Computational analysis demonstrates consistent ranking of neurotransmitters using structural topological indices and multi-criteria methods, highlighting a framework for neurological research.
In this article, we provide a unique framework for precisely ranking neurotransmitters by combining Multi-Criteria Decision-Making (MCDM) approaches with topological indices obtained from their molecular structures. Topological indices, which are quantitative descriptors of molecular graphs, were used to determine the structural and physicochemical properties of distinct neurotransmitters. These indices served as objective assessment criteria in an MCDM setting, allowing for systematic ranking based on a variety of qualities. TOPSIS, SAW, and VIKOR were used to determine the significance of each neurotransmitter based on predefined criteria. The results show a consistent ranking pattern that corresponds to known biological importance, demonstrating the efficiency of the suggested technique. This integrative method not only provides a computational tool for neurotransmitter analysis, but it also serves as a decision-support system for researchers seeking to focus on certain neurotransmitters in neurological and psychiatric investigations.
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Yousaf et al. (2026) studied this question.
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