Predicting Skin Permeability by means of Computational Approaches : Reliability and Caveats in Pharmaceutical Studies

© 2019 American Chemical Society.The skin is the main barrier between the internal body environment and the external one. The characteristics of this barrier and its properties are able to modify and affect drug delivery and chemical toxicity parameters. Therefore, it is not surprising that permeability of many different compounds has been measured through several in vitro and in vivo techniques. Moreover, many different in silico approaches have been used to identify the correlation between the structure of the permeants and their permeability, to reproduce the skin behavior, and to predict the ability of specific chemicals to permeate this barrier. A significant number of issues, like interlaboratory variability, experimental conditions, data set building rationales, and skin site of origin and hydration, still prevent us from obtaining a definitive predictive skin permeability model. This review wants to show the main advances and the principal approaches in computational methods used to predict this property, to enlighten the main issues that have arisen, and to address the challenges to develop in future research.Peer reviewedFinal Accepted Versio

In Silico Prediction of Physicochemical Properties

This report provides a critical review of computational models, and in particular(quantitative) structure-property relationship (QSPR) models, that are available for the prediction of physicochemical properties. The emphasis of the review is on the usefulness of the models for the regulatory assessment of chemicals, particularly for the purposes of the new European legislation for the Registration, Evaluation, Authorisation and Restriction of CHemicals (REACH), which entered into force in the European Union (EU) on 1 June 2007. It is estimated that some 30,000 chemicals will need to be further assessed under REACH. Clearly, the cost of determining the toxicological and ecotoxicological effects, the distribution and fate of 30,000 chemicals would be enormous. However, the legislation makes it clear that testing need not be carried out if adequate data can be obtained through information exchange between manufacturers, from in vitro testing, and from in silico predictions. The effects of a chemical on a living organism or on its distribution in the environment is controlled by the physicochemical properties of the chemical. Important physicochemical properties in this respect are, for example, partition coefficient, aqueous solubility, vapour pressure and dissociation constant. Whilst all of these properties can be measured, it is much quicker and cheaper, and in many cases just as accurate, to calculate them by using dedicated software packages or by using (QSPRs). These in silico approaches are critically reviewed in this report.JRC.I.3-Toxicology and chemical substance

An adaptive model for learning molecular endpoints

I will describe a recursive neural network that deals with undirected graphs, and its application to predicting property labels or activity values of small molecules. The model is entirely general, in that it can process any undirected graph with a finite number of nodes by factorising it into a number of directed graphs with the same skeleton. The model\u27s only input in the applications I will present is the graph representing the chemical structure of the molecule. In spite of its simplicity, the model outperforms or matches the state of the art in three of the four tasks, and in the fourth is outperformed only by a method resorting to a very problem-specific feature

Predicting the solvation of organic compounds in aqueous environments: from alkanes and alcohols to pharmaceuticals

The development of accurate models to predict the solvation, solubility, and partitioning of nonpolar and amphiphilic compounds in aqueous environments remains an important challenge. We develop state-of-the-art group-interaction models that deliver an accurate description of the thermodynamic properties of alkanes and alcohols in aqueous solution. The group-contribution formulation of the statistical associating fluid theory based on potentials with a variable Mie form (SAFT-γ Mie) is shown to provide accurate predictions of the phase equilibria, including liquid–liquid equilibria, solubility, free energies of solvation, and other infinite-dilution properties. The transferability of the model is further exemplified with predictions of octanol–water partitioning and solubility for a range of organic and pharmaceutically relevant compounds. Our SAFT-γ Mie platform is reliable for the prediction of challenging properties such as mutual solubilities of water and organic compounds which can span over 10 orders of magnitude, while remaining generic in its applicability to a wide range of compounds and thermodynamic conditions. Our work sheds light on contradictory findings related to alkane–water solubility data and the suitability of models that do not account explicitly for polarity

QSPR Studies on Aqueous Solubilities of Drug-Like Compounds

A rapidly growing area of modern pharmaceutical research is the prediction of aqueous solubility of drug-sized compounds from their molecular structures. There exist many different reasons for considering this physico-chemical property as a key parameter: the design of novel entities with adequate aqueous solubility brings many advantages to preclinical and clinical research and development, allowing improvement of the Absorption, Distribution, Metabolization, and Elimination/Toxicity profile and “screenability” of drug candidates in High Throughput Screening techniques. This work compiles recent QSPR linear models established by our research group devoted to the quantification of aqueous solubilities and their comparison to previous research on the topic

Development of a liquid-liquid extraction method of resveratrol from cell culture media using solubility parameters

YesThe extraction of bioactive compounds, produced by plant cell cultures, directly from their culture medium, which contains other by-products, is a great challenge. Resveratrol extraction from its grapevine cell cultures is considered here as an example to improve the extraction processes from plant cell cultures using solubility parameters. Successive liquid-liquid extraction (LLE) processes were exploited to extract resveratrol from the culture medium with an extraction ratio approaching 100%, high selectivity and minimum amounts of solvents. The calculations of partition coefficients as a function of solubility parameters demonstrated that benzyl benzoate is the most suitable intermediate solvent to extract resveratrol from its aqueous medium. The calculations also illustrated the high ability of methanol and ethanol to extract resveratrol from benzyl benzoate. The physicochemical properties of benzyl benzoate and processing conditions were exploited to separate it from aqueous media and organic solvents. The agitation method, component ratios and extraction time were studied to maximize the extraction yield. Under the best studied conditions, the recovery of resveratrol from different culture media approached ∼100% with a selectivity of ∼92%. Ultimately, the improved extraction processes of resveratrol are markedly efficient, selective, rapid and economical.Mohammad Amin Mohammad gratefully acknowledges CARA (The Council for At-Risk Academics, Stephen Wordsworth and Ryan Mundy) for providing the financial support for an academic fellowship

Fundamental Studies of Metal Ion Extraction into Ionic Liquids By Macrocyclic Polyethers

The liquid-liquid extraction (LLX) of metal ions from aqueous media into ionic liquids (ILs) by macrocyclic polyethers has proven to be an efficient and selective, but complex approach to their separation. Partitioning in these systems has previously been described using a so-called ‘three-path’ model comprising three distinct extraction pathways: neutral complex / ion pair extraction, exchange of the IL cation for a metal-extractant complex, and exchange of the metal ion for a hydronium ion bound to the extractant. The balance of these three paths has been reported to be affected by several characteristics of the LLX system, including the structure of the IL, the stereochemistry of the extractant, and the Lewis acidity of the metal ion, among others. Qualitative trends for many of these factors have been reported, but despite the tremendous number of anion-cation combinations yielding an ionic liquid (i.e., \u3e 108), only a single family (i.e., 1, 3-dialkylimidazolium) has been systematically studied. Evaluating the benefit (i.e., improved efficiency or selectivity), if any of employing other families of ILs as extraction solvents requires extensive partitioning studies. Consequently, the performance of most IL families remains largely unknown. Furthermore, a quantitative description of metal ion extraction from acidic media into ionic liquids is necessary before they can be considered useful extraction solvents. In general terms then, the objective of this work is to investigate several families of ionic liquids to determine whether qualitative trends reported previously represent a ‘generic’ description of metal ion extraction in IL-based systems and if these trends can be confirmed quantitatively. To this end, extraction studies employing quaternary ammonium- and N-alkylpyridinium-based ILs and alkali and alkaline earth cations have been conducted to determine if the ‘three-path’ model provides a satisfactory description of metal ion partitioning in these LLX systems. The results of these studies are consistent with those reported previously for systems employing 1, 3-dialkylimidazolium-based ILs, but they have also unexpectedly revealed a significant effect of the self-aggregation of the IL cation on extraction behavior. In an attempt to reduce the number of experimental measurements required to describe metal ion extraction into an ionic liquid, several parameters that define the hydrophobicity of an IL (e.g., hydrophilicity index, water solubility, and Dow) have been investigated and found to accurately predict extraction behavior. Lastly, a process by which to quantitatively describe the balance of pathways in an IL-based extraction system that can be used as a basis for future evaluation of ILs as extraction solvents has been developed