Journal of Mathematical Chemistry

, Volume 51, Issue 10, pp 2718–2730

Information content of molecular graph and prediction of gas phase thermal entropy of organic compounds

Original Paper

DOI: 10.1007/s10910-013-0233-9

Cite this article as:
Raychaudhury, C. & Pal, D. J Math Chem (2013) 51: 2718. doi:10.1007/s10910-013-0233-9


Entropy is a fundamental thermodynamic property that has attracted a wide attention across domains, including chemistry. Inference of entropy of chemical compounds using various approaches has been a widely studied topic. However, many aspects of entropy in chemical compounds remain unexplained. In the present work, we propose two new information-theoretical molecular descriptors for the prediction of gas phase thermal entropy of organic compounds. The descriptors reflect the bulk and size of the compounds as well as the gross topological symmetry in their structures, all of which are believed to determine entropy. A high correlation (\(\hbox {r}^{2} = 0.92\)) between the entropy values and our information-theoretical indices have been found and the predicted entropy values, obtained from the corresponding statistically significant regression model, have been found to be within acceptable approximation. We provide additional mathematical result in the form of a theorem and proof that might further help in assessing changes in gas phase thermal entropy values with the changes in molecular structures. The proposed information-theoretical molecular descriptors, regression model and the mathematical result are expected to augment predictions of gas phase thermal entropy for a large number of chemical compounds.


Thermal entropy Molecular descriptor Information content Regression model 

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Bioinformatics Centre and Supercomputer Education and Research CentreIndian Institute of ScienceBangaloreIndia

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