Use of Topological Indices to Predict Structure-Property Relationships of Selected Drugs

The purpose of this work aimed to determine different topological indices based on adjacency and distance matrix for selected antimicrobial, antiviral and immunosuppressive drug substances. The following topological indices: Gutman (M, Mν), Randić (0χ, 1χ, 0χν, 1χν), Wiener (W), Rouvray-Crafford (R) and Pyka (A, 0B, 1B) were calculated for the studied compounds. Furthermore, these indices were related with various physicochemical properties of these compounds including those key in the ADME process (absorption, distribution, metabolism, and excretion), such as lipophilicity parameters obtained using both theoretical (logP values) and experimental (RMW values from thin-layer chromatography) methods. The quantitative structure–property relationship (QSPR) analysis of presented topological indices shows a good correlation of studied descriptors with certain physicochemical properties of examined drugs. The obtained linear regression models can be helpful to predict these physicochemical properties of new derivatives of tested compounds and thus are significant in pharmaceutical product design. This study confirms that the newly calculated descriptors (TIs) represent an innovative tool in drug analysis and at the same time TIs are useful in determining important parameters for ADME profile prediction.