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Computer Prediction of Adverse Drug Effects on the Cardiovascular System

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Pharmaceutical Chemistry Journal Aims and scope

A structure–activity relationship model was constructed to predict adverse drug effects on the cardiovascular system. Models were constructed using sets of drug structures compiled by us with information about adverse effects from analyses and data integrated from various sources. The five most common cardiovascular adverse effects, i.e., myocardial infarction, ischemic stroke, cardiac failure, ventricular tachycardia, and arterial hypertension were analyzed in the work. The PASS software that has proved to be efficient in numerous studies was used to construct the appropriate models. The obtained models were accurate enough to be useful for estimating cardiovascular adverse effects of new drugs. An appropriate evaluation could be made in the very early stages of drug discovery because only the structural formula was needed for the prediction.

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References

  1. J. J. Hornberg, M. Laursen, N. Brenden, et al., Drug Discovery Today, 19(8), 1131 – 1136 (2014).

    Article  CAS  Google Scholar 

  2. T. A. Guskova, Khim.-farm. Zh., 35, No. 10, 3 – 8 (2001); Pharm. Chem. J., 35(10), 527 – 532 (2001).

  3. S. M. Ivanov, A. A. Lagunin, and V. V. Poroikov, Drug Discovery Today, 21(1), 58 – 71 (2016).

    Article  CAS  Google Scholar 

  4. O. A. Raevskii, A. N. Razdol’skii, Ya. V. Liplavskii, et al., Khim.-farm. Zh., 46(2), 3 – 8 (2012); Pharm. Chem. J., 46(2), 69 – 74 (2012).

  5. M. Chen, V. Vijay, Q. Shi, et al., Drug Discovery Today, 16(15 – 16), 697 – 703 (2011).

    Article  Google Scholar 

  6. M. Chen, A. Suzuki, S. Thakkar, et al., Drug Discovery Today, 21(4), 648 – 653 (2016).

    Article  CAS  Google Scholar 

  7. S. M. Ivanov, A. A. Lagunin, A. V. Rudik, et al., J. Chem. Inf. Model., 58(1), 8 – 11 (2018).

    Article  CAS  Google Scholar 

  8. E. J. Matthews and A. A. Frid, Regul. Toxicol. Pharmacol., 56(3), 247 – 275 (2010).

    Article  CAS  Google Scholar 

  9. N. P. Tatonetti, P. P. Ye, R. Daneshjou, and R. B. Altman, Sci. Transl. Med., 4(125), 125ra31 (2012).

    Article  Google Scholar 

  10. G. Jiang, H. Liu, H. R. Solbrig, and C. G. Chute, AMIA Jt. Summits Transl. Sci. Proc., 2013, 100 – 104 (2013).

  11. M. Kuhn, I. Letunic, L. J. Jensen, and P. Bork, Nucleic Acids Res., 44(D1), D1075 – D1079 (2016).

    Article  CAS  Google Scholar 

  12. URL: http://sideeffects.embl.de/

  13. J. M. Banda, L. Evans, R. S. Vanguri, et al., Sci. Data, No. 3, 160026 (2016).

  14. URL: http://informatics.mayo.edu/adepedia/index.php/MainPage

  15. A. P. Davis, C. J. Grondin, R. J. Johnson, et al., Nucleic Acids Res., 45(D1), D972-D978 (2017).

    Article  CAS  Google Scholar 

  16. URL: http://ctdbase.org/

  17. URL: https://crediblemeds.org/

  18. D. Fourches, E. Muratov, and A. Tropsha, Nat. Chem. Biol., 11(8), 535 (2015).

    Article  CAS  Google Scholar 

  19. D. A. Filimonov and V. V. Poroikov, Ross. Khim. Zh., 50(2), 66 – 75 (2006).

    CAS  Google Scholar 

  20. D. A. Filimonov, A. A. Lagunin, T. A. Gloriozova, et al., Khim. Geterotsikl. Soedin., No. 3, 483 – 499 (2014); Chem. Heterocycl. Compd., 50(3), 444 – 457 (2014).

  21. V. M. Bezhentsev, D. S. Druzhikovskii, S. M. Ivanov, et al., Khim.-farm. Zh., 51(2), 3 – 11 (2017); Pharm. Chem. J., 51(2), 91 – 99 (2017).

  22. D. S. Druzhikovskii, A. V. Rudik, D. A. Filimonov, et al., Izv. Akad. Nauk, Ser. Khim., No. 10, 1832 – 1841 (2017); Russ. Chem. Bull., Int. Ed., 66(10), 1832 – 1841 (2017).

  23. URL: http://www.way2drug.com/PASSOnline/

  24. P. M. Vasil’ev, K. Yu. Kalitin, A. A. Spasov, et al., Khim.-farm. Zh., 50(12), 3 – 8 (2016); Pharm. Chem. J., 50(12), 775 – 780 (2016).

  25. V. I. Zvarich, M. V. Stasevich, O. V. Stan’ko, et al., Khim.-farm. Zh., 48(9), 20 – 24 (2014); Pharm. Chem. J., 48(9), 584 – 588 (2014).

  26. S. A. Kryzhanovskii, R. M. Salimov, A. A. Lagunin, et al., Khim.-farm. Zh., 45(10), 25 – 31 (2011); Pharm. Chem. J., 45(10), 605 – 611 (2012).

  27. K. A. Murtazalieva, D. S. Druzhilovskiy, R. K. Goel, et al., SAR QSAR Environ. Res., 28(10), 843 – 862 (2017).

    Article  CAS  Google Scholar 

  28. D. Filimonov and V. Poroikov, in: Chemoinformatics Approaches to Virtual Screening, A. Varnek and A. Tropsha (eds.), RSC Publishing, Cambridge (2008), pp. 182 – 216.

  29. URL: https://www.whocc.no/atcdddindex/

  30. B. Sibbald, CMAJ, 171(9), 1027 – 1028 (2004).

    Article  Google Scholar 

  31. A. C. Pessina, M. Hlede, F. Morandin, et al., Int. J. Clin. Pharmacol. Res., 3(1), 41 – 55 (1983).

    CAS  PubMed  Google Scholar 

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Acknowledgments

The work was sponsored by the Russian Science Foundation (Project No. 17 – 75 – 10168).

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Authors and Affiliations

  1. V. N. Orekhovich Institute of Biomedical Chemistry, Moscow, 119121, Russia

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

  2. N. I. Pirogov Russian National Research Medical University, Moscow, 117997, Russia

    S. M. Ivanov & A. A. Lagunin

Authors
  1. S. M. Ivanov
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  2. A. A. Lagunin
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  3. D. A. Filimonov
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  4. V. V. Poroikov
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Corresponding author

Correspondence to S. M. Ivanov.

Additional information

Translated from Khimiko-Farmatsevticheskii Zhurnal, Vol. 52, No. 9, pp. 8 – 13, September, 2018.

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Ivanov, S.M., Lagunin, A.A., Filimonov, D.A. et al. Computer Prediction of Adverse Drug Effects on the Cardiovascular System. Pharm Chem J 52, 758–762 (2018). https://doi.org/10.1007/s11094-018-1895-1

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  • DOI: https://doi.org/10.1007/s11094-018-1895-1

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