Cumulative Millisecond-Long Sampling for a Comprehensive Energetic Evaluation of Aqueous Ionic Liquid Effects on Amino Acid Interactions.

The interactions of amino acid side-chains confer diverse energetic contributions and physical properties to a protein's stability and function. Various computational tools estimate the effect of changing a given amino acid on the protein's stability based on parametrized (free) energy functions. When parametrized for the prediction of protein stability in water, such energy functions can lead to suboptimal results for other solvents, such as ionic liquids (IL), aqueous ionic liquids (aIL), or salt solutions. However, to our knowledge, no comprehensive data are available describing the energetic effects of aIL on intramolecular protein interactions. Here, we present the most comprehensive set of potential of mean force (PMF) profiles of pairwise protein-residue interactions to date, covering 50 relevant interactions in water, the two biotechnologically relevant aIL [BMIM/Cl] and [BMIM/TfO], and [Na/Cl]. These results are based on a cumulated simulation time of >1 ms. aIL and salt ions can weaken, but also strengthen, specific residue interactions by more than 3 kcal mol-1, depending on the residue pair, residue-residue configuration, participating ions, and concentration, necessitating considering such interactions specifically. These changes originate from a complex interplay of competitive or cooperative noncovalent ion-residue interactions, changes in solvent structural dynamics, or unspecific charge screening effects and occur at the contact distance but also at larger, solvent-separated distances. This data provide explanations at the atomistic and energetic levels for complex IL effects on protein stability and should help improve the prediction accuracies of computational tools that estimate protein stability based on (free) energy functions.

Critical assessment of structure-based approaches to improve protein resistance in aqueous ionic liquids by enzyme-wide saturation mutagenesis.

Ionic liquids (IL) and aqueous ionic liquids (aIL) are attractive (co-)solvents for green industrial processes involving biocatalysts, but often reduce enzyme activity. Experimental and computational methods are applied to predict favorable substitution sites and, most often, subsequent site-directed surface charge modifications are introduced to enhance enzyme resistance towards aIL. However, almost no studies evaluate the prediction precision with random mutagenesis or the application of simple data-driven filtering processes. Here, we systematically and rigorously evaluated the performance of 22 previously described structure-based approaches to increase enzyme resistance to aIL based on an experimental complete site-saturation mutagenesis library of Bacillus subtilis Lipase A (BsLipA) screened against four aIL. We show that, surprisingly, most of the approaches yield low gain-in-precision (GiP) values, particularly for predicting relevant positions: 14 approaches perform worse than random mutagenesis. Encouragingly, exploiting experimental information on the thermostability of BsLipA or structural weak spots of BsLipA predicted by rigidity theory yields GiP = 3.03 and 2.39 for relevant variants and GiP = 1.61 and 1.41 for relevant positions. Combining five simple-to-compute physicochemical and evolutionary properties substantially increases the precision of predicting relevant variants and positions, yielding GiP = 3.35 and 1.29. Finally, combining these properties with predictions of structural weak spots identified by rigidity theory additionally improves GiP for relevant variants up to 4-fold to ∼10 and sustains or increases GiP for relevant positions, resulting in a prediction precision of ∼90% compared to ∼9% in random mutagenesis. This combination should be applicable to other enzyme systems for guiding protein engineering approaches towards improved aIL resistance.

Aqueous ionic liquids redistribute local enzyme stability via long-range perturbation pathways.

Ionic liquids (IL) and aqueous ionic liquids (aIL) are attractive (co-)solvents for biocatalysis due to their unique properties. On the other hand, the incubation of enzymes in IL or aIL often reduces enzyme activity. Recent studies proposed various aIL-induced effects to explain the reduction, classified as direct effects, e.g., local dehydration or competitive inhibition, and indirect effects, e.g., structural perturbations or disturbed catalytic site integrity. However, the molecular origin of indirect effects has largely remained elusive. Here we show by multi-µs long molecular dynamics simulations, free energy computations, and rigidity analyses that aIL favorably interact with specific residues of Bacillus subtilis Lipase A (BsLipA) and modify the local structural stability of this model enzyme by inducing long-range perturbations of noncovalent interactions. The perturbations percolate over neighboring residues and eventually affect the catalytic site and the buried protein core. Validation against a complete experimental site saturation mutagenesis library of BsLipA (3620 variants) reveals that the residues of the perturbation pathways are distinguished sequence positions where substitutions highly likely yield significantly improved residual activity. Our results demonstrate that identifying these perturbation pathways and specific IL ion-residue interactions there effectively predicts focused variant libraries with improved aIL tolerance.