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Monte Carlo Method and a Novel Modelling-Optimization Approach on QSAR Study of Doxazolidine Drugs and DNA-Binding

  • STRUCTURE OF CHEMICAL COMPOUNDS, QUANTUM CHEMISTRY, SPECTROSCOPY
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Abstract

Multiple Linear Regression (MLR), artificial neural networks (ANN), simulated annealing algorithm (SA), genetic algorithm (GA) and imperialist competitive algorithm (ICA) were employed to select the most appropriate descriptors. The obtained results from four combinations of modelling-optimization methods were compared. A high predictive ability was observed for the MLR–ICA model with the best number of empires/imperialists (nEmp = 30) with root-mean-sum-squared errors (RMSE) of 0.013941 in gas phase. In the Monte Carlo method, CORAL software was used and the correlation coefficient (R2), cross-validated correlation coefficient (Q2) and standard error of the model were calculated to be respectively 0.9827, 0.9761, 0.173 for the training set; and 0.9855, 0.9648 and 0.460 for the test set with an optimum threshold of 3. The best Doxazolidine derivative (according to –log IC50) was exposed to reaction with DNA at a 5'-NGC-3' using B3lyp/lanl2dz to investigate the stability of the formed complexes. It was concluded that the combination of different theoretical methods which was employed in this work, can be practically useful in designing new drugs by providing useful information on their physical and structural molecular properties, and understanding of the relation between physico-chemical, structural or theoretical molecular descriptors of drugs to their biological activities.

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REFERENCES

  1. A. Di Marco, M. Gaetani, and B. Scarpinato, Cancer Chemother. Rep. 53, 33 (1969).

    CAS  PubMed  Google Scholar 

  2. C. Young, R. F. Ozols, and C. E. Myers, N. Engl. J. Med. 305, 139 (1981).

    Article  CAS  Google Scholar 

  3. G. C. Post, B. L. Barthel, D. J. Burkhart, J. R. Hagadorn, and T. H. Koch, J. Med. Chem. 48, 7648 (2005).

    Article  CAS  Google Scholar 

  4. D. Fenick, D. J. Taatjes, and T. H. Koch, J. Med. Chem. 40, 2452 (1997).

    Article  CAS  Google Scholar 

  5. P. Gramatica and E. Papa, Mol. Inform. 22, 374 (2003).

    CAS  Google Scholar 

  6. D. B. Horvath and B. Mao, QSAR Comb. Sci. 22, 498 (2003).

    Article  CAS  Google Scholar 

  7. A. P. Toropova, A. A. Toropov, E. Benfenati, et al., J. Comput. Chem 32, 2727 (2011).

    Article  CAS  Google Scholar 

  8. A. A. Toropov, A. P. Toropova, S. E. Martyanov, et al., Chemom. Intell. Lab. 109, 94 (2011).

    Article  CAS  Google Scholar 

  9. E. Shokrollahpour, M. Zandieh, and B. Dorri, Int. J. Prod. Res. 49, 3087 (2011).

    Article  Google Scholar 

  10. S. Hosseini and A. Al Khaled, Appl. Soft. Comput. 24, 1078 (2017).

    Article  Google Scholar 

  11. S. J. MousaviRad, T. F. Akhlaghian, and K. Mollazade, Int. J. Comput. Appl. 40, 41 (2012).

    Google Scholar 

  12. E. Tanış, N. Çankaya, and S. Yalçın, Russ. J. Phys. Chem. B 13, 49 (2019).

    Article  Google Scholar 

  13. K. Levenberg, Quart. Appl. Math. 2, 164 (1944).

    Article  Google Scholar 

  14. S. H. Sadat Hayatshahi, P. Abdolmaleki, M. Ghiasi, and S. Safarian, FEBS Lett. 581, 506 (2007).

    Article  CAS  Google Scholar 

  15. R. Sayyadi kord Abadi, A. Alizadehdakhel, and S. Dorani Shiraz, Russ. J. Phys. Chem. B 11, 307 (2017).

  16. M. J. Frisch, G. W. Trucks, H. B. Schlegel, G. E. Scuseria, M. A. Robb, J. R. Cheeseman, G. Scalmani, V. Barone, B. Mennucci, G. A. Petersson, H. Nakatsuji, M. Caricato, X. Li, H. P. Hratchian, A. F. Izmaylov, et al., Gaussian 09 (Gaussian, Inc., Wallingford CT, 2009). https://gaussian.com/glossary/g09/.

  17. SPSS, Version 19. http://www.spssscience.com. Accessed 2010.

  18. O. G. Maksimova and A. V. Maksimov, Russ. J. Phys. Chem. B 11, 15 (2017).

    Article  CAS  Google Scholar 

  19. Yu. M. Sivergin, S. M. Kireeva, and S. M. Usmanov, Russ. J. Phys. Chem. B 9, 952 (2015).

    Article  CAS  Google Scholar 

  20. S. Putta, J. Eksterowicz, C. Lemmen, and R. Stanton, J. Chem. Inf. Comput. Sci. 43, 1623 (2003).

    Article  CAS  Google Scholar 

  21. E. Atashpaz-Gargari and C. Lucas, in Proceedings of the IEEE Congress on Evolutionary Computation (Inst. Electr. Electron. Eng., Singapore, 2007), p. 4661. https://homepages.ecs.vuw.ac.nz/~yimei/resources/ICA_Atashpaz.pdf.

    Google Scholar 

  22. E. A. Gargari, F. Hashemzadeh, R. Rajabioun, and C. Lucas, Int. J. Intell. Comput. Cybern. 1, 337 (2008).

    Article  Google Scholar 

  23. J.-L. Lin, Yu-H. Tsai, C.-Y. Yu, and M.-S. Li, Algorithms 5, 433 (2012).

    Article  Google Scholar 

  24. http://www.insilico.eu/coral.

  25. A. M. Veselinović, J. B. Milosavljević, A. A. Toropov, and G. M. Nikolić, Eur. J. Pharm. Sci. 48, 532 (2013).

    Article  Google Scholar 

  26. J. Veselinović, A. Veselinović, A. Toropov, A. Toropova, I. Damnjanović, and G. Nikolić, Sci. J. Faculty Med. Niš 31, 95 (2014).

  27. http://www.rcsb.org/.

  28. https://pubchem.ncbi.nlm.nih.gov.

  29. R. Todeschini and V. Consonni, Hand Book of Molecular Descriptors (Wiley-VCH, Weinheim, Germany, 2008).

    Google Scholar 

  30. J. H. Schurz, P. Selzer, and J. Gasteiger, J. Chem. Inform. Comput. Sci. 36, 334 (1996).

    Article  Google Scholar 

  31. R. Sayyadikord Abadi, A. Alizadehdakhel, and S. Tajadodi Paskiabei, J. Korean Chem. Soc. 60, 225 (2016).

    Article  Google Scholar 

  32. R. Sayyadikord Abadi and A. Alizadehdakhel, Rev. Roum. Chim. 63, 171 (2018).

    Google Scholar 

  33. R. Sayyadikord Abadi, A. Alizadehdakhel, and S. Dorani Shiraz, Russ. J. Phys. Chem. B 11, 307 (2017).

    Article  CAS  Google Scholar 

  34. A. Golbraikh and A. Tropsha, J. Mol. Graph. Model. 20, 269 (2002).

    Article  CAS  Google Scholar 

  35. A. Kumar and S. Chauhan, SAR QSAR Environ. Res. 28, 179 (2017).

    Article  CAS  Google Scholar 

  36. A.H.-J. Wang, Y. G. Gao, Y. C. Liaw, and Y. K. Li, Biochemistry 30, 3812 (1991).

    Article  CAS  Google Scholar 

  37. H. Zhang, Y. G. Gao, G. A. van der Marel, J. H. van Boom, and A. H. Wang, J. Biol. Chem. 268, 10095 (1993).

    Article  CAS  Google Scholar 

  38. B. T. Kalet, M. B. McBryde, J. M. Espinosa, and T. H. Koch, J. Med. Chem. 50, 4493 (2007).

    Article  CAS  Google Scholar 

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5. ACKNOWLEDGMENTS

The authors gratefully acknowledge the support provided by the Islamic Azad University of Rasht.

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Authors and Affiliations

  1. Department of Chemistry and Chemical Engineering, Rasht Branch, Islamic Azad University, Rasht, Iran

    Maria Nikkar,  Robabeh SayyadikordAbadi, Asghar Alizadehdakhel & Ghasem Ghasemi

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  1. Maria Nikkar
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  2. Robabeh SayyadikordAbadi
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  3. Asghar Alizadehdakhel
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  4. Ghasem Ghasemi
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Correspondence to Robabeh SayyadikordAbadi.

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Maria Nikkar, Robabeh SayyadikordAbadi, Alizadehdakhel, A. et al. Monte Carlo Method and a Novel Modelling-Optimization Approach on QSAR Study of Doxazolidine Drugs and DNA-Binding. Russ. J. Phys. Chem. B 15 (Suppl 1), S32–S41 (2021). https://doi.org/10.1134/S199079312109013X

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  • DOI: https://doi.org/10.1134/S199079312109013X

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