The role of the dominant descriptor in targeted quantitative structure property relationships

The targeted quantitative structure–property relationship (TQSPR) method of Brauner et al. [2006. A structurally “targeted” QSPR method for property prediction. Industrial & Engineering Chemistry Research 45, 8430–8437] is analyzed in this study with examples involving prediction of critical tem...

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Bibliographic Details
Published in:Chemical engineering science 2007-11, Vol.62 (22), p.6222-6233
Main Authors: Shacham, Mordechai, Kahrs, Olaf, Cholakov, Georgi St, Stateva, Roumiana P., Marquardt, Wolfgang, Brauner, Neima
Format: Article
Language:English
Subjects:
Applied sciences
Chemical engineering
Computational chemistry
Exact sciences and technology
Parameter identification
Process design
Product design
Property prediction
QSPR
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Summary:The targeted quantitative structure–property relationship (TQSPR) method of Brauner et al. [2006. A structurally “targeted” QSPR method for property prediction. Industrial & Engineering Chemistry Research 45, 8430–8437] is analyzed in this study with examples involving prediction of critical temperatures of hydrocarbons. Targeted are 108 hydrocarbons, for which experimental critical temperature values can be obtained from published sources. Each hydrocarbon structure is represented by 1630 calculated values of molecular descriptors. The availability of a wide variety of molecular descriptors and small training sets comprising compounds structurally similar to the target enables the detection of one, dominant descriptor, which is well correlated with a particular property and is sufficient to serve as a single predictor for this property. The analysis of the relationship between the dominant descriptor and property values for the training set and the target compound enables better understanding of the main causes for increased prediction errors. Based on this analysis, new quantitative indicators for assessing the reliability of the predicted property value are proposed, which may reduce considerably the uncertainty associated with property prediction.
ISSN:0009-2509
1873-4405
DOI:10.1016/j.ces.2007.07.029