Abstract
It has been generally observed in our work that molecular descriptors derived from a molecular graph theory or topological representation of structure play an important and often key role in many QSAR and QSPR models we have developed. These descriptors do not only provide the means to generate a good fit to the observed data used to train the models, but they also provide information that is needed to generate a clear physical interpretation of the underlying structure–activity or property relationships. In addition, these descriptors provide a conformation-independent method of measuring the key features of molecular structure that affect the observed properties of the molecules. These characteristics are exemplified in a model developed to predict critical micelle concentration (CMC). A model is described that exhibits excellent predictive strength, is independent of conformation of the structures used, and that yields a great deal of detail regarding the underlying structure–property relationship driving the observed CMC.














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Abbreviations
- 2D:
-
2-Dimensional
- 3D:
-
3-Dimensional
- CMC:
-
Critical micelle concentration
- LogCMC:
-
Base-10 logarithm of the CMC
- CPSA:
-
Charged partial surface area
- HAS:
-
Hydrophobic surface area
- PLS:
-
Partial least squares, or projection of latent structures
- PRESS:
-
Predicted sum of squared (error)
- QSAR:
-
Quantitative Structure–Activity Relationship
- QSPR:
-
Quantitative Structure–Property Relationship
- SIR:
-
Structure information representation
- SPR:
-
Structure–property relationship
- VIF:
-
Variance inflation factor
References
Stanton DT (2003) J Chem Inf Comput Sci 43:1423
Hall LH (2004) Chem Biodiv 1:183
Hall LH, Hall LM (2005) SAR QSAR in Environ Res 16:13
Kier LB, Hall LH (2005) Chem Biodiv 2:1428
Kubinyi H (1993) QSAR: Hansch analysis and related approaches. VCH, New York, pp 50–53
Rosen MJ (1989) Surfactants and interfacial phenomena. Wiley, New York, p 108
Tanford C (1973) The hydrophobic effect: formation of micelles and biological membranes. Wiley, New York, p 43
Rosen MJ (1989) Surfactants and interfacial phenomena. Wiley, New York, pp 116–132
Mukerjee P, Mysels KJ (1971) Critical micelle concentrations of aqueous surfactant systems, National Standard Reference Data Service, United States National Bureau of Standards, Washington, DC, pp 51–65
Evans HC (1956) J Chem Soc 579
Huibers PDT, Lobanov VS, Katritzky AR, Shah DO, Kaeelson M (1997) J Colloid Interface Sci 187:113
van Os NM, Daane GJ, Bolsman TABM (1988) J Colloid Interface Sci 123:267
van Os NM, Daane GJ, Bolsman TABM (1987) J Colloid Interface Sci 115:402
Gershman JW (1957) J Phys Chem 61:581
Fenghänel E, Ortman W, Behrmann K, Willscher S (1987) J Phys Chem 91:3700
Schick MJ, Fowkes FM (1957) J Phys Chem 61:1062
Lianos P, Lang J (1983) J Colloid Interface Sci 96:222
Jalali-Heravi M, Konouz E (2000) J Surfactants Deterg 3:47
Katrizky AR, Pacureanu L, Dobchev D, Karelson M (2007) J Chem Inf Model 47:782
Gasteiger-Huckel partial atomic charges are calculated using the Gasteiger-Marsili method to calculate the σ-electron contributions and the Huckel method for calculating the π-electron contributions, Sybyl Version 6.3 Force Field Manual, Tripos, St. Louis, MO, USA, 1996, p 290
Stuper AJ, Jurs PC (1976) J Chem Inf Comput Sci 2:99
Jurs PC, Chou JT, Yuan M (1979) In: Olson RC, Christoffersen RE (eds) Computer-assisted drug design. American Chemical Society, Washington DC, pp 103–129
Ivanciuc O, Balaban AT (1999) In: Devillers J, Balaban AT (eds) Topological indices and related descriptors in QSAR and QSPR. Gordon and Breach, The Netherlands, pp 59–167
Pearlman RS (1980) In: Yalkowsky SH, Sinkula AA, Valvani SC (eds) Physical chemical properties of drugs. Marcel Dekker, New York
Brugger WE, Stuper AJ, Jurs PC (1976) J Chem Inf Comput Sci 16:105
Todeschini R, Consonni V (2000) In: Mannhold R, Kubinyi H, Timmerman H (eds) Handbook of molecular descriptors. Wiley-VCH, Weinheim, Federal Republic of Germany, p 352
Dixon SL, Jurs PC (1992) J Comput Chem 13:492
Stanton DT, Jurs PC (1990) Anal Chem 62:2323
Stanton DT, Dimitrov S, Grancharov V, Mekenyan OG (2002) SAR QSAR Environ Res 13:341
Stanton DT, Mattioni B, Knittel JJ, Jurs PC (2004) J Chem Inf Comput Sci 44:1010
Stanton DT (2000) J Chem Inf Comput Sci 40:81
Sutter JM, Jurs PC (1995) Data Handl Sci Tech 15:111
Luke BT (1996) In: Devillers J (ed) Genetic algorithms in molecular modeling. Academic Press, New York NY, p 35–66
Kutner MH, Nachtshein CJ, Neter J, Li W (2005) Applied linear statistical models, 5th edn. McGraw-Hill Irwin, New York, p 266
Kutner MH, Nachtshein CJ, Neter J, Li W (2005) Applied linear statistical models, 5th edn. McGraw-Hill Irwin, New York, p 268
Kutner MH, Nachtshein CJ, Neter J, Li W (2005) Applied linear statistical models, 5th edn. McGraw-Hill Irwin, New York, pp 408–410
Geladi P, Kowalski BR (1986) Anal Chim Acta 185:1
Stanton DT, Egolf LM, Jurs PC (1992) J Chem Inf Comput Sci 32:306
Wildman SA, Crippen GM (1999) J Chem Inf Comput Sci 39:868
Kier LB, Hall LH (1976) Molecular connectivity in chemistry and drug research. Academic, New York
Kier LB, Hall LH (1986) Molecular connectivity in structure–activity analysis. Wiley, New York
Tanford C (1973) The hydrophobic effect: formation of micelles and biological membranes. Wiley, New York, p 36
Kier LB, Hall LH (1991) Quant Struct-Act Relat 10:134
Hall LH, Kellogg GE, Molconn-Z 3.50 Users Guide, EduSoft, 1999, Appendix II. Retrieved from http://www.edusoft-lc.com/molconn/manuals/350/appII.html, 30/9/2007
Kier LB, Hall LH (1999) Molecular structure description: the electrotopological state. Academic Press, London
Lin IJ, Moudgil BM, Somasundaran P (1974) Colloid Polym Sci 252:407
Shinoda K, Hato M, Hayashi T (1972) J Phys Chem 76:909
Rousseeuw PJ, Leroy AM (1987) Robust regression and outlier detection. Wiley, New York
Kutner MH, Nachtshein CJ, Neter J, Li W (2005) Applied linear statistical models, 5th edn. McGraw-Hill Irwin, New York, pp 398–400
Acknowledgements
The author wishes to thank Dr. M. Lynch of Procter & Gamble for providing access to the Mukerjee and Mysels compilation of CMC data, and also Dr. K. Anderson of Procter & Gamble for providing the result from the molecular dynamics simulation of sodium dodecyl sulfate.
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Stanton, D.T. On the importance of topological descriptors in understanding structure–property relationships. J Comput Aided Mol Des 22, 441–460 (2008). https://doi.org/10.1007/s10822-008-9204-9
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DOI: https://doi.org/10.1007/s10822-008-9204-9