Rational Design of Bioactive Molecules. Eds. Esin Aki Sener, Ismail Yalcin, Ankara (Turkey), CADD & D Society, p.514-515.
  25. Poroikov V., Filimonov D. (2005). PASS: Prediction of Biological Activity Spectra for Substances. In: Predictive Toxicology. Ed. by Christoph Helma. Taylor & Francis, 459-478.
  26. Gomazkov O.A. (2005). Neurotrophic and growth factors of the brain: regulatory specificity and therapeutic potential. Usp Fiziol Nauk, 36 (2):22-40. (Rus.).
  27. Gomazkov O.A. (2005). Vascular growth factors in hypertensive state pathogenesis. Cardiovascular Therapy and Prevention Journal, 3 (1): 93-103. (Rus.).
  28. Gomazkov O.A. (2004). Neurotrophic factors of the brain. Reference- informational edition. Electronic version on CD. (Rus.)
  29. Poroikov V., Filimonov D., Lagunin A., Gloriozova T., Rudik A., Stepachikova A., Akimov D.V., ZakharovA., Dmitriev A. (2004). Computer estimation of biological activity spectra for chemical compounds, to minimize the risks of their application in medicine. In: “Problems in Estimation of Risks to the Health of Population Caused by the Environmental Factors”, Moscow, pp. 167-169.
  30. Borodina Yu.V., Rudik A.V., Filimonov D.A., Blinova V., Dmitriev A., Kharchevnikova N.V., Poroikov V. (2004). Computer prediction of xenobiotic metabolism. Materials of XII International Conference and Debating Scientific Club “New informational technologies in medicine, biology, pharmacology and ecology”, Gurzuf. In.: Advances in Current Natural Sciences, № 6 (Rus) (sup.1, vol. 1), 77-79.
  31. Gomazkov O.A. (2003). Neurochemistry of the ischemic and age-related brain pathologies. Information & Analytical Edition. Moscow. 2003. 200 p. (Rus.).
  32. Akimov D.A., Filimonov D.A., Poroikov V.V. Computer-aided finding of new HIV-1 integrase inhibitors. (2003). In: EuroQSAR 2002. Designing Drugs and Crop Protectants: Processes, Problems and Solutions. Malden a.o.: Blackwell Publ., p.80.
  33. Filimonov D.A., Borodina Yu.V., Lagunin A.A., Akimov D.V., Sadym A.V., Poroikov V.V. (2003). Computer prediction of bioloical activity of chemical compounds. In: Problems in Development of New Pharmaceuticals. Ufa: GILEM, pp. 83-84.
  34. Sobolev B.N., Fomenko A.E., Filimonov D.A., Poroikov V.V. (2002). Protein profiles based on structural descriptors of amino acid residues. Proceedings of the Second International Conference on Bioinformatics of Genome Regulation and Structure (BGRS’2002, Eds. Kolchanov et al.), vol. 3, pp. 117-119.
  35. Poroikov V.V. (2002). Computer-aided analysis of structure-activity relationships. In: Students’ Manual on Chemistry andTechnology of Drugs, Ivanovo: ISCTU, pp. 23-33, 279.
  36. Gomazkov O.A. (2002). Neuropeptides and brain growth factors. Information/Reference Book. Moscow. 2003. 240 p. (Rus.).
  37. Poroikov V.V., Filimonov D.A. (2002). Computer prediction of biological activity of chemical compounds as the basis for finding and optimization of new pharmaceutical leads. In: Proceedings of International Conference “State-of-the-Art and Future Prospects for Development of Organic Chemistry in Kazakhstan” Almaty-Shimkent, pp. 201-206.

Partners

Valery Dembitsky, Centre for Applied Research and Innovation, Lethbridge College, Lethbridge, Canada.
James Devillers, Centre for the Treatment of the Scientific Information (CTIS), Rillieux La Pape, France.
Athina Geronikaki, Aristotle University of Thessaloniki, Thessaloniki, Greece.
Rajesh Goel, Panjabi University, Patiala, India.
Marina Gottikh, Dr.Sci.(Biology), A.N. Belozersky Institute of Physico-Chemical Biology MSU, Moscow, Russia.
Kazakova Oxana, Institute of Chemistry of Russian Academy of Sciences, Ufa, Russia.
Alexander Kel, GeneXplain GmbH, Germany.
Fedor Kolpakov, Institute of Systems Biology, Novosibirsk, Russia.
Vladimir Kukes, The First Moscow State Medical University, Moscow, Russia.
Vladimir Luzhanin, Saint-Petersburg Chemical-Pharmaceutical Academy, Saint-Petersburg, Russia.
Boris Margulis, Institute of Cytology of Russian Academy of Sciences, Saint-Petersburg, Russia.
Marc Nicklaus, National Cancer Institute, National Institute of Health. NCI-Frederick, MD, USA.
Niv Masha, The Hebrew University, Jerusalem, Israel.
Sergey Novikov, A.N. Sysin Research Institute of Human Ecology and Environmental Healt, Moscow, Russia.
Oleg Raevsky, Institute of Physiologically Active Compounds, Chernogolovka, Russia.
Narahari G. Sastry, CSIR Indian Institute of Chemical Technologies, Hyderabad, India.
Galina Selivanova, Karolinska Institute, Stockholm, Sweden.
Stasevych Maryna, Lviv Polytechnic National University, Lviv, Ukraine.
Alexander Tropsha, School of Pharmacy, University of North Carolina at Chapel Hill, USA.
Tatiana Voronina, V.V. Zakusov Research Institute of Pharmacology, Moscow, Russia.
Alexandre Varnek, Louis Pasteur University (Strasbourg I), France.
Pavel Vasil’ev, Volgograd State Medical University, Volgograd, Russia.