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2004 | 2 | 3 | 500-523
Tytuł artykułu

QSPR modeling aqueous solubility of polychlorinated biphenyls by optimization of correlation weights of local and global graph invariants

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Aqueous solubilities of polychlorinated biphenyls have been correlated with topological molecular descriptors which are functions of local and global invariants of labeled hydrogen filled graphs. Morgan extended connectivity and nearest neighboring codes have been used as local graph invariants. The number of chlorine atoms in biphenyls has been employed as a global graph invariant. Present results show that taking into account correlation weights of global invariants gives quite reasonable improvement of statistical characteristics for the prediction of aqueous solubilities of polychlorinated biphenyls.
Wydawca

Czasopismo
Rocznik
Tom
2
Numer
3
Strony
500-523
Opis fizyczny
Daty
wydano
2004-09-01
online
2004-09-01
Twórcy
  • INIFTA, Departmento de Química Facultad de Ciencias Exactas, Universidad Nacional de La Plata, Diag. 113 y 64, Suc. 4, C.C. 16, 1900, La Plata, Argentina, castro@quimica.unlp.edu.ar
  • Algorithm-Engineering Institute, Uzbekistan Academy of Sciences, F. Khodjaev Street 25, 700125, Tashkent, Uzbekistan
  • Algorithm-Engineering Institute, Uzbekistan Academy of Sciences, F. Khodjaev Street 25, 700125, Tashkent, Uzbekistan
autor
  • Algorithm-Engineering Institute, Uzbekistan Academy of Sciences, F. Khodjaev Street 25, 700125, Tashkent, Uzbekistan
Bibliografia
  • [1] F. Wania and D. Mackay: “Global Fractionation and Cold Condensation of Low Volatility Organochlorine Compounds in Polar Regions”, AMBIO, Vol. 22, (1993), pp. 10–18.
  • [2] Agency for Toxic Substances and Disease Registry (ATSDR), 1993. Toxicological Profile for Selected PCBs.. Atlanta: U.S. Public Health Service. U.S. Department of Health and Human Services.
  • [3] J.D. McKinney and C.L. Waller: “Polychlorinated Biphenyls as Hormonally Active Structural Analogues”, Environ. Health Perspect., Vol. 102, (1994), pp. 290–297. [Crossref]
  • [4] A. Brouwer, M.P. Longnecker, L.S. Birnbaum, J. Cogliano, P. Kostyniak, J. Moore, S. Schantz and G. Winneke: “Characterization of Potential Endocrine-Related Health Effects at Low-Dose Levels of Expopsure to PCBs”, Environ. Health Perspect., Vol. 107, (1999), pp. 639–649. [Crossref]
  • [5] U.S. Environmental Protection Agency, 1994. Integrated Risk Information System (IRIS) on PCBs. Cincinnati, OH: Environmental Criteria and Assesment Office. Office of Health and Environmental Assessment. Office of Research and Development.
  • [6] U.S. Environmental Protection Agency. 1996. PCBs: Cancer Dose-Response Assessment and Application to Environmental Mixtures, Report EPA, 600P-96002F.
  • [7] P. Ruelle and U.W. Kesserling: “Aqueous Solubility Prediction of Environmentally Important Chemicals from the Mobile Order Thermodynamic”, Chemosphere, Vol. 34, (1997), pp. 275–298. http://dx.doi.org/10.1016/S0045-6535(96)00377-3[Crossref]
  • [8] P. Ruelle, A. Cuendet and U.W. Kesselring: “Hydrophobic and Solvation Effects on the Solubility of Hydroxysteroids in Various Solvents: Quantitative and Qualitative Assessment by Application of the Mobile Order and Disorder Theory”, Perspective Drug Discovery Design, Vol. 18, (2000), pp. 61–112, and references herein. http://dx.doi.org/10.1023/A:1008703513479[Crossref]
  • [9] W.J. Doucette and A.W. Andren: “Estimation of Octanol/Water Partition Coefficients: Evaluation of Six Methods for Highly Hydrophobic Aromatic Hydrocarbons”, Chemosphere, Vol. 17, (1988), pp. 345–359. http://dx.doi.org/10.1016/0045-6535(88)90226-3[Crossref]
  • [10] R. Kuhne, R.-U. Ebert, F. Kleint, G. Schmidt and G. Schuurmann: “Group Contribution Methods to Estimate Water Solubility of Organic Chemicals”, Chemosphere, Vol. 30, (1995), pp. 2061–2077. http://dx.doi.org/10.1016/0045-6535(95)00084-L[Crossref]
  • [11] T.T. Blair, E. Gifford, W.E. Acree, Jr. and C.-C. Tsai: “Quantitative Structure-Property Relationships for Aqueous Solubilities of Halogenated Aromatic Compounds”, Phys. Chem. Liq., Vol. 24, (1992), pp. 137–160. [Crossref]
  • [12] S. Puri, J.S. Chickos and W.J. Welsh: “Three-Dimensional Quantitative Structure -Property Relationship (3D-QSPR) Models for Prediction of Thermodynamic Properties of Polychlorinated Biphenyls (PCBs): Enthalpies of Fusion and Their Application to Estimates of Enthalpies of Sublimation and Aqueous Solubilities”, J. Chem. Inf. Comput. Sci., Vol. 43, (2003), pp. 55–62. http://dx.doi.org/10.1021/ci0200164[Crossref]
  • [13] R.D. Cramer III, D.E. Patterson and J.E. Bunce: “Comparative Molecular Field Analysis (CoMFA). l. Effect of Shape on Binding of Steroids to Carriers Proteins”, J. Am. Chem. Soc., Vol. 110, (1988), pp. 5959–5967. http://dx.doi.org/10.1021/ja00226a005[Crossref]
  • [14] G. Klebe: “Structural Alignment of Molecules”, In: H. Kubinyi (Ed.), 3D-QSAR in Drug Design, ESCOM, Leiden, 1993, pp. 173–199.
  • [15] T.I. Oprea and C.L. Waller: “Theoretical and Practical Aspects of Three Dimensional Quantitative Structure-Activity Relationships”, In: K.B. Lipkowitz and D.B. Boyd(Eds.): Reviews in Computational Chemistry, Vol. 11, Wiley, New York, 1997, pp. 127–182.
  • [16] P.J. Peruzzo, D.J.G. Marino, E.A. Castro and A.A. Toropov: “Calculation of pK Values of Flavylium Salts from the Optimization of Correlation Weights of Local Graph Invariants”, J. Mol. Struct. THEOCHEM, Vol. 572, (2001), pp. 53–60. http://dx.doi.org/10.1016/S0166-1280(01)00559-0[Crossref]
  • [17] D.J.G. Marino, P.J. Peruzzo, E.A. Castro and A.A. Toropov: “QSAR Carcinogenic Study of Methylated Polycyclic Aromatic Hydrocarbons Based on Topological Descriptors Derived from Distance Matrices and Correlation Weights of Local Graph Invariants”, Internet Electron. J. Mol. Des., Vol. 1, (2002), pp. 108–133, http://www.biochempress.com.
  • [18] A.A. Toropov and A.P. Toropova: “Optimization of Correlation Weights of the Local Graph Invariants: Use of the Enthalpies of Formation of Complex Compounds for the QSPR Modeling”, Russ. J. Coord. Chem., Vol. 24, (1998), pp. 81–85.
  • [19] A.A. Toropov and A.P. Toropova: “Modeling of Acyclic Compounds Normal Boiling Points by Correlation Weighting of Nearest Neighboring Codes”, J. Mol. Struct. THEOCHEM, Vol. 581, (2002), pp. 11–15. http://dx.doi.org/10.1016/S0166-1280(01)00733-3[Crossref]
  • [20] A.A. Toropov, O.M. Nabiev, P.R. Duchowicz, E.A. Castro and F. Torrens: “QSPR Modeling of Hydrocarbon Dipole Moments by Means of Correlation Weighting of Local Graph Invariants”, J. Theor. Comp. Chem., Vol. 2, (2003), pp. 139–146. http://dx.doi.org/10.1142/S0219633603000409[Crossref]
  • [21] D.J.G. Marino, P.J. Peruzzo, E.A. Castro and A.A. Toropov: “QSPR Modeling of Lipophilicity by Means of Correlation Weights of Local Graph Invariants”, Internet Elect. J. Molec. Design, Vol. 2, (2003), pp. 334–347.
  • [22] A.A. Toropov, P.R. Duchowicz and E.A. Castro: “Structure-Toxicity Relationships for Aliphatic Compounds Based on Correlation Weighting of Local Graph Invariants”, Int. J. Mol. Sci., Vol. 2, (2003), pp. 272–283. http://dx.doi.org/10.3390/i4050272[Crossref]
  • [23] P.R. Duchowicz, E.A. Castro and A.A. Toropov: “QSPR Modeling of Normal Boiling Points of Aldehydes, Ketones and Esters by Means of Nearest Neighboring Codes Correlation Weighting”, J. Arg. Chem. Soc., Vol. 90, (2002), pp. 91–107.
  • [24] P.R. Duchowicz, E.A. Castro and A.A. Toropov: “Improved QSPR Analysis of Standard Entropy of Acyclic and Aromatic Compounds Using Optimized Correlation Weights of Linear Graph Invariants”, Comp. Chem., Vol. 26, (2002), pp. 327–332. http://dx.doi.org/10.1016/S0097-8485(01)00121-8[Crossref]
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.-psjd-doi-10_2478_BF02476204
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