Chemometrics of anisotropic lipophilicity of anticancer androstane derivatives determined by reversed-phase ultra high performance liquid chromatography with polar aprotic and protic modifiers

Evaluation of lipophilicity and drug-likeness of donepezil-like compounds using reversed-phase thin-layer chromatography

Fourteen donepezil-like acetylcholinesterase (AChE) inhibitors from our library were analyzed using reversed-phase thin-layer chromatography to assess their lipophilicity and blood-brain barrier permeability. Compounds possessed N-benzylpiperidine and N,N-diarylpiperazine moieties connected via a short carboxamide or amine linker. Retention parameters RM 0, b, and C0 were considered as the measures of lipophilicity. Besides, logD of the investigated compounds was determined chromatographically using standard compounds with known logPow and logD values at pH 11. Experimentally obtained lipophilicity parameters correlated well with in silico generated results, and the effect of the nature of the linker between two pharmacophores and substituents on the arylpiperazine part of the molecule was observed. As a result of drug-likeness analysis, both Lipinski's rule of five and Veber's rule parameters were determined, suggesting that examined compounds could be potential candidates for further drug development. Principal component analysis was performed to obtain an insight into a grouping of compounds based on calculated structural descriptors, experimentally obtained values of lipophilicity, and AChE inhibitory activity.

Evaluation of Physicochemical Properties of Ipsapirone Derivatives Based on Chromatographic and Chemometric Approaches

Drug discovery is a challenging process, with many compounds failing to progress due to unmet pharmacokinetic criteria. Lipophilicity is an important physicochemical parameter that affects various pharmacokinetic processes, including absorption, metabolism, and excretion. This study evaluated the lipophilic properties of a library of ipsapirone derivatives that were previously synthesized to affect dopamine and serotonin receptors. Lipophilicity indices were determined using computational and chromatographic approaches. In addition, the affinity to human serum albumin (HSA) and phospholipids was assessed using biomimetic chromatography protocols. Quantitative Structure-Retention Relationship (QSRR) methodologies were used to determine the impact of theoretical descriptors on experimentally determined properties. A multiple linear regression (MLR) model was calculated to identify the most important features, and genetic algorithms (GAs) were used to assist in the selection of features. The resultant models showed commendable predictive accuracy, minimal error, and good concordance correlation coefficient values of 0.876, 0.149, and 0.930 for the validation group, respectively.