Literature DB >> 10955520

QSPR modeling: graph connectivity indices versus line graph connectivity indices

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Abstract

Five QSPR models of alkanes were reinvestigated. Properties considered were molecular surface-dependent properties (boiling points and gas chromatographic retention indices) and molecular volume-dependent properties (molar volumes and molar refractions). The vertex- and edge-connectivity indices were used as structural parameters. In each studied case we computed connectivity indices of alkane trees and alkane line graphs and searched for the optimum exponent. Models based on indices with an optimum exponent and on the standard value of the exponent were compared. Thus, for each property we generated six QSPR models (four for alkane trees and two for the corresponding line graphs). In all studied cases QSPR models based on connectivity indices with optimum exponents have better statistical characteristics than the models based on connectivity indices with the standard value of the exponent. The comparison between models based on vertex- and edge-connectivity indices gave in two cases (molar volumes and molar refractions) better models based on edge-connectivity indices and in three cases (boiling points for octanes and nonanes and gas chromatographic retention indices) better models based on vertex-connectivity indices. Thus, it appears that the edge-connectivity index is more appropriate to be used in the structure-molecular volume properties modeling and the vertex-connectivity index in the structure-molecular surface properties modeling. The use of line graphs did not improve the predictive power of the connectivity indices. Only in one case (boiling points of nonanes) a better model was obtained with the use of line graphs.

Entities:  

Year:  2000        PMID: 10955520     DOI: 10.1021/ci990119v

Source DB:  PubMed          Journal:  J Chem Inf Comput Sci        ISSN: 0095-2338


  1 in total

1.  New polynomial-based molecular descriptors with low degeneracy.

Authors:  Matthias Dehmer; Laurin A J Mueller; Armin Graber
Journal:  PLoS One       Date:  2010-07-30       Impact factor: 3.240

  1 in total

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