Excess Enthalpy of Monoethanolamine + Ionic Liquid Mixtures: How Good are COSMO-RS Predictions?

An investigation of binding interactions of tumor-targeted peptide conjugated polyphenols with the kinase domain of ephrin B4 and B2 receptors

Recent studies have shown that Ephrin receptors may be upregulated in several types of cancers including breast, ovarian and endometrial cancers, making them a target for drug design. In this work, we have utilized a target-hopping approach to design new natural product-peptide conjugates and examined their interactions with the kinase-binding domain of EphB4 and EphB2 receptors. The peptide sequences were generated through point mutations of the known EphB4 antagonist peptide TNYLFSPNGPIA. Their anticancer properties and secondary structures were analyzed computationally. Conjugates of most optimum of peptides were then designed by binding the N-terminal of the peptides with the free carboxyl group of the polyphenols sinapate, gallate and coumarate, which are known for their inherent anticancer properties. To investigate if these conjugates have a potential to bind to the kinase domain, we carried out docking studies and MMGBSA free energy calculations of the trajectories based on the molecular dynamics simulations, with both the apo and the ATP bound kinase domains of both receptors. In most cases binding interactions occurred within the catalytic loop region, while in some cases the conjugates were found to spread out across the N-lobe and the DFG motif region. The conjugates were further tested for prediction of pharmacokinetic properties using ADME studies. Our results indicated that the conjugates were lipophilic and MDCK permeable with no CYP interactions. These findings provide an insight into the molecular interactions of these peptides and conjugates with the kinase domain of the EphB4 and EphB2 receptor. As a proof of concept, we synthesized and carried out SPR analysis with two of the conjugates (gallate-TNYLFSPNGPIA and sinapate-TNYLFSPNGPIA). Results indicated that the conjugates showed higher binding with the EphB4 receptor and minimal binding to EphB2 receptor. Sinapate-TNYLFSPNGPIA showed inhibitory activity against EphB4. These studies reveal that some of the conjugates may be developed for further investigation into in vitro and in vivo studies and potential development as therapeutics.

Computational study on organochlorine insecticides extraction using ionic liquids

Insecticides pose hazardous environmental effects and can enter the food chain and contaminate water resources. Ionic liquids (ILs) have recently drawn much interest as environmentally friendly solvents and have been an efficient choice for extracting pesticides because of their outstanding thermophysical characteristics and tunable nature. In this study, ILs were screened using COSMO-RS (Conductor-like Screening Model for Real Solvents) to extract organochlorine insecticides from water at 289 K. A total of 165 ILs, a combination of 33 cations with five anions, were screened by COSMO-RS to predict the selectivity and capacity of the organochlorine insecticides at infinite dilution. The Organochlorine insecticide compounds, such as benzene hexachloride (BHC), Heptachlor, Aldrin, Gamma-Chlordane (γ-Chlordane), Endrin, and Methoxychlor are selected for this study. Charge density profiles show that Endrin and Methoxychlor compounds are strong H-bond acceptors and weak H-bond donors, while the rest of the compounds are H-bond donors with no H-bond acceptor potential. Moreover, it has been shown that ILs composed of halides and heteroatomic anions in conjunction with cations have enhanced selectivity and capacity for insecticides. Moreover, the hydrophobic phosphonium-based ILs have enhanced selectivity and capacity for insecticides. In BHC extraction, the selectivity of 1,3-dimethyl-imidazolium chloride was found to be the highest at 1074.06, whereas 2-hydroxyethyl trimethyl ammonium chloride exhibited the highest capacity being 84.0.1,3-dimethyl-imidazolium chloride exhibits the highest performance index, which is 57064.77. In addition, the ILs that have been chosen are well-recognized as environmentally friendly and very effective solvents to extract insecticides from water. As a result, this study evaluated that ILs could be promising solvents that may be further developed for the extraction of insecticides from contaminated water.

Computer-Aided Molecular Design of Ionic Liquids as Advanced Process Media: A Review from Fundamentals to Applications

The unique physicochemical properties, flexible structural tunability, and giant chemical space of ionic liquids (ILs) provide them a great opportunity to match different target properties to work as advanced process media. The crux of the matter is how to efficiently and reliably tailor suitable ILs toward a specific application. In this regard, the computer-aided molecular design (CAMD) approach has been widely adapted to cover this family of high-profile chemicals, that is, to perform computer-aided IL design (CAILD). This review discusses the past developments that have contributed to the state-of-the-art of CAILD and provides a perspective about how future works could pursue the acceleration of the practical application of ILs. In a broad context of CAILD, key aspects related to the forward structure-property modeling and reverse molecular design of ILs are overviewed. For the former forward task, diverse IL molecular representations, modeling algorithms, as well as representative models on physical properties, thermodynamic properties, among others of ILs are introduced. For the latter reverse task, representative works formulating different molecular design scenarios are summarized. Beyond the substantial progress made, some future perspectives to move CAILD a step forward are finally provided.

Natural deep eutectic solvents for the extraction of lentinan from shiitake mushroom: COSMO-RS screening and ANN-GA optimizing conditions

Using natural deep eutectic solvents (NDES) for green extraction of lentinan from shiitake mushroom is a high-efficiency method. However, empirical and trial-and-error methods commonly used to select suitable NDES are unconvincing and time-consuming. Conductor-like screening model for realistic solvation (COSMO-RS) is helpful for the priori design of NDES by predicting the solubility of biomolecules. In this study, 372 NDES were used to evaluate lentinan dissolution capability via COSMO-RS. The results showed that the solvent formed by carnitine (15 wt%), urea (40.8 wt%), and water (44.2 wt%) exhibited the best performance for the extraction of lentinan. In the extraction stage, an artificial neural network coupled with genetic algorithm (ANN-GA) was developed to optimize the extraction conditions and to analyze their interaction effects on lentinan content. Therefore, COSMO-RS and ANN-GA can be used as powerful tools for solvent screening and extraction process optimization, which can be extended to various bioactive substance extraction.

A computational and laboratory approach for the investigation of interactions of peptide conjugated natural terpenes with EpHA2 receptor

CONTEXT

Ephrin type A receptor 2 (EphA2) is a well-known drug target for cancer treatment due to its overexpression in numerous types of cancers. Thus, it is crucial to determine the binding interactions of this receptor with both the ligand-binding domain (LBD) and the kinase-binding domain (KBD) through a targeted approach in order to modulate its activity. In this work, natural terpenes with inherent anticancer properties were conjugated with short peptides YSAYP and SWLAY that are known to bind to the LBD of EphA2 receptor. We examined the binding interactions of six terpenes (maslinic acid, levopimaric acid, quinopimaric acid, oleanolic, polyalthic, and hydroxybetulinic acid) conjugated to the above peptides with the ligand-binding domain (LBD) of EphA2 receptor computationally. Additionally, following the "target-hopping approach," we also examined the interactions of the conjugates with the KBD. Our results indicated that most of the conjugates showed higher binding interactions with the EphA2 kinase domain compared to LBD. Furthermore, the binding affinities of the terpenes increased upon conjugating the peptides with the terpenes. In order to further investigate the specificity toward EphA2 kinase domain, we also examined the binding interactions of the terpenes conjugated to VPWXE (x = norleucine), as VPWXE has been shown to bind to other RTKs. Our results indicated that the terpenes conjugated to SWLAY in particular showed high efficacy toward binding to the KBD. We also designed conjugates where in the peptide portion and the terpenes were separated by a butyl (C4) group linker to examine if the binding interactions could be enhanced. Docking studies showed that the conjugates with linkers had enhanced binding with the LBD compared to those without linkers, though binding remained slightly higher without linkers toward the KBD. As a proof of concept, maslinate and oleanolate conjugates of each of the peptides were then tested with F98 tumor cells which are known to overexpress EphA2 receptor. Results indicated that the oleanolate-amido-SWLAY conjugates were efficacious in reducing the cell proliferation of the tumor cells and may be potentially developed and further studied for targeting tumor cells overexpressing the EphA2 receptor. To test if these conjugates could bind to the receptor and potentially function as kinase inhibitors, we conducted SPR analysis and ADP-Glo assay. Our results indicated that OA conjugate with SWLAY showed the highest inhibition.

METHODS

Docking studies were carried out using AutoDock Vina, v.1.2.0; Molecular Dynamics and MMGBSA calculations were carried out through Schrodinger Software DESMOND.

Molecular dynamics, MMGBSA, and docking studies of natural products conjugated to tumor-targeted peptide for targeting BRAF V600E and MERTK receptors

Recent studies have revealed that MERTK and BRAF V600E receptors have been found to be over-expressed in several types of cancers including melanoma, making these receptors targets for drug design. In this study, we have designed novel peptide conjugates with the natural products vanillic acid, thiazole-2-carboxylic acid, cinnamic acid, theanine, and protocatechuic acid. Each of these compounds was conjugated with the tumor targeting peptide sequence TAASGVRSMH, known to bind to NG2 and target tumor neovasculature. We examined their binding affinities and stability with MERTK and BRAF V600E receptors using molecular docking and molecular dynamics studies. Compared to the neat compounds, the peptide conjugates displayed higher binding affinity toward both receptors. In the case of MERTK, the most stable complexes were formed with di-theaninate-peptide, vanillate-peptide, and thiazole-2-amido peptide conjugates and binding occurred in the hinge region. Additionally, it was discovered that the peptide alone also had high binding ability and stability with the MERTK receptor. In the case of BRAF V600E, the peptide conjugates of protocatechuate, vanillate and thiazole-2-amido peptide conjugates showed the formation of the most stable complexes and binding occurred in the ATP binding cleft. Further analysis revealed that the number of hydrogen bonds and hydrophobic interactions played a critical role in enhanced stability of the complexes. Docking studies also revealed that binding affinities for NG2 were similar to MERTK and higher for BRAF V600E. MMGBSA studies of the trajectories revealed that the protocatechuate-peptide conjugate showed the highest binding energy with BRAF V600E while the peptide-TAASGVRSMH showed the highest binding energy with MERTK. ADME studies revealed that each of the compounds showed medium to high permeability toward MDCK cells and were not hERG blockers. Furthermore, the conjugates were not CYP inhibitors or substrates, but they were found to be Pgp substrates. Our results indicated that the protocatechuate-TAASGVRSMH, thiazole-2-amido-TAASGVRSMH, and vanillate-TAASGVRSMH conjugates may be furthered developed for in vitro and in vivo studies as novel tumor targeting compounds for tumor cells over-expressing BRAF V600E, while di-theaninate-amido-TAASGVRSMH and thiazole-2-amido-TAASGVRSMH conjugates may be developed for targeting MERTK receptors. These studies provide insight into the molecular interactions of natural product-peptide conjugates and their potential for binding to and targeting MERTK and BRAF V600E receptors in developing new therapeutics for targeting cancer.

Multiscale molecular simulations for the solvation of lignin in ionic liquids

Lignin, the second most abundant biopolymer found in nature, has emerged as a potential source of sustainable fuels, chemicals, and materials. Finding suitable solvents, as well as technologies for efficient and affordable lignin dissolution and depolymerization, are major obstacles in the conversion of lignin to value-added products. Certain ionic liquids (ILs) are capable of dissolving and depolymerizing lignin but designing and developing an effective IL for lignin dissolution remains quite challenging. To address this issue, the COnductor-like Screening MOdel for Real Solvents (COSMO-RS) model was used to screen 5670 ILs by computing logarithmic activity coefficients (ln(γ)) and excess enthalpies (H^E) of lignin, respectively. Based on the COSMO-RS computed thermodynamic properties (ln(γ) and H^E) of lignin, anions such as acetate, methyl carbonate, octanoate, glycinate, alaninate, and lysinate in combination with cations like tetraalkylammonium, tetraalkylphosphonium, and pyridinium are predicted to be suitable solvents for lignin dissolution. The dissolution properties such as interaction energy between anion and cation, viscosity, Hansen solubility parameters, dissociation constants, and Kamlet-Taft parameters of selected ILs were evaluated to assess their propensity for lignin dissolution. Furthermore, molecular dynamics (MD) simulations were performed to understand the structural and dynamic properties of tetrabutylammonium [TBA]⁺-based ILs and lignin mixtures and to shed light on the mechanisms involved in lignin dissolution. MD simulation results suggested [TBA]⁺-based ILs have the potential to dissolve lignin because of their higher contact probability and interaction energies with lignin when compared to cholinium lysinate.

Prediction of biphasic separation in CO2 absorption using a molecular surface information-based machine learning model

Carbon dioxide capture technologies have become a focus to overcome global warming. Biphasic absorbents are one of the promising approaches for energy-saving CO₂ capture processes. These biphasic absorbents are mainly composed of a mixed solvent composed of alkanolamine and organic solvents like glycol ether or alcohol. However, screening experiments of the mixed-solvent absorbents are required to search for biphasic absorbents due to their complicated phase behavior. In this work, we developed a prediction method for the phase states of the mixed-solvent absorbents using a quantum calculation and machine learning models, including random forest, logistic regression, and support vector machine models. There are 61 mixed-solvent absorbents containing alkanolamine/glycol ether or alcohol in the dataset. The machine learning models successfully predicted the phase states of the mixed-solvent absorbents before and after CO₂ absorption with accuracies of more than 90%. Furthermore, we analyzed the contributions of explanatory variables for prediction using the learned model. As a result, we found that molecular surface charge of the amine species is more important than those of the other organic solvents to determine the phase behaviors during CO₂ absorption.

Renewable Schiff-Base Ionic Liquids for Lignocellulosic Biomass Pretreatment

Growing interest in sustainable sources of chemicals and energy from renewable and reliable sources has stimulated the design and synthesis of renewable Schiff-base (iminium) ionic liquids (ILs) to replace fossil-derived ILs. In this study, we report on the synthesis of three unique iminium-acetate ILs from lignin-derived aldehyde for a sustainable “future” lignocellulosic biorefinery. The synthesized ILs contained only imines or imines along with amines in their structure; the ILs with only imines group exhibited better pretreatment efficacy, achieving >89% sugar release. Various analytical and computational tools were employed to understand the pretreatment efficacy of these ILs. This is the first study to demonstrate the ease of synthesis of these renewable ILs, and therefore, opens the door for a new class of “Schiff-base ILs” for further investigation that could also be designed to be task specific.

Screening ionic liquids for dissolving hemicellulose by COSMO-RS based on the selective model

The utilization of biomass resources has attracted more and more attention due to the consumption of non-renewable resources. Compared with cellulose and lignin, hemicellulose has been less studied. Some ionic liquids (ILs) have been proved to be excellent solvents for lignocellulosic pretreatment. However, screening of more efficient ILs is difficult due to numerous possible ILs. Computational chemistry has been proved effective in solvent screening, but a precise model is indispensable. In this work, we focused on building several appropriate models and selected the most suitable one. According to the structure of hemicellulose, six hemicellulose models were constructed and the mid-dimer of the xylan chain hemicellulose (MDXC) model was proved to be the best compared with the reported experimental results. Based on the MDXC model, 1368 ILs were screened to evaluate their ability to dissolve hemicellulose by Conductor-like Screening Model for Real Solvents (COSMO-RS). The activity coefficient (γ), excess enthalpy (HE), and σ-profile indicated that the hydrogen-bond (H-bond) played a vital role in the dissolution of hemicellulose. Anions played a more critical role than cations, where small anions with H-bond acceptor groups could enhance the molecular interactions with hemicellulose. This work provided a thermodynamic understanding of hemicellulose and IL solvent systems. It highlights the importance of building appropriate solute models, which may be necessary to predict of the other thermodynamic properties in the future.

Experimental and Mathematical Modelling of Factors Influencing Carbon Dioxide Absorption into the Aqueous Solution of Monoethanolamine and 1-Butyl-3-methylimidazolium Dibutylphosphate Using Response Surface Methodology (RSM)

This paper investigated the solubility of carbon dioxide (CO₂) in an aqueous solution of monoethanolamine (MEA) and 1-butyl-3-methylimidazolium dibutylphosphate ((BMIM)(DBP)) ionic liquid (IL) hybrid solvents. Aqueous solutions of MEA-(BMIM)(DBP) hybrid solvents containing different concentrations of (BMIM)(DBP) were prepared to exploit the amine’s reactive nature, combined with the IL’s non-volatile nature for CO₂ absorption. Response surface methodology (RSM) based on central composite design (CCD) was used to design the CO₂ solubility experiments and to investigate the effects of three independent factors on the solubility of CO₂ in the aqueous MEA-(BMIM)(DBP) hybrid solvent. The three independent factors were the concentration of (BMIM)(DBP) (0–20 wt.%), temperature (30 °C–60 °C) and pressure of CO₂ (2–30 bar). The experimental data were fitted to a quadratic model with a coefficient of determination (R²) value of 0.9791. The accuracy of the developed model was confirmed through additional experiments where the experimental values were found to be within the 95% confidence interval. From the RSM-generated model, the optimum conditions for CO₂ absorption in aqueous 30 wt% MEA-(BMIM)(DBP) were 20 wt% of (BMIM)(DBP), a temperature of 41.1 °C and a pressure of 30 bar.

Molecular dynamics simulations, docking and MMGBSA studies of newly designed peptide-conjugated glucosyloxy stilbene derivatives with tumor cell receptors

In this work, for the first time, we designed derivatives of beta-D-glucosyloxy-3-hydroxy-trans-stiblene-2-carboxylic acid (GHS), by conjugating GHS with tumor targeting peptides RPARPAR and GGKRPAR to target over-expressed receptors in tumor cells. The sequences RPARPAR and GGKRPAR are known to target the neuropilin1 (NRP1) receptor due to the C-terminal Arg domain; however, their effectiveness has never been examined with other commonly over-expressed receptors in tumor cells, particularly of chronic lymphocytic leukemia that include integrin α1β1 and CD22. By conjugating these peptides with GHS, which is known for its inherent anti-cancer properties, the goal is to further enhance tumor cell targeting by developing compounds that can target multiple receptors. The physicochemical properties of the conjugates and individual peptides were analyzed using Turbomole and COSMOthermX20 in order to determine their hydrogen bond accepting and donating capabilities. The web server POCASA was used in order to determine the surface cavities and binding pockets of the three receptors. To explore the binding affinities, we conducted molecular docking studies with the peptides and the conjugates with each of the receptors. After molecular docking, the complexes were analyzed using Protein-Ligand Interaction Profiler to determine the types of interactions involved. Molecular dynamics simulation studies were conducted to explore the stability of the receptor-ligand complexes. Our results indicated that in most cases the conjugates showed higher binding and stability with the receptors. Additionally, highly stable complexes of conjugates were obtained with CD22, NRP1 and in most cases with the integrin α1β1 receptor as well. The binding energies were calculated for each of the receptor ligand complexes through trajectory analysis using MMGBSA studies. SwissADME studies revealed that the compounds showed low GI absorption and were not found to be CYP inhibitors and had bioavailability score that would allow them to be considered as potential drug candidates. Overall, our results for the first time show that the designed conjugates can target multiple over-expressed receptors in tumor cells and may be potentially developed as future therapeutics for targeting tumor cells.

In silico studies of interactions of peptide-conjugated cholesterol metabolites and betulinic acid with EGFR, LDR, and N-terminal fragment of CCKA receptors

In this work, we designed three new ligands by conjugating cholesterol metabolites 3-hydroxy-5-cholestenoic acid (3-HC) and 3-oxo-4-cholestenoic acid (3-OC) and the natural tri-terpenoid betulinic acid with the tumor-targeting peptide YHWYGYTPQNVI. Molecular interactions with the unconjugated peptide and the conjugates were examined with three receptors that are commonly overexpressed in pancreatic adenocarcinoma cells using ligand docking and molecular dynamics. This study demonstrated the utility of the designed conjugates as a valuable scaffold for potentially targeting EGFR and LDLR receptors. Our results indicate that the conjugates showed strong binding affinities and formation of stable complexes with EGFR, while the unconjugated peptide, BT-peptide conjugate, an 3-HC-peptide conjugate showed the formation of fairly stable complexes with LDLR receptor. For EGFR, two receptor kinase domains were explored. Interactions with the N-terminal domain of CCKA-R were relatively weaker. For LDLR, binding occurred in the beta-propeller region. For the N-terminal fragment of CCKA-R, the conjugates induced significant conformational changes in the receptor. The molecular dynamic simulations for 100 ns demonstrate that BT-peptide conjugates and the unconjugated peptide had the highest binding and formed the most stable complexes with EGFR. RMSD and trajectory analyses indicate that these molecules transit to a dynamically stable configuration in most cases within 60 ns. NMA analysis indicated that amongst the conjugates that showed relatively higher interactions with the respective receptors, the highest potential for deformability was seen for the N-terminal-47 amino acid region of the CCKA-R receptor with and the lowest for the LDLR-receptor. Thus, the newly designed compounds may be evaluated in the future toward developing drug delivery materials for targeting tumor cells overexpressing LDLR or EGFR.

Exploring the Interactions of Ionic Liquids with Bio-Organic Amphiphiles Using Computational Approaches

Bio-organic amphiphiles have been shown to effectively impart unique physicochemical properties to ionic liquids resulting in the formation of versatile hybrid composites. In this work, we utilized computational methods to probe the formation and properties of hybrids prepared by mixing three newly designed bio-organic amphiphiles with 14 ionic liquids containing cholinium or glycine betaine cations and a variety of anions. The three amphiphiles were designed such that they contain unique biological moieties found in nature by conjugating (a) malic acid with the amino acid glutamine, (b) thiomalic acid with the antiviral, antibacterial pyrazole compound [3-(3,5-dimethyl-1H-pyrazol-1-yl)benzyl]amine, and (c) Fmoc-protected valine with diphenyl amine. Conductor-like screening model for real solvents (COSMO-RS) was used to obtain sigma profiles of the hybrid mixtures and to predict viscosities and mixing enthalpies of each composite. These results were used to determine optimal ionic liquid-bio-organic amphiphile mixtures. Molecular dynamics simulations of three optimal hybrids were then performed, and the interactions involved in the formation of the hybrids were analyzed. Our results indicated that cholinium-based ILs interacted most favorably with the amphiphiles through a variety of inter- and intramolecular interactions. This work serves to illustrate important factors that influence the interactions between bio-organic amphiphiles and bio-ILs and aids in the development of novel ionic liquid-based composites for a wide variety of potential biological applications.

Experimental investigation of density, viscosity, and surface tension of aqueous tetrabutylammonium-based ionic liquids

The physical properties such as density, dynamic viscosity, and surface tension of aqueous tetrabutylammonium-based ionic liquids were measured experimentally by varying temperature (283.4 to 333.4 K) and concentration of ILs (10-50 wt%) at an interval of 10 K and 10 wt% respectively. In this study, the aqueous tetrabutylammonium-based ionic liquids namely tetrabutylammonium acetate [TBA][OAC], tetrabutylammonium bromide [TBA][Br], and tetrabutylammonium hydroxide [TBA][OH] was used to investigate the influence of temperature and concentration of ILs on the physical properties data was examined. It is observed that both density and surface tension increase with increasing concentration of [TBA][Br], whereas the opposite trend is observed for [TBA][OAC] and [TBA][OH] respectively. This is due to stronger molecular interaction between [TBA][Br] and water compared to other ILs. The dynamic viscosity of all aqueous ILs increases with increasing IL concentration. The measured physical properties of ILs decrease as temperature increases. Furthermore, the experimental data is correlated and compared with that of the calculated model; the agreement was satisfactory. Graphical abstract.

Thermodynamic models applied to CO2 absorption modelling

Carbon capture, utilisation, and storage (CCUS) is considered as the least cost-intensive option towards achieving the emission reduction target by 2050. One of the important technologies to remove CO2 from different gas streams is solvent-based CO2 capture. Modelling and simulation of solvent-based CO2 capture processes have been attracting a lot of attention in recent years. Thermodynamic models play a vital role in these modelling and simulation studies. Hence, this study critically reviews the thermodynamic models applied in the modelling of solvent-based CO2 capture systems over the past years, to provide a guideline for the selection of the optimum models for future studies. These models have wide applications in two main areas: equilibrium modelling [vapour-liquid equilibrium (VLE) (physical) and speciation equilibrium (chemical)], and calculation of some thermodynamic properties. VLE and speciation modelling methods are classified rigorously. VLE modelling methods are classified as homogeneous, heterogeneous, and empirical, and speciation modelling methods are classified as iterative (which could be stoichiometric and non-stoichiometric) and non-iterative. Thermodynamic models are categorised into three key families: activity-coefficient based, equation of state based, and quantum mechanical based. Theory and concepts of different thermodynamic models are presented. Some selected studies that used each family of thermodynamic models are reviewed.

MoDoop: An Automated Computational Approach for COSMO-RS Prediction of Biopolymer Solubilities in Ionic Liquids

An automated computational framework (MoDoop) was developed to predict the biopolymer solubilities in ionic liquids (ILs) on the basis of conductor-like screening model for real solvents calculations of two thermodynamic properties: logarithmic activity coefficient (ln γ) at infinite dilution and excess enthalpy (H ^E) of mixture. The calculation was based on the optimized two-dimensional structures of biopolymer models and ILs by searching the lowest-energy conformer and optimizing molecular geometry. Three lignin models together with one IL dataset were used to evaluate the prediction ability of the developed method. The evaluation results show that ln γ is a more reliable property to predict lignin solubilities in ILs and the p-coumaryl alcohol model is considered as the best model to represent lignin molecules. The developed MoDoop approach is efficient for rapid in silico screening of suitable ionic liquids to dissolve biopolymers.

Carbon dioxide capture by amino-functionalized ionic liquids: DFT based theoretical analysis substantiated by FT-IR investigation

Both computational and experimental studies show amino-functionalized ionic liquids, [aEMMIM][X] (X = F, Cl, Br, and I), can chemically capture CO₂.

Recovery of tyrosol from aqueous streams using hydrophobic ionic liquids: a first step towards developing sustainable processes for olive mill wastewater (OMW) management

Hydrophobic ILs have been proposed as VOCs replacements for tyrosol recovery from aqueous solutions, revealing promising extraction efficiency and regeneration capacity. This will help developing sustainable processes for olive mill waste management.

Solubility of CO2 in [1-n-butylthiolanium][Tf2N]+toluene mixtures: liquid-liquid phase split separation and modelling

Carbon dioxide has been shown to be an effective antisolvent gas for separating organic compounds from ionic liquids (ILs) by inducing a liquid-vapour to liquid-liquid-vapour transition. Using carbon dioxide, toluene can be separated from imidazolium, phosphonium and pyridinum cation-based ILs with the bis(trifluoromethylsulfonyl)imide anion, which is relatively hydrophobic and has a high toluene solubility. A new IL with relatively low viscosity is tested here for the same toluene separation process: 1-n-butylthiolanium bis(trifluoromethylsulfonyl)imide. Carbon dioxide solubility in binary and ternary systems containing toluene and 1-n-butylthiolanium bis(trifluoromethylsulfonyl)imide is measured at 298.15 and 313.15 K up to 7.4 MPa. Solubility behaviour in this IL is similar to imidazolium-based ILs with the same anion. However, phase split pressures are lower when 1-n-butylthiolanium bis (trifluoromethylsulfonyl)imide is used instead of 1- n-hexyl-3-methylimidazolium bis(trifluoromethylsu- lfonyl)imide at the same conditions of temperature and initial composition of toluene in the IL. Solubility data are modelled with the conductor-like screening model for real solvents combined with the Soave-Redlich-Kwong equation of state, which provides good qualitative results.

Imidazole tailored deep eutectic solvents for CO2 capture enhanced by hydrogen bonds

Hydrogen bonds enhance the CO₂ uptake in novel imidazolium tailored deep eutectic solvents.