Gamachu Adugna Ganati

Abstract Typically, Quantitative Structure–Property Relationship (QSPR) models are created for compounds related to a particular therapeutic use and might be restricted in scope. To explore the wider use of neighbourhood connectivity descriptors, ten drug molecules, encompassing a wide range of chemical and therapeutic classes, were chosen: anti-inflammatory, anti-bacterial, anti-viral, anti-hypertensive, anesthetic, anti-depressant and neuromuscular agents.

Abstract In biological and chemical networks, in which the strength of interactions is often not absolute, uncertainty is an inherent feature of many real-world networks. A fuzzy graph consists of vertices with fuzzy memberships and fuzzy relationships among vertices and edges; therefore, fuzzy graph theory is a natural approach for modelling systems in which the connections between the vertices are fuzzy or not precisely known.

Abstract Topological indices are an important part of chemical graph theory as a representation of the molecular structure and a predictor of the physicochemical properties. In this paper, nine neighborhood degree sum based topological indices are use as indicators of predictive potential in a QSPR analysis of twenty antifungal drug molecules.