Solubility Of Small Molecules Research Articles

The openOCHEM consensus model is the best-performing open-source predictive model in the First EUOS/SLAS joint compound solubility challenge

The EUOS/SLAS challenge aimed to facilitate the development of reliable algorithms to predict the aqueous solubility of small molecules using experimental data from 100 K compounds. In total, hundred teams took part in the challenge to predict low, medium and highly soluble compounds as measured by the nephelometry assay. This article describes the winning model, which was developed using the publicly available Online CHEmical database and Modeling environment (OCHEM) available on the website https://ochem.eu/article/27. We describe in detail the assumptions and steps used to select methods, descriptors and strategy which contributed to the winning solution. In particular we show that consensus based on 28 models calculated using descriptor-based and representation learning methods allowed us to obtain the best score, which was higher than those based on individual approaches or consensus models developed using each individual approach. A combination of diverse models allowed us to decrease both bias and variance of individual models and to calculate the highest score. The model based on Transformer CNN contributed the best individual score thus highlighting the power of Natural Language Processing (NLP) methods. The inclusion of information about aleatoric uncertainty would be important to better understand and use the challenge data by the contestants.

Building Machine Learning Small Molecule Melting Points and Solubility Models Using CCDC Melting Points Dataset.

Predicting solubility of small molecules is a very difficult undertaking due to the lack of reliable and consistent experimental solubility data. It is well known that for a molecule in a crystal lattice to be dissolved, it must, first, dissociate from the lattice and then, second, be solvated. The melting point of a compound is proportional to the lattice energy, and the octanol-water partition coefficient (log P) is a measure of the compound's solvation efficiency. The CCDC's melting point dataset of almost one hundred thousand compounds was utilized to create widely applicable machine learning models of small molecule melting points. Using the general solubility equation, the aqueous thermodynamic solubilities of the same compounds can be predicted. The global model could be easily localized by adding additional melting point measurements for a chemical series of interest.

CHARMM-GUI Free Energy Calculator for Absolute and Relative Ligand Solvation and Binding Free Energy Simulations.

Alchemical free energy simulations have long been utilized to predict free energy changes for binding affinity and solubility of small molecules. However, while the theoretical foundation of these methods is well established, seamlessly handling many of the practical aspects regarding the preparation of the different thermodynamic end states of complex molecular systems and the numerous processing scripts often remains a burden for successful applications. In this work, we present CHARMM-GUI Free Energy Calculator (http://www.charmm-gui.org/input/fec) that provides various alchemical free energy perturbation molecular dynamics (FEP/MD) systems with input and post-processing scripts for NAMD and GENESIS. Four submodules are available: Absolute Ligand Binder (for absolute ligand binding FEP/MD), Relative Ligand Binder (for relative ligand binding FEP/MD), Absolute Ligand Solvator (for absolute ligand solvation FEP/MD), and Relative Ligand Solvator (for relative ligand solvation FEP/MD). Each module is designed to build multiple systems of a set of selected ligands at once for high-throughput FEP/MD simulations. The capability of Free Energy Calculator is illustrated by absolute and relative solvation FEP/MD of a set of ligands and absolute and relative binding FEP/MD of a set of ligands for T4-lysozyme in solution and the adenosine A2A receptor in a membrane. The calculated free energy values are overall consistent with the experimental and published free energy results (within ∼1 kcal/mol). We hope that Free Energy Calculator is useful to carry out high-throughput FEP/MD simulations in the field of biomolecular sciences and drug discovery.

Development of picomolar liver receptor homolog‐1 agonist

Nuclear receptors are ligand‐regulated transcription factors that alter target gene expression in response to the binding of lipophilic signaling molecules. Liver receptor homolog‐1 (LRH‐1) is a nuclear receptor that has shown promise as an anti‐diabetic therapeutic in murine studies and regulates bile acid biosynthesis, steroidogenesis, and glucose homeostasis, making it an attractive target for treating a variety of metabolic diseases. Although phospholipids are the putative endogenous ligands for LRH‐1, they are insoluble, readily remodeled and hydrolyzed, and are only efficacious at very high concentrations, making development of synthetic agonists critical for targeting LRH‐1 in clinical and laboratory contexts. Using structural data that delineated the binding pose of the only class of synthetic agonists known for LRH‐1, we have conducted structure‐activity relationship studies to enhance potency, efficacy, and solubility of small molecules. Specifically, we targeted residues deep within the binding pocket that radically enhance potency, which has led to the first low‐nanomolar LRH‐1 agonist (“6N”). We have also targeted residues contacted by the headgroups of activating phospholipids as a complementary strategy for activation. These modifications resulted in our most efficacious small molecule (“10CA”). To capture the characteristics of both compounds (6N and 10CA), we have synthesized a chimeric small molecule that includes the key moieties of 6N and 10CA responsible for high affinity and efficacy, respectively. Excitingly, this new hybrid compound binds with picomolar affinity, is more efficacious than 10CA, and elicits LRH‐1 target gene expression to a greater degree than either 6N or 10CA alone. The hybrid molecule is our most effective agonist to date, providing a critical tool for both studying LRH‐1 biology and treating a range of metabolic disorders.Support or Funding InformationNIH‐5T32GM008367‐29 (BCDB Training Grant) | NIH‐5R01DK115213‐02 | Emory Catalyst ProgramBinding mode and residue contacts of leading agonists.Figure 1Binding and in‐cell reporter data demonstrating affinity, potency, and efficacy of the hybrid compound relative to our two leading agonists.Figure 2

Predicting Solubility of Small Molecules in Macromolecular Compounds for Nanomedicine Application from Atomistic Simulations

AbstractSolubility of small molecules in macromolecular compounds is of fundamental importance for a number of applications, including the growing field of nanomedicine. Here, approaches for in silico solubility predictions based on atomistic models are evaluated. A computationally efficient atomistic simulation procedure based on the concept of inherent structures is proposed for statistical sampling of polymer conformations. Comprehensive test simulations of several polymers and common solvents confirm the accuracy of the procedure for calculation of physicochemical properties such as cohesive energy densities, which along with the Hansen solubility parameters and the Flory–Huggins (FH) theory facilitate rapid, qualitative solubility predictions. However, the FH theory fails to model specific interactions such as hydrogen bonding. Therefore, more accurate predictions are obtained employing the perturbed hard sphere chain (PHSC) equation of state (EOS). As test case, aqueous poly(ethylene oxide) (PEO) solutions revealing strong hydrogen bonding are used. The physicochemical properties including the PEO‐water phase diagram calculated by the PHSC EOS show good agreement with experimental observations. Consequently, the combination of qualitative predictions using the FH theory for rapid prescreening with computationally more demanding parameterization of the PHSC EOS provides a promising tool for in silico solubility predictions with potential applications in nanomedicine.

Polyamidoamine Dendrimers for Enhanced Solubility of Small Molecules and Other Desirable Properties for Site Specific Delivery: Insights from Experimental and Computational Studies.

Clinical applications of many small molecules are limited due to poor solubility and lack of controlled release besides lack of other desirable properties. Experimental and computational studies have reported on the therapeutic potential of polyamidoamine (PAMAM) dendrimers as solubility enhancers in pre-clinical and clinical settings. Besides formulation strategies, factors such as pH, PAMAM dendrimer generation, PAMAM dendrimer concentration, nature of the PAMAM core, special ligand and surface modifications of PAMAM dendrimer have an influence on drug solubility and other recommendable pharmacological properties. This review, therefore, compiles the recently reported applications of PAMAM dendrimers in pre-clinical and clinical uses as enhancers of solubility and other desirable properties such as sustained and controlled release, bioavailability, bio-distribution, toxicity reduction or enhancement, and targeted delivery of small molecules with emphasis on cancer treatment.

Characterizing the Effects of a "Switchable Water" Additive on the Aqueous Solubility of Small Molecules.

"Switchable water" is an aqueous solution containing a water-soluble amine additive that exhibits CO2 -switchable properties, such as large changes in ionic strength, by forming an ammonium bicarbonate salt. Switchable water has been used to reversibly "salt-out" organic compounds from water. This study explores the salting out of several compounds in switchable water when CO2 is present and also explores the solubility of small molecules in switchable water, compared to pure water, when CO2 is absent. The results show that organic compounds are generally more soluble in switchable water than pure water in the absence of CO2 , but less soluble in the presence of 1 atm CO2 . Exceptions include carboxylic acids and phenols which, presumably due to their acidity, are more soluble in switchable water than in pure water, even when CO2 is applied. Kirkwood-Buff solvation theory was applied to gain insights into the effects of the amine additive on the aqueous solubility of caffeine. Furthermore, the switchable properties of the additives allow for the preparation of switchable aqueous two-phase systems.

Experimental Study of the Synergistic Plasticizing Effect of Carbon Dioxide and Ibuprofen on the Glass Transition Temperature of Poly(methyl methacrylate)

The solubility of small molecules in a polymer and the consequent glass transition temperature reduction of the polymer with a plasticizing effect are two of the most important thermodynamic properties of small molecule–polymer systems. In this study, with an improved dual QCM device and corresponding method for determination, the solubilities of CO2 in poly(methyl methacrylate) (PMMA) film, ibuprofen (IBU) in supercritical carbon dioxide (SCCO2), and the CO2/IBU compound into PMMA film at different temperatures and pressures were determined, respectively, and then the solubility of IBU in PMMA film was calculated according to the theory of infinite dilute solution. Both CO2 and IBU molecules can plasticize the polymer in CO2–polymer and drug–polymer systems. For the CO2–IBU–PMMA ternary system, the glass transition temperature reduction behavior of PMMA versus the pressure of CO2 and proportion of IBU in PMMA was investigated, which would illustrate the synergistic plasticizing effect of CO2 and IBU on the glass transition temperature of PMMA.

Mapping a Disordered Portion of the Brz2001-Binding Site on a Plant Monooxygenase, DWARF4, Using a Quartz-Crystal Microbalance Biosensor-Based T7 Phage Display

In small-molecule/protein interaction studies, technical difficulties such as low solubility of small molecules or low abundance of protein samples often restrict the progress of research. Here, we describe a quartz-crystal microbalance (QCM) biosensor-based T7 phage display in combination use with a receptor-ligand contacts (RELIC) bioinformatics server for application in a plant Brz2001/DWARF4 system. Brz2001 is a brassinosteroid biosynthesis inhibitor in the less-soluble triazole series of compounds that targets DWARF4, a cytochrome P450 (Cyp450) monooxygenase containing heme and iron. Using a Brz2001 derivative that has higher solubility in 70% EtOH and forms a self-assembled monolayer on gold electrode, we selected 34 Brz2001-recognizing peptides from a 15-mer T7 phage-displayed random peptide library using a total of four sets of one-cycle biopanning. The RELIC/MOTIF program revealed continuous and discontinuous short motifs conserved within the 34 Brz2001-selected 15-mer peptide sequences, indicating the increase of information content for Brz2001 recognition. Furthermore, an analysis of similarity between the 34 peptides and the amino-acid sequence of DWARF4 using the RELIC/MATCH program generated a similarity plot and a cluster diagram of the amino-acid sequence. Both of these data highlighted an internally located disordered portion of a catalytic site on DWARF4, indicating that this portion is essential for Brz2001 recognition. A similar trend was also noted by an analysis using another 26 Brz2001-selected peptides, and not observed using the 27 gold electrode-recognizing control peptides, demonstrating the reproducibility and specificity of this method. Thus, this affinity-based strategy enables high-throughput detection of the small-molecule-recognizing portion on the target protein, which overcomes technical difficulties such as sample solubility or preparation that occur when conventional methods are used.

Two approaches for the engineering of homogeneous small-molecule hydrogels

Small-molecule hydrogelators have been widely used to engineer supramolecular hydrogels for biomedical applications. Typically, a change of the solubility of small molecules in solvent is used to trigger the gelation process. This requires a switch of pH or solvent by mixing two different types of solutions. However, due to the intrinsic ragged free energy landscape that underlies the self-assembly process and the high viscosity of the solution that limits the diffusion, the hydrogels made by these methods are often limited by their inhomogeneity and irreproducible physical properties. It is therefore desirable to circumvent these drawbacks and produce homogeneous hydrogels. Conversely, only a few studies have been done towards this direction. In this article, we present two novel approaches to engineer homogeneous hydrogels. One is based on the nano-dispersed colloids to hydrogel transition and the other is based on the decomposition of potassium persulfate to mildly change the pH. These two methods allow kinetically controlling the self-assembly process and the resulting hydrogels are indeed more homogeneous and reproducible. Moreover, the structural and morphological characterizations suggest that the structures of the hydrogels prepared by different approaches are distinct from each other, leading to diverse macroscopic mechanical properties. These results suggest that besides the thermodynamics, the self-assembly kinetics also plays an important role in determining the properties of the final assembled hydrogels. We propose that it is possible to rationally tune the physical properties of the hydrogels by simply control the self-assembly kinetics without changing the structure of the small-molecule hydrogelators.

Improvement in Aqueous Solubility in Small Molecule Drug Discovery Programs by Disruption of Molecular Planarity and Symmetry

Aqueous solubility is essential for drug candidates. Poor aqueous solubility is likely to result in poor absorption, even if the permeation rate is high, since the flux of a drug across the intestinal membrane is proportional to the concentration gradient between the intestinal lumen and the blood. The Biopharmaceutical Classification System (BCS) was introduced in the mid-1990s to classify drug substances with respect to their aqueous solubility and membrane permeability. Drug substrates, for which solubility enhancement can improve the oral bioavailability, are classified in class 2 (poorly soluble/ permeable) and class 4 (poorly soluble/poorly permeable). The FDA regulations concerning oral medications require more extensive investigation of compounds with low solubility, and low solubility may have an even greater impact in the case of iv dosage forms. In addition, risk assessment of poorly soluble compounds is challenging because exposure may be difficult to define and test sensitivity may be reduced. Further, high concentrations of poorly soluble drugs in organisms may result in crystallization and acute toxicity, as in the case of uric acid and gout. Overall, poor solubility of drug candidates has been identified as the cause of numerous drug development failures. According to the simplest definition, the thermodynamic solubility of a compound in a solvent is the maximum amount of the most stable crystalline form of the compound that can remain in solution under equilibrium conditions. The most stable form is invariably the form that has the highest melting point. The importance of thermodynamic assessment is greater in late discovery/early development, when it is useful to confirm earlier kinetic solubility results, to rule out potential artifacts, and to generate high-quality solubility data. The kinetic solubility of a molecule depends on its crystal form, and crystal polymorphs of a molecule can show different kinetic solubility. Therefore, crystal modification can produce an increase in dissolution rate and a temporary or apparent increase of solubility. However, it cannot produce a permanent alteration of solubility. Given sufficient time, the undissolved solute will revert to its most stable crystal form, and the solubility will approach the true thermodynamic solubility. Therefore, the role of crystal modification is confined to increasing the dissolution rate of drugs. Appropriate formulation can help in addressing these problems, but the extent of absorption and solubility enhancement that can realistically be achieved is severely limited. Stability and manufacturing problems also have to be taken into account, since it is likely that an insoluble drug candidate may not be formulated as a conventional tablet or capsule and will require a less conventional approach such as, for example, a soft gel capsule. Thus, it would be better to generate drug candidates with sufficient aqueous solubility at the drug discovery stage. In other words, it is much better to improve solubility by chemical means, i.e., by modification of the molecule itself. But on the other hand, application of combinatorial chemistry and highthroughput screening (HTS) systems has tended to change the profile of compound libraries in the direction of greater hydrophobicity and higher molecular weight, and this in turn has resulted in a profile of lower solubility. This is a problem for medicinal chemists, and improvement of the aqueous solubility of bioactive molecules is a major and common issue in medicinal chemistry. In general, the aqueous solubility of small molecules depends on their hydrophobicity (log P). The partition coefficient, logP, is defined as follows: logP = log[(solute in n-octanol)/ (solute in water)]. Increase of aqueous solubility leads to an increase of the denominator of the above equation and a decrease of log P. Thus, decrease of log P by chemical modification, i.e., introduction of hydrophilic group(s) into molecules, is a classical and general strategy for improving aqueous solubility. But this approach is not universally effective because the introduced hydrophilic group(s) sometimes interferes with the target proteindrug interaction. In addition, this strategy is not effective when both solubility and hydrophobicity need to be increased, for example, to improve the oral bioavailability of highly hydrophilic compounds with insufficient solubility. Furthermore, compounds with poor solubility in both octanol and water sometimes retain poor absolute values of aqueous solubility despite a decrease of log P values, because log P values are just ratios. Therefore, a novel and general strategy to increase the aqueous solubility of drug candidates would have a great impact on drug discovery and medicinal chemistry. Here, we review an alternative strategy for improving aqueous solubility by means of disruption of molecular planarity and symmetry.

Modulation of small molecule solubility and protein binding by arginine

We previously showed that arginine increases the aqueous solubility of the low molecular weight aromatic compounds octyl-gallate (OG) and coumarin. In this study, we focused on acycloguanosine (ACV), an antiherpic agent with moderate aqueous solubility, and examined the effects of arginine on its solubility at a neutral pH. The solubility of ACV increased by approximately 1.9- and 2.6-fold in the presence of 1 and 2M arginine, respectively, while no solubility changes were observed at an arginine concentration below 0.1M. These results were found to be consistent with observed changes in OG solubility in the presence of arginine. However, ACV and OG exhibited differential binding to bovine serum albumin (BSA): ACV showed no binding to BSA, while OG showed substantial BSA binding. In conclusion, Arginine partially blocked the protein binding of OG.

Monte Carlo simulation of the molecular properties of poly(vinyl chloride) and poly(vinyl alcohol) melts

NPT Monte Carlo simulations were performed to calculate the molecular properties of syndiotactic poly(vinyl chloride) (PVC) and syndiotactic poly(vinyl alcohol) (PVA) melts using the configurational bias Monte Carlo move, concerted rotation, reptation, and volume fluctuation. The density, mean square backbone end-to-end distance, mean square radius of gyration, fractional free-volume distribution, distribution of torsional angles, small molecule solubility constant, and radial distribution function of PVC at 0.1 MPa and above the glass transition temperature were calculated/measured, and those of PVA were calculated. The calculated results were compared with the corresponding experimental data and discussed. The calculated densities of PVC and PVA were smaller than the experimental values, probably due to the very low molecular weight of the model polymer used in the simulation. The fractional free-volume distribution and radial distribution function for PVC and PVA were nearly independent of temperature.

Effect of blend composition on diffusivity and solubility of small molecules in polystyrene/poly(vinyl methyl ether) blends

AbstractThe capillary column inverse gas chromatography technique was used to determine diffusivity and solubility data for several solvents in polymer blends composed of polystyrene and poly(vinyl methyl ether) (PVME). Diffusivity behaved as expected, increasing as the concentration of PVME increased in the blend. Knowing only the free‐volume parameters for the pure polymers, the free‐volume theory was successfully applied to predict the dependence of the diffusion coefficients on the blend composition. Transport in blends above the glass transition temperature is controlled by free volume, and the effect of concentration fluctuations is minimal at the temperatures studied. Experimental data show an increase in the partition coefficient of some solvents in the blends with respect to the pure polymers. © 2007 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 45: 2071–2082, 2007

Prediction of Activities of Small Molecules in Polymer Membrane Materials Using the Group Contribution Equation of State

Estimation of the activities or solubility of small molecules in polymers is essential in a number of process applications such as the mixture separation by polymeric membrane, polymeric membrane preparation, polymer preparation, especially, the selection of membrane material for a predefined separation process. The VTPR EoS-GE group contribution model has been used to predict the activities of water, alkane, and aromatic small molecules in poly(vinyl alcohol), poly(dimethyl siloxane), and polyisobutylene polymeric membrane materials. The influence of temperature and the molar mass of polymer on the activities of small molecules in the polymeric membrane are discussed. It has been shown that the results predicted by the VTPR EoS-GE model are good agreement with the experimental ones, and the total average deviation between the experimental and the calculated is no more than 3%. It should be expected that the VTPR EoS-GE group contribution model could be applied to the polymeric membrane material selection, to the polymeric membrane preparation processes and to the polymeric material preparation processes.

Solubility of Alkylbenzenes and a Model for Predicting the Solubility of Liquid Organics in High-Temperature Water

The solubility of ethylbenzene, m-xylene, and benzene in water was determined using a laboratory-made system at temperatures ranging from 298 K to 473 K and a pressure of 50 bars. The solubility was enhanced by at least 1 order of magnitude by increasing the temperature from ambient to 473 K. A simple approximation model was developed to predict the solubility of liquid organics in high-temperature water. This model delivers an excellent estimation of the solubility of small molecules of liquid organic compounds in water at temperatures at or higher than 373 K.

Solubility prediction by recursive partitioning.

To build and test a computational model for predicting small molecule solubility, to improve the cost-effectiveness of the selection of vendor compounds suitable for nuclear magnetic resonance (NMR) screening. A simple recursive partitioning decision tree-based classification model was generated utilizing "off-the-shelf" commercial software from Accelrys Inc., with a training set of 1992 compounds based on a series of calculated topologic and physical properties. The predictive ability of the decision tree was then assessed by employing it to classify a test set of 2851 vendor compounds, and the classification was subsequently used to guide the purchase of 686 compounds for the purpose of NMR screening. When the decision tree was used to guide purchasing, the percentage of "acceptable" compounds suitable for NMR screening doubled compared with the use of a simple cLogP cutoff, improving the successful selection rate from 25% to 50%. A simple recursive partitioning decision tree may successfully be used to improve cost-effectiveness by reducing the wastage associated with the unnecessary purchase of vendor compounds unsuitable for NMR screening because of insolubility.

Solubility of Gases in Vitreous Silica Described by a Distribution of Dissolution Energies

The solubility of gases in vitreous silica complies well with Henry's Law at low pressures. Deviations observed at high pressures have been explained by site saturation, i.e., the number of dissolved molecules approaches the number of available sites that are assumed to have all the same energy of solution. In the present study, the observed deviations from Henry's Law are explained by a gradual saturation of sites of increasing energy. Experimental data of the solubility of hydrogen, helium, and neon in vitreous silica can be described by a Gaussian distribution of dissolution energies and Fermi-Dirac statistics. The solubility of hydrogen in metallic glasses, as well as the solubility of small molecules in glassy polymers, has been interpreted, and now, glasses in vitreous silica fit into this general concept of small particles in amorphous matrices.

Novel method to estimate solubility of small molecules in cis-polyisoprene by molecular dynamics simulations

A novel method to predict gas solubility in cis-1,4-polyisoprene is developed using molecular dynamics (MD) simulations under constant particle number, constant pressure and constant temperature (NPT) conditions. Analogous to the experimental sorption technique, the binary-phase model constructed of gas/polymer was prepared. In order to maintain external pressure of the whole system during long NPT-MD runs, the vapor phase was filled with virtual liquid which has no interaction with the gas molecules and has only a repulsive interaction with the polymer. After attaining equilibration of the system, the solubility of oxygen and carbon dioxide in the polymer phase were estimated in the temperature range from 273 K to 373 K by counting the number of gas molecules inside the polymer phase. The average solubility linearly increased with the increase in the external pressure, indicating that Henry’s Law was satisfied. The solubility coefficient obtained from the present method showed good agreement with the experimental data. Concentration profiles of gas molecule showed that it was significantly higher near the interface than both in the gas phase and inside the polymer phase. The distinction between “adsorbed” and “absorbed” gas molecules and also their effect on the solubility was discussed.

A molecular simulation study on gas diffusion in a dense poly(ether–ether–ketone) membrane

Results of molecular dynamics (MD) simulations on transport and solubility of small molecules in amorphous cardo poly–ether–ether–ketone membranes are discussed. Atomistic simulation techniques have proven to be a useful tool for the understanding of structure–property relationships of materials. Although MD are still not an ideal tool for the quantitative prediction of gas permeation properties, this methodology can be used for a detailed description of the complex morphologies and transport mechanisms associated with rigid glassy structures.The diffusion process results from jumps of penetrant molecules between adjacent holes in the polymer matrix. The free volume and the occurring jump mechanism are characterized and visualized with different methods. Constants of diffusion and solubility coefficients have been calculated by the Transition State Gusev–Suter Monte Carlo method revealing a considerable agreement between simulated and calculated data.