Skip to main content
Log in

Bonding alkane attributes with topological indices: a statistical intervention

  • Original Paper
  • Published:
Journal of Mathematical Chemistry Aims and scope Submit manuscript

Abstract

This research delves into a comprehensive investigation of a specific group of alkanes, with the primary objective of establishing meaningful associations between their inherent physical attributes and a set of graphical parameters ranging from topological indices to their associated graphical entropies. Though there are countless techniques to relate molecular structure and physical properties of chemical compounds, the pursuit has often been pricey and arduous. With a view to curb the expense and intense labour, this work focuses on attaining some of these properties using graphical interpretations and statistical interventions. Driven by this objective, we compute Sombor index, a recently developed topological tool and some of its variants for all structural isomers of alkanes with carbon range four to nine. Furthermore, our study employs multiple regression analysis to explore their connections with some physical attributes of alkanes while concurrently addressing the challenge posed by multicollinearity. We have adopted the technique of robust regression to scale down the impact of outliers in the dataset, while generating regression models. Further, the established results are justified with a 10-fold cross validation process and a comparison with the results obtained from different topological indices. The results of this research contribute a valuable insight to the fields of chemical informatics and structural analysis, offering an enhanced comprehension of the interplay between molecular structure and physical attributes within alkanes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Similar content being viewed by others

Data availability

Not applicable.

Code availability

Not applicable.

References

  1. I. Gutman, Geometric approach to degree-based topological indices: Sombor indices. MATCH Commun. Math. Comput. Chem 86(1), 11–16 (2021)

    Google Scholar 

  2. V. Kulli, Neighborhood Sombor indices. Int. J. Math. Trends Technol. 68(6), 195–202 (2022)

    Google Scholar 

  3. K.C. Das, I. Gutman, On Sombor index of trees. Appl. Math. Comput. 412, 126575 (2022)

    MathSciNet  Google Scholar 

  4. K.C. Das, A.S. Çevik, I.N. Cangul, Y. Shang, On Sombor index. Symmetry 13(1), 140 (2021)

    Article  ADS  MathSciNet  Google Scholar 

  5. K.C. Das, Y. Shang, Some extremal graphs with respect to Sombor index. Mathematics 9(11), 1202 (2021)

    Article  Google Scholar 

  6. R. Cruz, I. Gutman, J. Rada, Sombor index of chemical graphs. Appl. Math. Comput. 399, 126018 (2021)

    MathSciNet  Google Scholar 

  7. H. Deng, Z. Tang, R. Wu, Molecular trees with extremal values of Sombor indices. Int. J. Quantum Chem. 121(11), 26622 (2021)

    Article  Google Scholar 

  8. N. Ghanbari, S. Alikhani, Sombor index of certain graphs. arXiv preprint (2021). arXiv:2102.10409

  9. N.J.M.M. Raja, A. Anuradha, On Sombor indices of generalized tensor product of graph families. Results Control Optim. 14, 100375 (2024)

    Article  Google Scholar 

  10. R. Cruz, J. Rada, Extremal values of the Sombor index in unicyclic and bicyclic graphs. J. Math. Chem. 59, 1098–1116 (2021)

    Article  MathSciNet  CAS  Google Scholar 

  11. J.-B. Liu, Y.-Q. Zheng, X.-B. Peng, The statistical analysis for Sombor indices in a random polygonal chain networks. Discret. Appl. Math. 338, 218–233 (2023)

    Article  MathSciNet  Google Scholar 

  12. V. Kulli, Neighborhood Sombor index of some nanostructures. Int. J. Math. Trends Technol. 67(5), 101–108 (2021)

    Article  Google Scholar 

  13. J. Rada, J.M. Rodríguez, J.M. Sigarreta, General properties on Sombor indices. Discret. Appl. Math. 299, 87–97 (2021)

    Article  MathSciNet  Google Scholar 

  14. T. Radhakrishnan, W. Herndon, Molar volumes of alkanes and topological indices. J. Math. Chem. 2(4), 391–399 (1988)

    Article  MathSciNet  CAS  Google Scholar 

  15. J.-B. Liu, D.A. Xavier, E.S. Varghese, A. Baby, D. Mathew, Molecular descriptors of porphyrin-based dendrimer. Polycyclic Aromat. Compd. 43(7), 6126–6137 (2023)

    Article  CAS  Google Scholar 

  16. J.-B. Liu, H. Iqbal, K. Shahzad, Topological properties of concealed non-Kekulean benzenoid hydrocarbon. Polycyclic Aromat. Compd. 43(2), 1776–1787 (2023)

    Article  CAS  Google Scholar 

  17. S. Das, S. Rai, V. Kumar, On topological indices of Molnupiravir and its QSPR modelling with some other antiviral drugs to treat COVID-19 patients. J. Math. Chem. (2023). https://doi.org/10.1007/s10910-023-01518-z

    Article  Google Scholar 

  18. X. Zuo, M.F. Nadeem, M.K. Siddiqui, M. Azeem, Edge weight based entropy of different topologies of carbon nanotubes. IEEE Access 9, 102019–102029 (2021)

    Article  Google Scholar 

  19. P. Bustamante, S. Romero, A. Peña, B. Escalera, A. Reillo, Enthalpy–entropy compensation for the solubility of drugs in solvent mixtures: paracetamol, acetanilide, and nalidixic acid in dioxane-water. J. Pharm. Sci. 87(12), 1590–1596 (1998)

    Article  PubMed  CAS  Google Scholar 

  20. F. Prado-Prado, X. García-Mera, P. Abeijón, N. Alonso, O. Caamaño, M. Yáñez, T. Gárate, M. Mezo, M. González-Warleta, L. Muiño et al., Using entropy of drug and protein graphs to predict FDA drug-target network: theoretic-experimental study of MAO inhibitors and hemoglobin peptides from Fasciola hepatica. Eur. J. Med. Chem. 46(4), 1074–1094 (2011)

    Article  PubMed  CAS  Google Scholar 

  21. P.G. Seybold, M. May, U.A. Bagal, Molecular structure: property relationships. J. Chem. Educ. 64(7), 575 (1987)

    Article  CAS  Google Scholar 

  22. R. Guha, D. Velegol, Harnessing Shannon entropy-based descriptors in machine learning models to enhance the prediction accuracy of molecular properties. J. Cheminform. 15(1), 1–11 (2023)

    Article  Google Scholar 

  23. M.D. Vale Cunha, C.C. Ribeiro Santos, M.A. Moret, H.B. Barros Pereira, Shannon entropy in time-varying semantic networks of titles of scientific paper. Appl. Netw. Sci. 5(1), 53 (2020)

    Article  Google Scholar 

  24. W. Gao, M. Imran, A.Q. Baig, H. Ali, M.R. Farahani, Computing topological indices of sudoku graphs. J. Appl. Math. Comput. 55, 99–117 (2017)

    Article  MathSciNet  Google Scholar 

  25. S.C. Basak, G.J. Niemi, G.D. Veith, Predicting properties of molecules using graph invariants. J. Math. Chem. 7(1), 243–272 (1991)

    Article  CAS  Google Scholar 

  26. S. Hosamani, D. Perigidad, S. Jamagoud, Y. Maled, S. Gavade, QSPR analysis of certain degree based topological indices. J. Stat. Appl. Probab. 6(2), 361–371 (2017)

    Article  Google Scholar 

  27. N.J.M.M. Raja, A. Anuradha, Topological entropies of single walled carbon nanotubes. J. Math. Chem. (2023). https://doi.org/10.1007/s10910-023-01532-1

    Article  Google Scholar 

  28. S. Chatterjee, B. Price, Regression Diagnostics (Wiley, New York, 1991)

    Google Scholar 

  29. S. Das, S. Chatterjee, Multicollinearity problem—root cause, diagnostics and way outs. Diagnostics and Way Outs, 29 April 2011

  30. J. Jacob, R. Varadharajan, Simultaneous raise regression: a novel approach to combating collinearity in linear regression models. Qual. Quant. 57(5), 4365–4386 (2023)

    Article  Google Scholar 

  31. J. Neter, W. Wasserman, M.H. Kutner, Applied linear statistical models: regression. Anal. Var. Exp. Des. 1(985), 382–393 (1985)

    Google Scholar 

  32. K. Aarthi, S. Elumalai, S. Balachandran, S. Mondal, Extremal values of the atom-bond sum-connectivity index in bicyclic graphs. J. Appl. Math. Comput. 69(6), 4269–4285 (2023)

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgements

The corresponding author (A. Anuradha) would like to thank SRM Institute of Science and Technology, Tamil Nadu, India for supporting her research under the “Selective Excellence Research Initiative - 2021” grant.

Author information

Authors and Affiliations

Authors

Contributions

Nadar Jenita Mary Masilamani Raja and A. Anuradha have contributed equally to this work.

Corresponding author

Correspondence to A. Anuradha.

Ethics declarations

Conflict of interest

The authors declare that they have no competing interests.

Ethical approval

Not applicable.

Consent to participate

Not applicable.

Consent for publication

The authors approve to publish in the journal.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Raja, N.J.M.M., Anuradha, A. Bonding alkane attributes with topological indices: a statistical intervention. J Math Chem (2024). https://doi.org/10.1007/s10910-024-01584-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10910-024-01584-x

Keywords

Mathematics Subject Classification

Navigation