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QSAR as a random event: criteria of predictive potential for a chance model

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Abstract

The CORAL software (http://www.insilico.eu/coral) was suggested as a tool to build up quantitative structure–property/activity relationships (QSPRs/QSARs). This software is based on conception “a QSPR/QSAR model should be interpreted as a random event.” This is reflection of fact: different distributions into the training set (substances involved in modeling process) and the validation set (substances, which are not known at the moment of the modeling process) give models with significant dispersion in the statistical quality of the QSPR/QSAR. Results of experiments with the software and possible ways of further improvement of this software are discussed. The most attractive new ways to estimate predictive potential of the CORAL model seem to be the following ones: (i) index of ideality of correlation and (ii) correlation contradiction index. These can be also proposed as criteria of predictive potential for arbitrary QSPR/QSAR.

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References

  1. Doweyko AM (2008). J Comput Aided Mol Des 22(2):81–89

    Article  CAS  PubMed  Google Scholar 

  2. Johnson SR (2008). J Chem Inf Model 48(1):25–26

    Article  CAS  PubMed  Google Scholar 

  3. Toropova AP, Toropov AA, Benfenati E, Leszczynska D, Leszczynski J (2015). Bioorg Med Chem 23(6):1223–1230

    Article  CAS  PubMed  Google Scholar 

  4. Toropov AA, Toropova AP, Puzyn T, Benfenati E, Gini G, Leszczynska D, Leszczynski J (2013). Chemosphere 92(1):31–37

    Article  CAS  PubMed  Google Scholar 

  5. Duchowicz PR, Bacelo DE, Fioressi SE, Palermo V, Ibezim NE, Romanelli GP (2018). Med Chem Res 27(2):420–428

    Article  CAS  Google Scholar 

  6. Fioressi SE, Bacelo DE, Rojas C, Aranda JF, Duchowicz PR (2019). Ecotoxicol Environ Saf 171:47–53

    Article  CAS  PubMed  Google Scholar 

  7. Rücker C, Rücker G, Meringer M (2007). J Chem Inf Model 47(6):2345–2357

    Article  CAS  PubMed  Google Scholar 

  8. Consonni V, Ballabio D, Todeschini R (2009). J Chem Inf Model 49(7):1669–1678

    Article  CAS  PubMed  Google Scholar 

  9. Toropova AP, Toropov AA (2019). Mol Inf 38:1800157

    Article  CAS  Google Scholar 

  10. Golbraikh A, Shen M, Xiao Z, Xiao Y-D, Lee K-H, Tropsha A (2003). J Comput Aided Mol Des 17(2–4):241–253

    Article  CAS  PubMed  Google Scholar 

  11. Gaikwad R, Ghorai S, Amin SA, Adhikari N, Patel T, Das K, Jha T, Gayen S (2018). Toxicol in Vitro 52:23–32

    Article  CAS  PubMed  Google Scholar 

  12. Simon L, Imane A, Srinivasan KK, Pathak L, Daoud I (2017). Interdiscip Sci Comput Life Sci 9(3):445–458

    Article  CAS  Google Scholar 

  13. Ahmadi S, Mardinia F, Azimi N, Qomi M, Balali E (2019). J Mol Struct 1181:305–311

    Article  CAS  Google Scholar 

  14. Stoičkov V, Šarić S, Golubović M, Zlatanović D, Krtinić D, Dinić L, Mladenović B, Sokolović D, Veselinović AM (2018). SAR QSAR Environ Res 29(7):503–515

    Article  PubMed  Google Scholar 

  15. Achary PGR (2014). SAR QSAR Environ Res 25(1):73–90

    Article  CAS  PubMed  Google Scholar 

  16. Živković JV, Trutić NV, Veselinović JB, Nikolić GM, Veselinović AM (2015). Comput Biol Med 64:276–282

    Article  CAS  PubMed  Google Scholar 

  17. Kumar P, Kumar A, Sindhu J (2019). SAR QSAR Environ Res 30(2):63–80

    Article  CAS  PubMed  Google Scholar 

  18. Begum S, Achary PGR (2015). SAR QSAR Environ Res 26(5):343–361

    Article  CAS  PubMed  Google Scholar 

  19. Kumar P, Kumar A (2018). Drug Res 68(4):189–195

    Article  CAS  Google Scholar 

  20. Ćirić Zdravković S, Pavlović M, Apostlović S, Koraćević G, Šalinger Martinović S, Stanojević D, Sokolović D, Veselinović AM (2019). Comput Biol Chem 79:55–62

    Article  CAS  PubMed  Google Scholar 

  21. Trinh TX, Choi J-S, Jeon H, Byun H-G, Yoon T-H, Kim J (2018). Chem Res Toxicol 31(3):183–190

    Article  CAS  PubMed  Google Scholar 

  22. Heidari A, Fatemi MH (2017). J Chin Chem Soc 64(3):289–295

    Article  CAS  Google Scholar 

  23. Ahmadi S, Akbari A (2018). SAR QSAR Environ Res 29(11):895–909

    Article  CAS  PubMed  Google Scholar 

  24. Bhargava S, Adhikari N, Amin SA, Das K, Gayen S, Jha T (2017). SAR QSAR Environ Res 28(12):973–990

    Article  CAS  PubMed  Google Scholar 

  25. Islam MA, Pillay TS (2016). Chemom Intell Lab Syst 153:67–74

    Article  CAS  Google Scholar 

  26. Halder AK (2018). SAR QSAR Environ Res 29(11):911–933

    Article  CAS  PubMed  Google Scholar 

  27. Golubović M, Lazarević M, Zlatanović D, Krtinić D, Stoičkov V, Mladenović B, Milić DJ, Sokolović D, Veselinović AM (2018). Comput Biol Chem 75:32–38

    Article  CAS  PubMed  Google Scholar 

  28. Stoičkov V, Stojanović D, Tasić I, Šarić S, Radenković D, Babović P, Sokolović D, Veselinović AM (2018). Struct Chem 29(2):441–449

    Article  CAS  Google Scholar 

  29. Veselinović JB, Đorđević V, Bogdanović M, Morić I, Veselinović AM (2018). Struct Chem 29(2):541–551

    Article  CAS  Google Scholar 

  30. Amin SA, Bhargava S, Adhikari N, Gayen S, Jha T (2018). J Biomol Struct Dyn 36(3):590–608

    Article  CAS  PubMed  Google Scholar 

  31. Zdravković M, Antović A, Veselinović JB, Sokolović D, Veselinović AM (2018). Talanta 178:656–662

    Article  CAS  PubMed  Google Scholar 

  32. Kumar A, Chauhan S (2017). SAR QSAR Environ Res 28(3):179–197

    Article  CAS  PubMed  Google Scholar 

  33. Kumar A, Chauhan S (2018). Future Med Chem 10(13):1603–1622

    Article  CAS  PubMed  Google Scholar 

  34. Amata E, Marrazzo A, Dichiara M, Modica MN, Salerno L, Prezzavento O, Nastasi G, Rescifina A, Romeo G, Pittalà V (2017). ChemMedChem 12(22):1873–1881

    Article  CAS  PubMed  Google Scholar 

  35. Rescifina A, Floresta G, Marrazzo A, Parenti C, Prezzavento O, Nastasi G, Dichiara M, Amata E (2017). Eur J Pharm Sci 106:94–101

    Article  CAS  PubMed  Google Scholar 

  36. Sokolović D, Ranković J, Stanković V, Stefanović R, Karaleić S, Mekić B, Milenković V, Kocić J, Veselinović AM (2017). Med Chem Res 26(4):796–804

    Article  CAS  Google Scholar 

  37. Kumar A, Chauhan S (2017). Arch Pharm 350(1):e1600268

    Article  CAS  Google Scholar 

  38. Kumar A, Chauhan S (2017). Drug Res 67(3):156–162

    CAS  Google Scholar 

  39. Sokolović D, Aleksić D, Milenković V, Karaleić S, Mitić D, Kocić J, Mekić B, Veselinović JB, Veselinović AM (2016). Med Chem Res 25(12):2989–2998

    Article  CAS  Google Scholar 

  40. Sokolović D, Stanković V, Toskić D, Lilić L, Ranković G, Ranković J, Nedin-Ranković G, Veselinović AM (2016). Struct Chem 27(5):1511–1519

    Article  CAS  Google Scholar 

  41. Toropova MA (2017). Curr Drug Metab 18(12):1123–1131

    Article  CAS  PubMed  Google Scholar 

  42. Mondal C, Halder AK, Adhikari N, Saha A, Saha KD, Gayen S, Jha T (2015). Eur J Med Chem 90:860–875

    Article  CAS  PubMed  Google Scholar 

  43. Veselinović JB, Nikolić GM, Trutić NV, Živković JV, Veselinović AM (2015). SAR QSAR Environ Res 26(6):449–460

    Article  CAS  PubMed  Google Scholar 

  44. Li Q, Ding X, Si H, Gao H (2014). Chemom Intell Lab Syst 139:132–138

    Article  CAS  Google Scholar 

  45. Achary PGR (2014). SAR QSAR Environ Res 25(6):507–526

    Article  CAS  PubMed  Google Scholar 

  46. Garro Martinez JC, Duchowicz PR, Estrada MR, Zamarbide GN, Castro EA (2011). Int J Mol Sci 12(12):9354–9368

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Toropov AA, Toropova AP (2019). Toxicol Mech Methods 29:43–52

    Article  CAS  PubMed  Google Scholar 

  48. Ojha PK, Mitra I, Das RN, Roy K (2011). Chemom Intell Lab Syst 107(1):194–205

    Article  CAS  Google Scholar 

  49. I-Kuei Lin L (1989). Biometrics 45(1):255–268

    Article  PubMed  Google Scholar 

  50. Toropov AA, Toropova AP (2017). Mutat Res Genet Toxicol Environ Mutagen 819:31–37

    Article  CAS  Google Scholar 

  51. Toropov AA, Carbó-Dorca R, Toropova AP (2018). Struct Chem 29(1):33–38

    Article  CAS  Google Scholar 

  52. Toropova AP, Toropov AA (2019). J Mol Struct 1182:141–149

    Article  CAS  Google Scholar 

  53. Toropov AA, Raška I, Toropova AP, Raškova M, Veselinović AM, Veselinović JB (2019). Sci Total Environ 659:1387–1394

    Article  CAS  PubMed  Google Scholar 

  54. Toropova AP, Toropov AA, Veselinović AM, Veselinović JB, Leszczynska D, Leszczynski J (2019). Mol Cell Biochem 452(1–2):133–140

    Article  CAS  PubMed  Google Scholar 

  55. Basak SC, Mills DR, Balaban AT, Gute BD (2001). J Chem Inf Comput Sci 41(3):671–678

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The authors express gratitude to the administration of Istituto di Ricerche Farmacologiche Mario Negri for possibility to carry out this research.

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  1. Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Science (Dipartimento: Ambiente e Salute), Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via La Masa 19, 20156, Milan, Italy

    Andrey A. Toropov & Alla P. Toropova

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  1. Andrey A. Toropov
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  2. Alla P. Toropova
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Correspondence to Alla P. Toropova.

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Toropov, A.A., Toropova, A.P. QSAR as a random event: criteria of predictive potential for a chance model. Struct Chem 30, 1677–1683 (2019). https://doi.org/10.1007/s11224-019-01361-6

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