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Graphical abstract, 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.

Enzymatic oxidative decarboxylation is an up-and-coming reaction yet lacking efficient screening methods for the directed evolution of decarboxylases. Here, we describe a simple photoclick assay for the detection of decarboxylation products and its application in a proof-of-principle directed evolution study on the decarboxylase OleT. The assay was compatible with two frequently used OleT operation modes (directly using hydrogen peroxide as the enzyme's co-substrate or using a reductase partner) and the screening of saturation mutagenesis libraries identified two enzyme variants shifting the enzyme's substrate preference from long chain fatty acids toward styrene derivatives. Overall, this photoclick assay holds promise to speed-up the directed evolution of OleT and other decarboxylases. © 2020 The Authors. Published by Wiley-VCH GmbH

ChemBioChem : a European journal of chemical biology (2020). doi:10.1002/cbic.202000681, Published by Wiley-VCH, Weinheim

Frontiers in Bioengineering and Biotechnology 9, 728501 (2021). doi:10.3389/fbioe.2021.728501, Published by Frontiers Media, Lausanne

Additional file 1. Additional Tables and Figures.

Cellulases are industrially important enzymes, e.g., in the production of bioethanol, in pulp and paper industry, feedstock, and textile. Thermostability is often a prerequisite for high process stability and improving thermostability without affecting specific activities at lower temperatures is challenging and often time-consuming. Protein engineering strategies that combine experimental and computational are emerging in order to reduce experimental screening efforts and speed up enzyme engineering campaigns. Constraint Network Analysis (CNA) is a promising computational method that identifies beneficial positions in enzymes to improve thermostability. In this study, we compare CNA and directed evolution in the identification of beneficial positions in order to evaluate the potential of CNA in protein engineering campaigns (e.g., in the identification phase of KnowVolution). We engineered the industrially relevant endoglucanase EGLII from Penicillium verruculosum towards increased thermostability. From the CNA approach, six variants were obtained with an up to 2-fold improvement in thermostability. The overall experimental burden was reduced to 40% utilizing the CNA method in comparison to directed evolution. On a variant level, the success rate was similar for both strategies, with 0.27% and 0.18% improved variants in the epPCR and CNA-guided library, respectively. In essence, CNA is an effective method for identification of positions that improve thermostability.

Efficient synthetic techniques for the diversification of natural products are incremental for drug discovery processes of the pharmaceutical industry because these complex bioactive compounds often require an adjustment of properties. Human liver P450 3A4, key player of the body's detoxification system and decisive factor of a drug's metabolic fate, is renowned for its broad substrate scope including many natural products. In this study, we investigated the synthetic potential of human P450 3A4 for the diversification of natural product classes and isolated the produced metabolites of six selected natural products at a preparative 100-mg scale. Aided by efficient expression levels in P. pastoris, this whole-cell biocatalyst was found to be highly effective at the intended job allowing the identification of a total of 31 authentic human metabolites, many of them for the first time. By revealing an unprecedented degree of diversification, this study extends the synthetic repertoire for efficient enzymatic natural product modification in a one-step fashion and adds a completely new view to an old enzyme traditionally used for inhibition and toxicology studies. Europäische Kommission 722390 Version of record

Graphical abstract, Cellulases are industrially important enzymes, e.g., in the production of bioethanol, in pulp and paper industry, feedstock, and textile. Thermostability is often a prerequisite for high process stability and improving thermostability without affecting specific activities at lower temperatures is challenging and often time-consuming. Protein engineering strategies that combine experimental and computational are emerging in order to reduce experimental screening efforts and speed up enzyme engineering campaigns. Constraint Network Analysis (CNA) is a promising computational method that identifies beneficial positions in enzymes to improve thermostability. In this study, we compare CNA and directed evolution in the identification of beneficial positions in order to evaluate the potential of CNA in protein engineering campaigns (e.g., in the identification phase of KnowVolution). We engineered the industrially relevant endoglucanase EGLII from Penicillium verruculosum towards increased thermostability. From the CNA approach, six variants were obtained with an up to 2-fold improvement in thermostability. The overall experimental burden was reduced to 40% utilizing the CNA method in comparison to directed evolution. On a variant level, the success rate was similar for both strategies, with 0.27% and 0.18% improved variants in the epPCR and CNA-guided library, respectively. In essence, CNA is an effective method for identification of positions that improve thermostability.