Literature DB >> 32533372

Predictive potential of eigenvalue-based topological molecular descriptors.

Izudin Redžepović1, Boris Furtula2.   

Abstract

This study is directed toward assessing the predictive potential of eigenvalue-based topological molecular descriptors. The graph energy, Estrada index, resolvent energy, and the Laplacian energy were tested as parameters for the prediction of boiling points, heats of formation, and octanol/water partition coefficients of alkanes. It was shown that an eigenvalue-based molecular descriptor cannot be individually used for successful prediction of these physico-chemical properties, but the first Zagreb index, the number of zeros in the spectrum and the number of methyl groups must be also involved in the models. Performed statistics show that the models constructed using the Estrada index and resolvent energy are significantly better than ones with the energy of a graph and the Laplacian energy. Such a trend is even more noticeable in the case of octanol/water partition coefficients of alkanes.

Entities:  

Keywords:  Boiling points; Graph invariants; Heats of formation; Molecular modeling; Octanol/water partition coefficients

Year:  2020        PMID: 32533372     DOI: 10.1007/s10822-020-00320-2

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN: 0920-654X            Impact factor:   3.686


  1 in total

1.  Prediction of Exchange-Correlation Energy of Graphene Sheets from Reverse Degree-Based Molecular Descriptors with Applications.

Authors:  Mohammed Albadrani; Parvez Ali; Waleed H El-Garaihy; Hassan Abd El-Hafez
Journal:  Materials (Basel)       Date:  2022-04-14       Impact factor: 3.623

  1 in total

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