Comparative Study of Entropies in Silicate and Oxide Frameworks

Arockiaraj, Micheal; Fiona, J. Celin; Shalini, Arul Jeya

doi:10.1007/s12633-024-02892-2

Cited by 2 publications

(1 citation statement)

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“…These indices utilize mathematical algorithms based on the structural information encoded in the molecular graphs, offering quantitative insights into the compounds’ topological features and connectivity patterns. Some interesting results on topological indices are characterized in ( Natarajan et al, 2022 ; Zaman and He, 2022 ; Ullah et al, 2023a ; Ullah et al, 2023b ; Yan et al, 2023 ; Zaman et al, 2023 ; Arockiaraj et al, 2024a ; Hayat et al, 2024a ; Arockiaraj et al, 2024b ; Hayat et al, 2024b ; Arockiaraj et al, 2024c ; Chidambaram et al, 2024 ). This numerical representation facilitates the characterization and comparison of different molecular structures, contributing to the understanding of their properties and potential activities, including anti-cancer effects.…”

Section: Introductionmentioning

confidence: 99%

Predictive modeling and regression analysis of diverse sulfonamide compounds employed in cancer therapy

Danish,

Liaquat,

Ashraf

et al. 2024

Front. Chem.

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Topological indices (TIs) have rich applications in various biological contexts, particularly in therapeutic strategies for cancer. Predicting the performance of compounds in the treatment of cancer is one such application, wherein TIs offer insights into the molecular structures and related properties of compounds. By examining, various compounds exhibit different degree-based TIs, analysts can pinpoint the treatments that are most efficient for specific types of cancer. This paper specifically delves into the topological indices (TIs) implementations in forecasting the biological and physical attributes of innovative compounds utilized in addressing cancer through therapeutic interventions. The analysis being conducted to derivatives of sulfonamides, namely, 4-[(2,4-dichlorophenylsulfonamido)methyl]cyclohexanecarboxylic acid (1), ethyl 4-[(naphthalene-2-sulfonamido)methyl]cyclohexanecarboxylate (2), ethyl 4-[(2,5-dichlorophenylsulfonamido)methyl]cyclohexanecarboxylate (3), 4-[(naphthalene-2-sulfonamido)methyl]cyclohexane-1-carboxylic acid (4) and (2S)-3-methyl-2-(naphthalene-1-sulfonamido)-butanoic acid (5), is performed by utilizing edge partitioning for the computation of degree-based graph descriptors. Subsequently, a linear regression-based model is established to forecast characteristics, like, melting point and formula weight in a quantitative structure-property relationship. The outcomes emphasize the effectiveness or capability of topological indices as a valuable asset for inventing and creating of compounds within the realm of cancer therapy.

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