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Items: 1 to 50 of 147

1.

Prediction of Severity of Drug-Drug Interactions Caused by Enzyme Inhibition and Activation.

Dmitriev A, Filimonov D, Lagunin A, Karasev D, Pogodin P, Rudik A, Poroikov V.

Molecules. 2019 Oct 31;24(21). pii: E3955. doi: 10.3390/molecules24213955.

2.

AntiBac-Pred: A Web Application for Predicting Antibacterial Activity of Chemical Compounds.

Pogodin PV, Lagunin AA, Rudik AV, Druzhilovskiy DS, Filimonov DA, Poroikov VV.

J Chem Inf Model. 2019 Nov 25;59(11):4513-4518. doi: 10.1021/acs.jcim.9b00436. Epub 2019 Nov 12.

PMID:
31661960
3.

Improving (Q)SAR predictions by examining bias in the selection of compounds for experimental testing.

Pogodin PV, Lagunin AA, Filimonov DA, Nicklaus MC, Poroikov VV.

SAR QSAR Environ Res. 2019 Oct;30(10):759-773. doi: 10.1080/1062936X.2019.1665580. Epub 2019 Sep 24.

PMID:
31547686
4.

PASS-based prediction of metabolites detection in biological systems.

Rudik AV, Dmitriev AV, Lagunin AA, Filimonov DA, Poroikov VV.

SAR QSAR Environ Res. 2019 Oct;30(10):751-758. doi: 10.1080/1062936X.2019.1665099. Epub 2019 Sep 23.

PMID:
31542944
5.

Drug-drug interaction prediction using PASS.

Dmitriev AV, Filimonov DA, Rudik AV, Pogodin PV, Karasev DA, Lagunin AA, Poroikov VV.

SAR QSAR Environ Res. 2019 Sep 4:1-10. doi: 10.1080/1062936X.2019.1653966. [Epub ahead of print]

PMID:
31482727
6.

Data Mining Approach for Extraction of Useful Information About Biologically Active Compounds from Publications.

Tarasova OA, Biziukova NY, Filimonov DA, Poroikov VV, Nicklaus MC.

J Chem Inf Model. 2019 Sep 23;59(9):3635-3644. doi: 10.1021/acs.jcim.9b00164. Epub 2019 Sep 10.

PMID:
31453694
7.

AntiHIV-Pred: Web-resource for in silico prediction of anti-HIV/AIDS activity.

Stolbov L, Druzhilovskiy D, Rudik A, Filimonov D, Poroikov V, Nicklaus M.

Bioinformatics. 2019 Aug 16. pii: btz638. doi: 10.1093/bioinformatics/btz638. [Epub ahead of print]

PMID:
31418763
8.

Assessment of the cardiovascular adverse effects of drug-drug interactions through a combined analysis of spontaneous reports and predicted drug-target interactions.

Ivanov S, Lagunin A, Filimonov D, Poroikov V.

PLoS Comput Biol. 2019 Jul 19;15(7):e1006851. doi: 10.1371/journal.pcbi.1006851. eCollection 2019 Jul.

9.

[Xenobiotic toxicity prediction combined with xenobiotic metabolism prediction in the human body].

Rudik AV, Dmitriev AV, Lagunin AA, Ivanov SM, Filimonov DA, Poroikov VV.

Biomed Khim. 2019 Feb;65(2):114-122. doi: 10.18097/PBMC20196502114. Russian.

PMID:
30950816
10.

[Discovering new antiretroviral compounds in "Big Data" chemical space of the SAVI library].

Savosina PI, Stolbov LA, Druzhilovskiy DS, Filimonov DA, Nicklaus MC, Poroikov VV.

Biomed Khim. 2019 Feb;65(2):73-79. doi: 10.18097/PBMC20196502073. Russian.

PMID:
30950810
11.

Hydroperoxy steroids and triterpenoids derived from plant and fungi: Origin, structures and biological activities.

Vil VA, Terent'ev AO, Savidov N, Gloriozova TA, Poroikov VV, Pounina TA, Dembitsky VM.

J Steroid Biochem Mol Biol. 2019 Jun;190:76-87. doi: 10.1016/j.jsbmb.2019.03.020. Epub 2019 Mar 25. Review.

PMID:
30923015
12.

Metatox - Web application for generation of metabolic pathways and toxicity estimation.

Rudik A, Bezhentsev V, Dmitriev A, Lagunin A, Filimonov D, Poroikov V.

J Bioinform Comput Biol. 2019 Feb;17(1):1940001. doi: 10.1142/S0219720019400018.

PMID:
30866738
13.

Naturally occurring of α,β-diepoxy-containing compounds: origin, structures, and biological activities.

Vil V, Gloriozova TA, Poroikov VV, Terent'ev AO, Savidov N, Dembitsky VM.

Appl Microbiol Biotechnol. 2019 Apr;103(8):3249-3264. doi: 10.1007/s00253-019-09711-4. Epub 2019 Mar 9. Review.

PMID:
30852659
14.

Novel antimicrobial agents' discovery among the steroid derivatives.

Nadaraia NS, Amiranashvili LS, Merlani M, Kakhabrishvili ML, Barbakadze NN, Geronikaki A, Petrou A, Poroikov V, Ciric A, Glamoclija J, Sokovic M.

Steroids. 2019 Apr;144:52-65. doi: 10.1016/j.steroids.2019.02.012. Epub 2019 Feb 15.

PMID:
30776376
15.

Derivatives of Piperazines as Potential Therapeutic Agents for Alzheimer's Disease.

Popugaeva E, Chernyuk D, Zhang H, Postnikova TY, Pats K, Fedorova E, Poroikov V, Zaitsev AV, Bezprozvanny I.

Mol Pharmacol. 2019 Apr;95(4):337-348. doi: 10.1124/mol.118.114348. Epub 2019 Jan 29.

PMID:
30696719
16.

Prediction of Drug-Drug Interactions Related to Inhibition or Induction of Drug-Metabolizing Enzymes.

Dmitriev AV, Lagunin AA, Karasev DА, Rudik AV, Pogodin PV, Filimonov DA, Poroikov VV.

Curr Top Med Chem. 2019;19(5):319-336. doi: 10.2174/1568026619666190123160406. Review.

PMID:
30674264
17.

New Caffeic Acid Derivatives as Antimicrobial Agents: Design, Synthesis, Evaluation and Docking.

Merlani M, Barbakadze V, Amiranashvili L, Gogilashvili L, Poroikov V, Petrou A, Geronikaki A, Ciric A, Glamoclija J, Sokovic M.

Curr Top Med Chem. 2019;19(4):292-304. doi: 10.2174/1568026619666190122152957.

PMID:
30674263
18.

Comparison of Quantitative and Qualitative (Q)SAR Models Created for the Prediction of Ki and IC50 Values of Antitarget Inhibitors.

Lagunin AA, Romanova MA, Zadorozhny AD, Kurilenko NS, Shilov BV, Pogodin PV, Ivanov SM, Filimonov DA, Poroikov VV.

Front Pharmacol. 2018 Oct 10;9:1136. doi: 10.3389/fphar.2018.01136. eCollection 2018.

19.

A Computational Approach for the Prediction of HIV Resistance Based on Amino Acid and Nucleotide Descriptors.

Tarasova O, Biziukova N, Filimonov D, Poroikov V.

Molecules. 2018 Oct 24;23(11). pii: E2751. doi: 10.3390/molecules23112751.

20.

Highly oxygenated isoprenoid lipids derived from fungi and fungal endophytes: Origin and biological activities.

Savidov N, Gloriozova TA, Poroikov VV, Dembitsky VM.

Steroids. 2018 Dec;140:114-124. doi: 10.1016/j.steroids.2018.10.006. Epub 2018 Oct 14. Review.

PMID:
30326211
21.

Etoposide-Induced Apoptosis in Cancer Cells Can Be Reinforced by an Uncoupled Link between Hsp70 and Caspase-3.

Sverchinsky DV, Nikotina AD, Komarova EY, Mikhaylova ER, Aksenov ND, Lazarev VF, Mitkevich VA, Suezov R, Druzhilovskiy DS, Poroikov VV, Margulis BA, Guzhova IV.

Int J Mol Sci. 2018 Aug 25;19(9). pii: E2519. doi: 10.3390/ijms19092519.

22.

Molecular property diagnostic suite for diabetes mellitus (MPDSDM): An integrated web portal for drug discovery and drug repurposing.

Gaur AS, Nagamani S, Tanneeru K, Druzhilovskiy D, Rudik A, Poroikov V, Narahari Sastry G.

J Biomed Inform. 2018 Sep;85:114-125. doi: 10.1016/j.jbi.2018.08.003. Epub 2018 Aug 6.

23.

Peroxy steroids derived from plant and fungi and their biological activities.

Vil VA, Gloriozova TA, Poroikov VV, Terent'ev AO, Savidov N, Dembitsky VM.

Appl Microbiol Biotechnol. 2018 Sep;102(18):7657-7667. doi: 10.1007/s00253-018-9211-2. Epub 2018 Jul 10. Review.

PMID:
29987343
24.

Molecular Docking Studies of HIV-1 Resistance to Reverse Transcriptase Inhibitors: Mini-Review.

Tarasova O, Poroikov V, Veselovsky A.

Molecules. 2018 May 21;23(5). pii: E1233. doi: 10.3390/molecules23051233. Review.

25.

How to Achieve Better Results Using PASS-Based Virtual Screening: Case Study for Kinase Inhibitors.

Pogodin PV, Lagunin AA, Rudik AV, Filimonov DA, Druzhilovskiy DS, Nicklaus MC, Poroikov VV.

Front Chem. 2018 Apr 26;6:133. doi: 10.3389/fchem.2018.00133. eCollection 2018.

26.

Naturally occurring aromatic steroids and their biological activities.

Dembitsky VM, Savidov N, Poroikov VV, Gloriozova TA, Imbs AB.

Appl Microbiol Biotechnol. 2018 Jun;102(11):4663-4674. doi: 10.1007/s00253-018-8968-7. Epub 2018 Apr 21. Review.

PMID:
29680899
27.

HIV Resistance Prediction to Reverse Transcriptase Inhibitors: Focus on Open Data.

Tarasova O, Poroikov V.

Molecules. 2018 Apr 19;23(4). pii: E956. doi: 10.3390/molecules23040956. Review.

28.

CLC-Pred: A freely available web-service for in silico prediction of human cell line cytotoxicity for drug-like compounds.

Lagunin AA, Dubovskaja VI, Rudik AV, Pogodin PV, Druzhilovskiy DS, Gloriozova TA, Filimonov DA, Sastry NG, Poroikov VV.

PLoS One. 2018 Jan 25;13(1):e0191838. doi: 10.1371/journal.pone.0191838. eCollection 2018.

29.

Identification of potential drug targets for treatment of refractory epilepsy using network pharmacology.

Bezhentsev V, Ivanov S, Kumar S, Goel R, Poroikov V.

J Bioinform Comput Biol. 2018 Feb;16(1):1840002. doi: 10.1142/S0219720018400024. Epub 2018 Jan 24.

PMID:
29361895
30.

Pharmacological repositioning of Achyranthes aspera as an antidepressant using pharmacoinformatic tools PASS and PharmaExpert: a case study with wet lab validation.

Goel RK, Gawande DY, Lagunin AA, Poroikov VV.

SAR QSAR Environ Res. 2018 Jan;29(1):69-81. doi: 10.1080/1062936X.2017.1408683. Epub 2017 Dec 19.

PMID:
29256630
31.

Molecular property diagnostic suite (MPDS): Development of disease-specific open source web portals for drug discovery.

Nagamani S, Gaur AS, Tanneeru K, Muneeswaran G, Madugula SS, Consortium M, Druzhilovskiy D, Poroikov VV, Sastry GN.

SAR QSAR Environ Res. 2017 Nov;28(11):913-926. doi: 10.1080/1062936X.2017.1402819.

PMID:
29206500
32.

ADVERPred-Web Service for Prediction of Adverse Effects of Drugs.

Ivanov SM, Lagunin AA, Rudik AV, Filimonov DA, Poroikov VV.

J Chem Inf Model. 2018 Jan 22;58(1):8-11. doi: 10.1021/acs.jcim.7b00568. Epub 2017 Dec 22.

PMID:
29206457
33.

QNA-Based Prediction of Sites of Metabolism.

Tarasova O, Rudik A, Dmitriev A, Lagunin A, Filimonov D, Poroikov V.

Molecules. 2017 Dec 1;22(12). pii: E2123. doi: 10.3390/molecules22122123.

34.

A QSAR and molecular modelling study towards new lead finding: polypharmacological approach to Mycobacterium tuberculosis.

Janardhan S, John L, Prasanthi M, Poroikov V, Narahari Sastry G.

SAR QSAR Environ Res. 2017 Oct;28(10):815-832. doi: 10.1080/1062936X.2017.1398782.

PMID:
29183232
35.

How good are publicly available web services that predict bioactivity profiles for drug repurposing?

Murtazalieva KA, Druzhilovskiy DS, Goel RK, Sastry GN, Poroikov VV.

SAR QSAR Environ Res. 2017 Oct;28(10):843-862. doi: 10.1080/1062936X.2017.1399448.

PMID:
29183230
36.

Prediction of metabolites of epoxidation reaction in MetaTox.

Rudik AV, Dmitriev AV, Bezhentsev VM, Lagunin AA, Filimonov DA, Poroikov VV.

SAR QSAR Environ Res. 2017 Oct;28(10):833-842. doi: 10.1080/1062936X.2017.1399165. Epub 2017 Nov 20.

PMID:
29157013
37.

[Computational prediction of human immunodeficiency resistance to reverse transcriptase inhibitors].

Tarasova OA, Filimonov DA, Poroikov VV.

Biomed Khim. 2017 Oct;63(5):457-460. doi: 10.18097/PBMC20176305457. Russian.

PMID:
29080881
38.

ROSC-Pred: web-service for rodent organ-specific carcinogenicity prediction.

Lagunin A, Rudik A, Druzhilovsky D, Filimonov D, Poroikov V, Wren J.

Bioinformatics. 2018 Feb 15;34(4):710-712. doi: 10.1093/bioinformatics/btx678.

PMID:
29069300
39.

Recent Advances in the Development of Pharmaceutical Agents for Metabolic Disorders: A Computational Perspective.

Janardhan S, Dubovskaja V, Lagunin A, Rao BV, Sastry GN, Poroikov V.

Curr Med Chem. 2018;25(39):5432-5463. doi: 10.2174/0929867324666171002120647. Review.

PMID:
28969540
40.

Computer-aided prediction and cytotoxicity evaluation of dithiocarbamates of 9,10-anthracenedione as new anticancer agents.

Stasevych M, Zvarych V, Lunin V, Deniz NG, Gokmen Z, Akgun O, Ulukaya E, Poroikov V, Gloriozova T, Novikov V.

SAR QSAR Environ Res. 2017 May;28(5):355-366. doi: 10.1080/1062936X.2017.1323796. Epub 2017 May 19.

PMID:
28524703
41.

MetaTox: Web Application for Predicting Structure and Toxicity of Xenobiotics' Metabolites.

Rudik AV, Bezhentsev VM, Dmitriev AV, Druzhilovskiy DS, Lagunin AA, Filimonov DA, Poroikov VV.

J Chem Inf Model. 2017 Apr 24;57(4):638-642. doi: 10.1021/acs.jcim.6b00662. Epub 2017 Apr 3.

PMID:
28345905
42.

Anticonvulsant activity and acute neurotoxic profile of Achyranthes aspera Linn.

Gawande DY, Druzhilovsky D, Gupta RC, Poroikov V, Goel RK.

J Ethnopharmacol. 2017 Apr 18;202:97-102. doi: 10.1016/j.jep.2017.03.018. Epub 2017 Mar 14.

PMID:
28315457
43.

In Silico Identification of Proteins Associated with Drug-induced Liver Injury Based on the Prediction of Drug-target Interactions.

Ivanov S, Semin M, Lagunin A, Filimonov D, Poroikov V.

Mol Inform. 2017 Jul;36(7). doi: 10.1002/minf.201600142. Epub 2017 Feb 1.

PMID:
28145637
44.

Pharmacological and Predicted Activities of Natural Azo Compounds.

Dembitsky VM, Gloriozova TA, Poroikov VV.

Nat Prod Bioprospect. 2017 Feb;7(1):151-169. doi: 10.1007/s13659-016-0117-3. Epub 2017 Jan 4.

45.

PASS-based approach to predict HIV-1 reverse transcriptase resistance.

Tarasova O, Filimonov D, Poroikov V.

J Bioinform Comput Biol. 2017 Apr;15(2):1650040. doi: 10.1142/S0219720016500402. Epub 2016 Nov 22.

PMID:
28033735
46.

Prediction of reacting atoms for the major biotransformation reactions of organic xenobiotics.

Rudik AV, Dmitriev AV, Lagunin AA, Filimonov DA, Poroikov VV.

J Cheminform. 2016 Nov 28;8:68. eCollection 2016.

47.

Multi-omics "upstream analysis" of regulatory genomic regions helps identifying targets against methotrexate resistance of colon cancer.

Kel AE, Stegmaier P, Valeev T, Koschmann J, Poroikov V, Kel-Margoulis OV, Wingender E.

EuPA Open Proteom. 2016 Sep 9;13:1-13. doi: 10.1016/j.euprot.2016.09.002. eCollection 2016 Dec.

48.

QSAR Modeling and Prediction of Drug-Drug Interactions.

Zakharov AV, Varlamova EV, Lagunin AA, Dmitriev AV, Muratov EN, Fourches D, Kuz'min VE, Poroikov VV, Tropsha A, Nicklaus MC.

Mol Pharm. 2016 Feb 1;13(2):545-56. doi: 10.1021/acs.molpharmaceut.5b00762. Epub 2016 Jan 5.

PMID:
26669717
49.

Virtual screening of chemical compounds active against breast cancer cell lines based on cell cycle modelling, prediction of cytotoxicity and interaction with targets.

Konova V, Lagunin A, Pogodin P, Kolotova E, Shtil A, Poroikov V.

SAR QSAR Environ Res. 2015;26(7-9):595-604. doi: 10.1080/1062936X.2015.1076516. Epub 2015 Sep 11.

PMID:
26358808
50.

PASS Targets: Ligand-based multi-target computational system based on a public data and naïve Bayes approach.

Pogodin PV, Lagunin AA, Filimonov DA, Poroikov VV.

SAR QSAR Environ Res. 2015;26(10):783-93. doi: 10.1080/1062936X.2015.1078407. Epub 2015 Aug 25.

PMID:
26305108

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