Company Info





by Julia Auf der Maur

Open your mind -

Predict biological effects of druglike molecules

in less than a second

accurate greater than 80%

Try it yourself - open http://isciencesearch.com/issl

draw any molecules. If the compounds is not known you will see immediately the PASS predictions

or click on "Predict biological activities using PASS".



 The developers of PASS added a number of new tools and publish them on


The list of publications given below tells you about new developments on the way2drug platform .

 1. Ivanov S.M., Lagunin A.A., Rudik A.V., Filimonov D.A., Poroikov V.V. (2017). ADVERPred web service for prediction of adverse effects of drugs. Journal of Chemical Information and Modeling, DOI: https://doi.org/10.1021/acs.jcim.7b00568

 2. Lagunin A., Rudik A., Filimonov D., Druzhilovsky D., Poroikov V. (2017). ROSC-Pred: web-service for rodent organ-specific carcinogenicity prediction. Bioinformatics. DOI: https://doi.org/10.1093/bioinformatics/btx678

 3. Janardhan S, Konova V., Lagunin A., Rao B.V., Sastry G.N., Poroikov V. (2017). Recent Advances in the development of pharmaceutical agents for metabolic disorders: a computational perspective. Curr. Med. Chem. DOI: https://doi.org/10.2174/0929867324666171002120647

 4. Nagamani S., Gaur A.S., Tanneeru K., Muneeswaran G., Madugula S.S., MPDS Consortium, Druzhilovskiy D., Poroikov V.V., Sastry G.N. (2017) Molecular property diagnostic suite (MPDS): Development of disease-specific open source web portals for drug discovery. SAR and QSAR in Environmental Research, 28 (11), 913-926. DOI: https://doi.org/10.1080/1062936X.2017.1402819

 5. Tarasova O, Rudik A, Dmitriev A, Lagunin A, Filimonov D, Poroikov V. (2017). QNA-Based Prediction of Sites of Metabolism. Molecules, 22 (12), 2123. DOI: https://doi.org/10.3390/molecules22122123

 6. Janardhan S., John L., Prasanthi M., Poroikov V.V., Sastry G.N. (2017). A QSAR and molecular modeling study towards new lead finding: Polypharmacological approach to Mycobacterium tuberculosis. SAR and QSAR in Environmental Research, 28 (10), 815-832. DOI:  https://doi.org/10.1080/1062936X.2017.1398782

 7. Murtazalieva K.A., Druzhilovskiy D.S., Goel R.K., Sastry G.N., Poroikov V.V. (2017). How good are publicly available web services that predict bioactivity profiles for drug repurposing? SAR and QSAR in Environmental Research, 28 (10), 843-862. DOI:  https://doi.org/10.1080/1062936X.2017.1399448

 8. Druzhilovskiy D.S., Rudik A.V., Filimonov D.A., Gloriozova T.A., Lagunin A.A., Dmitriev A.V., Pogodin P.V., Dubovskaja V.I., Ivanov S.M., Tarasova O.A., Bezhentsev V.M., Murtazalieva K.A., Semin M.I., Mayorov I.S., Gaur A.S., Sastry G.N., and Poroikov V.V. (2017). Computational platform Way2Drug: from the prediction of biological activity to drug repurposing. Russian Chemical Bulletin, International Edition, 66 (10), 1832-1841.

9. 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

 10. 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: https://doi.org/10.1002/minf.201600142

 11. 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: https://doi.org/10.1080/1062936X.2017.1323796

 12. 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), 638642. DOI: https://doi.org/10.1021/acs.jcim.6b00662

13.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

14. Bezhentsev V.M., Druzhilovskii 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), 9199. DOI: https://doi.org/10.1007/s11094-017-1563-x

 15. 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: https://doi.org/10.1016/j.jep.2017.03.018

 16. Dembitsky V.M., Gloriozova T.A., Poroikov V.V. (2017). Pharmacological and predicted activities of natural azo compounds. Nat. Prod. Bioprospect., 7, 151. DOI: https://doi.org/10.1007/s13659-016-0117-3

 17. Rudik A.V., Dmitriev A.V., Lagunin A.A., Filimonov D.A., Poroikov V.V. (2016). Prediction of reacting atoms for the major biotransformation reactions of organic xenobiotics. J. Cheminform., 8, 68. DOI: https://doi.org/10.1186/s13321-016-0183-x

 18. 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.

 19. 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), 545556. DOI: https://doi.org/10.1021/acs.molpharmaceut.5b00762

 20. Druzhilovskiy D.S., Rudik A.V., Filimonov D.A., Lagunin A.A., Gloriozova T.A., and Poroikov V.V. (2016). Online resources for the prediction of biological activity of organic compounds. Russian Chemical Bulletin, International Edition, 65 (2), 384-393. DOI: https://doi.org/10.1007/s11172-016-1310-6

 21. 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: https://doi.org/10.1016/j.drudis.2015.07.018

 22. 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, 16 (4), 441-448. DOI: https://doi.org/10.2174/1568026615666150813150433

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