Dawid Wardecki

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.

Due to the observed increase in the importance of computational methods in determining selected physicochemical parameters of biologically active compounds that are key to understanding their ADME/T profile, such as lipophilicity, there is a great need to work on accurate and precise in silico models based on some structural descriptors, such as topological indices for predicting lipophilicity of certain anti-androgenic and hypouricemic agents and their derivatives, for which the experimental lipophilicity parameter is not accurately described in the available literature, e.g., febuxostat, oxypurinol, ailanthone, abiraterone and teriflunomide. Therefore, the following topological indices were accurately calculated in this paper: Gutman (M, M^ν), Randić (⁰χ, ¹χ, ⁰χ^ν, ¹χ^ν), Wiener (W), Rouvray–Crafford (R) and Pyka (A, ⁰B, ¹B) for the selected anti-androgenic drugs (abiraterone, bicalutamide, flutamide, nilutamide, leflunomide, teriflunomide, ailanthone) and some hypouricemic compounds (allopurinol, oxypurinol, febuxostat). Linear regression analysis was used to create simple linear correlations between the newly calculated topological indices and some physicochemical parameters, including lipophilicity descriptors of the tested compounds (previously obtained by TLC and theoretical methods). Our studies confirmed the usefulness of the obtained linear regression equations based on topological indices to predict ADME/T important parameters, such as lipophilicity descriptors of tested compounds with anti-androgenic and hypouricemic effects. The proposed calculation method based on topological indices is fast, easy to use and avoids valuable and lengthy laboratory experiments required in the case of experimental ADME/T studies.

Lipophilicity in addition to the solubility, acid-base character and stability is one of the most important physicochemical parameters of a compound required to assess the ADMET properties (absorption, distribution, metabolism, excretion and toxicity) of a bioactive molecule. Therefore, the subject of this work was to determine the lipophilicity parameters of selected antimicrobial and immunosuppressive compounds such as delafloxacin, linezolid, sutezolid, ceftazidime, everolimus and zotarolimus using thin-layer chromatography in reversed phase system (RP-TLC). The chromatographic parameters of lipophilicity (R_MW) for tested compounds were determined on different stationary phases: RP18F₂₅₄, RP18WF₂₅₄ and RP2F₂₅₄ using ethanol, acetonitrile, and propan-2-ol as organic modifiers of mobile phases used. Chromatographically established R_MW values were compared with partition coefficients obtained by different computational methods (AlogPs, AClogP, AlogP, MlogP, XlogP2, XlogP3, logP_KOWWIN, ACD/logP, milogP). Both cluster and principal component analysis (CA and PCA) of the received results allowed us to compare the lipophilic nature of the studied compounds. The sum of ranking differences analysis (SRD) of all lipophilicity parameters was helpful to select the most effective method of determining the lipophilicity of the investigated compounds. The presented results demonstrate that RP-TLC method may be a good tool in determining the lipophilic properties of studied substances. Obtained lipophilic parameters of the compounds can be valuable in the design of their new derivatives as efficient antimicrobial and immunosuppressive agents.

This study aimed to evaluate the lipophilicity of a series substances lowering the concentration of uric acid in blood and anti-androgen drugs by thin-layer chromatography in reversed-phase systems (RP-TLC, RP-HPTLC) and computational methods. The chromatographic parameter of lipophilicity (R_MW) of tested compounds was determined on three stationary phases, i.e., RP18F₂₅₄, RP18WF₂₅₄ and RP2F₂₅₄, using ethanol–water, propan-2-ol-water and acetonitrile–water in various volume compositions as mobile phases. The chromatographic analysis led to determining the experimental value of the lipophilicity parameter for each of the tested compounds, including those for which the experimental value of the partition coefficient (logP_exp) as a measure of lipophilicity is not well described in available databases, such as febuxostat, oxypurinol, ailanthone, abiraterone and teriflunomide. The chromatographic parameters of lipophilicity were compared with the logP values obtained with various software packages, such as AClogP, AlogPs, AlogP, MlogP, XlogP2, XlogP3, ACD/logP and logP_KOWWIN. The obtained results indicate that, among selected chromatographic parameters of lipophilicity, both experimental and calculated logP values gave similar results, and these RP-TLC or RP-HPTLC systems can be successfully applied to estimate the lipophilicity of studied heterocyclic compounds belonging to two different pharmacological groups. This work also illustrates the similarity and difference existing between the tested compounds under study using the chemometric methods, such as principal component analysis (PCA) and cluster analysis (CA). In addition, a relatively new approach based on the sum of ranking differences (SRD) was used to compare the chromatographically obtained and theoretical lipophilicity descriptors of studied compounds.

The aim of this work was the use of both cluster analysis (CA) and Principal Component Analysis (PCA) for the evaluation of the lipophilicity of selected antiandrogen drugs such as abiraterone, bicalutamide, flutamide, nilutamide, leflunomide, teriflunomide and ailanthone. Lipophilicity is an important physicochemical parameter that is useful in determining the ADMET properties (absorption, distribution, metabolism, elimination and toxicity) of organic compounds that are being considered as potential drugs or drug candidates. Therefore, there is an urgent need to develop rapid, economical and efficient tools like theoretical methods that include CA and PCA analyses for the evaluation of the lipophilic properties of different bioactive compounds such as antiandrogens. In this study, we used both methods for comparison of the physicochemical properties (including lipophilicity) of seven antiandrogens with differ chemical structures. The lipophilicity parameters of the studied compounds were obtained in the form of R_MW by using a thin-layer chromatographic method (RP-TLC) under different conditions (i.e., various mobile phases composed of ethanol-water, propan-2-ol-water and acetonitrile-water and chromatographic plates RP2F₂₅₄, RP18F₂₅₄ and RP18WF₂₅₄), as well as logP values predicted using calculation methods (AlogPs, AClogP, AlogP, MlogP, xlogP2 and xlogP3). The CA and PCA analyses allowed the comparison of the examined compounds based on their lipophilicity parameters determined using RP-TLC and calculated logP values. Our study confirms the utility of both statistical methods (i.e., CA and PCA) to evaluate the lipophilicity of bioactive compounds belonging to the class of antiandrogen drugs.