Abstract

In order to focus on more promising drug candidates by reducing the failures that occur in the time-consuming and expensive discovery process of new drugs, it is highly efficient to predict the bioactivity and metabolism behaviors of drug candidates using computational chemistry methods. In this context, this study presents a comparative quantum chemical analysis of the buspirone, used in the treatment of anxiety, and its three structurally related derivatives, kaspar, mesmar, and gepirone, based on Density Functional Theory (DFT) calculations. Geometry optimization and frequency calculations of each molecule were implemented at B3LYP/6–31G (d, p) and B3LYP/6–311++G (d, p) levels of theory. Linear correlation coefficients (R2) were calculated for each piperazine derivative to detect the power of the relationship between theoretical and experimental structural parameters. Subsequently, frontier molecular orbital (FMO) analysis, quantum chemical reactivity descriptors, electrostatic surface properties (ESP), and natural bond orbital (NBO) analysis were examined in detail. The lipophilicity evaluations of mentioned piperazine derivatives were interpreted not only according to the data obtained from the DFT calculations, but also according to the results obtained from the Molinspiration software. As a result of both methods, the order of lipophilicity emerged as kaspar > mesmar > buspirone > gepirone. It is revealed that on account of the substitution of the pyrimidine ring in buspirone and gepirone with the quinoline ring, both lipophilicity increased and the direction of the lipophilic interaction predominantly changed. Based on all the obtained results, it is concluded that although the studied molecules are structurally very similar, they support different lipophilic interactions. Therefore, their pharmacological activities differ.

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