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Modelling of copper(II) binding to pentapeptides related to atrial natriuretic factor using the 3χv connectivity index / Modeliranje vezivanja bakra(II) za pentapeptide povezane s atrijalnim natriuretičkim faktorom pomoću indeksa povezanosti 3χv


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1. Flynn TG, Davies PL. The biochemistry and molecular biology of atrial natriuretic factor. Biochem J 1985;232:313-21. PMCID: PMC115288110.1042/bj2320313Search in Google Scholar

2. Rosenzweig A, Seidman CE. Atrial natriuretic factor and related peptide hormones. Annu Rev Biochem 1991;60:229-55. doi: 10.1146/annurev.bi.60.070191.00130510.1146/annurev.bi.60.070191.001305Search in Google Scholar

3. Prohaska JR. Biochemical changes in copper deficiency. J Nutr Biochem 1990;1:452-61. doi: 10.1016/0955-2863(90)90080-510.1016/0955-2863(90)90080-5Search in Google Scholar

4. Kang YJ, Zhou ZX, Wu H, Wang GW, Saari JT, Klein JB. Metallothionein inhibits myocardial apoptosis in copperdeficient mice: role of atrial natriuretic peptide. Lab Invest 2000;80:745-57. PMID: 1083078510.1038/labinvest.3780078Search in Google Scholar

5. Janicka-Klos A, Porciatti E, Valensin D, Conato C, Remelli M, Oldziej S, Valensin G, Kozlowski H. The unusual stabilization of the Ni2+ and Cu2+ complexes with NSFRY. Dalton Trans 2013;42:448-58. doi: 10.1039/c2dt31959d10.1039/C2DT31959DSearch in Google Scholar

6. Odani A, Yamauchi O. Preferential formation of ternary copper(II) complexes involving substituted ethylenediamines and amino acids with an aromatic side chain. Inorg Chim Acta 1984;93:13-8.10.1016/S0020-1693(00)85951-4Search in Google Scholar

7. Yamauchi O, Odani A, Takani M. Metal-amino acid chemistry. Weak interactions and related functions of side chain groups. J Chem Soc, Dalton Trans 2002;3411-21. doi: 10.1039/B202385G10.1039/B202385GSearch in Google Scholar

8. Sugimori T, Masuda H, Ohata N, Koiwai K, Odani A, Yamauchi O. Structural dependence of aromatic ring stacking and related weak interactions in ternary amino acidcopper( II) complexes and its biological implication. Inorg Chem 1997;36:576-83. doi: 10.1021/ic960855610.1021/ic9608556Search in Google Scholar

9. Siegel H, Tribolet R, Scheller KH. Solvent effects on intramolecular hydrophobic ligand - ligand interactions in binary and ternary complexes. Inorg Chim Acta 1985;100:151-64. doi: 10.1016/S0020-1693(00)88303-610.1016/S0020-1693(00)88303-6Search in Google Scholar

10. Aoki K, Yamazaki H. A model for coenzyme-metal ionapoenzyme interactions: crystal structure of the ternary complex [(thiamine pyrophosphate)(1,10-phenanthroline) aquacopper]-dinitrate-water. J Am Chem Soc 1980;102:6878-80. doi: 10.1021/ja00542a05110.1021/ja00542a051Search in Google Scholar

11. Yamauchi O, Odani A. Structure-stability relationship in ternary copper(II) complexes involving aromatic amines and tyrosine or related amino acids. Intramolecular aromatic ring stacking and its regulation through tyrosine phosphorylation. J Am Chem Soc 1985;107:5938-45. doi: 10.1021/ ja00307a01910.1021/ja00307a019Search in Google Scholar

12. Sigel H. Intramolecular equilibria in metal ion complexes of artificial nucleotide analogues with antiviral properties. A case study. Coord Chem Rev 1995;144:287-319. doi: 10.1016/0010-8545(95)01158-L10.1016/0010-8545(95)01158-LSearch in Google Scholar

13. Yajima T, Takamido R, Shimazaki Y, Odani A, Nakabayashi Y, Yamauchi O. π-π Stacking assisted binding of aromatic amino acids by copper(II) - aromatic diimine complexes. Effects of ring substituents on ternary complex stability. Dalton Trans 2007;21:299-307. doi: 10.1039/B612394E10.1039/B612394ESearch in Google Scholar

14. Rouvray DE. The modeling of chemical phenomena using topological indices. J Comput Chem 1987;8:470-80. doi: 10.1002/jcc.54008042710.1002/jcc.540080427Search in Google Scholar

15. Trinajstić N. Chemical Graph Theory. 2nd ed. Boca Raton (FL): CRC Press; 1992.Search in Google Scholar

16. Todeschini R, Consonni V. Handbook of Molecular Descriptors. Weinheim: Wiley-VCH; 2000.10.1002/9783527613106Search in Google Scholar

17. Gutman I. Degree-based topological indices. Croat Chem Acta 2013;86:351-61. doi: 10.5562/cca229410.5562/cca2294Search in Google Scholar

18. Raos N, Miličević A. Estimation of stability constants of coordination compounds using models based on topological indices. Arh Hig Rada Toksikol 2009;60:123-8. doi: 10.2478/10004-1254-60-2009-192310.2478/10004-1254-60-2009-192319329384Search in Google Scholar

19. Miličević A, Raos N. Estimation of stability of coordination compounds by using topological indices. Polyhedron 2006;25:2800-8. doi: 10.1016/j.poly.2006.04.01210.1016/j.poly.2006.04.012Search in Google Scholar

20. Miličević A, Raos N. Influence of chelate ring interactions on copper(II) chelate stability studied by connectivity index functions. J Phys Chem A 2008;112:7745-9. doi: 10.1021/ jp802018m10.1021/jp802018m18665572Search in Google Scholar

21. Miličević A, Raos N. A model to estimate stability constants of amino acid chelates with Cu(II) and Ni(II) at different ionic strengths. J Mol Liq 2012;165:139-42. doi: 0.1016/j. molliq.2011.11.00110.1016/j.molliq.2011.11.001Search in Google Scholar

22. Miličević A, Raos N. Estimation of stability constants of mixed copper(II) chelates using valence connectivity index of the 3rd order derived from two molecular graph representations. Acta Chim Slov 2009;56:373-8.Search in Google Scholar

23. Miličević A, Raos N. Empirical model for the stability constants of acetate mono-complexes with La3+, Nd3+, Gd3+, and Yb3+ at different temperatures and ionic strengths. J Mol Liq 2013;177:60-2. doi: 10.1016/j.molliq.2012.09.00310.1016/j.molliq.2012.09.003Search in Google Scholar

24. Miličević A, Raos N. Stability prediction of Cu2+, Ni2+ and Zn2+ N-salicylidene-aminoacidato complexes by models based on connectivity index 3χv. Cent Eur J Chem 2014;12:74-9. doi: 10.2478/s11532-013-0345-x10.2478/s11532-013-0345-xSearch in Google Scholar

25. Miličević A, Raos N. Comparison of two methods for the estimation of stability of copper(II) bis-complexes with aromatic ligands relevant to Alzheimer’s disease. Arh Hig Rada Toksikol 2013;64:539-45. doi: 10.2478/10004-1254-64-2013-241810.2478/10004-1254-64-2013-241824384760Search in Google Scholar

26. Miličević A, Raos N. Estimation of stability constants of copper(II) and nickel(II) chelates with dipeptides by using topological indices. Polyhedron 2008;27:887-92. doi: 10.1016/j.poly.2007.11.01710.1016/j.poly.2007.11.017Search in Google Scholar

27. Miličević A, Raos N. Estimation of stability constants with connectivity index: development of bivariate and multivariate linear models for copper(II) chelates with oligopeptides. Croat Chem Acta 2009;82:633-9.Search in Google Scholar

28. Miličević A, Raos N. Stability prediction of copper(II) complexes with peptides containing cysteinic disulfide bridge by models based on the connectivity index 3χv. J Coord Chem 2014;67:623-9. doi: 10.1080/00958972.2014.88871610.1080/00958972.2014.888716Search in Google Scholar

29. Tetko IV, Gasteiger J, Todeschini R, Mauri A, Livingstone D, Ertl P, Palyulin VA, Radchenko EV, Zefirov NS, Makarenko AS, Tanchuk VY, Prokopenko VV. Virtual computational chemistry laboratory-design and description. J Comput Aid Mol Des 2005;19:453-63. doi: 10.1007/ s10822-005-8694-y10.1007/s10822-005-8694-y16231203Search in Google Scholar

30. VCCLAB, Virtual Computational Chemistry Laboratory [displayed 23 April 2015]. Available at http://www.vcclab. orgSearch in Google Scholar

31. National Cancer Institute. Online SMILES Translator and Structure File Generator [displayed 23 April 2015]. Available at http://cactus.nci.nih.gov/services/translate/Search in Google Scholar

32. Kier LB, Hall LH. Molecular connectivity VII: Specific treatment to heteroatoms. J Pharm Sci 1976;65:1806-9. PMID: 103266710.1002/jps.26006512281032667Search in Google Scholar

33. Kier LB, Hall LH. Molecular Connectivity in Chemistry and Drug Research. New York: Academic Press; 1976.Search in Google Scholar

34. Kier LB, Hall LH. Molecular Connectivity in Structure- Activity Analysis. New York: Willey; 1986.Search in Google Scholar

35. Randić M. On history of the Randic index and emerging hostility toward chemical graph theory. MATCH Commun Math Comput Chem 2008;59:5-124.Search in Google Scholar

36. Lučić B, Trinajstić N. Multivariate regression outperforms several robust architectures of neural networks in QSAR modeling. J Chem Inf Comput Sci 1999;39:121-32. doi: 10.1021/ci980090f 10.1021/ci980090fSearch in Google Scholar

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