ArticleScientific reports2024
Valency based novel quantitative structure property relationship (QSPR) approach for predicting physical properties of polycyclic chemical compounds.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Topological indices and QSPR analysis of drug molecules from different therapeutic classes.Scientific reports · 2026Article
- Exploring anticancer drug structures through vertex based resolving parameters.Scientific reports · 2026Article
- Prediction of Standard Combustion Enthalpy of Organic Compounds Combining Machine Learning and Chemical Graph Theory: A Strategy.ACS omega · 2025Article
- On QSPR analysis of pulmonary cancer drugs using python-driven topological modeling.Scientific reports · 2025Article
- Predictive potential of distance-related spectral graphical descriptors for structure-property modeling of thermodynamic properties of polycyclic hydrocarbons with applications.Scientific reports · 2024Article
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3 authors.
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Abstract
In this study, we introduce a novel valency-based index, the neighborhood face index (NFI), designed to characterize the structural attributes of benzenoid hydrocarbons. To assess the practical applicability of NFI, we conducted a linear regression analysis utilizing numerous physiochemical properties associated with benzenoid hydrocarbons. Remarkably, the results revealed an extraordinary correlation exceeding 0.9991 between NFI and these properties, underscoring the robust predictive capability of the index. The NFI, identified as the best-performing descriptor, is subsequently investigated within certain infinite families of carbon nanotubes. This analysis demonstrates the index's exceptional predictive accuracy, suggesting its potential as a versatile tool for characterizing and predicting properties across diverse molecular structures, particularly in the context of carbon nanotubes.
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