Cellular Quantitative Structure–Activity Relationship (Cell-QSAR): Conceptual Dissection of Receptor Binding and Intracellular Disposition in Antifilarial Activities of Selwood Antimycins

Abstract

We present the cellular quantitative structure–activity relationship (cell-QSAR) concept that adapts ligand-based and receptor-based 3D-QSAR methods for use with cell-level activities. The unknown intracellular drug disposition is accounted for by the disposition function (DF), a model-based, nonlinear function of a drug’s lipophilicity, acidity, and other properties. We conceptually combined the DF with our multispecies, multimode version of the frequently used ligand-based comparative molecular field analysis (CoMFA) method, forming a single correlation function for fitting the cell-level activities. The resulting cell-QSAR model was applied to the Selwood data on filaricidal activities of antimycin analogues. Their molecules are flexible, ionize under physiologic conditions, form different intramolecular H-bonds for neutral and ionized species, and cross several membranes to reach unknown receptors. The calibrated cell-QSAR model is significantly more predictive than other models lacking the disposition part and provides valuable structure optimization clues by factorizing the cell-level activity of each compound into the contributions of the receptor binding and disposition.

Does transbilayer diffusion have a role in membrane transport of drugs?

“…Some cell organelles contain aqueous phases with the pH values differing from that of cytoplasm: lysosomes are at the low end with pH ~ 5 and the interior of mitochondria is at the opposite end of the range with pH ~ 8. Therefore, dissolved weak bases prefer lysosomes [36,37] and dissolved weak acids accumulate in mitochondria [48]. For instance, the cells of liver and kidney have a higher concentration of lysosomes [34,39] and mitochondria [40] than those of heart and muscle, and uneven accumulation of ionizable compounds in these organs can be explained by the solvation of ionized species.…”

“…We have shown that in several cases of drug action in cell suspension, the kinetics of membrane transport does not need to be considered and a pseudo-equilibrium accumulation is sufficient to create good-quality, model-based QSARs for a limited series of compounds [47,48]. The agreement of the model with experimental data indicates that drugs were distributed according to the lipophilic-hydrophilic equilibrium, which eliminates the involvement of transporters.…”

“…The agreement of the model with experimental data indicates that drugs were distributed according to the lipophilic-hydrophilic equilibrium, which eliminates the involvement of transporters. The advanced, model-based QSAR techniques, such as our cell-QSAR approach [48], are able to resolve whether the disposition underlying the analyzed biological effect is caused by passive diffusion or transporter-mediated processes. This issue may only represent a problem for low-resolution QSAR approaches, which select significant descriptors from large descriptor pools using usually linear combination of descriptors and neglecting possible mechanisms.…”

Rigorous Incorporation of Tautomers, Ionization Species, and Different Binding Modes into Ligand-Based and Receptor-Based 3D-QSAR Methods

“…Thus, f i and f j are independent variables in the correlation equations, which are calculated before optimization assuming that the pH value of the medium is known. For cell-QSAR applications predicting binding affinities of the receptors inside the cells, the pH of the medium may differ from the plasma value and can become an optimized parameter for some simple speciation cases [78]. …”

Trend of Multi-Scale QSAR in Drug Design

“…In terms of the equation, log K is an MSMM-CoMFA expression for the receptor binding and the remaining terms (log DF) describe disposition function. Cell-based QSAR was successfully used to study the antifilarial activities of antimycin analogues 61 . Compared to the models of traditional CoMFA method, DF was a necessary part to ensure reliably predictive abilities.…”