Open Access Article
Shuaiqi
Meng
ab,
Yu
Ji
*ab,
Maxine
Yew
c,
Leilei
Zhu
*c and
Ulrich
Schwaneberg
*ab
aState Key Laboratory of Green Biomanufacturing, National Energy R&D Center for Biorefinery, Beijing Key Lab of Bioprocess, College of Life Science and Technology, Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China. E-mail: yuji@buct.edu.cn; u.schwaneberg@biotec.rwth-aachen.de
bInstitute of Biotechnology, RWTH Aachen University, Worringerweg 3, 52074 Aachen, Germany
cState Key Laboratory of Engineering Biology for Low-Carbon Manufacturing, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, 32 West 7th Avenue, Tianjin 300308, PR China. E-mail: zhu_ll@tib.cas.cn
First published on 23rd February 2026
Ionic liquids (ILs) are attractive reaction media in biocatalysis due to their excellent substrate solubilization properties and their promotion of mild and often environmentally friendly reaction conditions. However, enzyme activity is typically reduced at IL concentrations above 10%. In recent decades, continuous efforts in enzyme engineering have aimed to improve enzyme resistance to ILs, yet achieving robust enzymes remains challenging. This review summarizes research efforts over the past decades aimed at improving IL resistance of enzymes, spanning mechanistic insights and engineering strategies. Analyses of enzyme–IL interactions revealed that the primary effect of ILs is the stripping of water molecules from the enzyme surface. Subsequently, a comprehensive site-saturation mutagenesis (SSM) library of Bacillus subtilis lipase A (BSLA), covering all 181 positions, provided a systematic basis for understanding IL tolerance. Screening this library in the presence of four [BMIM]-based ILs ([BMIM]Cl, [BMIM]Br, [BMIM]I, and [BMIM][TfO]) revealed a general engineering principle: the hydration shell of enzymes is a key determinant of IL resistance. Finally, strategies to identify functional positions associated with improved IL resistance and to efficiently recombine beneficial substitutions are discussed. These engineering approaches minimize experimental effort while maximizing enzyme performance in ILs, providing a powerful and broadly applicable framework for the future design of IL-tolerant enzymes.
Green foundation1. Ionic liquids are promising green solvents for enzyme catalysis, offering low volatility, tunable properties, and potential to replace harmful organic solvents; however, limited enzyme resistance has restricted their wider use.2. This review elaborates on the interactions between enzymes and ionic liquids, and discusses state-of-the-art strategies to enhance enzyme tolerance, providing pathways to unlock their sustainable potential in biocatalysis and expand industrial relevance. 3. Future advances could focus on designing even more robust enzymes, integrating ionic liquids with renewable feedstocks, and scaling applications to maximize their role in sustainable manufacturing. |
ILs possess unique properties such as strong solvating power, negligible vapor pressure, and high thermal stability, which make them especially attractive for biocatalytic processes.25 In simple terms, ILs are molten salts with melting points typically below 100 °C. They are generally composed of organic cations (e.g. imidazolium, pyridinium, alkylated ammonium) paired with organic or inorganic anions (e.g. chloride, nitrate, tetrafluoroborate, hexafluorophosphate, methylsulfate), as illustrated in Fig. 1.26,27 ILs are often referred to as “designer solvents” as the cationic and anionic components can be independently varied.28 This tunability allows the fine adjustment of key solvent properties, such as polarity, viscosity, miscibility, and hydrophobicity or hydrophilicity. Moreover, ILs can be mixed with other solvents to form homogeneous aqueous or multiphasic systems, expanding their versatility in application. In such systems, ionic composition can be tailored to manipulate solvent–solute interactions by altering physicochemical properties.29 For instance, ILs can be designed to be immiscible with low-polarity or non-polar organic solvents, thereby enabling selective extraction and product separation.30
The main limitation to the broad range of IL applications is the limited availability of enzymes capable of withstanding high IL concentrations while maintaining adequate process stability.31–33 The selection of the cation–anion pair plays a critical role in determining the stability and compatibility of IL–enzyme systems. Certain classes of ILs are known to be toxic to whole cells and proteins, often causing irreversible deactivation of enzymatic function. For instance, CALB retains only 3% of its catalytic activity after incubation in [BMIM][NO3], primarily due to strong hydrogen bonding between the anions and the enzyme, which disrupts its secondary structure and leads to inactivation.34 The general effects of ILs on enzyme activity and stability include (Fig. 2):
(a) Ionic interactions (e.g., salt bridges), particularly on the enzyme surface, which can destabilize the protein's secondary structure;35,36
(b) Water-stripping effects, where ILs remove essential hydration layers from the enzyme surface, reducing flexibility and altering conformation of enzyme;37,38
(c) Occupation of the enzyme's active site by IL molecules, which can act as reversible inhibitors by blocking substrate binding;39
(d) Destabilization of the folded state of proteins, potentially leading to unfolding, aggregation, and loss of catalytic activity.40,41
Both the anion and the cation part of IL can significantly influence the activity of enzyme depending on their interactions with water and the specific enzyme involved.42 For example, in imidazolium-based ILs used for cellulose dissolution, the anion is generally considered as the dominant factor responsible for cellulase deactivation.43 In contrast, for enzymes such as Bacillus subtilis lipase A (BSLA) and CALB, imidazolium cations with varying alkyl chain lengths have more pronounced effect on enzyme structure and stability.37,41,44,45
The influence of individual ions on protein stability can be briefly understood through the Hofmeister series, which classifies ions as either kosmo tropes (structure stabilizers) or chaotropes (structure disruptors) based on their ability to order or disorder water molecules.46 Based on the Hofmeister series, an overall trend in anion-induced destabilization is observed in the following order: C4H4O62− > SO42−>HPO42− > C3H5O(CO2)33− > CH3CO2− > HCO3− > CrO42− > Cl− > NO3− > ClO3−.47 The corresponding sequence for cations is: Li+ > K+ ≈ Na+ > NH4+ > Mg2+.47 However, the Hofmeister series does not always reliably predict enzyme behavior in ILs. For instance, while halide anions such as Cl− and Br− are generally considered denaturing agents, CALB has shown 6-fold improvement in activity in the presence of 1-decyl-3-methylimidazolium chloride.48 The effects of ILs on proteins also influenced by various factors such as protein structure, IL concentration, temperature, and pH.49,50
Overall, the influence of ILs on enzymes is complex. Several successful strategies have been reported to enhance enzyme resistance to ILs through enzyme engineering51–53 and chemical modification.15,54,55 An example of chemical modifications is the modification of CALB structure with betaine ionic liquids of different chain lengths resulting in improved enzyme activity, thermal stability and DMSO tolerance.15 The flexibility of CALB was enhanced by the IL modifier which results in increased number of water molecules surrounding the enzymatic active sites. Among the enzyme engineering reports several cases employed site-saturation mutagenesis libraries (SSM).13,56 A representative example is the BSLA SSM library, which encompasses 3620 BSLA variants and represents the complete natural sequence diversity generated by single amino acid substitutions at all BSLA positions.13 The BSLA-SSM libraries were screened in four ionic liquids: [BMIM][Cl], [BMIM][Br], [BMIM][I], and [BMIM][TfO]. The generated datasets offer a comprehensive study for quantifying and analyzing enzyme resistance to ILs, providing the first insight into how lipases can be rationally redesigned to function effectively in ILs. This dataset provides a robust model system for elucidating general design principles governing enzyme resistance in IL environments.
The application of ILs as solvents for enzymatic reactions has been extensively summarized in previous reviews, which provide comprehensive overviews of their physicochemical properties, effects on catalysis, and potential process advantages.57–61 As these aspects have been well covered elsewhere, they are not the focus of the present review. Instead, this review concentrates on enzyme engineering strategies aimed at evolving enzymes with enhanced tolerance toward ILs. Using large-scale mutational fitness landscape analysis of BSLA as an entry point, we comprehensively discuss enzyme behavior in IL environments, elucidate molecular mechanisms of enzyme–IL interactions, and summarize engineering and rational recombination strategies. Based on these systematic analyses, generalizable design principles for the development of IL-tolerant enzymes are developed, providing a framework to guide future biocatalyst design in non-conventional reaction media.
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| Fig. 3 Geometrical properties and protein solvation phenomenon investigation for BSLA WT in 4 ILs ([BMIM]Cl, [BMIM]Br, [BMIM]I, and [BMIM][TfO]). Color representation highlights higher (light blue), unchanged (blue), and lower (dark blue) enzyme performances in ILs relative to that in an aqueous environment.63–65 This figure adapted from ref. 63–65 with permission from Royal Society of Chemistry, copyright © 2019,63 and American Chemical Society. Copyright © 2019.64 | ||
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| Fig. 4 The BSLA properties in ILs. Spatial distribution function (SDF) for the solvent distribution of the BSLA surface in water and ILs simulations.64 Color code: gray, enzyme surface; orange, oxyanion hole; green, catalytic triad; blue, water; purple, BMIM+, and cyan, anions. This figure reproduced from ref. 64 with permission from Copyright © 2019, American Chemical Society. | ||
The radial distribution function elucidates the orientation of ions and thus unveils the binding mode between ions and BSLA. For BMIM+ cation, the initial solvation shells appeared within approximately 5 Å.64 BMIM+ cation primarily interacts with BSLA using its hydrophobic tail, indicating that the interaction between BMIM+ and BSLA occurs through hydrophobic interactions. Additionally, π–π interactions between BMIM+ cation and Y139 and W42 of BSLA are also observed.64 Modifying the protein surface potential has demonstrated to have effects on BMIM+ cation binding.66 These observations suggested that multiple factors contribute to the interaction between ions and BSLA. As for the anions, all halogen ions exhibit the first solvation shell at approximately 2.25 Å, while TfO− has its initial solvation shell at 5 Å. The hydrophobic C-terminal of TfO− exhibits a preferential interaction with BSLA.64
Ionic liquids could interact more strongly with BSLA surfaces than water.67 Notably, the distribution of water on enzyme surface is reduced in ILs compared to pure water environment.64,66 The dominant surface interactions of ionic species and the displacement of structurally essential water molecules from the BSLA surface collectively resulted in significant attenuation of enzymatic activity. Compared with halogen anion, the BMIM+ cations displayed a strong affinity for the enzyme surface, especially towards the catalytic triad.63,64 Meanwhile, the binding of both anions and cations of [BMIM][TfO] on BSLA surface contributed to the stripping off of essential water molecules.64
In another case, laccase from T. versicolor was evolved through two rounds of error-prone PCR (epPCR), screening a total of 2800 clones. This effort yielded the variant M3 (F265S/A318 V) with a 4.5-fold improved activity compared to the WT in the presence of 15% (v/v) [EMIM] [EtSO4].68 The two substitutions are distant from each other but both are located on the enzyme surface.68 Relative folding free-energy calculations (ΔΔGfold) indicated that A318 V contributes to enzyme stabilization, whereas F265S is slightly destabilizing, suggesting that their combined effect may be synergistic rather than additive.68
However, despite directed evolution has been proven to be effective, its drawbacks are equally notable, including the extensive screening load and its inability to investigate the entire protein sequence, rather only a limited number of protein variants can be examined at a time. It is therefore challenging to rely on directed evolution alone to provide a comprehensive understanding of how to enhance enzyme resistance to ILs, as a prerequisite for protein engineering based on rational design.
BSLA has a minimal α/β-hydrolase fold, making it an ideal model enzyme for studying IL resistance.72 To gather a comprehensive understanding of enzyme IL resistance and elucidate the fitness landscape of the BSLA library, Schwaneberg et al. generated a BSLA-site saturation mutagenesis (SSM) library comprising 3620 variants.13 This library offered the 20 naturally occurring amino acids of BSLA at all 181 positions through SSM. The evaluation of resistance of four imidazolium-based ILs ([BMIM]Cl, [BMIM]Br, [BMIM]I, and [BMIM][TfO]) revealed that 6%–13% (13% for [BMIM][Cl], 6% for [BMIM][Br], 7% for [BMIM][I], and 8% for [BMIM][TfO]) of all substitutions show increased ILs resistance than BSLA WT (Fig. 5A and Table 1). These beneficial substitutions were distributed across 50%–69% (69% for [BMIM][Cl], 50% for [BMIM][Br], 52% for [BMIM][I], and 57% for [BMIM][TfO]) of all BSLA positions (Fig. 5B).13,73 The BSLA WT consists of 43% non-polar, 34% polar, 9% negatively charged, and 14% positively charged amino acids. Generally, there is a preference for substitutions by chemically different amino acids (such as aromatic to polar/aliphatic/charged amino acids) over chemically similar ones.13 Therefore, using mutagenesis methods, such as SDM and SeSaM, to introduce chemically different substitutions could be considered to enhance the enzyme IL resistance.74 Among the 20, naturally charged amino acids are more favored as beneficial substitutions (Table 1).13
| Ionic liquids | Amino acid type % (variant number) | ||||
|---|---|---|---|---|---|
| Positively charged | Negatively charged | Non-polar | Polar | Total | |
| a The entire BSLA-SSM library contains 3620 variants. b All percentage values are normalized to BSLA amino acid composition, as BSLA amino acid composition is not evenly distributed (43% non-polar, 34% polar, 9% negatively charged, and 14% positively charged amino acid). The following amino acid classification was used: nonpolar: G, A, V, L, I, M, F, W, P. Polar: S, T, C, Y, N, Q. Negatively charged: D, E. Positively charged: K, R, H. | |||||
| [BMIM][Cl] | 29.1% (85) | 31.4% (59) | 20.4% (183) | 19.1% (135) | 100% (462) |
| [BMIM][Br] | 28.5% (37) | 32.3% (27) | 21.8% (87) | 17.4% (55) | 100% (206) |
| [BMIM][I] | 28.6% (49) | 34.5% (38) | 20.7% (109) | 16.1% (67) | 100% (263) |
| [BMIM][TfO] | 24.9% (46) | 34.5% (41) | 19.0% (108) | 21.6% (97) | 100% (292) |
On average, the ratio of beneficial substitutions of BSLA was 8.5%, and for positions, it was 57%. The high ratio makes it easy to obtain key positions and promising variants in simple calculational design. Analyses that largely focus on limited variants may lead to conclusions that deviate from the actual mechanism, resembling a “blind person touching an elephant”. Harrar et al. compared 22 previously described structure-based approaches that aimed at increasing enzyme IL resistance.73 Surprisingly, most of the approaches performed worse than random mutagenesis, and only 2 methods (leveraging experimental information on thermostability and targeting the structural weak spots of enzymes) showed improved prediction accuracy.73 This comprehensive study showed that global design principles of enzymes cannot be found from the analysis on limited variants. It highlights the importance of considering sufficient prior information from large and diverse datasets to enhance enzyme IL resistance.
The importance of the hydration layer in driving improved enzyme IL resistance was further explored by Cui et al. through comprehensive MD simulations on 25 BSLA substitutions at 19 positions from the BSLA-SSM library.75 They evaluated 45 molecular observables, including geometrical properties, solvation phenomena, and BSLA-solvent interaction energies, to assess the dynamic and structural behavior of BSLA substitutions. Surprisingly, most observables exhibited unpredictable behavior in both beneficial and non-beneficial variants.75 Certain observables, such as [BMIM]+-residue contact frequency and the distance between Ile12-N and Met78-N, showed significance in a specific IL but not in another IL. Among all observables, the only general factor related to IL resistance was the enzyme hydration layer. Thus, tailoring enzymes with high IL resistance based on enhancing the hydration layer was feasible. Cui et al. further generated beneficial variants using the stepwise recombination method (Fig. 6).75 These variants showed an evidently positive correlation with the number of water molecules around substituted positions (up to R2 = 0.96 in [BMIM][TfO] and R2 = 0.85 in [BMIM]Cl, Fig. 6B). Importantly, the mutagenesis effects were not limited to the mutagenesis site; the locally improved hydration level could “pass” to the entire protein, thereby enhancing the hydration shell of the entire protein (Fig. 6C).75 In summary, the determinant factor influencing the difference in IL resistance is the hydration shell surrounding the enzyme. Appropriate engineering strategies could be developed based on enhancing the hydration shell to improve enzyme IL resistance.
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| Fig. 6 Solvation behaviors of BSLA variants in 18.3% (v/v) [BMIM]Cl and 15.0% (v/v) [BMIM][TfO].75 (A) Visualization of the targeted mutation positions in BSLA. (B) Influence of the hydration shell on the IL resistance of the BSLA variants relative to the WT. (C) Spatial distribution of water, BMIM+, and Cl−/TfO− occupancy on the surface of BSLA variants. This Figure reproduced from ref. 75 with permission from Copyright © 2022, American Chemical Society. | ||
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| Fig. 7 Effect of surface charged substitutions on BSLA variants.66 (A) Visualization of the targeted mutation positions in BSLA. At the targeted positions, beneficial substitutions introducing positively charged residues are marked in orange, whereas beneficial substitutions introducing negatively charged residues are marked in green. (B) Heatmaps showing the number of BMIM+ cations, Cl− anions, and water molecules surrounding the substituted sites in BSLA wild type and variants. In the top five variants, beneficial substitutions introduce positively charged residues, whereas in the bottom five variants, beneficial substitutions introduce negatively charged residues. This Figure adapted from ref. 66 with permission from Copyright © 2022, American Chemical Society. | ||
The effects of positively and negatively charged substitutions on enzyme–IL interactions are not equivalent and can lead to distinct solvation behaviors. Charged residues tend to preferentially interact with oppositely charged IL ions, thereby modulating the local ionic environment around the protein surface. Consequently, the choice of introduced residues can, in principle, be guided by the dominant ionic species present in a given IL system. In the case of BSLA in [BMIM]-based ILs, the bulky [BMIM]+ cation exerts a stronger perturbing effect on the enzyme surface than smaller anions such as Cl−, Br−, or I−.64 Therefore, introducing positively charged residues is more effective in repelling [BMIM]+ cations and promoting the retention of water molecules at the enzyme surface.66
Pramanik and colleagues systematically investigated the effect of charged substitutions on BSLA IL resistance.66 In terms of the ability to form salt bridges, their exploration revealed that negatively charged substitutions might be more prone to form additional salt bridges compared to positively charged substitutions.66 Meanwhile, the charged nature of substitution could influence the repulsion or attraction towards ILs (Fig. 7). Compared with the BSLA WT, positively charged substitutions resulted in the repulsion of BMIM+ cations and the attraction of anions. Conversely, negatively charged substitutions repulsed anions and attracted cations. MD simulation demonstrated that positive substitutions showed strong repulsion to BMIM+ cations and weak attraction to anions, while the negative substitutions had obvious attraction to BMIM+ cations.66 Therefore, positively charged substitutions allowed for the retention of more water molecules at the BSLA surface than the negative ones. Analysis of the BSLA-SSM library also showed that most of the positions favorable for resistance improvement are located in the BMIM + binding region, thus weakening the interaction between BMIM and the enzyme.13,63,66,75
In this context, beneficial substitutions at buried positions are more likely to enhance intrinsic protein stability rather than directly affect interactions with ILs. Given that the hydrophobic network exists within the protein, a potential strategy is to introduce hydrophobic amino acids at buried sites, thereby enhancing the hydrophobic interactions near the substitutions and therefore stabilizing the protein.63
To tackle this challenge, Schwaneberg et al. developed the CompassR strategy, which aims to guide the recombination of beneficial substitutions.79,80 The principle of CompassR is to utilize the relative free energy of folding (ΔΔGfold) to predict the effects of substitutions in recombinant variants (Fig. 8). This strategy could efficiently enhance enzyme properties by recombining beneficial substitutions that contribute to intrinsic stability, resulting in enzymes with improved resistance in ILs. An application of the CompassR strategy is the generation of BSLA variant M1a (F17S/V54K/D64N/D91E/G155N), which exhibited up to a 6.7-fold higher resistance against 40% (v/v) [BMIM]Cl, 5.6-fold in 80% (v/v) [BMIM]Br, 5.0-fold in 30% (v/v) [BMIM][TfO], and 2.7-fold in 10% (v/v) [BMIM]I.56 The power of the CompassR strategy suggests the possibility of recombining more than five beneficial substitutions, paving the way for the design of enzymes with much-improved IL resistance in the future.
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| Fig. 8 Enzyme engineering pipeline for engineering high IL-resistant lipases. The parent lipase was diversified and screened/designed, yielding beneficial substitutions with improved hydration layer. These substitutions were then recombined using the CompassR strategy to preserve the enzyme's inherent stability, resulting in stable recombinants with enhanced ILs resistance. Part of this figure was reproduced from ref. 81 with permission from Copyright © 2020, American Chemical Society. | ||
When sufficient computational resources are available, MD simulations could also be employed to predict beneficial recombinants.82 For example, these simulations could monitor changes in hydration layers, thus predicting ILs resistance of variants. While CompassR is based on thermodynamic stability analysis, molecular dynamics focuses on kinetic analysis. By combining the strengths of both methods, more effective reorganization strategies can be developed. Furthermore, these data can feed into data-driven approaches such as machine learning to reduce experimental workload and further improve IL resistance of variants.
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