QSPR Modeling of Degree-Based Topological Indices with Hepatocellular Carcinoma Drugs

The study discussed the QSPR analysis of the mentioned topological indices. The study also demonstrated that the characteristics obtained are highly correlated with those of Hepatocellular Carcinoma (Liver Cancer) drugs through linear regression. drugs are represented as molecular graphs where each vertex represents an atom and each edge represents a link between two atoms. Consider G (V, E) as a molecular graph, where V is the set of vertices and E is the set of edges. In this study, used 6 degree based topological indices, M1(G), M2(G), F(G), S(G), Y(G) and D(G). These indices were used to model five representative physical properties of five liver cancer drugs: BP, FP, P, ST, and MV. The values for these properties were obtained from ChemSpider. The study concluded that degree-based topological indices are effective molecular descriptors for predicting the physical properties of liver cancer drugs. The regression models revealed significant correlations between Surface Tension (ST) and indices such as the Forgotten Index (F(G)) and the Sum-Connectivity Index (S(G)). Although other properties, such as Boiling Point (BP) and Flash Point (FP), demonstrated weaker correlations, the overall findings suggest that topological indices can be valuable tools in Quantitative Structure-Property Relationship (QSPR) studies

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Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-08-22
DOI
https://doi.org/10.22214/ijraset.2025.73745
Primary Topic
Computational Drug Discovery Methods
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article
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article

QSPR Modeling of Degree-Based Topological Indices with Hepatocellular Carcinoma Drugs

S Ranjitham
International Journal for Research in Applied Science and Engineering Technology
Computational Drug Discovery Methods
article

QSPR Modeling of Degree-Based Topological Indices with Hepatocellular Carcinoma Drugs

S Ranjitham
article en

Abstract

The study discussed the QSPR analysis of the mentioned topological indices. The study also demonstrated that the characteristics obtained are highly correlated with those of Hepatocellular Carcinoma (Liver Cancer) drugs through linear regression. drugs are represented as molecular graphs where each vertex represents an atom and each edge represents a link between two atoms. Consider G (V, E) as a molecular graph, where V is the set of vertices and E is the set of edges. In this study, used 6 degree based topological indices, M1(G), M2(G), F(G), S(G), Y(G) and D(G). These indices were used to model five representative physical properties of five liver cancer drugs: BP, FP, P, ST, and MV. The values for these properties were obtained from ChemSpider. The study concluded that degree-based topological indices are effective molecular descriptors for predicting the physical properties of liver cancer drugs. The regression models revealed significant correlations between Surface Tension (ST) and indices such as the Forgotten Index (F(G)) and the Sum-Connectivity Index (S(G)). Although other properties, such as Boiling Point (BP) and Flash Point (FP), demonstrated weaker correlations, the overall findings suggest that topological indices can be valuable tools in Quantitative Structure-Property Relationship (QSPR) studies

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(8)
Openalex Percentile: Top 77%
Computational Drug Discovery Methods
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QSPR Modeling of Degree-Based Topological Indices with Hepatocellular Carcinoma Drugs — S Ranjitham · International Journal for Research in Applied Science and Engineering Technology (2025) | TGRS Research Map | TGRS