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Development of the Latest Tools for Building up “Nano-QSAR”: Quantitative Features—Property/Activity Relationships (QFPRs/QFARs)

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Abstract

Computational studies of common compounds are already standard ways of their investigations. However, modeling properties of nanomaterials has been always a challenging task. This chapter reveals important differences between approaches applied to these two groups of species. The development of an optimal descriptor provides one of the efficient ways for the computational techniques to estimate endpoints related to nanospecies. Notably, the optimal descriptor can represent a translator of eclectic information into the endpoint prediction. Development of the optimal descriptor could start with consideration of a hybrid of topological indices calculated with the adjacency matrix of the molecular graph and application of additive scheme where a physicochemical parameter is modeled as the summation of contributions of molecular fragments. Further, the optimal descriptor might be advanced by taking into account contributions of various physicochemical conditions. Such contributions include presence/absence of defined chemical elements and/or defined kinds of covalent bonds, as well as different kinds of rings in the molecular system—factors which are able to modify the physicochemical (biochemical) behavior of a substance. Finally, the latest version of optimal descriptor involves the applications of eclectic data into building up model for endpoints related to nanomaterials. A recently acquired collection of models developed to predict various endpoints of nanomaterials is presented and discussed in this chapter.

Keywords

  • QSPR/QSAR
  • Monte Carlo method
  • CORAL software
  • QFPR/QFAR

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References

  1. Wiener H (1947) J Am Chem Soc 69(1):17

    CAS  CrossRef  Google Scholar 

  2. Wiener H (1947) J Am Chem Soc 69(11):2636

    CAS  CrossRef  Google Scholar 

  3. Wiener H (1948) J Phys Chem Soc 52(6):1082

    CAS  CrossRef  Google Scholar 

  4. Wiener H (1948) J Phys Chem Soc 52(2):425

    CAS  CrossRef  Google Scholar 

  5. Hosoya H (1972) J Chem Doc 12:181

    CAS  CrossRef  Google Scholar 

  6. Amidon GL, Anik ST (1976) J Pharm Sci 65:801

    CAS  CrossRef  Google Scholar 

  7. Bonchev D, Balaban AT, Mekenyan O (1980) J Chem Inf Comput Sci 20:106

    CAS  CrossRef  Google Scholar 

  8. Chemical application of topology and graph theory: a collection of papers from a symposium held at the University of Georgia, Athens, Georgia, U.S.A, 18–22 April 1983

    Google Scholar 

  9. Randic M (2001) J Chem Inf Comput Sci 41(3):627

    CAS  CrossRef  Google Scholar 

  10. Randic M, Basak SC (2001) J Chem Inf Comput Sci 41:614

    CAS  CrossRef  Google Scholar 

  11. Randic M, Plavsic D, Lers N (2001) J Chem Inf Comput Sci 41(3):657

    CAS  CrossRef  Google Scholar 

  12. Roy K, Leonard TJ (2004) Bioorg Med Chem 12:745

    CAS  CrossRef  Google Scholar 

  13. Jalbout AF, Li X (2003) J Mol Struct (Theochem) 663:19

    Google Scholar 

  14. Visco DP Jr, Poppale RS, Rintoul MD, Faulon J-L (2002) J Mol Graph Mod 20:429

    CAS  CrossRef  Google Scholar 

  15. http://www.esi.umontreal-a/accelrys/life/cerius46/qsar/theory_descriptors.html. Accessed 22 Jan 2015

  16. Toropov AA, Toropova AP (1988) Russ J Coord Chem 24:81

    Google Scholar 

  17. Toropov AA, Toropova AP (2003) J Mol Struct (Theochem) 637:1

    CAS  CrossRef  Google Scholar 

  18. Krenkel G, Castro EA, Toropov AA (2001) J Mol Struct (Theochem) 542:107

    CAS  CrossRef  Google Scholar 

  19. Toropov AA, Toropova AP (2004) J Mol Struct (Theochem) 711:173

    CAS  CrossRef  Google Scholar 

  20. Toropov AA, Gutman I, Furtula B (2005) J Serb Chem Soc 70:669

    CrossRef  Google Scholar 

  21. Gutman I, Toropov AA, Toropova AP (2005) MATCH Commun Math Comput Chem 53:215

    CAS  Google Scholar 

  22. Gutman I, Furtula B, Toropov AA, Toropova AP (2005) MATCH Commun Math Comput Chem 53:225

    CAS  Google Scholar 

  23. Toropov AA, Schultz TW (2003) J Chem Inf Comput Sci 43:560

    CAS  CrossRef  Google Scholar 

  24. Weininger D (1988) J Chem Inf Comput Sci 28:31

    CAS  CrossRef  Google Scholar 

  25. Weininger D, Weininger A, Weininger JL (1989) J Chem Inf Comput Sci 29:97

    CAS  CrossRef  Google Scholar 

  26. Weininger D (1990) J Chem Inf Comput Sci 30:237

    CAS  CrossRef  Google Scholar 

  27. Achary PGR (2014) SAR QSAR Environ Res 25(6):507

    CAS  CrossRef  Google Scholar 

  28. Toropov AA, Toropova AP, Martyanov SE, Benfenati E, Gini G, Leszczynska D, Leszczynski J (2011) Chemometr Intell Lab Syst 109(1):94

    CAS  CrossRef  Google Scholar 

  29. Toropova AP, Toropov AA, Martyanov SE, Benfenati E, Gini G, Leszczynska D, Leszczynski J (2013) Mol Inf 32(2):145

    CAS  CrossRef  Google Scholar 

  30. Toropova AP, Toropov AA, Rasulev BF, Benfenati E, Gini G, Leszczynska D, Leszczynski J (2012) Struct Chem 23(6):1873

    CAS  CrossRef  Google Scholar 

  31. Toropov AA, Toropova AP, Martyanov SE, Benfenati E, Gini G, Leszczynska D, Leszczynski J (2012) Chemom Intell Lab Syst 112:65

    CAS  CrossRef  Google Scholar 

  32. Toropova AP, Toropov AA, Martyanov SE, Benfenati E, Gini G, Leszczynska D, Leszczynski J (2012) Chemom Intell Lab Syst 110(1):177

    CAS  CrossRef  Google Scholar 

  33. Toropov AA, Toropova AP, Raska I Jr, Benfenati E, Gini G (2012) Struct Chem 23:1891

    CAS  CrossRef  Google Scholar 

  34. Apul OG, Wang Q, Shao T, Rieck JR, Karanfil T (2013) Environ Sci Technol 47(5):2295

    CAS  CrossRef  Google Scholar 

  35. Yousefinejad S, Hemmateenejad B (2014) Colloids Surf A 441:766

    CAS  CrossRef  Google Scholar 

  36. Toropov AA, Toropova AP (2015) Chemosphere 124:40

    CAS  CrossRef  Google Scholar 

  37. Melagraki G, Afantitis A (2014) RSC Adv 4(92):50713

    CAS  CrossRef  Google Scholar 

  38. Petrova T, Rasulev BF, Toropov AA, Leszczynska D, Leszczynski J (2011) J Nanopart Res 13(8):3235

    CAS  CrossRef  Google Scholar 

  39. Toropov AA, Rasulev BF, Leszczynska D, Leszczynski J (2008) Chem Phys Lett 457(4–6):332

    CAS  CrossRef  Google Scholar 

  40. Toropov AA, Rasulev BF, Leszczynska D, Leszczynski J (2007) Chem Phys Lett 444(1–3):209

    CAS  CrossRef  Google Scholar 

  41. MEMSnet: https://www.memsnet.org/material. Accessed 19 Feb 2013

  42. Shinohara N, Matsumoto K, Endoh S, Maru J, Nakanishi J (2009) Toxicol Lett 191:289

    CAS  CrossRef  Google Scholar 

  43. Toropov AA, Toropova AP (2014) Chemosphere 104:262

    CAS  CrossRef  Google Scholar 

  44. Sayes C, Ivanov I (2010) Risk Anal 30:1723

    CrossRef  Google Scholar 

  45. Patel T, Low-Kam C, Ji ZH, Zhang H, Xia T, Nel AE, Zinc JI, Telesca D (2012) COBRA preprint series 2012, Working Paper 101. http://biostats.bepress.com/cobra/art101

  46. Toropova AP, Toropov AA, Benfenati E, Korenstein R, Leszczynska D, Leszczynski J (2015) Environ Sci Pollut Res 22:745

    CAS  CrossRef  Google Scholar 

  47. Toropov AA, Leszczynska D, Leszczynski J (2007) Mater Lett 61(26):4777

    CAS  CrossRef  Google Scholar 

  48. Toropova AP, Toropov AA, Puzyn T, Benfenati E, Leszczynska D, Leszczynski J (2013) J Math Chem 51(8):2230

    CAS  CrossRef  Google Scholar 

  49. Veselinović AM, Milosavljević JB, Toropov AA, Nikolić GM (2013) Eur J Pharm Sci 48:532

    CrossRef  Google Scholar 

  50. Veselinović AM, Milosavljević JB, Toropov AA, Nikolić GM (2013) Arch Pharm 346:134

    CrossRef  Google Scholar 

  51. Nesměrák K, Toropov AA, Toropova AP (2014) Struct Chem 25(1):311

    CrossRef  Google Scholar 

  52. Nesměrák K, Toropov AA, Toropova AP, Kohoutova P, Waisser K (2013) Eur J Med Chem 67:111

    CrossRef  Google Scholar 

  53. Worachartcheewan A, Nantasenamat C, Isarankura-Na-Ayudhya C, Prachayasittikul V (2014) Lett Drug Des Discovery 11(4):420

    CAS  CrossRef  Google Scholar 

  54. Masand VH, Toropov AA, Toropova AP, Mahajan DT (2014) Curr Comput Aided Drug Des 10(1):75

    CAS  CrossRef  Google Scholar 

  55. Achary PGR (2014) SAR QSAR Environ Res 25(1):73

    CAS  CrossRef  Google Scholar 

  56. Mullen LMA, Duchowicz PR, Castro EA (2011) Chemom Intell Lab Syst 107(2):269

    CAS  CrossRef  Google Scholar 

  57. OECD: Organisation for Economic Co-operation and Development (2007) Guidance document on the validation of (Quantitative) Structure-Activity Relationships ((Q)SAR) models, OECD, Paris. http://www.oecd.org/dataoecd/55/35/38130292.pdf

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Acknowledgments

The authors are grateful to the EU project PROSIL funded under the LIFE program (Project LIFE12 ENV/IT/000154), the EC FP7 project NanoPUZZLES (Project Reference: 309837) and EU FP7 project PreNanoTox (contract 309666). D.L. and J.L. acknowledge support from the National Science Foundation (NSF/CREST HRD-0833178), and EPSCoR (Award #: 362492-190200-01/NSFEPS-090378).

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Correspondence to Andrey A. Toropov or Jerzy Leszczynski .

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Toropov, A.A. et al. (2016). Development of the Latest Tools for Building up “Nano-QSAR”: Quantitative Features—Property/Activity Relationships (QFPRs/QFARs). In: Leszczynski, J., Shukla, M. (eds) Practical Aspects of Computational Chemistry IV. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7699-4_12

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