2020-06-30 02:17:12danielshbg

Publications

只要90天,減脂塑形改變體態

2007

Filimonov D.A., Zakharov A.V., Lagunin A.A., Poroikov V.V. QNA based “Star Track” QSAR approach. SAR and QSAR in Environmental Research, 2009, 20: 679-709.

Kokurkina G.V., Dutov M.D., Shevelev S.A., Popkov S.V., Zakharov A.V., Poroikov V.V. Synthesis, antifungal activity and QSAR study of 2-arylhydroxynitroindoles. Eur. J. Med. Chem., 2011, 46: 4374-4382.

2000

Rudik A.V., Dmitriev A.V., Lagunin A.A., Filimonov D.A., Poroikov V.V.  Metabolism sites prediction based on xenobiotics structural formulae and PASS prediction algorithm. Journal of Chemical Information and Modeling, 2014, 54: 498–507.

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.

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.

Poroikov V. (2015). 20th EuroQSAR: Understanding Chemical-Biological Interactions. Molecular Informatics, 34 (6-7), 340. DOI: 10.1002/minf.201580631.

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.

Fedorova E.V., Buryakina A.V., Zakharov A.V., Filimonov D.A., Lagunin A.A., Poroikov V.V. Design, synthesis and pharmacological evaluation of novel vanadium-containing complexes as antidiabetic agents. PLoS ONE, 2014, 9 (7): e100386.

Zakharov A.V., Lagunin A.A., Filimonov D.A., Poroikov V.V. Quantitative prediction of antitarget interaction profiles for chemical compounds. Chemical Research in Toxicology, 2012: 25: 2378-2385.

Lagunin A., Stepanchikova A., Filimonov D., Poroikov V. PASS: prediction of activity spectra for biologically active substances. Bioinformatics, 2000, 16: 747-748.

2003

Geronikaki A., Druzhilovsky D., Zakharov A., Poroikov V. Computer-aided predictions for medicinal chemistry via Internet. SAR and QSAR in Environ. Res., 2008, 19: 27-38.

Cronin M. Report on the "Review of the Status of the Development of Alternatives to using Animals in Chemical Safety Testing and Identification of New Areas for Development or Research in the Context of the Proposed REACH Regulation". Liverpool John Moores University and The Fund for the Replacement of Animals in Medical Experiments, May 2005.

減肥

2012

2013

Our web-resources PASS Online, GUSAR Online, DIGEP-Pred, CLC-Pred, SOMP and others will help you to select the most promising compounds for synthesis and biological testing, filter out drug-candidates with potential adverse effects & toxicity, and finally, reduce the time & financial expenses needed for drug discovery.

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.

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.

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.

2016

 

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Ekins S., Williams5 A.J., Krasowski M.D., Freundlich J.S. In silico repositioning of approved drugs for rare and neglected diseases. Drug Discovery Today, 2011, 16: 298-310.

Borodina Yu., Sadym A., Filimonov D., Blinova V., Dmitriev A., Poroikov V. Predicting biotransformation potential from molecular structure. J. Chem. Inform. Comput. Sci., 2003, 43: 1636-1646.

Van de Waterbeemd H. and Gifford E. ADMET in silico modelling: towards prediction paradise? Nature Reviews Drug Discovery, 2003, 2: 192-204.

Bender A., Young D.W., Jenkins J.L., Serrano M., Mikhailov D., Clemons P.A., Davies J.W. Chemogenomic data analysis: prediction of small-molecule targets and the advent of biological fingerprints. Combinatorial Chemistry & High Throughput Screening, 2007, 10: 719-731.

Borodina Yu., Rudik A., Filimonov D., Kharchevnikova N., Dmitriev A., Blinova V., Poroikov V. A new statistical approach to predicting aromatic hydroxylation sites. Comparison with model-based approaches. J. Chem. Inform. Comput. Sci., 2004, 44: 1998-2009.

Filimonov D., Poroikov V., Borodina Yu., Gloriozova T. Chemical similarity assessment through multilevel neighborhoods of atoms: definition and comparison with the other descriptors. Journal of Chemical Information and Computational Sciences, 1999, 39: 666-670.

減肥

2015

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.

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.

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 (7-9), 595-604. DOI: 10.1080/1062936X.2015.1076516.

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.

Lagunin A., Zakharov A., Filimonov D., Poroikov V. QSAR Modelling of Rat Acute Toxicity on the Basis of PASS Prediction. Molecular Informatics, 2011, 30: 241–250.

Poroikov V., Akimov D., Shabelnikova E., Filimonov D. Top 200 medicines: can new actions be discovered through computer-aided prediction? SAR and QSAR in Environmental Research, 2001, 12: 327-344.

2008

Ekins S., Mestres J., Testa B. In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling. British Journal of Pharmacology, 2007, 152: 9–20.

2004

Sadym A., Lagunin A., Filimonov D., Poroikov V. Prediction of biological activity spectra via Internet. SAR and QSAR in Environmental Research, 2003, 14: 339-347.

Lagunin A., Ivanov S., Rudik A., Filimonov D., Poroikov V. DIGEP-Pred: web-service for in-silico prediction of drug-induced expression profiles based on structural formula. Bioinformatics, 2013, 29: 2062-2063.

Filimonov D.A., Lagunin A.A., Gloriozova T.A., Rudik A.V., Druzhilovskii D.S., Pogodin P.V., Poroikov V.V. Prediction of the biological activity spectra of organic compounds using the PASS online web resource. Chemistry of Heterocyclic Compounds, 2014, 50: 444-457.

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.

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 naïve bayes approach. SAR and QSAR in Environmental Research, 26 (10), 783-793. DOI: 10.1080/1062936X.2015.1078407.

2014

Kryzhanovskii S.A., Salimov R.M., Lagunin A.A., Filimonov D.A., Gloriozova T.A., Poroikov V.V. Nootropic action of some antihypertensive drugs: computer predicting and experimental testing. Pharmaceutical Chemistry Journal, 2012, 45: 605-611.

References

1999

Guasch L., Zakharov A.V., Tarasova O.A., Poroikov V.V., Liao C., Nicklaus M.C. (2015). Novel HIV-1 integrase inhibitor development by virtual screening based on QSAR models. Current Topics in Medicinal Chemistry, 16 (4), 441-448. DOI: 10.2174/1568026615666150813150433.



來自: http://www.way2drug.com/References.php