Parameterization of an empirical model for the prediction of n-octanol, alkane and cyclohexane/water as well as brain/blood partition coefficients

Assessment of liquid-liquid partition for the assignment of descriptors for the solvation parameter model

The solvation parameter model uses five system independent descriptors to characterize compound properties defined as excess molar refraction, E, dipolarity/polarizability, S, hydrogen-bond acidity, A, hydrogen-bond basicity, B, and McGowan's characteristic volume, V, to model transfer properties between condensed phases. The V descriptor is assigned from structure. For compounds liquid at 20 °C the E descriptor can be assigned from the characteristic volume and its refractive index. The E descriptor for compounds solid at 20 °C and the S, A, and B descriptors are experimental properties traditionally assigned from chromatographic, liquid-liquid partition, and solubility measurements. In this report liquid-liquid partition constants in totally organic and aqueous biphasic systems are evaluated as a standalone technique for descriptor assignments. Using six totally organic biphasic systems the S, A, and B descriptors were assigned with an average absolute deviation (AAD) of about 0.04, 0.03, and 0.04, respectively, compared with the best estimate of the true descriptor values for 65 compounds. The E descriptor for compounds solid at 20 °C can only be estimated with an AAD of approximately 0.1. For six aqueous biphasic systems the B descriptor is assigned with a lower AAD of 0.028 and higher AAD of 0.08 and 0.05 for the S and A descriptors, respectively, than for the totally organic biphasic systems for compounds with a reliable value for the E descriptor. The preferred system for descriptor assignments utilizes both totally organic biphasic systems (heptane-1,1,1-trifluoroethanol, isopentyl ether-propylene carbonate, isopentyl ether-ethanolamine, heptane-ethylene glycol, heptane-formamide, and 1,2-dichloroethane-ethylene glycol) and aqueous biphasic systems (octanol-water, cyclohexane-water) with the possible substitution of some systems with alternative systems of similar selectivity. For 55 varied compounds this combination of eight organic and aqueous biphasic systems resulted in an AAD of approximately 0.03, 0.02, and 0.02 for the S, A, and B descriptors compared to the best estimate of the true descriptor value. For 30 compounds solid at 20 °C the AAD for the E descriptor of 0.11 is poorly assigned. The relative average absolute deviation in percent (RAAD) corresponds to 9.7 %, 3.1 %. 4.0 % and 8.3 % for E, S, A, and B, respectively, for the eight biphasic systems. Liquid-liquid partition is compared to reversed-phase liquid and gas chromatography as a standalone technique for descriptor assignments.

Physicochemical Profile of Antiandrogen Drug Bicalutamide: Solubility, Distribution, Permeability

The pharmacologically relevant physicochemical properties of the antiandrogen drug bicalutamide (BCL) have been determined for the first time. Solubility in aqueous solution, 1-octanol, n-hexane, and ethanol was measured by the shake flask method in the temperature range of 293.15−313.15 K. The compound was shown to be poorly soluble in aqueous medium and n-hexane; at the same time, an essentially higher solubility in the alcohols was revealed. The following order of molar solubility was determined: ethanol > 1-octanol > water ≈ n-hexane. The solubility was correlated with the Van’t Hoff and Apelblat equations. Evaluation of the Hansen solubility parameters and the atomic group contribution approach of Hoftyzer and Van Krevelen demonstrated consistency with the experimental data and good potential adsorption of bicalutamide. The temperature dependences of the distribution coefficients in the 1-octanol/water and n-hexane/water two-phase systems were measured and discussed in the framework of the thermodynamic approach. The ∆logD parameter determined from the distribution experiment clearly demonstrated the preference of the lipophilic delivery pathways for the compound in the biological media. The overall thermodynamic analysis based on the solubility and distribution results of the present study and the sublimation characteristics published previously has been performed. To this end, the thermodynamic parameters of the dissolution, solvation, and transfer processes were calculated and discussed in view of the solute-solvent interactions. The permeation rate of BCL through the PermeaPad barrier was measured and compared with PAMPA permeability.

Design, synthesis, and biological evaluation of diosgenin-indole derivatives as dual-functional agents for the treatment of Alzheimer's disease

The complex pathogenesis of Alzheimer's disease (AD) has become a major obstacle in its treatment. An effective approach is to develop multifunctional agents that simultaneously target multiple pathological processes. Here, a series of diosgenin-indole compounds were designed, synthesized and evaluated for their neuroprotective effects against H₂O₂ (hydrogen peroxide), 6-OHDA (6-hydroxydopamine) and Aβ (beta amyloid) damages. Preliminary structure-activities relationship revealed that the introduction of indole fragment and electron-donating group at C-5 on ring indole could be beneficial for neuroprotective activities. Results indicated that compound 5b was the most promising candidate against cellular damage induced by H₂O₂ (52.9 ± 1.9%), 6-OHDA (38.4 ± 2.4%) and Aβ_1-42 (54.4 ± 2.7%). Molecular docking study suggested the affinity for 5b bound to Aβ_1-42 was -40.59 kcal/mol, which revealed the strong binding affinity of 5b to Aβ_1-42. The predicted values of brain/blood partition coefficient (-0.733) and polar surface area (85.118 Å²) indicated the favorable abilities of BBB permeation and absorption of 5b. In addition, 5b significantly decreased ROS (reactive oxygen species) production induced by H₂O₂. In the following in vivo experiment, 5b obviously attenuated memory and learning impairments of Aβ-injected mice. In summary, compound 5b could be considered as a promising dual-functional neuroprotective agent against AD.

Calculating Partition Coefficients of Small Molecules in Octanol/Water and Cyclohexane/Water

Partition coefficients describe how a solute is distributed between two immiscible solvents. They are used in drug design as a measure of a solute's hydrophobicity and a proxy for its membrane permeability. We calculate partition coefficients from transfer free energies using molecular dynamics simulations in explicit solvent. Setup is done by our new Solvation Toolkit which automates the process of creating input files for any combination of solutes and solvents for many popular molecular dynamics software packages. We calculate partition coefficients between octanol/water and cyclohexane/water with the Generalized AMBER Force Field (GAFF) and the Dielectric Corrected GAFF (GAFF-DC). With similar methods in the past we found a root-mean-squared error (RMSE) of 6.3 kJ/mol in hydration free energies which would correspond to an error of around 1.6 log units in partition coefficients if solvation free energies in both solvents were estimated with comparable accuracy. Here we find an overall RMSE of about 1.2 log units with both force fields. Results from GAFF and GAFF-DC seem to exhibit systematic biases in opposite directions for calculated cyclohexane/water partition coefficients.

Extended solvent-contact model approach to blind SAMPL5 prediction challenge for the distribution coefficients of drug-like molecules

The performance of the extended solvent-contact model has been addressed in the SAMPL5 blind prediction challenge for distribution coefficient (LogD) of drug-like molecules with respect to the cyclohexane/water partitioning system. All the atomic parameters defined for 41 atom types in the solvation free energy function were optimized by operating a standard genetic algorithm with respect to water and cyclohexane solvents. In the parameterizations for cyclohexane, the experimental solvation free energy (ΔG _sol ) data of 15 molecules for 1-octanol were combined with those of 77 molecules for cyclohexane to construct a training set because ΔG _sol values of the former were unavailable for cyclohexane in publicly accessible databases. Using this hybrid training set, we established the LogD prediction model with the correlation coefficient (R), average error (AE), and root mean square error (RMSE) of 0.55, 1.53, and 3.03, respectively, for the comparison of experimental and computational results for 53 SAMPL5 molecules. The modest accuracy in LogD prediction could be attributed to the incomplete optimization of atomic solvation parameters for cyclohexane. With respect to 31 SAMPL5 molecules containing the atom types for which experimental reference data for ΔG _sol were available for both water and cyclohexane, the accuracy in LogD prediction increased remarkably with the R, AE, and RMSE values of 0.82, 0.89, and 1.60, respectively. This significant enhancement in performance stemmed from the better optimization of atomic solvation parameters by limiting the element of training set to the molecules with experimental ΔG _sol data for cyclohexane. Due to the simplicity in model building and to low computational cost for parameterizations, the extended solvent-contact model is anticipated to serve as a valuable computational tool for LogD prediction upon the enrichment of experimental ΔG _sol data for organic solvents.

Structural determinants of drug partitioning in n-hexadecane/water system

Surrogate phases have been widely used as correlates for modeling transport and partitioning of drugs in biological systems, taking advantage of chemical similarity between the surrogate and the phospholipid bilayer as the elementary unit of biological phases, which is responsible for most of the transport and partitioning. Solvation in strata of the phospholipid bilayer is an important drug characteristic because it affects the rates of absorption and distribution, as well as the interactions with the membrane proteins having the binding sites located inside the bilayer. The bilayer core can be emulated by n-hexadecane (C16), and the headgroup stratum is often considered a hydrophilic phase because of the high water content. Therefore, we tested the hypothesis that the C16/water partition coefficients (P) can predict the bilayer locations of drugs and other small molecules better than other surrogate systems. Altogether 514 PC16/W values for nonionizable (458) and completely ionized (56) compounds were collected from the literature or measured, when necessary. With the intent to create a fragment-based prediction system, the PC16/W values were factorized into the fragment solvation parameters (f) and correction factors based on the ClogP fragmentation scheme. A script for the PC16/W prediction using the ClogP output is provided. To further expand the prediction system and reveal solvation differences, the fC16/W values were correlated with their more widely available counterparts for the 1-octanol/water system (O/W) using solvatochromic parameters. The analysis for 50 compounds with known bilayer location shows that the available and predicted PC16/W and PO/W values alone or the PC16/O values representing their ratio do not satisfactorily predict the preference for drug accumulation in bilayer strata. These observations indicate that the headgroups stratum, albeit well hydrated, does not have solvation characteristics similar to water and is also poorly described by the O/W partition characteristics.

Qualitative prediction of blood-brain barrier permeability on a large and refined dataset

The prediction of blood-brain barrier permeation is vitally important for the optimization of drugs targeting the central nervous system as well as for avoiding side effects of peripheral drugs. Following a previously proposed model on blood-brain barrier penetration, we calculated the cross-sectional area perpendicular to the amphiphilic axis. We obtained a high correlation between calculated and experimental cross-sectional area (r = 0.898, n = 32). Based on these results, we examined a correlation of the calculated cross-sectional area with blood-brain barrier penetration given by logBB values. We combined various literature data sets to form a large-scale logBB dataset with 362 experimental logBB values. Quantitative models were calculated using bootstrap validated multiple linear regression. Qualitative models were built by a bootstrapped random forest algorithm. Both methods found similar descriptors such as polar surface area, pKa, logP, charges and number of positive ionisable groups to be predictive for logBB. In contrast to our initial assumption, we were not able to obtain models with the cross-sectional area chosen as relevant parameter for both approaches. Comparing those two different techniques, qualitative random forest models are better suited for blood-brain barrier permeability prediction, especially when reducing the number of descriptors and using a large dataset. A random forest prediction system (n(trees) = 5) based on only four descriptors yields a validated accuracy of 88%.

Identification of novel functional inhibitors of acid sphingomyelinase

We describe a hitherto unknown feature for 27 small drug-like molecules, namely functional inhibition of acid sphingomyelinase (ASM). These entities named FIASMAs (Functional Inhibitors of Acid SphingoMyelinAse), therefore, can be potentially used to treat diseases associated with enhanced activity of ASM, such as Alzheimer's disease, major depression, radiation- and chemotherapy-induced apoptosis and endotoxic shock syndrome. Residual activity of ASM measured in the presence of 10 µM drug concentration shows a bimodal distribution; thus the tested drugs can be classified into two groups with lower and higher inhibitory activity. All FIASMAs share distinct physicochemical properties in showing lipophilic and weakly basic properties. Hierarchical clustering of Tanimoto coefficients revealed that FIASMAs occur among drugs of various chemical scaffolds. Moreover, FIASMAs more frequently violate Lipinski's Rule-of-Five than compounds without effect on ASM. Inhibition of ASM appears to be associated with good permeability across the blood-brain barrier. In the present investigation, we developed a novel structure-property-activity relationship by using a random forest-based binary classification learner. Virtual screening revealed that only six out of 768 (0.78%) compounds of natural products functionally inhibit ASM, whereas this inhibitory activity occurs in 135 out of 2028 (6.66%) drugs licensed for medical use in humans.

Water-solvent partition coefficients and Delta Log P values as predictors for blood-brain distribution; application of the Akaike information criterion

It is shown that log P values for water-alkane or water-cyclohexane partitions, and the corresponding Delta log P values when used as descriptors for blood-brain distribution, as log BB, yield equations with very poor correlation coefficients but very good standard deviations, S from 0.25 to 0.33 log units. Using quite large data sets, we have verified that similar S-values apply to predictions of log BB. A suggested model, based on log P for water-dodecane and water-hexadecane partition coefficients, has 109 data points and a fitted S = 0.254 log units. It is essential to include in the model an indicator variable for volatile compounds, and an indicator variable for drugs that contain the carboxylic group. A similar equation based on water-chloroform partition coefficients has 83 data points and a fitted S = 0.287 log units. We can find no causal connection between these log P values and log BB in terms of correlation or in terms of chemical similarity, but conclude that the log P descriptor will yield excellent predictions of log BB provided that predictions are within the chemical space of the compounds used to set up the model. We also show that model based on log P(octanol) and an Abraham descriptor provides a simple and easy method of predicting log BB with an error of no more than 0.31 log units. We have used the Akaike information criterion to investigate the most economic models for log BB.