4.4 Review

Physicochemical Significance of Topological Indices: Importance in Drug Discovery Research

Journal

CURRENT TOPICS IN MEDICINAL CHEMISTRY
Volume -, Issue -, Pages -

Publisher

BENTHAM SCIENCE PUBL LTD
DOI: 10.2174/1568026623666230731103309

Keywords

Topological indices; Physicochemical significance; Molar refractivity; QSAR; QSPR; Drug designing

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Quantitative Structure-Activity Relationship (QSAR) studies are important in drug discovery research, and they involve correlating biological activity with physicochemical and structural descriptors. Topological indices (TIs) play a crucial role in drug discovery, but have a lack of physicochemical interpretation which is essential for understanding the mechanism of action. This review discusses the advances in TIs, their physicochemical significance, and their role in developing QSAR models.
Background Quantitative Structure-Activity Relationship (QSAR) studies describing the correlations between biological activity as dependent parameters and physicochemical and structural descriptors, including topological indices (TIs) as independent parameters, play an important role in drug discovery research. The emergence of graph theory in exploring the structural attributes of the chemical space has led to the evolution of various TIs, which have made their way into drug discovery. The TIs are easy to compute compared to the empirical parameters, but they lack physiochemical interpretation, which is essential in understanding the mechanism of action.Objectives Hence, efforts have been made to review the work on the advances in topological indices, their physicochemical significance, and their role in developing QSAR models.Methods A literature search has been carried out, and the research article providing evidence of the physicochemical significance of the topological parameters as well as some recent studies utilizing these parameters in the development of QSAR models, have been evaluated.Results In this review, the physicochemical significance of TIs have been described through their correlations between empirical parameters in terms of explainable physicochemical properties, along with their application in the development of predictive QSAR models.Conclusion Most of these findings suggest a common trend of TIs correlation with MR rather than logP or other parameters; nevertheless, the developed models may be useful in both drug and vaccine development.

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