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On the importance of topological descriptors in understanding structure–property relationships

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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

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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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Correspondence to David T. Stanton.

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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

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