A QSPR analysis of physical properties of antituberculosis drugs using neighbourhood degree-based topological indices and support vector regression

Muhammad Shafii Abubakar, Kazeem Olalekan Aremu*, Maggie Aphane, Lateef Babatunde Amusa

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Topological indices are molecular descriptors used in QSPR modelling to predict the physicochemical properties of molecules. Topological indices are used in numerous applications in drug design. In this work, we compute the neighbourhood degree-based topological indices of 15 antituberculosis drugs, we studied the QSPR analysis of these drugs using support vector regression. The efficiency of support vector regression is determined by comparing it with the classical linear regression. Our QSPR model further shows the superiority of the SVR model as a better predictive model in QSPR analysis of the physical properties of antituberculosis drugs. The findings in this study are a further contribution to the field of chemical graph theory and drug design, providing a deeper understanding of neighbourhood degree-based topological indices and their predictive capabilities in QSPR model.

Original languageEnglish
Article numbere28260
JournalHeliyon
Volume10
Issue number7
DOIs
Publication statusPublished - 15 Apr 2024

Keywords

  • Antituberculosis drugs
  • Neighbourhood degree-based topological indices
  • QSPR analysis
  • Support vector regression

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