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Distance-related indexes in the quantitative structure-property relationship modeling
B Lucić1, I Lukovits, S Nikolić
1The Rugjer Boskovic Institute, P.O. Box 180, HR-10002 Zagreb, Croatia, and Chemical Research Center, Hungarian Academy of Sciences, P.O. Box 17, H-1525 Budapest, Hungary.
Journal of Chemical Information and Computer Sciences
|June 21, 2001
Summary
This study models hydrocarbon boiling points using graph theory indices. The best predictive models combine the Hosoya index, detour index, and number of rings for alkanes and cycloalkanes.
Area of Science:
- * Chemical Informatics
- * Physical Organic Chemistry
- * Computational Chemistry
Background:
- * Accurate prediction of boiling points is crucial for chemical process design and safety.
- * Molecular descriptors, particularly graph-based indices, have shown promise in quantitative structure-property relationships (QSPR).
- * Previous work established the utility of Wiener, detour, and Hosoya indices for modeling alkane and cycloalkane boiling points.
Purpose of the Study:
- * To comparatively evaluate known and novel distance-related molecular indices for modeling boiling points.
- * To develop and validate robust structure-boiling point models for diverse sets of acyclic and cyclic hydrocarbons.
- * To identify the most effective combination of descriptors for predicting boiling points.
Main Methods:
- * Utilized a dataset of 180 acyclic and cyclic hydrocarbons (DS-180) and its subsets (DS-76, DS-104).
- * Calculated and assessed a range of distance-related indices: Wiener, hyper-Wiener, detour, hyper-detour, Harary, Pasaréti, Vérhalom, Wiener-sum, inverse Wiener-sum, product-form Wiener index, total number of paths, Hosoya Z index, total walk count, carbon atom count, and ring count.
- * Employed statistical modeling to identify the best predictors of boiling points.
Main Results:
- * The most effective models for predicting boiling points of alkanes and cycloalkanes incorporated the natural logarithm of the cross-products of the Hosoya index and the detour index, and the Pasaréti index and the number of rings.
- * These findings extend and support previous research on the application of graph-based indices in boiling point prediction.
- * The developed models demonstrate high predictive accuracy for the tested hydrocarbon datasets.
Conclusions:
- * Graph-theoretical descriptors, particularly the Hosoya and detour indices combined with the number of rings, are powerful tools for modeling hydrocarbon boiling points.
- * The study validates and extends the use of specific distance-related indices in quantitative structure-property relationship studies.
- * The findings contribute to the development of more accurate and efficient methods for predicting physical properties of chemical compounds.