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Performance assessment of semiempirical molecular orbital methods in the structural prediction of Sb(III) and Bi(III) complexes

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Abstract

In this paper we carried out a systematic study in order to assess the quality of some semiempirical methods (AM1, PM3 and PM6), comparing predicted structural properties of many Sb(III) and Bi(III) complexes with the corresponding experimental data, indicating which one is more appropriate to describe the structure of such compounds. Root-mean squared deviation (RMSD) and unsigned mean error (UME) were used to evaluate the accuracy of the semiempirical methods to predict the ground state geometries of complexes with many ligand types. Our results have shown that, in general, PM3 predicts more accurately the geometry of Sb(III) complexes, being considered by us as the method of choice to study Sb(III) complexes with a great variety of ligands. PM6 is indicated as the method of choice to study Bi(III) complexes with many types of ligands and also to study Sb(III) thiocompounds, even though PM6 showed an inability to reproduce Sb-N bonds for complexes with flexible ligands, presenting an average deviation of 71.5 % compared the X-ray data.

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References

  1. Silvestru C, Breunig H, Althaus H (1999) Chem Rev 99:3277–3327

    Article  CAS  Google Scholar 

  2. Sanderson J, Basey CA (2008) Tetrahedron 64:7685–7689

    Article  CAS  Google Scholar 

  3. Yang N, Sun H (2011) in: Sun H (ed) Biological chemistry of antimony and bismuth. Wiley, New York

  4. Sun H, Ge R (2007) Acc Chem Res 40:267–274

    Article  Google Scholar 

  5. Ilari A, Baiocco P, Colotti G, Franceschini SJ (2009) Med Chem 52:2603–2612

    Article  Google Scholar 

  6. Ozuturk II, Handjikakou SK, Hadjiliadis NKN, Kubicki M, Baril M, Butler IS, Balzarini J (2007) Inorg Chem 46:8652–8661

    Article  Google Scholar 

  7. Ozuturk II, Hadjikakou SK, Hadjiliadis N, Kourkoumelis N, Kubicki M, Tasiopoulos AJ, Scleiman H, Barsan MM, Butler IS, Balzarini J (2009) Inorg Chem 48:2233–2245

    Article  Google Scholar 

  8. Nomiya K, Kasuga NC, Onodera K, Nakano S, Hayashi K (2006) J Inorg Biochem 100:1176–1186

    Article  Google Scholar 

  9. Andrews PC, Frank R, Junk PC, Kedzierski L, Kumar I, Maclellan JG (2011) J Inorg Biochem 105:454–461

    Article  CAS  Google Scholar 

  10. Hassfjell S, Brechbiel MW (2001) Chem Rev 101:2019–2020

    Article  CAS  Google Scholar 

  11. Sun H, Yang N (2007) Coord Chem Rev 251:2354–2366

    Article  Google Scholar 

  12. Briand GG, Burford N, Eelman MD, Aumeerally N, Chen L, Carmeron TS, Robertson KN (2004) Inorg Chem 43:6495–6500

    Article  CAS  Google Scholar 

  13. Asato E, Katsura K, Mikuriya M, Fujii T, Reedijk J (1993) Inorg Chem 32:5322–5329

    Article  CAS  Google Scholar 

  14. Tiekink ERT (2002) Crit Rev Oncol Hematol 42:217–224

    Article  Google Scholar 

  15. Mahajan K, Swami M, Singh RV (2009) Russ J Coord Chem 35:179–185

    Article  CAS  Google Scholar 

  16. Boitrel B, Halime Z, Balieu S, Lachkar M (2007) C R Chim 10:587–589

    Article  Google Scholar 

  17. Comba P, Hambley TW (2001) Molecular Modeling of Inorganic Compouds. Wiley-VHC, Weinheim

  18. Hoge B, Boatz JA, Hegge J, Christe KO (1999) Inorg Chem 38:3143–3149

    Article  CAS  Google Scholar 

  19. Bachmann C, Frapper G (2008) Chem Phys Lett 457:292–297

    Article  CAS  Google Scholar 

  20. Poleshchuk OK, Shevchenko EL, Branchadell V, Frenking ML (2005) Int J Quantum Chem 101:869–877

    Article  CAS  Google Scholar 

  21. Virko S, Petrenko T, Yaremko A, Wysokinski R, Michalska D (2002) J Mol Struct:Theochem 582:137–142

    Article  CAS  Google Scholar 

  22. Yurchenko SN, Breidung J, Thiel W (2005) Theor Chem Acc 114:333–340

    Article  CAS  Google Scholar 

  23. Karttunen AJ, Linnolahti M, Pakkanen TA (2011) Theor Chem Acc 129:413–422

    Article  CAS  Google Scholar 

  24. Pye CC, Gunasekara M, Rudolph WW (2007) Can J Chem 85:945–950

    Article  CAS  Google Scholar 

  25. Kuznetsov AM, Shapnik MS, Masliy AN, Zelenetskaya KV (2002) Russ J Electrochem 38:669–675

    Article  CAS  Google Scholar 

  26. Wadt WR, Hay PJ (1985) J Chem Phys 82:284

    Article  CAS  Google Scholar 

  27. Poleshchuk OK, Koput J, Latosinska JN, Nogaj BJ (1996) J Mol Struct 380:267–275

    Article  CAS  Google Scholar 

  28. Stewart JJP (1991) J Comput Chem 12:320–341

    Article  CAS  Google Scholar 

  29. Pankratov AN, Uchaeva IM (2002) Phosphorus. Sulfur Silicon Relat Elem 177:2611–2621

    Article  CAS  Google Scholar 

  30. Pankratov AN, Uchaeva IM (2002) Phosphorus. Sulfur Silicon Relat Elem 177:791–802

    Article  CAS  Google Scholar 

  31. Stewart JJP, MOPAC 2009 version 9.069W; Stewart Computational Chemistry. http://OpenMOPAC.net

  32. Allen FH (2002) Acta Crystallogr Sect B 58:380–388

    Article  Google Scholar 

  33. Scott DW (1979) Biometrika 66:605–610

    Article  Google Scholar 

  34. Stewart JJP (2007) J Mol Model 13:1173–1213

    Article  CAS  Google Scholar 

  35. Thiel W, Voityuk AA (1996) J Phys Chem 100:616–626

    Article  CAS  Google Scholar 

  36. Thiel W, Voityuk AA (1992) Theor Chim Acta 81:391–404

    Article  CAS  Google Scholar 

  37. Thiel W, Voityuk AA (1992) Int J Quantum Chem 44:807–829

    Article  CAS  Google Scholar 

  38. Seitz M, Alzakhem N (2010) J Chem Inf Model 50:217–220

    Article  CAS  Google Scholar 

  39. Stewart JJP (1989) J Comput Chem 10:209–220

    Article  CAS  Google Scholar 

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Acknowledgments

We appreciate the financial support from CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico) and CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior), Brazilian agencies, and INCT-INAMI (Instituto Nacional de Ciência e Tecnologia - Nanotecnologia para Marcadores Integrados). We also wish to thank CENAPAD/SP (Centro Nacional de Processamento de Alto Desempenho) at Campinas, Brazil, for having made available to us their computational facilities Finally, we gratefully acknowledge the Cambridge Crystallographic Data Centre for the Cambridge Structural Database.

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Correspondence to Gerd B. Rocha.

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Martins, E.P.S., Rocha, G.B. Performance assessment of semiempirical molecular orbital methods in the structural prediction of Sb(III) and Bi(III) complexes. J Mol Model 19, 4575–4584 (2013). https://doi.org/10.1007/s00894-013-1974-x

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  • DOI: https://doi.org/10.1007/s00894-013-1974-x

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