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Article Abstract
Background: This study investigated many cancer medicines using a wide range of degree sum-based topological indices and entropy. These numerical numbers, commonly referred to as topological indices or molecular descriptors, depict a substance's molecular structure. They have been successfully used to properly reflect different physicochemical properties in a number of Quantitative Structure-Property Relationship (QSPR) and Quanti-tative Structure-Activity Relationship (QSAR) research studies.
Objective: The purpose of the study was to investigate the relationships between topological neighborhood indices and physicochemical properties using the QSPR model and linear re-gression methodology.
Methods: We employed linear regression methodology within the QSPR model to examine the connections between physicochemical characteristics and topological neighborhood in-dices.
Results: The results revealed a significant correlation between the neighborhood indices un-der scrutiny and the physicochemical features of the potential drugs under investigation.
Conclusion: As a result, both neighborhood topological indices and entropy demonstrate potential as valuable tools for future QSPR investigations when evaluating anticancer medi-cations.
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| http://dx.doi.org/10.2174/0115701794349166241217085334 | DOI Listing |
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