Predictive potential of K‐Banhatti and Zagreb type molecular descriptors in structure–property relationship analysis of some novel drug molecules

Abstract

Topological indices (TIs) can be used to forecast molecules' biological activity, physicochemical features, and toxicity. The use of topological indices and regression analysis can help us better understand drug behavior and contribute to the development of tailored drugs. This study investigates the predictive potential and efficacy of K‐Banhatti and Zagreb type degree‐based topological indices in quantitative structure–property relationship (QSPR) analysis of a comprehensive set of medications used for diabetes type‐I and type‐II disease. The K‐Banhatti and Zagreb type degree‐based topological indices are computed for 14 anti‐diabetes drug molecules using edge/vertex partitioning techniques. By leveraging these topological indices, QSPR regression models are developed to predict the physicochemical properties of the understudy drugs. The results show that the values of these topological indices are highly correlated with certain physicochemical properties of the anti‐diabetes drugs. Furthermore, the comparative analysis revealed that, for all the considered properties except enthalpy of vaporization, Zagreb type indices outperform K‐Banhatti indices with high predictive ability. Hence, it can be concluded that the Zagreb type indices are the best alternatives to theoretically predict the properties of anti‐diabetes drugs. This theoretical analysis can help chemists in their right choice of the topological indices to theoretically predict the properties of anti‐diabetes drugs without going into laborious experimentation.

Applications of magnesium iodide structure via modified-polynomials

“…modified polynomials contribute to the efficient design, development, and assessment of magnesium iodide-based materials for diverse technical and scientific uses by creating connections between structure and characteristics. For further detail on the topic, we refer to see [50][51][52] .…”

Molecular structural modeling and physical characteristics of anti-breast cancer drugs via some novel topological descriptors and regression models

“…Gutman and Trinajstic established the earliest topological indices, the Zagreb type indices ( Ali et al, 2020 ; Furtula et al, 2013 ; Gutman and Trinajstić, 1972 ; Kwun et al, 2018 ), which have been utilized to investigate molecular difficulty, boiling point, and chirality. Several researchers have investigated the QSPR and QSAR analysis of the molecular structures of drugs by leveraging degree based topological indices ( Bokhary et al, 2021 ; Mondal et al, 2021 ; Rauf et al, 2022 ; Ullah et al, 2024 ; Zhong et al, 2021 ) in order to gain a deeper understanding of their behavior and physical properties. However, despite intensive studies, the molecular structural topology is still not well understood.…”

Resistance distance and sharp bounds of two-mode electrical networks

“…These descriptors are distance, degree and eccentricity based, which help in understanding different networks such as biological, social networks and circuits in physics, and improve electrical circuits, identify critical components, study electrical flow and voltage distribution [7][8][9][10]. In chemistry, topological indices are useful in analysis of chemical reactions and enabling to predict molecular properties [11][12][13][14][15][16][17][18][19][20][21].…”