COSMO-RS as a Predictive Tool for Lipophilicity

LogP determination for highly lipophilic hydrogen-bonding anion receptor molecules

Lipophilicity, usually expressed as octanol-water partition coefficient (logP_o/w), is an important property in biomedical research, drug design and technology. However, high logP_o/w values of complex hydrogen-bonding molecules are not easy to measure or calculate. Exemplary problematic molecules are prospective active components (ionophores) of polymeric sensor membranes - the working elements of ion-selective electrodes. High lipophilicities of the membrane components are crucial for the sensor lifetime. In this work, lipophilicities of a wide range of urea-, carbazole- and indolocarbazole-based anion receptor molecules (some newly synthesized) and two common plasticizers were determined using a chromatography-based approach and/or the COSMO-RS method. Very high logP_o/w values, up to around 20, i.e. far beyond directly experimentally accessible range, were obtained. The agreement between the two approaches ranged from very good to satisfactory. Based on these results, simple fragment-based equations were developed for quick lipophilicity estimation without any specialized software. Membrane-water partition coefficients for the studied compounds were modeled. Limitations and biases of the used methods are discussed.

Impact of the chemical structure on the distribution of neuroprotective N-alkyl-9H-carbazoles at octanol/water interfaces

All-atom molecular dynamics (MD) simulations were performed on distribution and agglomeration dynamics of neuroprotective N-(3-anilinopropyl)-9H-carbazoles at octanol/water interfaces.

Classification of biphasic solvent systems according to Abraham descriptors for countercurrent chromatography

The method development of liquid-liquid chromatography, either countercurrent chromatography or centrifugal partition chromatography, is slowed down by the selection of the biphasic solvent system that constitutes its column. This paper introduces a classification of 19 solvent systems, including the most popular systems based on heptane/ethyl acetate/methanol/water, some non-aqueous systems and some greener systems. This classification is based on Abraham descriptors determined through the partition coefficients of 43 probes. Among 21 determined models, nine of them allow an accurate prediction of partition coefficients from solute descriptors and another ten provide a description of the chromatographic interactions at the 5% significance level. A graphical tool (spider diagram) is built for the comparison of the chromatographic columns previously characterized with the solvation parameter model. The position of a solvent system in this spider diagram relates to the interactions at stake, thus the selection of columns offering similar or orthogonal interactions is facilitated, with no previous knowledge of the solute required. This semi-empirical strategy cannot fully predict the retention behavior but can judiciously orientate the user towards a limited number of solvent systems to be experimentally tested.

Physics-Based Method for Modeling Passive Membrane Permeability and Translocation Pathways of Bioactive Molecules

Assessment of permeability is a critical step in the drug development process for selection of drug candidates with favorable ADME properties. We have developed a novel physics-based method for fast computational modeling of passive permeation of diverse classes of molecules across lipid membranes. The method is based on heterogeneous solubility-diffusion theory and operates with all-atom 3D structures of solutes and the anisotropic solvent model of the lipid bilayer characterized by transbilayer profiles of dielectric and hydrogen bonding capacity parameters. The optimal translocation pathway of a solute is determined by moving an ensemble of representative conformations of the molecule through the dioleoyl-phosphatidylcholine (DOPC) bilayer and optimizing their rotational orientations in every point of the transmembrane trajectory. The method calculates (1) the membrane-bound state of the solute molecule; (2) free energy profile of the solute along the permeation pathway; and (3) the permeability coefficient obtained by integration over the transbilayer energy profile and assuming a constant size-dependent diffusivity along the membrane normal. The accuracy of the predictions was evaluated against experimental permeability coefficients measured in pure lipid membranes (for 78 compounds, R² was 0.88 and rmse was 1.15 log units), PAMPA-DS (for 280 compounds, R² was 0.75 and rmse was 1.59 log units), BBB (for 182 compounds, R² was 0.69 and rmse was 0.87 log units), and Caco-2/MDCK assays (for 165 compounds, R² was 0.52 and rmse was 0.89 log units).

Prediction of partition and distribution coefficients in various solvent pairs with COSMO-RS

Performance of COSMO-RS method as a tool for partition and distribution modeling in 20 solvent pairs-composed of neutral or acidic aqueous solution and organic solvents of different polarity, ranging from alcohols to toluene and hexane-was evaluated. Experimental partition/distribution data of lignin-related and drug-like compounds (neutral, acidic, moderately basic) were used as reference. Several aspects of partition modeling were addressed: accounting for mutual saturation of aqueous and organic phases, variability of systematic prediction errors across solvent pairs, taking solute ionization into account. COSMO-RS was found to predict extraction outcome for both ligneous and drug-like compounds in various solvent pairs fairly well without any additional empirical input. The solvent-specific systematic errors were found to be moderate, despite being statistically significant, and related to the solvent hydrophobicity. Accounting for mutual solubilities of the two liquids was proven crucial in cases where water was considerably soluble in the organic solvent. The root mean square error of a priori logP prediction varied, depending mainly on the solvent pair, from 0.2 to 0.7, overall value being 0.6 log units. The accuracy was higher in case of hydrophilic than hydrophobic solvents. The logD predictions were less accurate, due to pK_a prediction being an additional source of error, and also because of the complexity of modeling the behaviour of ionic species in the two-phase system. A simple correction for partitioning of free ions was found to notably improve logD prediction accuracy in case of the most hydrophilic organic phase (butanol/water).

High throughput methods to measure the propensity of compounds to form intramolecular hydrogen bonding

Implementation of IMHB considerations in drug discovery needs robust and validated descriptors to experimentally verify the propensity of compounds to exhibit IMHBs. The first part of the paper presents an overview of the most common techniques to measure the propensity of compounds to form IMHBs. Then we review and discuss recently proposed high throughput (HT) physicochemical descriptors (i.e. Δlog Poct-tol, EPSA and log k'80 PLRP-S) which provide the same information. Analysis of the available data enabled us to extract guidelines for the application of these descriptors in drug discovery programs.

Enhancing silymarin fractionation using the conductor-like screening model for real solvents

A significant hurdle for discovery of plant-derived products is the numerous trial-and-error experiments required to develop an effective purification strategy. To overcome the experimental burden, a quantum mechanics-based molecular modeling approach - known as the COnductor-like Screening Model for Real Solvents (COSMO-RS) - was used to predict a suitable two-phase solvent system to purify six silymarins from an aqueous mixture. Silymarins, a class of flavonolignans found in milk thistle (Silybum marianum L.), are well suited for assessing the use of a molecular modeling approach to predict partitioning in a countercurrent chromatography (CCC) separation because they are well characterized and previous studies report low purity fractionation in liquid-liquid solvent systems. They also present an opportunity to evaluate the use of COSMO-RS in predicting the partitioning of structurally similar isomeric compounds that are present together in an aqueous solution upon extraction from their native source. The COSMO-RS model results predicted the partition coefficients in: three traditional ARIZONA solvent systems (composed of heptane, ethyl acetate, methanol, and water), nine additional variations of this quaternary solvent system, and two chloroform, methanol, and water solvent systems. Predicted results were concise but not accurate when compared to experimental results determined by the shake flask method. The 1:4:3:5 n-heptane:ethyl acetate:methanol:water (v/v/v/v) system was identified to be an improvement on the 1:4:3:4 system previously reported. The present study verified the ability of COSMO-RS to hone in on one or two solvent systems that will yield the best fractionation using CCC.

The influence of hydrogen bonding on partition coefficients

This Perspective explores how consideration of hydrogen bonding can be used to both predict and better understand partition coefficients. It is shown how polarity of both compounds and substructures can be estimated from measured alkane/water partition coefficients. When polarity is defined in this manner, hydrogen bond donors are typically less polar than hydrogen bond acceptors. Analysis of alkane/water partition coefficients in conjunction with molecular electrostatic potential calculations suggests that aromatic chloro substituents may be less lipophilic than is generally believed and that some of the effect of chloro-substitution stems from making the aromatic π-cloud less available to hydrogen bond donors. Relationships between polarity and calculated hydrogen bond basicity are derived for aromatic nitrogen and carbonyl oxygen. Aligned hydrogen bond acceptors appear to present special challenges for prediction of alkane/water partition coefficients and this may reflect 'frustration' of solvation resulting from overlapping hydration spheres. It is also shown how calculated hydrogen bond basicity can be used to model the effect of aromatic aza-substitution on octanol/water partition coefficients.

Experimental methods and prediction with COSMO-RS to determine partition coefficients in complex surfactant systems

Surfactant-based separation processes are a promising alternative to conventional organic solvent processes. A crucial parameter to describe the efficiency of such processes is the partition coefficient between the surfactant aggregates (micelles) and the aqueous bulk phase. In this work, several experimental methods to determine these partition coefficients (micellar liquid chromatography, micellar enhanced ultrafiltration, and cloud point extraction) are evaluated and compared. In addition, these results are compared to predictions with the thermodynamic model COSMO-RS. In particular, systems with the nonionic surfactant TritonX-100 are studied. The partition equilibria of various solutes (pyrene, naphthalene, phenanthrene, phenol, 3-methoxyphenol, and vanillin) and the influence of different additives (alcohols) are investigated. All experimental methods show very good reproducibility. Moreover, the results from different methods are in good agreement, supplementing one another concerning the temperature ranges. Notably, the COSMO-RS model is capable of predicting partition coefficients between micelles and water in the investigated temperature range and at different alcohol concentrations. The results demonstrate the potential of the model COSMO-RS to facilitate the selection of optimized process parameters for a given separation problem. By predicting partition equilibria in multicomponent systems, the selection of surfactant, temperature, and appropriate additives can be facilitated.