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Prediction of Physicochemical Properties of Organic Compounds from Molecular Structure

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Book cover Physical Property Prediction in Organic Chemistry

Abstract

Relationships between molecular structure and biological activity or molecular structure and physical properties can be investigated for large sets of organic compounds using computer-assisted methods. Our research involves the design, implementation, testing, and application of computer software for the purpose of discovering structure-property and structure-activity relationships and thus developing the capability to predict properties for unknown compounds. The approach involves the graphical entry and storage of structures, three-dimensional molecular modeling, molecular structure descriptor generation, and analysis of the descriptors using pattern recognition methods or multivariate statistical methods. The computer-generated structural descriptors represent the molecules topologically (e.g., path counts, molecular connectivity), geometrically (e.g., molecular volume, surface area, principal moments), electronically (e.g., partial charges, bond orders), and physicochemically (e.g., log P, molar refractivity). A large, fully-integrated, interactive software system, called ADAPT for Automated Data Analysis and Pattern recognition Toolkit, has been developed to make such S AR and SPR research convenient. ADAPT is under continual development through the introduction of new molecular structure descriptors and new analysis methods. A number of successful studies have been reported in property prediction (prediction of boiling points of olefins, GC and HPLC retention indices, and simulation of 13C NMR chemical shifts) and in the structure-activity area (pharmaceutical drugs, olfactory stimulants, mutagens, carcinogens, anti-tumor drugs). Examples of current studies include: S AR of anti-tumor retinoids, carcinogenicity of N-nitroso compounds, HPLC retention indices of PACs and the importance of molecular shape, GC retention indices of polychlorinated biphenyls, 13C NMR simulation of substituted norbornanes.

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References Cited

  1. R.C. Reid, J.M. Prausnitz, T.K. Sherwood, Properties of Gases and Liquids, 3rd Ed., McGraw-Hill, New York, 1977.

    Google Scholar 

  2. W.J. Lyman, W.F. Reehl, D.H. Rosenblatt, Handbook of Chemical Property Estimation Methods, McGraw-Hill, New York, 1982.

    Google Scholar 

  3. A.J. Stuper, W.E. Brugger, P.C. Jurs, Computer Assisted Studies of Chemical Structure and Biological Function, Wiley-Interscience, New York, 1979.

    Google Scholar 

  4. N.L. Allinger and Y.H. Yuh, Molecular Mechanics, Operating Instructions for MM2 and MMP2 Programs, 1977 Force Field, Quantum Chemistry Program Exchange, QCPE Program No. 395, 1980.

    Google Scholar 

  5. U. Burkert and N.L. Allinger, Molecular Mechanics, American Chemical Society, Washington, DC, 1982.

    Google Scholar 

  6. L.B. Kier and L.H. Hall, Molecular Connectivity in Structure-Activity Analysis, John Wiley and Sons, Inc., New York, 1986.

    Google Scholar 

  7. L.B. Kier, A Shape Index from Molecular Graphs, Quant. Struct-Act. Relat., 4: 109 (1985).

    Article  CAS  Google Scholar 

  8. L.B. Kier, Shape Indexes of Orders One and Three from Molecular Graphs, Quant. Struct.-Act. Relat., 5:1–7(1986).

    Article  CAS  Google Scholar 

  9. L.B. Kier, Distinguishing Atom Differences in a Molecular Graph Shape Index, Quant. Struct.- Act. Relat., 5: 7–12 (1986).

    Article  CAS  Google Scholar 

  10. A.T. Balaban, Highly Discriminating Distance-Based Topological Index, Chem. Phys. Letters 89: 399–404.

    Google Scholar 

  11. P.A. Edwards and P.C. Jurs, Correlation of Odor Intensities with Structural Properties of Odorants, Chemical Senses, in review.

    Google Scholar 

  12. G. Del Re, A Simple MO-LCAO Method for the Calculation of Charge Distributions in Saturated Organic Molecules, Jour. Chem. Soc., 4031–4040 (1958).

    Google Scholar 

  13. N.J. Nilsson, Learning Machines, McGraw-Hill Book Co., New York, 1965.

    Google Scholar 

  14. J.T. Tou and R.C. Gonzalez, Pattern Recognition Principles, Addison-Wesley, Reading, Mass., 1974.

    Google Scholar 

  15. K. Varmuza, Pattern Recognition in Chemistry, Springer-Verlag, Berlin, 1980.

    Google Scholar 

  16. D.D. Wolff and M.L. Parsons, Pattern Recognition Approach to Data Interpretation, Plenum Press, New York, 1983.

    Google Scholar 

  17. M.A. Sharaf, D.L. Illman, B.R. Kowalski, Chemometrics, Wiley, New York, 1986.

    Google Scholar 

  18. D.L. Massart, B.G.M. Vandeginste, S.N. Deming, Y. Michotte, L. Kaufman, Chemometrics: A Textbook, Elsevier Scientific Publishers, Amsterdam, 1987.

    Google Scholar 

  19. I. Moriguchi, K. Komatsu, Y. Matushita, Adaptive Least Squares Method Applied to Structure-Activity Correlation of Hypotensive N-Alkyl-N″-cyano-N′-pyridylguanidines, Jour. Med. Chem., 23: 20–26 (1980).

    Article  CAS  Google Scholar 

  20. W.T. Williams and G.N. Lance, Hierarchical Classificatory Methods, in Statistical Methods for Digital Computers, K. Enslein, A. Ralston, H.S. Wilf (Eds.), Wiley-Interscience, New York, 1975.

    Google Scholar 

  21. G.H. Ball and D J. Hall, Isodata, an Iterative Method of Multivariate Analysis and Pattern Classification, Proceedings of the IFIPS Congress, 1965.

    Google Scholar 

  22. J. MacQueen, Some Methods for Classification and Analysis of Multivariate Data, Proc. Of the 5th Berkeley Symposium on Probability and Statistics, University of California Press, Berkeley, CA, 1967.

    Google Scholar 

  23. B.G. Batchelor and B.R. Wilkins, Method for Location of Clusters of Patterns to Initialize a Learning Machine, Electronics Letters, 5, 481–483 (1969).

    Article  Google Scholar 

  24. N.R. Draper and H. Smith, Applied Regression Analysis, 2nd. Ed., Wiley, 1981.

    Google Scholar 

  25. D. A. Belsley, E. Kuh, R.E. Welsch, Regression Diagnostics: Identifying Influential Data and Sources of Collinearity, Wiley, 1980.

    Book  Google Scholar 

  26. G.M. Furnival and R.W. Wilson, Jr., Regressions by Leaps and Bounds, Technometics, 16: 499 (1974).

    Article  Google Scholar 

  27. D.W. Marquardt and R.D. Snee, Ridge Regression in Practice, Amer. Stat., 29: 3–20 (1975).

    Article  Google Scholar 

  28. J.M. Chambers, W.S. Cleveland, B. Kliener, P. A. Tukey, Graphical Methods for Data Analysis, Duxbury Press, Boston, 1983.

    Google Scholar 

  29. G.P. McCabe, Jr., Computations for Variable Selection in Discriminant Analysis, Technometrics, 17: 103–109 (1975).

    Article  Google Scholar 

  30. R.H. Rohrbaugh and P.C. Jurs, Prediction of Gas Chromatographic Retention Indexes of Polycyclic Aromatic Compounds and Nitrated Polycyclic Aromatic Compounds, Anal. Chem. 58: 1210–1212 (1986).

    Article  CAS  Google Scholar 

  31. R.H. Rohrbaugh and P.C. Jurs, Prediction of Gas Chromatographic Retention Indexes of Selected Olefins, Anal. Chem. 57: 2770–2773 (1985).

    Article  CAS  Google Scholar 

  32. R.H. Rohrbaugh and P.C. Jurs, Molecular Shape and the Prediction of High-Performance Liquid Chromatographic Retention Indexes of Polycyclic Aromatic Hydrocarbons, Anal. Chem. 59: 1048–1054 (1987).

    Article  CAS  Google Scholar 

  33. M.N. Hasan and P.C. Jurs, Computer Assisted Prediction of Liquid Chromatographic Retention Indices of Polycyclic Aromatic Hydrocarbons, Anal. Chem. 55: 263–269 (1983).

    Article  CAS  Google Scholar 

  34. P.J. Hansen and P.C. Jurs, Prediction of Olefin Boiling Points from Molecular Structure, Anal. Chem. 59: 2322–2327 (1987).

    Article  CAS  Google Scholar 

  35. Mohamed Noor Hasan and P.C. Jurs, Computer-Assisted Prediction of Gas Chromatographic Retention Indexes of Polychlorinated Biphenyls, Anal. Chem., in press.

    Google Scholar 

  36. N.R. Greiner, L.E. Wangen, P.C. Jurs, R. Heaton, G. Peterson, C.B. Storm, M. Phillips, A Chemometrics Approach to Impact Sensitivity, Working Group Meeting on Sensitivity of Explosives, CETR, Socorro, NM, Mar 1987.

    Google Scholar 

  37. R.H. Rohrbaugh and P.C. Jurs, Descriptions of Molecular Shape Applied to StructureActivity and Structure-Property Relationship Studies, Anal. Chim. Acta 199: 99–109 (1987).

    Article  CAS  Google Scholar 

  38. L.C. Sander and S.A. Wise, Investigations of Selectivity in RPLC of Polycyclic Aromatic Hydrocarbons, in Advances in Chromatography, J.C. Giddings (Ed.), Vol. 25, 1986, pp. 139–218.

    Google Scholar 

  39. R.S. Pearlman, Molecular Surface Areas and Volumes and Their Use in Structure/Activity Relationships, in Physical Chemical Properties of Drugs, S.H. Yalkowsky, A. A. Sinkula, S.C. Valvani (Eds.), Marcel Dekker, New York 1980.

    Google Scholar 

  40. L.C. Sander and S.A. Wise, Synthesis and Characterization of Polymeric C-18 Stationary Phases for Liquid Chromatography, Anal. Chem. 56: 504–510 (1984).

    Article  CAS  Google Scholar 

  41. A. Radecki, H. Lamparczyk, R. Kaliszan, A Relationship between the Retention Indices on Nematic and Isotropic Phases and the Shape of Polycyclic Aromatic Hydrocarbons, Chromatographia, 12: 595–599 (1979).

    Article  CAS  Google Scholar 

  42. T.R. Stouch and P.C. Jurs, A Simple Method for the Representation, Quantification, and Comparison of Volumes and Shapes of Chemical Compounds, Jour. Chem. Inf. Comp. Sci. 26: 4–12 (1986).

    Article  CAS  Google Scholar 

  43. TRC Thermodynamic Tables — Hydrocarbons, Thermodynamics Research Center, Texas A&M University, College Station, TX, 1986; Vol. I, Part a.

    Google Scholar 

  44. M.D. Mullin, et al., High-Resolution PCB Analysis: Synthesis and Chromatographic Properties of All 209 PCB Congeners, Environ. Sci. Tech. 18:468–476 (1984).

    Article  Google Scholar 

  45. M.J. Kamlet, The Relationship of Impact Sensitivity with Structure of Organic High Explosives. I. Polynitroaliphatic Explosives, in Proc. 6th Symposium (International) on Detonation, San Diego, CA Aug 1976; ONR Report ACR 221, p. 312.

    Google Scholar 

  46. M.J. Kamlet and H.G. Adolph, The Relationship of Impact Sensitivity with Structure of Organic High Explosives. II. Polynitroaromatic Explosives, Propellants and Explosives, 4: 30–24 (1979).

    Article  CAS  Google Scholar 

  47. M.J. Kamlet and H.G. Adolph, Some Comments Regarding the Sensitivities, Thermal Stabilities, and Explosive Performance Characteristics of Fluorodinitromethyl Compounds, in Proc. 7th Symposium (International) on Detonation, Anapolis, MD, Jun 1981; NSWC MP 82–334, p. 84.

    Google Scholar 

  48. H.G. Adolph, J.R. Holden, D.A. Cichra, Relationships Between the Impact Sensitivity of High Energy Compounds and Some Molecular Properties which Determine their Performance: N, M, and rho(0), NSWC TR 80–495, Apr 1981.

    Google Scholar 

  49. I. Fukuyama, T. Ogawa, A. Miyake, Sensitivity and Evaluation of Explosive Substances, Propellants, Explosives, Pyrotechnics 11: 140–143 (1986).

    Article  CAS  Google Scholar 

  50. Predicting Viscosity from Molecular Structure, Applications Note, Molecular Design, Ltd., 1985.

    Google Scholar 

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© 1988 Springer-Verlag Berlin Heidelberg

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Jurs, P.C., Hasan, M.N., Hansen, P.J., Rohrbaugh, R.H. (1988). Prediction of Physicochemical Properties of Organic Compounds from Molecular Structure. In: Jochum, C., Hicks, M.G., Sunkel, J. (eds) Physical Property Prediction in Organic Chemistry. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-74140-1_16

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  • DOI: https://doi.org/10.1007/978-3-642-74140-1_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-74142-5

  • Online ISBN: 978-3-642-74140-1

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