03 Fakultät Chemie
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/4
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Item Open Access The Bacteroidetes Aequorivita sp. and Kaistella jeonii produce promiscuous esterases with PET-hydrolyzing activity(2022) Zhang, Hongli; Perez-Garcia, Pablo; Dierkes, Robert F.; Applegate, Violetta; Schumacher, Julia; Chibani, Cynthia Maria; Sternagel, Stefanie; Preuss, Lena; Weigert, Sebastian; Schmeisser, Christel; Danso, Dominik; Pleiss, Jürgen; Almeida, Alexandre; Höcker, Birte; Hallam, Steven J.; Schmitz, Ruth A.; Smits, Sander H. J.; Chow, Jennifer; Streit, Wolfgang R.Certain members of the Actinobacteria and Proteobacteria are known to degrade polyethylene terephthalate (PET). Here, we describe the first functional PET-active enzymes from the Bacteroidetes phylum. Using a PETase-specific Hidden-Markov-Model- (HMM-) based search algorithm, we identified several PETase candidates from Flavobacteriaceae and Porphyromonadaceae. Among them, two promiscuous and cold-active esterases derived from Aequorivita sp. (PET27) and Kaistella jeonii (PET30) showed depolymerizing activity on polycaprolactone (PCL), amorphous PET foil and on the polyester polyurethane Impranil® DLN. PET27 is a 37.8 kDa enzyme that released an average of 174.4 nmol terephthalic acid (TPA) after 120 h at 30°C from a 7 mg PET foil platelet in a 200 μl reaction volume, 38-times more than PET30 (37.4 kDa) released under the same conditions. The crystal structure of PET30 without its C-terminal Por-domain (PET30ΔPorC) was solved at 2.1 Å and displays high structural similarity to the IsPETase. PET30 shows a Phe-Met-Tyr substrate binding motif, which seems to be a unique feature, as IsPETase, LCC and PET2 all contain Tyr-Met-Trp binding residues, while PET27 possesses a Phe-Met-Trp motif that is identical to Cut190. Microscopic analyses showed that K. jeonii cells are indeed able to bind on and colonize PET surfaces after a few days of incubation. Homologs of PET27 and PET30 were detected in metagenomes, predominantly aquatic habitats, encompassing a wide range of different global climate zones and suggesting a hitherto unknown influence of this bacterial phylum on man-made polymer degradation.Item Open Access The triple variant K170D/N174L/D239A compensates the destabilizing effect of variant K170D/N174L in β-hydroxyacid dehydrogenase (βHAD) from Arabidopsis thaliana(2020) Schelle, Luca S.; Stockinger, Peter; Pleiss, Jürgen; Nestl, Bettina M.Chiral amines are essential building blocks in biologically active compounds, fine chemicals, agrochemicals and pharmaceuticals. In the last ten years, various enzymes were identified as new biocatalysts for chiral amine synthesis. Promising enzymes for the synthesis of primary, secondary, and tertiary amines are NADPH-dependent imine reductases (IREDs). Bioinformatics analysis revealed that IREDs are closely related to β-hydroxyacid dehydrogenases (βHADs). In recent work, we engineered the βHAD from Arabidopsis thaliana (βHAD_At) into imine-reducing enzymes by a single amino acid exchange. The exchange of the proton-donor described lysine (K170) in βHAD_At by aspartic acid, the most common amino acid at this position in R-selective IREDs, led to a 12-fold increase in activity for the model substrate 2-methylpyrroline. At the same time, the activity for the natural substrate glyoxylic acid is reduced 885-fold, resulting in a total of 8200-fold change in catalytic activity through the exchange of an amino acid. At the same time, highly decreased soluble expression has been observed by exchanging asparagine at position 174 (N174) with leucine. We thus hypothesized, that the aspartic acid residue (D239) in near proximity to N174 will stabilize the underlying α-helix. Consequently, replacement of D239 with alanine should result in soluble expression of variants containing the N174 mutations. We generated variants K170D/D239A, as well as, and tested them on imine reduction of test substrates 2-methylpyrroline, 3,4-dihydroisoquinoline and 6-phenyl-2,3,4,5-tetrahydropyridine. Due to loss of essential cofactor and precipitation of purified proteins during purification procedure, activities of variants were determined using cell lysates. Notably, variants N174L/D239A and K170D/N174L/D239A demonstrated soluble expression and imine-reducing activities of up to 98 mU per mg of variant.Item Open Access Impact of remote mutations on metallo-beta-lactamase substrate specificity : implications for the evolution of antibiotic resistance(2005) Ölschläger, Peter; Mayo, Stephen L.; Pleiss, JürgenMetallo-beta-lactamases have raised concerns due to their ability to hydrolyze a broad spectrum of beta-lactam antibiotics. The G262S point mutation distinguishing the metallo-beta-lactamase IMP 1 from IMP 6 has no effect on the hydrolysis of the drugs cephalothin and cefotaxime, but significantly improves catalytic efficiency toward cephaloridine, ceftazidime, benzylpenicillin, ampicillin, and imipenem. This change in specificity occurs even though residue 262 is remote from the active site. We investigated the substrate specificities of five other point mutants resulting from single nucleotide substitutions at positions near residue 262: G262A, G262V, S121G, F218Y and F218I. The results suggest two types of substrates: type I (nitrocefin, cephalothin and cefotaxime), which are converted equally well by IMP-6, IMP-1, and G262A, but even more efficiently by the other mutants, and type II (ceftazidime, benzylpenicillin, ampicillin, and imipenem), which are hydrolyzed much less efficiently by all the mutants, with IMP-1 being the most active. G262V, S121G, F218Y, and F218I improve conversion of type I substrates, whereas G262A and IMP-1 improve conversion of type II substrates, indicating two distinct evolutionary adaptations from IMP-6. Substrate structure may explain the catalytic efficiencies observed. Type I substrates have R2 electron donors, which may stabilize the substrate intermediate in the binding pocket and lead to enhanced activity. In contrast, the absence of these stabilizing interactions with type II substrates may result in poor conversion and increased sensitivity to mutations. This observation may assist future drug design. As the G262A and F218Y mutants confer effective resistance to Escherichia coli BL21(DE3) cells (high minimal inhibitory concentrations), they are likely to evolve naturally.Item Open Access Fluent integration of laboratory data into biocatalytic process simulation using EnzymeML, DWSIM, and ontologies(2024) Behr, Alexander S.; Surkamp, Julia; Abbaspour, Elnaz; Häußler, Max; Lütz, Stephan; Pleiss, Jürgen; Kockmann, Norbert; Rosenthal, KatrinThe importance of biocatalysis for ecologically sustainable syntheses in the chemical industry and for applications in everyday life is increasing. To design efficient applications, it is important to know the related enzyme kinetics; however, the measurement is laborious and error-prone. Flow reactors are suitable for rapid reaction parameter screening; here, a novel workflow is proposed including digital image processing (DIP) for the quantification of product concentrations, and the use of structured data acquisition with EnzymeML spreadsheets combined with ontology-based semantic information, leading to rapid and smooth data integration into a simulation tool for kinetics evaluation. One of the major findings is that a flexibly adaptive ontology is essential for FAIR (findability, accessibility, interoperability, reusability) data handling. Further, Python interfaces enable consistent data transfer.Item Open Access How to find soluble proteins : a comprehensive analysis of alpha/beta hydrolases for recombinant expression in E. coli(2005) Koschorreck, Markus; Fischer, Markus; Barth, Sandra; Pleiss, JürgenBackground: In screening of libraries derived by expression cloning, expression of active proteinsin E. coli can be limited by formation of inclusion bodies. In these cases it would be desirable to enrich gene libraries for coding sequences with soluble gene products in E. coli and thus to improve the efficiency of screening. Previously Wilkinson and Harrison showed that solubility can be predicted from amino acid composition (Biotechnology 1991, 9(5):443-448). We have applied this analysis to members of the alpha/beta hydrolase fold family to predict their solubility in E. coli. alpha/beta hydrolases are a highly diverse family with more than 1800 proteins which have been grouped into homologous families and superfamilies. Results: The predicted solubility in E. coli depends on hydrolase size, phylogenetic origin of the host organism, the homologous family and the superfamily, to which the hydrolase belongs. In general small hydrolases are predicted to be more soluble than large hydrolases, and eukaryotic hydrolases are predicted to be less soluble in E. coli than prokaryotic ones. However, combining phylogenetic origin and size leads to more complex conclusions. Hydrolases from prokaryotic, fungal and metazoan origin are predicted to be most soluble if they are of small, medium and large size, respectively. We observed large variations of predicted solubility between hydrolases from different homologous families and from different taxa. Conclusion: A comprehensive analysis of all alpha/beta hydrolase sequences allows more efficient screenings for new soluble alpha/beta hydrolases by the use of libraries which contain more soluble gene products. Screening of hydrolases from families whose members are hard to express as soluble proteins in E. coli should first be done in coding sequences of organisms from phylogenetic groups with the highest average of predicted solubility for proteins of this family. The tools developed here can be used to identify attractive target genes for expression using protein sequences published in databases. This analysis also directs the design of degenerate, family- specific primers to amplify new members from homologous families or superfamilies with a high probability of soluble alpha/beta hydrolases.Item Open Access EnzymeML : a data exchange format for biocatalysis and enzymology(2021) Range, Jan; Halupczok, Colin; Lohmann, Jens; Swainston, Neil; Kettner, Carsten; Bergmann, Frank T.; Weidemann, Andreas; Wittig, Ulrike; Schnell, Santiago; Pleiss, JürgenEnzymeML is an XML‐based data exchange format that supports the comprehensive documentation of enzymatic data by describing reaction conditions, time courses of substrate and product concentrations, the kinetic model, and the estimated kinetic constants. EnzymeML is based on the Systems Biology Markup Language, which was extended by implementing the STRENDA Guidelines. An EnzymeML document serves as a container to transfer data between experimental platforms, modeling tools, and databases. EnzymeML supports the scientific community by introducing a standardized data exchange format to make enzymatic data findable, accessible, interoperable, and reusable according to the FAIR data principles. An application programming interface in Python supports the integration of software tools for data acquisition, data analysis, and publication. The feasibility of a seamless data flow using EnzymeML is demonstrated by creating an EnzymeML document from a structured spreadsheet or from a STRENDA DB database entry, by kinetic modeling using the modeling platform COPASI, and by uploading to the enzymatic reaction kinetics database SABIO‐RK.Item Open Access Mesoporous confinement enables activity boost in cooperative asymmetric catalysis in analogy to enzymes(2026) Rautenbach, Liam; Nandeshwar, Muneshwar; Goldstein, Elizabeth; Högler, Marc; Häußler, Max; Allgaier, Alexander; Bauer, Alina; Hornung, Dominik; Beck, Alexander; Franke, Claudia; Osterbrink, Johanna; Bruckner, Johanna R.; Kästner, Johannes; Fischer, Felix R.; Bauer, Matthias; Slageren, Joris van; Pleiss, Jürgen; Hansen, Niels; Buchmeiser, Michael R.; Peters, RenéEnzymes achieve substantial rate accelerations by combining cooperative functional group activation with confinement inside organized active sites, which reduce entropic costs and enforce productive orientations of activated substrates. Here, we translate these principles into artificial cooperative asymmetric catalysis using mesoporous confinement. Embedding a chiral bifunctional catalyst into ordered mesoporous silica creates a synthetic analogue of enzymatic pockets, in which cooperative activation and nanoscale confinement act synergistically. By such confinement, reaction half-lives could be reduced by up to 97% in asymmetric 1,4-additions. Kinetic analyses attribute this enhancement to entropic advantages of confinement, while molecular dynamics simulations reveal narrowing of the catalyst’s conformational space closely paralleling the enzymatic preorganization as a molecular origin. Unlike enzymes, however, the mesoporous framework remains tunable, allowing linker length and pore size to systematically adjust reactivity. This work establishes confinement engineering as a modular strategy to design “unnatural active sites” that merge enzymatic efficiency with synthetic catalyst flexibility. It could thus bridge the gap between nature’s precision and the versatility of synthetic chemistry.Item Open Access Visual analysis of large‐scale protein‐ligand interaction data(2021) Schatz, Karsten; Franco‐Moreno, Juan José; Schäfer, Marco; Rose, Alexander S.; Ferrario, Valerio; Pleiss, Jürgen; Vázquez, Pere‐Pau; Ertl, Thomas; Krone, MichaelWhen studying protein‐ligand interactions, many different factors can influence the behaviour of the protein as well as the ligands. Molecular visualisation tools typically concentrate on the movement of single ligand molecules; however, viewing only one molecule can merely provide a hint of the overall behaviour of the system. To tackle this issue, we do not focus on the visualisation of the local actions of individual ligand molecules but on the influence of a protein and their overall movement. Since the simulations required to study these problems can have millions of time steps, our presented system decouples visualisation and data preprocessing: our preprocessing pipeline aggregates the movement of ligand molecules relative to a receptor protein. For data analysis, we present a web‐based visualisation application that combines multiple linked 2D and 3D views that display the previously calculated data The central view, a novel enhanced sequence diagram that shows the calculated values, is linked to a traditional surface visualisation of the protein. This results in an interactive visualisation that is independent of the size of the underlying data, since the memory footprint of the aggregated data for visualisation is constant and very low, even if the raw input consisted of several terabytes.Item Open Access Meta-analysis of viscosity of aqueous deep eutectic solvents and their components(2020) Gygli, Gudrun; Xu, Xinmeng; Pleiss, JürgenDeep eutectic solvents (DES) formed by quaternary ammonium salts and hydrogen bond donors are a promising green alternative to organic solvents. Their high viscosity at ambient temperatures can limit biocatalytic applications and therefore requires fine-tuning by adjusting water content and temperature. Here, we performed a meta-analysis of the impact of water content and temperature on the viscosities of four deep eutectic solvents (glyceline, reline, N,N-diethylethanol ammonium chloride-glycerol, N,N-diethylethanol ammonium chloride-ethylene glycol), their components (choline chloride, urea, glycerol, ethylene glycol), methanol, and pure water. We analyzed the viscosity data by an automated workflow, using Arrhenius and Vogel-Fulcher-Tammann-Hesse models. The consistency and completeness of experimental data and metadata was used as an essential criterion of data quality. We found that viscosities were reported for different temperature ranges, half the time without specifying a method of desiccation, and in almost half of the reports without specifying experimental errors. We found that the viscosity of the pure components varied widely, but that all aqueous mixtures (except for reline) have similar excess activation energy of viscous flow Eexcessη= 3-5 kJ/mol, whereas reline had a negative excess activation energy (Eexcessη= - 19 kJ/mol). The data and workflows used are accessible at https://doi.org/10.15490/FAIRDOMHUB.1.STUDY.767.1.Item Open Access Best practices for machine learning-assisted protein engineering(2025) Herrera-Rocha, Fabio; Medina-Ortiz, David; Mauz, Fabian; Pleiss, Jürgen; Davari, Mehdi D.Data-driven modeling based on machine learning (ML) is becoming a central component of protein engineering workflows. This perspective presents the elements necessary to develop effective, reliable, and reproducible ML models, and a set of guidelines for ML developments for protein engineering. This includes a critical discussion of software engineering good practices for the development and evaluation of ML-based protein engineering projects, emphasizing supervised learning. These guidelines cover all of the necessary steps for ML development, from data acquisition to model deployment. Additionally, the present perspective provides practical resources for the implementation of the outlined guidelines. These recommendations are also intended to support editors and scientific journals in enforcing good practices in ML-based protein engineering publications, promoting high standards across the community. With this, the aim is to further contribute to improved ML transparency and credibility by easing the adoption of software engineering best practices into ML development for protein engineering. We envision that the wide adoption and continuous update of best practices will encourage informed use of ML on real-world problems related to protein engineering.