Modelling for antimicrobial activities of ionic liquids towards Escherichia coli, Staphylococcus aureus and Candida albicans using linear free energy relationship descriptors

Ionic Liquids: Emerging Antimicrobial Agents

Antimicrobial resistance has become a serious threat to global health. New antimicrobials are thus urgently needed. Ionic liquids (ILs), salts consisting of organic cations and anions with melting points less than 100°C, have been recently found to be promising in antimicrobial field as they may disrupt the bacterial wall and membrane and consequently lead to cell leakage and death. Different types of antimicrobial ILs are introduced in the review, including cationic, polymeric, and anionic ILs. Being the main type of the antimicrobial ILs, the review focuses on the structure and the antimicrobial mechanisms of cationic ILs. The quantitative structure-activity relationship (QSAR) models of the cationic ILs are also included. Increase in alkyl chain length and lipophilicity is beneficial to increase the antimicrobial effects of cationic ILs. Polymeric ILs are homopolymers of monomer ILs or copolymers of ILs and other monomers. They have great potential in the field of antibiotics as they provide stronger antimicrobial effects than the sum of the monomer ILs. Anionic ILs are composed of existing anionic antibiotics and organic cations, being capable to enhance the solubility and bioavailability of the original form. Nonetheless, the medical application of antimicrobial ILs is limited by the toxicity. The structural optimization aided by QSAR model and combination with existing antibiotics may provide a solution to this problem and expand the application range of ILs in antimicrobial field.

Review of the toxic effects of ionic liquids

Interest in ionic liquids (ILs), called green or designer solvents, has been increasing because of their excellent properties such as thermal stability and low vapor pressure; thus, they can replace harmful organic chemicals and help several industrial fields e.g., energy-storage materials production and biomaterial pretreatment. However, the claim that ILs are green solvents should be carefully considered from an environmental perspective. ILs, given their minimal vapor pressure, may not directly cause atmospheric pollution. However, they have the potential to cause adverse effects if leaked into the environment, for instance if they are spilled due to human mistakes or technical errors. To estimate the risks of ILs, numerous ILs have had their toxicity assessed toward several micro- and macro-organisms over the past few decades. Since the toxic effects of ILs depend on the method of estimating toxicity, it is necessary to briefly summarize and comprehensively discuss the biological effects of ILs according to their structure and toxicity testing levels. This can help simplify our understanding of the toxicity of ILs. Therefore, in this review, we discuss the key findings of toxicological information of ILs, collect some toxicity data of ILs to different species, and explain the influence of IL structure on their toxic properties. In the discussion, we estimated two different sensitivity values of toxicity testing levels depending on the experiment condition, which are theoretical magnitudes of the inherent sensitivity of toxicity testing levels in various conditions and their changes in biological response according to the change in IL structure. Finally, some perspectives, future research directions, and limitations to toxicological research of ILs, presented so far, are discussed.

Compound Prioritization through Meta-Analysis Enhances the Discovery of Antimicrobial Hits against Bacterial Pathogens

The development of informatic tools to improve the identification of novel antimicrobials would significantly reduce the cost and time of drug discovery. We previously screened several plant (Xanthomonas sp., Clavibacter sp., Acidovorax sp., and Erwinia sp.), animal (Avian pathogenic Escherichia coli and Mycoplasma sp.), and human (Salmonella sp. and Campylobacter sp.) pathogens against a pre-selected small molecule library (n = 4182 SM) to identify novel SM (hits) that completely inhibited the bacterial growth or attenuated at least 75% of the virulence (quorum sensing or biofilm). Our meta-analysis of the primary screens (n = 11) using the pre-selected library (approx. 10.2 ± 9.3% hit rate per screen) demonstrated that the antimicrobial activity and spectrum of activity, and type of inhibition (growth versus virulence inhibitors) correlated with several physico-chemical properties (PCP; e.g., molecular weight, molar refraction, Zagreb group indexes, Kiers shape, lipophilicity, and hydrogen bond donors and acceptors). Based on these correlations, we build an in silico model that accurately classified 80.8% of the hits (n = 1676/2073). Therefore, the pre-selected SM library of 4182 SM was narrowed down to 1676 active SM with predictable PCP. Further, 926 hits affected only one species and 1254 hits were active against specific type of pathogens; however, no correlation was detected between PCP and the type of pathogen (29%, 34%, and 46% were specific for animal, human foodborne and plant pathogens, respectively). In conclusion, our in silico model allowed rational identification of SM with potential antimicrobial activity against bacterial pathogens. Therefore, the model developed in this study may facilitate future drug discovery efforts by accelerating the identification of uncharacterized antimicrobial molecules and predict their spectrum of activity.

Ionic Liquids-A Review of Their Toxicity to Living Organisms

Ionic liquids (ILs) were initially hailed as a green alternative to traditional solvents because of their almost non-existent vapor pressure as ecological replacement of most common volatile solvents in industrial processes for their damaging effects on the environment. It is common knowledge that they are not as green as desired, and more thought must be put into the biological consequences of their industrial use. Still, compared to the amount of research studying their physicochemical properties and potential applications in different areas, there is a scarcity of scientific papers regarding how these substances interact with different organisms. The intent of this review was to compile the information published in this area since 2015 to allow the reader to better understand how, for example, bacteria, plants, fish, etc., react to the presence of this family of liquids. In general, lipophilicity is one of the main drivers of toxicity and thus the type of cation. The anion tends to play a minor (but not negligible) role, but more research is needed since, owing to the very nature of ILs, except for the most common ones (imidazolium and ammonium-based), many of them are subject to only one or two articles.

Prediction of organic pollutant removal using Corynebacterium glutamicum fermentation waste

The disposal of bio-waste (e.g., Corynebacterium glutamicum) produced by the fermentation industry is a serious problem and has a negative impact on economic returns. Some fermentation waste can be recycled as livestock feed, but much cannot be used. Therefore, other recycling methods must be developed to increase its applications, for example, as an environmentally friendly adsorbent for the removal or recovery of chemicals. To broaden its application as an adsorbent, we carried out comprehensive experimental and theoretical analysis. From the experiments, adsorption affinity values between C. glutamicum and micropollutants were measured, and, based on the experimental values, we developed a predictive model. The experimental results reveal that the degree of adsorption is dependent on the structural properties of the micropollutants. In particular, the adsorbent has remarkable adsorption ability toward cations, whereas anionic and neutral compounds interact weakly with the adsorbent. In addition, we found that adsorption is affected by the sodium chloride concentration. Briefly, an increase in salt concentration increases the adsorption of anions, whereas the opposite behavior is observed for cations. In contrast, the adsorption of neutral compounds was not affected by the presence of salt. The modeling studies revealed that a linear free energy relationship model can be used to predict the adsorption affinity. Based on the developed model, we found that hydrogen-bond basicity, anionic coulombic interactions, and molecular volume are the main contributing factors to the adsorption model. However, to achieve the best predictability (a coefficient of determination (R²) of 0.902), additional parameters, such as the dipolarity/polarizability and dispersive interaction, should be included. This indicates that adsorption is a product of complex interactions.

Quantitative structure-activity relationship model for classifying the diverse series of antifungal agents using ratio weighted penalized logistic regression

One of the most challenging issues when facing a Quantitative structure-activity relationship (QSAR) classification model is to deal with the descriptor selection. Penalized methods have been adapted and have gained popularity as a key for simultaneously performing descriptor selection and QSAR classification model estimation. However, penalized methods have drawbacks such as having biases and inconsistencies that make they lack the oracle properties. This paper proposes an adaptive penalized logistic regression (APLR) to overcome these drawbacks. This is done by employing a ratio (BWR) of the descriptors between-groups sum of squares (BSS) to the within-groups sum of squares (WSS) for each descriptor as a weight inside the L₁-norm. The proposed method was applied to one dataset that consists of a diverse series of antimicrobial agents with their respective bioactivities against Candida albicans. By experimental study, it has been shown that the proposed method (APLR) was more efficient in the selection of descriptors and classification accuracy than the other competitive methods that could be used in developing QSAR classification models. Another dataset was also successfully experienced. Therefore, it can be concluded that the APLR method had significant impact on QSAR analysis and studies.

Recovery of gold via adsorption-incineration techniques using banana peel and its derivatives: Selectivity and mechanisms

In this study, banana peel (BP) and its derivatives after sequential extraction of biochemical components were evaluated for selective recovery of gold. In-depth instrumental characterizations including XPS, FTIR, XRD and HR-TEM were performed to understand the adsorption mechanisms. The biomass after lipid extraction, BP-L, demonstrated very good affinity and selectivity towards gold. In multi-metal systems containing 100 mg/L of Pt(IV), Au(III), Pd(II), Zn(II), Co(II), Ni(II) and Li(I), the selectivity coefficient increased from 978.45 in BP to 2034.70 in BP-L. Moreover, the equilibrium gold uptake was improved and reached 475.48 ± 3.08 mg/g owing to reduction-coupled adsorption mechanisms. The BP-L also showed improved gold nanoparticle formation properties that were pH-dependent. In a strategic adsorption-combined incineration process, metallic gold reaching 99.96% in purity was obtained. The BP and its derivative, BP-L have thus shown potentials for multiple applications in the areas of precious metal recovery and nanoscience.

Representation of the Structure-A Key Point of Building QSAR/QSPR Models for Ionic Liquids

The process of encoding the structure of chemicals by molecular descriptors is a crucial step in quantitative structure-activity/property relationships (QSAR/QSPR) modeling. Since ionic liquids (ILs) are disconnected structures, various ways of representing their structure are used in the QSAR studies: the models can be based on descriptors either derived for particular ions or for the whole ionic pair. We have examined the influence of the type of IL representation (separate ions vs. ionic pairs) on the model's quality, the process of the automated descriptors selection and reliability of the applicability domain (AD) assessment. The result of the benchmark study showed that a less precise description of ionic liquid, based on the 2D descriptors calculated for ionic pairs, is sufficient to develop a reliable QSAR/QSPR model with the highest accuracy in terms of calibration as well as validation. Moreover, the process of a descriptors' selection is more effective when the possible number of variables can be decreased at the beginning of model development. Additionally, 2D descriptors usually demand less effort in mechanistic interpretation and are more convenient for virtual screening studies.

Application of general toxic effects of ionic liquids to predict toxicities of ionic liquids to Spodoptera frugiperda 9, Eisenia fetida, Caenorhabditis elegans, and Danio rerio

Modeling for the toxicity of ionic liquids (ILs) is necessary to fill data gaps for untested chemicals and to understand the relevant mechanisms at the molecular level. In order for many researchers to easily predict toxicity and/or develop some prediction model, simple method(s) based on a single parameter should be proposed. Therefore, previously our group developed a comprehensive toxicity prediction model with unified linear free-energy relationship descriptors to address the single parameter for predicting the toxicities, as follows (Cho et al., 2016b). Log 1/toxicity in the unit of mM= (2.254 E_c - 2.545 S_c + 0.646 A_c - 1.471 B_c + 1.650 V_c + 2.917 J⁺ - 0.201 E_a + 0.418 V_a + 0.131 J^-) - 0.709. It is considered that the model can calculate the general toxicological effect of ILs in parenthesis, as it was developed on the basis of numerous toxic effects i.e., 58 toxicity testing methods and about 1600 data points. In order to check the hypothesis, the values calculated by the model were correlated with four different datasets from insect cell line (Spodoptera frugiperda 9), earthworm (Eisenia fetida), nematode (Caenorhabditis elegans), and fish (Danio rerio). The results clearly showed that the calculated values are in good agreement with each dataset. In the case of S. frugiperda 9 cells, the calculated parameters were correlated with log1/LC₅₀ values, measured after 24 h and 48 h incubation, in R² of 0.67 and 0.88, respectively. The R² values for the earthworm, nematode, and fish were 0.88, 0.96, and 0.94-0.95, respectively. This study confirmed that the comprehensive model can be simply and accurately used to predict toxicity of ILs.

QSAR classification model for diverse series of antifungal agents based on improved binary differential search algorithm

An improved binary differential search (improved BDS) algorithm is proposed for QSAR classification of diverse series of antimicrobial compounds against Candida albicans inhibitors. The transfer functions is the most important component of the BDS algorithm, and converts continuous values of the donor into discrete values. In this paper, the eight types of transfer functions are investigated to verify their efficiency in improving BDS algorithm performance in QSAR classification. The performance was evaluated using three metrics: classification accuracy (CA), geometric mean of sensitivity and specificity (G-mean), and area under the curve. The Kruskal-Wallis test was also applied to show the statistical differences between the functions. Two functions, S1 and V4, show the best classification achievement, with a slightly better performance of V4 than S1. The V4 function takes the lowest iterations and selects the fewest descriptors. In addition, the V4 function yields the best CA and G-mean of 98.07% and 0.977%, respectively. The results prove that the V4 transfer function significantly improves the performance of the original BDS.

Effect of imidazolium-based ionic liquids with varying carbon chain lengths on Arabidopsis thaliana: Response of growth and photosynthetic fluorescence parameters

As green and novel solvents, ionic liquids (ILs) are popular in many industries, which may threaten ecosystems. The effects of three imidazolium-based ILs with different alkyl chain lengths, including 1-octyl-3-methylimidazolium chloride ([C₈mim]Cl), 1-decyl-3-methylimidazolium chloride ([C₁₀mim]Cl), and 1-dodecyl-3-methylimidazolium chloride ([C₁₂mim]Cl) on growth and photosystem of Arabidopsis thaliana were investigated. Root length, fresh weight, cell membrane permeability, and chlorophyll content of whole plant were significantly affected by ILs. Vein clearing, leaf chlorosis, and browning on the A. thaliana leaf abaxial surface occurred, with a dose-response relationship. The effect of ILs on whole plant increased with alkyl chain lengths. Chlorophyll fluorescence parameters of photosynthetic system II (PSII) were all affected in [C₈mim]Cl and [C₁₀mim]Cl treatments, electron-transfer was blocked, and photochemical energy conversion was damaged. There were no significant changes in chlorophyll fluorescence of newly-growing leaves in [C₁₂mim]Cl treatment, but has severe effect on aged leaves. The number and size of starch granules and osmiophilic globules increased, plasmolysis and the chloroplast swelling occurred in [C₈mim]Cl, [C₁₀mim]Cl treatments and on aged leaves in [C₁₂mim]Cl treatment, but no significant damages occurred on newly-growing leaves of [C₁₂mim]Cl treatment, perhaps due to plant self-protection of plant. The results indicating the appropriate use of ILs is needed.

The Use of Liquids Ionic Fluids as Pharmaceutically Active Substances Helpful in Combating Nosocomial Infections Induced by Klebsiella Pneumoniae New Delhi Strain, Acinetobacter Baumannii and Enterococcus Species

This review deals with various microbiological activities of ionic liquids, which constitute the first anti-infective defense against multi-drug-resistant bacteria-with a particular emphasis placed on medicine and pharmacology. The quoted data on the biological activity of ionic liquids including their antimicrobial properties (depending on the type of a cation or an anion) and are discussed in view of possible applications in nosocomial infections. Dedicated attention is given to finding infections with the Klebsiella pneumoniae New Delhi strain, Acinetobacter baumannii, and Enterococcus species, which are responsible for the induction of antibiotic resistance in intensive care units. Diagnosis and treatment using current antibiotics is a significant problem in hospital care, and the relevant burden on the health systems of the European Union member states induces the search for new, effective methods of treatment. Ionic liquids, due to their antibacterial effect, can be considered topical and general medications and may provide the basis for treatment to eliminate the antibiotic resistance phenomenon in the future. At present, the number of infections with resistant pathogens in hospitals and outpatient clinics in the European Union is growing. In 2015⁻2017, a significant incidence of respiratory and bloodstream infections with bacteria resistant to antibiotics from the 3rd generation group of cephalosporins, glycopeptides, and carbapenems were observed. The paper presents examples of synthesized bifunctional salts with at least one pharmaceutically active ion in obtaining a controlled release, controlled delivery, and biological impact on the pathogenic bacteria, viruses and fungi. The ionic liquids obtained in the presented way may find applications in the treatment of wounds and infections.

QSAR models for describing the toxicological effects of ILs against Staphylococcus aureus based on norm indexes

The hazardous potential of ionic liquids (ILs) is becoming an issue of great concern due to their important role in many industrial fields as green agents. The mathematical model for the toxicological effects of ILs is useful for the risk assessment and design of environmentally benign ILs. The objective of this work is to develop QSAR models to describe the minimal inhibitory concentration (MIC) and minimal bactericidal concentration (MBC) of ILs against Staphylococcus aureus (S. aureus). A total of 169 and 101 ILs with MICs and MBCs, respectively, are used to obtain multiple linear regression models based on matrix norm indexes. The norm indexes used in this work are proposed by our research group and they are first applied to estimate the antibacterial toxicity of these ILs against S. aureus. These two models precisely and reliably calculated the IL toxicities with a square of correlation coefficient (R²) of 0.919 and a standard error of estimate (SE) of 0.341 (in log unit of mM) for pMIC, and an R² of 0.913 and SE of 0.282 for pMBC.

Multicomponent ionic liquid CMC prediction

We created a model to predict CMC of ILs based on 704 experimental values published in 43 publications since 2000. Our model was able to predict CMC of variety of ILs in binary or ternary system in a presence of salt or alcohol. The molecular volume of IL (V_m), solvent-accessible surface (Ŝ), solvation enthalpy (Δ_solvG^∞), concentration of salt (C_s) or alcohol (C_a) and their molecular volumes (V_ms and V_ma, respectively) were chosen as descriptors, and Kernel Support Vector Machine (KSVM) and Evolutionary Algorithm (EA) as regression methodologies to create the models. Data was split into training and validation set (80/20) and subjected to bootstrap aggregation. KSVM provided better fit with average R² of 0.843, and MSE of 0.608, whereas EA resulted in R² of 0.794 and MSE of 0.973. From the sensitivity analysis it was shown that V_m and Ŝ have the highest impact on ILs micellization in both binary and ternary systems, however surprisingly in the presence of alcohol the V_m becomes insignificant/irrelevant. Micelle stabilizing or destabilizing influence of the descriptors depends upon the additives. Previous attempts at modelling the CMC of ILs was generally limited to small number of ILs in simplified (binary) systems. We however showed successful prediction of the CMC over a range of different systems (binary and ternary).

The effects of structural changes on the anti-microbial and anti-proliferative activities of diimidazolium salts

Anti-microbial and anti-proliferative activities of diimidazolium salts have been analyzed as a function of the main changes in their structural features.

Comprehensive approach for predicting toxicological effects of ionic liquids on several biological systems using unified descriptors

The challenge and opportunity for design of environmentally-benign ionic liquids (ILs) would start from prediction of their toxicological effects on several endpoints solely based on the structural formulas. Especially, a comprehensive yet simple equation able to predict several biological responses to IL toxicity is of much advantage. Therefore, based on 50 toxicity testing systems on ILs a comprehensively approachable prediction method was developed. For the modelling, approximately 1600 toxicity values measured by several biological systems and an amended linear free energy relationship (LFER) model were used. Since the toxicological activities of an IL could be differently described according to sensitivity of toxicity testing systems, the sensitivity of each of toxicity testing systems was also estimated in the modelling. By statistical analysis with the calculated descriptors, a LFER model was built. Also the sensitivity value of each system on the basis of the comprehensively approachable model was numerically estimated. In results, it was observed that the combination of single model and sensitivity terms was able to predict each of 50 toxicological effects of ILs with R(2) of 0.593~0.978, and SE of 0.098~0.699 log unit, and the total data set with R(2) of 0.901 and SE of 0.426 log unit.

Interpretation of toxicological activity of ionic liquids to acetylcholinesterase inhibition via in silico modelling

For designing environmentally friendly ionic liquids (ILs), their structural effects on the toxicity should be interpreted via modelling based on the quantitative-structure-activity-relationship (QSAR) concept. For the purpose, QSAR models for predicting IL toxicity in acetylcholinesterase activity were developed by using linear free-energy relationship (LFER) descriptors, whose chemical meanings are well defined. These are excess molar refraction (Ec or a), dipolarity/polarizability (Sc or a), H-bonding acidity (Ac or a), H-bonding basicity (Bc or a), McGowan volume (Vc or a), and ionic interactions of cation (J(+)) and anion (J(-)). Since the experimentally determined LFER descriptors are not available, we calculated them based on density functional theory, conductor-like screening model and the open-source software, obprop. The toxicity values of imidazolium- and pyridinium-based ILs could be predicted by a combination of four descriptors (Ac, Bc, Vc and Sa) with an R(2) of 0.828, and (Ec, Ac, Ea and Sa) with an R(2) of 0.879, respectively. In prediction study using the overall dataset containing various IL structures, the six calculated terms (Ec, Sc, Ac, J(+), Ea, and Sa) were selected and correlated with the observed toxicity values in R(2) of 0.748 for the training set, R(2) of 0.711 for the test set and R(2) of 0.655 for external validation set. And this study explains how the selected terms are contributing to the prediction models, and their chemical meanings were understood.